Construction Research Congress 2018: Sustainable Design and Construction and Education

Conventional code compliance checking of building envelope energy efficiency is a complex process with tremendous manual calculation work. Automating the checking process can avoid potential calculation mistakes and allow designers to optimize building envelope design more efficiently. To this end, machine-readable code translation with high level of accuracy and correctness is a strong need. This paper thus presents a visual programming language (VPL)-based code translation approach for automated compliance checking of building envelope energy efficiency. Analysis of energy code for building envelope design in Hong Kong is first conducted to identify data sources and key intermediate checking requirements. Based on the identification, atomic methods are selected, and nested program are created, which gives designers and architects the flexibility to reuse these nodes to build or update relevant checking rules. Finally, an architecture of VPL-based energy code translation for overall thermal transfer value (OTTV) checking is presented for future verification of the performance of our approach.

This paper intends to present a bibliometric analysis of the body of knowledge published in the Proceedings of Construction Research Congress (CRC), to highlight the intellectual discourse that has occurred and emerged within the last 14 years. To this end, the citation data for the 1,373 studies published in the Proceedings of CRC, and the 18,032 studies associated with them through citations were examined. Creation, visualization, and analyses of co-occurring terms, co-citations, and co-authorship networks of published studies in CRC provided original insights. Findings reveal that published studies in CRC have devoted serious attention to “project management” as opposed to emerging areas such as “building information modeling” that only recently has received attention. Analysis of the citations among published studies in CRC demonstrated that these studies are almost influenced by many relevant journals in the field of construction. Moreover, analyses of collaboration networks in CRC brought to light an overemphasize on the U.S. authors. By providing a view from a meta-perspective, the study contributes to CRC body of knowledge by exposing trends, gaps, areas in need of extra attention, directions for future research themes, and grounds for fostering collaboration efforts.

Public private partnerships (PPPs) have spread from their typical use on infrastructure projects such as roadways and water sanitation to their more recent use for projects in higher education institutions such as universities and colleges. These PPP projects have diverse attributes depending on the type of project, institutional culture, and structure of ownership and management. Based on these key aspects, the projects can either be successful or unsuccessful depending on economic and financial measures. This paper investigates the use of PPPs for the delivery of higher education institutions and finds trends of PPP usage in the United States. This is performed by first collecting records of PPP projects in educational institutions by applying the systematic literature review (SLR) methodology. The result of the SLR methodology is a collection of U.S.-based higher education PPP projects and a classification of project types and where they are located. The results at this stage show that PPP projects have been used the most in the South and Northeast as compared to other geographic locations in the U.S. majority of the projects were student housing complexes for the universities and there has been a trend for expansion to other areas such as utilities, parking garages, and health centers. The results also show an increasing trend in project sizes between 1994 and 2017. This paper provides a detailed review of the use of PPPs in higher education institutions with a focus on how SLR was conducted and the identified trends. It was noticed that PPP was not only used by public universities, but also spread to private universities. The results of this paper are expected to shed light on the increased PPP usage in the educational sector in the U.S.

Construction projects have unavoidable impacts on surrounding environment, such as public safety, emergency response, noise, and dust. These impacts are especially significant when construction projects are located in urban settings with tight space and high population constraints. Current means to evaluate construction impacts on the quality of life in urban settings are ineffective, because the current methods are reactive (in response to complaints reported to related city agencies) instead of being proactive. The broader availability of public city data from metropolitans such as New York City provides opportunities for practitioners, researchers, and civic organizations to extract knowledge from historical data and take proactive actions. Current efforts on analyzing data using open data platforms are mainly focused on tackling travel delays, predicting climate for hazard mitigation, and understanding the energy usage profiles. Continuous construction and rehabilitation in urban settings are part of the city life, yet with limited tools to understand their impacts. This paper investigates the impact of construction projects on urban quality of life by analyzing open city datasets through a method containing data selection, analysis and prediction model creation. The analysis uses road reconstruction projects as testbeds, complaints due to construction as measurement and leverages a machine-learning technique, hidden Markov models (HMM), to predict the future impact of similar construction projects.

Engineering education tends to place extensive emphasis on theories with limited applications to real world problems. Research in the field of education confirms that this emphasis on theory, and relatively little emphasis on application, contributes to students’ lack of knowledge about tools used in industry to solve interdisciplinary challenges. Construction courses may involve industry practitioners in classes through construction site visits, guest lectures, or even leverage practitioners as instructors. Some courses also focus on “tools” used in construction practice, e.g., a course in building information modeling (BIM) or front end planning. However, most introductory construction courses do not teach students about project management tools used in industry, e.g., scheduling software, front end planning, or site logistics planning. This paper presents first steps in discussing how to integrate one such project management tool, the project definition rating index (PDRI), into an introductory construction management course. The construction industry utilizes the PDRI to improve the predictability of project performance and define the scope of a project during front end planning. This paper shows initial results from a case study where the authors introduced the PDRI in a building construction materials, methods, and equipment course at Arizona State University. The results suggest that students felt that learning about the PDRI improved their understanding of course material. The paper closes with a discussion of lessons learned to support other instructors and educators integrate the PDRI, or another project management tool, into an introductory construction management course to enhance student engagement and learning.

Construction students must have the necessary competencies to be successful in the construction industry and the use of information technology is key to successful project administration. In order for students to be prepared, construction educators must be able to effectively teach broad information technology (IT) concepts to construction students to enhance their professional careers. The problem is that there are limited, readily available resources in academic literature regarding a teaching strategy for IT in construction that goes beyond teaching building information modeling (BIM) or virtual design and construction (VDC) to construction students. This paper presents the re-development of a course on IT in construction, for Drexel University’s Construction Management program utilizing the systematic course development process which is based on preparation, development, and improvement and the framework of course development processes based on needs assessment, course objectives, conceptualizing and organizing content, materials, and activities, evaluation techniques, and understanding available resources and constraints. The 10-week course covers topics in IT for construction that highlights the relevance of IT use by constructors at various project phases. Students are predominately evaluated via practical approaches, supplemented by theoretical evaluation. The course utilizes various software that have been evaluated by faculty to ensure applicability and practicality of industry use. Student competency of various IT skill sets, collaboration, and innovation were fundamental considerations for course development. Continuous improvement to the course is necessary and changes have been made to each iteration of the course. There is still a need to determine the efficacy of the course, collaboration among peer institutions, development of an online offering, and development of a graduate offering of the course.

The construction industry, one of the largest job providers in the U.S., is suffering from critical problems pertaining to labor shortage in the workforce. The researchers have recognized as a critical issue an insufficient interest and poorly sustained participation in the architecture, engineering, and construction (AEC) industry by underrepresented demographic groups. To address the issue of workforce income inequality and bias, the industry must be able to understand the current situation regarding inequality and pinpoint some of the basic problems. To address this need, this study analyzes current inequality within the construction workforce by race/ethnicity and gender. The preliminary results of the study show that White construction workers are, in average, 16.2 times more than African Americans and 3.6 times more than Hispanics in average, African Americans being the least in number in the construction workforce. Also, the study shows that men in construction workforce, on average, earn 4.2% more than women in the years sampled. Our trend analysis shows that these gaps relating to the number of employed personnel and median weekly earnings did not change.

Evolving engineering and construction education places emphasis on the broader context of globalization, economics, the environment, and society. This broad and complex challenge necessitates the continued investigation of innovative interdisciplinary approaches for engineering and construction education. The 360 degree model for educating socially responsible global citizens developed by the authors (360 Global Ed model) addresses these current needs through a structured approach for developing students as global citizens through purposeful engagement. The 360 Global Ed model includes a theoretical framework, educational environment, academic coursework, and outcomes. At the core of the model is an international service learning experience. The service-learning component provides a collaborative, interdisciplinary classroom environment combined with an authentic international field experience. Four years of a mix-methods research assessment demonstrate outstanding results on the impact of student learning in the areas of global citizenship, personal and professional growth, and cultural intelligence. The authors have also observed challenges when working in an international environment in interdisciplinary student teams. This paper provides a background on the need for globalization, social responsibility and service learning in engineering and construction management education, introduces the 360 Global Ed model for educating socially responsible global citizens, and discusses assessment results on the impact of student learning. Additionally, the paper addresses observed challenges to an interdisciplinary international service course approach and provides curricular responses to those challenges.

There is an increasing trend towards more integrated project delivery (IPD) methods in the construction industry. However, the definition of IPD and its practical framework includes a wide range of collaborative principles or strategies. A synthesis of the research on IPD can provide a better understanding of the variety of practices and dimensions of what has been studied as IPD. Such a synthesis can help future researchers and practitioners to frame benefits and challenges associated with the range of IPD practices. In this paper, the authors report on an on-going research to perform a tertiary review of the research on IPD. In addition, the authors explore potential applications of the synthesis in the case of a project under construction in Peru, emphasizing the implementation of the lean concepts in IPD. The deductive tertiary review is used to identify IPD principles and was complemented by an inductive case study where the authors explore IPD implementation besides motivations and barriers to its application. The case study is being built by a company with extensive expertise in using lean, while it is the first trial of the company on implementing IPD. Practitioners can use the observations as a broad perspective of IPD to facilitate justification of implementing strategies associated with the IPD practices.

Technology is playing an essential role in both academia and the professional communities of today’s construction industry. It has become a critical constituent of college construction management (CM) curricula to expose students to emerging technology and develop their technological competencies, i.e., knowledge, skills, and abilities (KSAs). The goal is to cultivate a workforce that is better prepared to perform job tasks and deal with technological challenges anticipated in a rapidly transforming industry environment that is characterized with building information modeling (BIM), lean construction, sustainability, and other important trends. This research investigated effective pedagogical approaches and experimented with experiential and project based learning (E+PBL) in an entry level construction graphics course to engage lower-division undergraduate CM students in learning BIM with educational technology scaffold including cloud-based project collaboration tools and learning management systems. Noticeably, service-learning ingredients were incorporated to allow concurrent examination of social dimensions in CM education to instill a culture of professional responsibility and civic engagement. This uniquely blended technological and social context became a facilitator to enhance student learning outcomes (SLOs) in teamwork, collaboration, communication, and leadership, which are deemed as essential social competencies of the CM workforce. This paper presents the pedagogical design and instructional practices of E+PBL and discusses findings of the assessment of student learning engagement using well-established metrics. This research is a pilot and cornerstone to a full-fledged student learning engagement framework built upon digital education and learning technology.

Graduate students will go on to be future scholars in sustainability, and the ability to design and execute research projects are necessary skills for them to build scholarship. In response, many STEM programs, including construction engineering, civil engineering, and architectural engineering, provide graduate level courses in research design and methods. Graduate students learn the skills in research methodology either formally from such a course or informally from their advisor(s). However, little to no evidence has been obtained to quantify such learning outcomes. This paper reports a case study that was designed to assess graduate students’ understanding and implementation of research methodologies. To do so, a mixed research methods approach was conducted. The work applies mixed research methods. Data were collected from the Michael Horman Sustainability Symposium, a forum for faculty and students from multiple U.S. universities focusing on the discussion of sustainability topics. The attendees (N = 53) were required to prepare a statement to detail their research plan and associated research method and to present in a focus group setting. The authors evaluated the statement in the topic (i.e., merit, impacts, originality, and relevance) and methodology (i.e., rationale, feasibility, creativity, and scalability) using a 5-point Likert scale. The evaluation criteria are based on ASCE journal reviewing standards. Both quantitative analysis on the evaluation scores and qualitative analysis on the focus group notes were performed. Results reveal that graduate students know how to identify emerging research problems in sustainability, yet lack the capability to select appropriate research methods to support the intended investigation. The findings help better understand the research methodologies required for conducting sustainability studies, and illuminate teaching strategies that can strengthen students’ capability of problem-solving.

There are currently seventeen ABET (Accreditation Board for Engineering and Technology) accredited construction engineering programs in the United States and 245 civil engineering programs. Every 6 years these programs undergo a stringent review to assure that the programs meet the quality standards expected for the engineering profession. As part of this review, programs must demonstrate that upon graduation, students have achieved a set of eleven student outcomes, affectionately known as (a) through (k). These eleven outcomes are the same, regardless of which engineering program they are being applied, civil, construction, mechanical, chemical, or agricultural. Some programs have found it useful to develop a set of rubrics that can be used to evaluate student’s work, to demonstrate student achievement of the outcomes. While some programs have worked through this exercise, few examples were found to directly relate to construction engineering curriculum. In preparation for the next ABET review, one university, with the largest construction engineering undergraduate enrollment, worked with faculty and industry to develop rubrics to evaluate student performance related to the student outcomes that are intended to directly represent the construction engineering profession. The process and rubrics are described in this paper and can be helpful for other programs aspiring to ABET accreditation or expecting an ABET accreditation review.

Research shows that college retention is a major issue in the United States. To improve student retention it is necessary to understand the factors which influence students’ college persistence decisions. Student persistence is affected by several factors such as family background, financial attitude, pre-college scoring, and faculty interaction. We examine how such factors affect student persistence in a construction management technology program through the use of a causal loop diagram (CLD). Preliminary CLD work suggests what data is required and how they will be collected. Future work will require collecting data from a construction management technology program and developing a system dynamic model which provides tools to test different scenarios and predict system behavior in different conditions. Such models can suggest to policy makers what factors to consider to increase student persistence.

The overwhelming consensus in the scientific community is that anthropogenic climate change will irreversibly affect future generations. Engineering professionals who design and construct our built environment can protect society against the effects of global warming through implementation of building strategies that reduce climate changing emissions. There is little research to assess if students who intend to pursue careers in the design and construction of our built environment hope to address such important environmental and societal challenges. To advance understanding, a survey instrument was developed and validated to measure undergraduate engineering students’ climate change literacy, career motivations, and agency to address climate change in their career. Preliminary results compare responses of engineering students intending to pursue a career in civil and construction industries to those of engineering students intending to pursue other engineering careers. The results indicate that civil and construction engineering students are more likely to take sustainability courses and learn about climate change in the classroom, but they do not excel above other engineers in their knowledge of climate science. The educational gap in engineering sustainability courses must be closed to ensure those who will design and construct our built environment are properly equipped to succeed in the sustainability-related careers they desire.

Augmented reality (AR) is becoming widely used in construction industry for training, education, onsite inspection and etc. In this paper, the authors developed a AR-based learning tool for construction engineering students and evaluated the impact of AR for students’ learning performance. The tool, ARBridge, was developed using PTC Vuforia, AutoDesk Revit, Sketchup, and Unity. Various types of bridge structure can be supported for learning in this tool. After completion of the tool development, 40 undergraduate students are divided into experimental group and control group to learn a mini-module on bridge engineering using the ARBridge and traditional education way. Pre-experiment and post-experiment tests were conducted for the 40 students. Result findings collected and analyzed from case-based experiment, feedback survey and interview demonstrated the suitability of the app to evidently enhance students’ learning experience and knowledge-acquisition process through application of the technology in educational settings as a supplementary teaching material in learning components of complex bridge structures.

Expertise is important in construction projects and organizations as people tend to seek knowledge from those they perceive to be experts. Frequently, engineers perceive expertise as objective and assume that experts have superior knowledge to solve everyday project problems. Expertise is defined as the perceived quality of knowledge and is known to be important for project performance. It is expected that people who have higher expertise will positively contribute to project performance emphasizing the importance of this project. Nevertheless, this research shows that expertise is not objective and that there are gender biases in the process of expertise assessment. Using survey data delivered to 855 employees in one company, the research confirms the presence of gender biases in employees’ perceptions of expertise. First, men were likely to be assessed higher on their expertise compared to women. Second, men were likely to assess women lower on their expertise compared to women assessing women. This research underlines gender biases that exist in construction and engineering workforce and emphasizes the need for cultural changes among practitioners. Finally, the research contributes to a social theory of expertise by showing that people use demographic cues (e.g., gender) to assess expertise. The research also validates inter-group behavior as explained by the social dominance theory.

Owners and agencies that build or renovate projects have a need to know how their portfolio of construction projects is performing and how to optimize future projects. However, owners are challenged with spending the time to collect and analyze the data on their history of projects, while also managing the workload of their current projects. Without historical data, owners face the difficult task of understanding what areas need improvements and how to optimize performance. Institutions, such as universities and colleges, are uniquely challenged as their portfolio of projects consists of varying project sizes, complexities, and occupants. Further, many institutions are faced with these obstacles amid budget cuts and departmental re-organizations. A model for construction portfolio management for institutions is developed and currently being tested on three institutions in the USA at different levels of maturity. Through a series of audits, interviews, and data collection from both owners and contractors across a period of 4 years and 26 institutions, the researchers developed the model. The model is a three-stage approach, with a structure for identifying the current state of performance, a framework for the ongoing collection of data as new projects arise, and linking decision-making indicators to improve overall performance. The model, results, and lessons learned from the institutions are presented to serve as examples for institutions looking to understand and improve the performance of their construction portfolio. This research can also be extended to owners outside of institutions and serve as valuable insights to contractors looking to measure their performance.

The fundamental goal of any building is to deliver value to humans. A well-designed indoor environment could enhance human comfort, health, and productivity, thus delivering high value to the building occupants. However, each occupant is different with different comfort zones or comfort levels. Thus, even the same design could offer different value to different building occupants. Therefore, the value or evaluation of an indoor environmental design should be coupled with a comprehensive understanding of human comfort (i.e., what are the factors that affect the human comfort and how important these factors are). A variety of methods have been developed to solicit information on human comfort. However, existing methods have been criticized of either not accounting for individual human factors (e.g., human sensation, human perception) or lacking real-time responses from the building occupants. Therefore, to address the gap, this paper proposes to use a physiological sensing device to capture human sensation in respond to different indoor environments, thus providing real-time information to support human-centered indoor environment design of the buildings. This paper focuses on using physiological status monitoring (PSM) devices to capture non-intrusive physiological data such as respiration, heart rate and skin temperature, pertaining to the building occupants. Experiments were designed and conducted in different indoor environmental contexts in a classroom of Florida International University. Different combinations of air temperature, relative humidity, air speed, and CO₂ levels were designed. A set of building occupants were invited to use the PSM devices to record their sensation data in different environmental settings. The results of the experiments were analyzed and compared against objective physical measurements and traditional subjective measurements. By quantitatively capturing human sensation, which is a vital factor in building design, this research has the potential to provide a better understanding of human building interaction and to facilitate human-centered indoor environment design.

Building information modeling (BIM) is relatively slow in China in the early 21st century, and its practical application was only used in one stage of a project. Accordingly, the specific application of BIM in each stage was analyzed based on the advantages and values of BIM, and then the BIM framework was established in the whole life cycle of construction projects. According to the situation of BIM in China and the successful experience of BIM development in other countries, the problems of BIM application in China were identified, and corresponding measures were put forward to ensure better implementation of BIM in the whole life cycle. This study would provide reference for promoting the application of BIM in the whole life cycle of construction projects in China.

Equipment operations account for more than 50% of fuel use as well as emission production in the construction industry. Currently construction firms have investigated into engine technologies and fuel attributes for reducing the fuel consumption, which may not be economical and can hardly be applied to the existing fleet of equipment. This paper aims to optimize the fuel use of on-road construction equipment through developing operational level fuel reduction strategies. Acceleration, speed, weight, and road slope have been investigated as main parameters influencing fuel use of on-road construction vehicles in this study. Field experimentations were conducted to collect real-world data from seven in-use heavy duty on-road construction trucks. Artificial neural network (ANN) analysis was applied to model the effect of investigated variables on fuel use rate. Considering operational factors and road conditions, optimal driving speed is determined to minimize the amount of fuel used per travelled distance. It is also verified quantitatively that fuel use will rise significantly by increasing the weight of vehicles and road slope. Mitigating idling time and reducing equipment stops are other effective means that are applicable to decrease the rate of fuel use. These operational level optimization measures can be readily used as a guideline for equipment operators to enhance the fuel efficiency of construction equipment while saving operational cost considerably.

Occupant behavior data is an important factor to advance more accurate building energy simulations. To date, this type of data has been mainly collected using the field (in-situ) observations or chamber experiments. However, occupancy data is more uniquely relevant to the context from which the data has been collected. Furthermore, in-situ observations are rather expensive and lengthy. With that said, this study proposes the use of immersive virtual environment (IVE) to collect occupant behavior data over a relatively shorter period of time. However, since longitudinal observations are not practically possible in IVEs, a spatial-temporal event-driven (STED) model, which coherently connects a series of critical events, will be used. To test this model, a pilot study employing sensors will be carried out, whereby the authors will compare the participant’s behavior in the use of window-blinds in IVE.

Virtual reality (VR) has gained reputation in many research areas. It has been increasingly employed in the area of human behavior study. For the study of occupant behavior in buildings, VR is capable of allowing researchers to study occupant behavior in non-existing or future buildings to understand and refine building functions to fulfill occupants’ satisfaction. However, doing research in VR has some limitations specially the sample size. In general, VR experiment generates a fewer number of samples compared to data from sensors a real environment (in-situ). Having a small sample size, sometimes VR data are insufficient to accurately perform further analyses. To overcome this problem, the authors utilize the potential of the Hidden Morkov Model (HMM) Baum-Welch algorithm to statistically learn the sequences and outcomes of VR data and repopulate synthetic data that are good enough for applications. The outcome of repopulated data was evaluated and compared with VR data and showed that HMM precisely estimated and generated the additional VR data.

Despite the damages experienced in the last few years due to disasters, encouraging owners and developers to invest in resiliency by taking preventive mitigation measure has been a challenge. What motivates some owners or developers to invest in resiliency measure even when they are not required but needed is not very well understood. This paper aims to understand how owners and developers can be motivated to voluntarily invest in resiliency beyond the required building code on new structures or on the existing buildings that are grandfathered to less stringent codes. A conceptual model that integrates resiliency culture, motivation, and resiliency behavior is proposed. By applying self-determination theory (SDT), the study presented in this paper is able to examine the causal relationship between resiliency culture, motivation, and resiliency behavior. Particularly, resiliency culture can be measured by individual’s perception of government’s commitment to resiliency efforts, policies and regulations, stakeholders’ involvement, communication, and competency to resiliency. SDT introduces a multidimensional concept of motivations by looking into different forms of motivation, namely external motivation, introjection motivation, identification motivation, and intrinsic motivation. Most importantly, internalization of motivation shifting from external motivation to intrinsic motivation changes the behavior from regulatory compliance to active participation in resiliency efforts. This paper extends the current research in resiliency by introducing SDT to provide a better understanding of the motivation mechanism that drives decision makers to invest in resiliency. This paper seeks to help policymakers identify the resiliency culture factors that predict different types of motivations, and allow them to develop effective strategies that increase voluntary investment in resiliency by owners and developers.

Due to the raised environmental awareness nowadays, new construction projects-especially those in sensitive areas-must comply with numerous and strict environmental regulations. In fact, it is estimated that the value of issued penalties for non-complying with environmental regulations is $237 million in 2015 alone. Relevant literature discusses issues in environmental management and hazard minimization extensively; yet it falls short in investigating environmental regulation from a contractual angle, i.e., detailing the rights and obligations of the associated stakeholders as related to environmental permits and regulations. This paper aims at providing insights into how construction contracts are impacted by environmental regulation and permitting. The first step was reviewing federal and local U.S. environmental compliance requirements. The second step was analyzing contractual provisions of the San Francisco-Oakland New Bay Bridge project as a representative case study that involved rigorous environmental requirements which were clearly reflected in the associated contractual provisions. Throughout these steps, the authors developed: (1) an extensive checklist formed of 95 questions under 11 categories that assists parties in drafting contractual provisions related to environmental regulations and permitting, and (2) a preliminary transaction cost theory framework for assisting owners in making organizational decisions related to environmental compliance. This study provides better means for owners and contractors entering into projects of critical environmental conditions to efficiently understand and draft the special provisions related to environmental compliance. Eventually, this will lead to decreasing the number of environmental disputes and penalties resulting from poor contract drafting and administration.

Traditional energy efficiency certificates for buildings, such as LEED (Leadership in Energy and Environmental Design), in spite of their worldwide success, have not yet gained the expected penetration in some developing (and less-developed) countries. Some factors contributing to such a trend include cost, complexity, and demand for new resources that may not be always available. In an effort to aid the building sector, the World Bank, which is one of the principal carbon emissions productive sectors and the user of a big amount of resources that implies high energy and water consumption, has developed a new tool called EDGE (Excellence in Design for Greater Efficiencies). This paper aims to examine the capabilities of EDGE and test if it can have qualities and features required to gain more momentum for energy upgrade in the building sector within developing countries. According to its proposal, EDGE is low-cost; has a user-friendly software to apply; and a “do-it-yourself” nature. We have focused on Colombian building construction market, and have investigated the opportunities for EDGE in three dimensions of: cost, operability, and penetrability. The opinion of energy rehabilitation and construction experts in Colombian building industry was mined through survey questionnaires and studied through a detailed qualitative and quantitative analysis of requirements for applying EDGE to building projects. Through analysis of the experts’ inputs, the paper aims to evaluate the success chance of such simplified methods in the Colombian building market.

The Construction industry is one of the most hazardous industries in the U.S. Construction workers, on a daily basis, are exposed to numerous risks while performing a range of activities involving construction, alteration, and/or repair. Dust and diesel exhaust emissions from construction equipment are considered harmful to the workers in the long run. Several studies have highlighted the ill-effects of constant exposure to diesel fumes and dust, but without directly relating the conditions at a construction site. A variety of construction activities generate tons of PM_2.5 and other dust particles which are suspended to the atmosphere. These particles pose a threat to the environment and humans alike. The method that is currently in practice measures the amount of exhaust gases released by the construction equipment and not the amount of dust and emissions the equipment operators are constantly exposed to. This paper presents a novel methodology to measure PM_2.5 concentration levels inside the operator cabin of construction equipment. The concentrations of PM_2.5 were measured using an aerosol monitor, TSI DustTrak II 8530. The measuring device was placed (1) inside the operator cabin while collecting data from an excavator; and (2) inside the DustTrak II 8535 enclosure while collecting data from an open, cabinless dozer. DustTrak II 8530. The results of this study can be used to develop studies to determine the exposure of equipment to diesel exhaust emissions.

Residential buildings contribute to a large portion of world growing energy expenditure and carbon emissions. Despite the great potential of promoting sustainable occupant behavior in reducing energy consumption in buildings, how to design and execute effective tailored energy feedback is yet to be fully explored. In this paper we adopted the concept of the behavioral inhibition system (BIS) and the behavioral activation system (BAS) from the biopsychological theory of personality to study individual’s personality traits on the sensitivities to punishment and reward. We conducted empirical studies with different intervention strategy settings in a major city in China where electricity tariffs are charged differently depending on peak and non-peak energy usage. We found that, regardless of different intervention strategies and information conveying means, occupants’ BAS award responsiveness was significantly positively correlated to their household non-peak energy usage changes during the treatment period. Similarly, occupants with higher BAS Drive scores tend to consume more energy during non-peak hours. However, no clear relationship was found between BIS scores and peak energy usage that higher electricity tariffs are generally considered punishment during peak hours. These findings expand and deepen our understanding of relationship between personality traits and behavior changes. It could help develop personality-based interventions to potentially maximize energy savings, as well as provide broad implications for energy policy making.

Previous research by the Construction Industry Institute (CII) has recognized that the shipbuilding industry has accomplished high levels of both design standardization and modularization, reaping substantial benefits. In addition, to maximize modularization benefits on capital projects, the levels of design standardization also must be increased substantially. However, the levels of standardized facility design in the upstream, midstream, and mining commodity (UMMC) market fall short of the desired criteria. As the market understands and recognizes its value more fully, the level of design standardization will increase. The CII UMMC standardization research team was established in 2017 to address this situation. In framing their purpose, the team posed this question: How can higher levels of facility design standardization be achieved in the UMMC sector? To answer this research question, first, there was a need to better understand barriers and challenges of achieving higher levels of facility design standardization in the UMMC market. Thus, this paper focuses on identifying these barriers and challenges by conducting an extensive literature review and subject matter expert interviews. The authors have concluded from this study that the key barriers and challenges rest with owners, standard and specs, engineers, mindset/culture of customization, quality vendor availability and as such. These have been further explained in later sections of this paper. Facility owner/operators, contractors, and fabricators will be the beneficiaries of this research, especially those from the UMMC Market.

Time-to-market demands frequently drive construction and retrofitting of facilities in the manufacturing and life sciences industry. Thus, using traditional design-bid-build delivery after a product, such as a new microprocessor or pharmaceutical, is fully developed is rarely a viable economic option. In many cases, this means designing and constructing a facility without knowing the full functional requirements of the building or having complete knowledge of the manufacturing processes that the facility will house. One solution to this challenge is the concept of a flexible facility, where specific building components or systems are generalized and decoupled from one another to expedite delivery. This paper, as part of a larger research effort by the Construction Industry Institute (CII), presents the findings of an extensive literature review to define the state-of-the-practice in delivering flexible facilities. Our review concludes that flexible facilities are a domain-spanning area of research that can benefit from work in industrial engineering, as well as construction management. Specifically, the principles underlying flexible manufacturing systems (FMS), concurrent engineering, and modularization directly impact the goals of flexible facility development. This information creates a point of departure and direction for future research to explore new, more holistic methodologies for identifying areas of flexibility in facility delivery.

Asset management strategies are necessary to keep buildings operational for a longer period and to avoid serious problems including deterioration or premature failures. The most fundamental function that should be carefully developed is the inventory of the different types of assets. Therefore, it is imperative that a proper classification system is needed to effectively achieve the goals of building asset management. This paper discusses the systems that are currently used to classify building assets and establishes the need for a new classification system. It then describes the development of a framework for building asset management that is based on the work breakdown structure (WBS) concept to address the shortcomings in existing systems. The framework will facilitate maintenance work assignments and allow information integration between the various phases in the lifecycle of a building. A case study will also be presented in this paper to demonstrate the capabilities of the proposed methodology.

The internet of things (IoT) is considered one of the fastest-growing topics attracting the attention of the technological world. Building internet of things (BIoT) focusses on the IP-marked components of a building, connected to the network (internet), generating and collecting data, or executing orders autonomously and sim-autonomously. BIoT encompasses various classes of applications including energy, water, building automation, security and fire protection. The success of BIoT solutions, however, relies highly on the business outcomes expected from implementing them. The present study focuses on building energy solutions (and the associated building automation applications). In an attempt to formulate a high-level and generic business model, this paper uses Osterwalder business canvas as a framework, and compiles extensive number of case studies in the city of Montréal, QC. Experts opinions are sought through survey questionnaires to enhance, validate, and verify the model, and provide an overview of the BIoT market in Montreal. Our model provides an opportunity to explore other classes of BIoT and move towards formulating generic business model canvas for IoT in building sector.

Reinforced fault diagnosis to discover inefficiency sources on energy performance of residential systems is critical for taking targeted retrofitting measures to enhance the effectiveness of energy upgrading investments. Data-driven energy benchmarking through nonparametric data envelopment analysis (DEA) has been classically adopted to locate malfunctions of energy systems with its unique capability of isolating the effects of diverse factors to differentiate overall efficiency, scale efficiency, and management efficiency. Nevertheless, extant works tend to subjectively process climate effects which could result in errors during DEA. This paper provides an empirical case to examine the reliability of two candidate methods on handling climate factors in residential energy efficiency evaluation, including the normalization-based and the weighting-based approaches. By investigating the performance of 70 single-family homes within a 3-year dynamic context, the improved robustness of normalization-based DEA approach is observed with statistical testing. It shows that the overall relative low energy efficiency is mainly due to poor management. This research intends to benefit retrofitting managers to make solid decisions.

Embodied energy of the building is sufficiently determined by buildings structure. Prior studies have examined the embodied energy of office buildings for alternative wood, steel and concrete structure frames. However, most of the studied buildings were low-rise and small-scale. The embodied energy of high-rise office buildings is still largely unknown. Reinforced concrete frame structure is predominant in high-rise buildings. The aim of this paper is thus to investigate the embodied energy demand of high-rise office buildings with reinforced concrete frame structure. The research was carried out through a critical literature review and case studies of eight high-rise office buildings from Hong Kong. The data analysis was conducted through the use of life cycle assessment (LCA) modelling tools SimaPro. The results indicate that energy embodied in material manufacturing take the largest part (about 96%) of the overall embodied energy use of the high-rise buildings, followed by transportation and on-site construction. Moreover, galvanised steel, structural steel and reinforcing bar are identified to be the top three energy-intensive building materials for reinforced concrete frame buildings. The conclusions suggest that those energy-intensive building materials are with a significant potential for the reduction in embodied energy demand. This paper profiles the embodied energy use of high-rise office buildings. The findings should help to highlight the importance of extending the energy conservation to the before-use stage of the buildings.

Economic distress and deindustrialization over the past 50 years has led to wide-spread structural abandonment in the United States, peaking at an estimated 7.2 million abandoned homes in the United States in 2012. Such large-scale structural abandonment typically necessitates removal of buildings from the landscape, typically via demolition. While expedient, demolition contributes millions of tons of debris to landfills. Deconstruction has emerged as an alternate strategy to demolition, and reduces landfilling through the increased salvage and reuse of building materials. As a result, deconstruction has been suggested as an environmentally-friendly alternative to demolition; however, deconstruction is often costlier and more time-intensive. Despite these differences, little existing literature has focused on assessing the comparative environmental, social, and economic impacts of deconstruction and demolition. This research seeks to answer the question, “What are the environmental, social, and economic impacts of building demolition and deconstruction?” and proposes a preliminary sustainable life cycle assessment framework, which is the primary contribution. The framework focuses on development of a life cycle inventory matrix for observed environmental, economic, and social aspects related to demolition and deconstruction projects. The framework was developed (1) through a comprehensive literature review, (2) interviews with demolition and deconstruction professionals, and (3) field observation and measurement of selected impact categories. Flows for the assessment framework have been proposed as (1) environmental—landfilling of debris, energy use and fuel consumption, and air/water/soil pollution; (2) economic—energy and fuel costs, equipment and labor rates, value of salvaged materials, hazardous material abatement,and tax exemption; and (3) Social—public health, worker and jobsite safety, noise, and job creation and community involvement.

Currently the majority of residential heating, ventilation, and air conditioning (HVAC) systems are being controlled by thermostats that either have a fixed schedule or temperature. This technology is not very energy efficient and can be improved by the use of smart sensors to reduce the operation times of the HVAC systems when they are not needed. The smart sensors discussed throughout this research study are based on mobile phones, select portable devices, and various smart wearable devices. These smart sensors allow for human motion detection and body/ambient temperature sensors. There are a variety of new products from various HVAC companies (e.g., Nest, Honeywell, etc.) that allow the connection of an application (app) to remotely control the smart thermostat device. These products are a step in the right direction, but smart sensors will lead to more efficient electricity use in HVAC systems. Sensors can allow for variable operation to a variety of settings, such as human comfort, climate control, performance, and cost. The sensors used for this research measured a variety of conditions, especially human temperature, and location of occupants. HVAC systems account for a large portion of the global annual total energy consumption. Future HVAC systems will use sensors to control indoor climate comfort conditions. These systems will allow a more efficient use of energy for a greater habitant comfort; further reducing the impact on climate change. Building information modeling (BIM) can be used to develop a comparative analysis for different HVAC loadings based on various smart sensors. The main objective of this research is to determine if the use of smart devices as sensors can simultaneously provide a comfortable environment and reduce the operation time of HVAC systems; which can reduce the overall cost and maintenance problems associated with fixed operation systems that currently dominate the residential market.

The use of prefabrication for buildings has been found to lead to benefits including improved efficiency in the construction processes, and reduced waste and environmental effects over a building’s life cycle. Studies of buildings’ life cycle carbon emissions (LCCa) have been conducted, but the unavailability of reliable data restricts the estimation of accurate LCCa of prefabricated buildings, making it difficult to compare the results using databases with different backgrounds. This paper aims to examine the differences among the existing databases for estimating prefabricated buildings’ LCCa. In total, 17 databases focused on construction life cycle assessment (LCA) were analyzed and three databases were compared on prefabricated building component level. Façades, kitchens and staircases of a high-rise prefabricated building in Hong Kong were selected for detailed comparison. The results show that the carbon emissions calculated using “ecoinvent” and the “ETH-ESU 96” databases are similar while the results calculated using “IDEMAT 2001” are different. The differences among the three databases are mainly caused by three reasons: the lack of enough data on construction materials, the differences in the geographical representativeness of the material extraction and electricity generation, and the inconsistent LCA system boundaries used in these databases. Based on these findings, actions are suggested to improve the comparability of different databases, namely, developing a uniform communication system for LCA databases, enriching the open LCA databases, and achieving the consistency of LCA system boundaries. This paper provides a starting point to select a suitable database for prefabricated buildings’ LCCa. It also presents an effective method to overcome the barriers to achieving comparability among different databases and benchmark the carbon emissions calculated using different databases.

To counteract the high energy consumption in buildings, different interventions are used such as improving the envelope, using building systems that are more efficient, and reducing energy demand but not enough is done to address the end users, their activities, and energy use behavior. Productivity is important in office buildings and it can be linked to occupant wellbeing. Also vital is understanding the impact of occupant behavior on energy consumption as people take action to improve their comfort indoors. Human behavior is dynamic and challenging to accurately predict. Energy simulation tools are used in the design and sizing of building systems but they do not adequately capture the occupant-related factors (values, preferences, and behavior). Agent-based modeling (ABM) approaches have been used to represent human behavior in different contexts, they have also been used to model building occupants. This paper examines selected literature on ABM for occupant behavior modeling and it also discusses the practicality of ABM to study occupant-related factors in office buildings. Through this study, recommendations for potential applications of ABM for occupant modeling in buildings are presented. The need for actual data to better represent occupant-related factors was also observed.

Buildings account for a large percentage of the energy consumption in the United States. A significant portion of this energy is used to achieve thermal comfort in buildings. Recent studies showed that occupant behavior is one of the most influential factors that affect building energy consumption. A significant amount of energy, therefore, can be saved through improving the behavior of occupants. Although a large body of studies have been conducted to better understand and improve occupant behavior, there is still a lack of research attention to identifying the occupant behavior that would achieve both reduction in energy consumption and improvement in occupant comfort. To address this need, this paper presents a machine-learning-based approach (1) to model the impact of occupant behavior on building cooling energy consumption, and (2) optimize a set of occupant-behavior-related variables for reduced cooling energy consumption while maintaining occupant thermal comfort. The research methodology included three primary phases. First, a set of buildings were modelled and simulated in EnergyPlus, with different values for occupant-behavior-related variables. Second, learning from the simulation-generated data, support vector machine (SVM)-based occupant-behavior-sensitive models for predicting hourly building cooling energy consumption, operative temperature, and relative humidity were developed. Third, using genetic algorithm, a preliminary hourly occupant-behavior optimization was conducted to determine the optimal values for occupant-behavior-related variables for achieving minimum hourly cooling energy consumption levels while maintaining occupant thermal comfort. The results showed that the proposed machine-learning-based approach can be successful in optimizing occupant behavior.

Hybrid ventilation buildings, or mixed mode buildings, represent the buildings that have the capability of running the natural ventilation and mechanical ventilation concurrently or switching between these two modes during the building operation. To establish a hybrid ventilation building with robust performance, a well-developed building control algorithm is one of the key factors that determines it. In this paper, we developed a model predictive control (MPC) strategy for maintaining an acceptable indoor environment for building occupants while minimizing the energy consumption of a hybrid ventilation building. Established based on atomic neural network models, the developed model predictive control has the capability of accurately predicting the indoor environment conditions and energy consumption in different status of hybrid ventilation operation. In the model development process, 10 prediction variables are selected first and tested to see its influence on the prediction of response we are interested in. Six variables including indoor and outdoor air temperature, the outdoor relative humidity, the season and office hour index, and the wind speed were finally incorporated into our neural network models for predictions. At last, the model validation results showed that the developed MPC could perform as expected in maintaining the occupants thermal comfort.

Home energy audits are a commonly used method to assess the performance and energy efficiency of residential buildings. In many cases these audits are offered to residential homeowners as a way to gauge the need for and possible implementation of energy efficiency retrofits. However, these energy audits are also time-intensive, and can have low benefit-cost ratios if the recommendations developed are not acted on in the form of energy efficiency investments on the part of the homeowner. Additionally many homeowners can be hesitant to conduct an energy audit, limiting the amount of homes that can be targeted for improvements. Given the increasing amount of data and information available today, particularly thanks to smart grid infrastructure, smart meters, IoT devices, reanalysis-based weather data, utility data, etc, as well as improved connectivity and communication, this offers an opportunity to utilize data-driven methods to assess the performance of a residential building. Using data-driven techniques, this research works towards an assessment tool that can be used to assess the efficiency of residential buildings without the need for a physical energy audit. Energy use data and weather data are collected for 74 homes in multiple climate zones to develop inverse models. These inverse models are then used, in conjunction with a community-level model comparisons, to detect abnormalities. These point outliers or use-pattern abnormalities may indicate an inefficiency, or a relatively lower-performing home in comparison to neighboring homes. Types of inefficiencies are identified and several case study homes are analyzed. The results of this work will help to the construction community to target homes in need of energy efficiency upgrades, ultimately motivating improved sustainability of residential buildings.

Every year approximately $50B is spent nationally to maintain the facility operations of primary and secondary educational buildings across the United States. An expanding body of academic research attributes the performance of building systems and the standard of care of educational environments with academic performance. The research indicates an investment in strategic capital improvements to educational facilities can provide value in terms of student achievement, teacher retention, and standardized test scores. Despite this awareness, America’s educational infrastructure by most accounts is underfunded. The purpose of this paper is to explore the value of plant maintenance and operations indirect expense spending at K-12 schools in the state of Arizona. A Pearson correlative analysis of facility maintenance spending and student performance in Arizona over a 5-year period, 2010 through 2015, indicates essentially no relationship exists between student performance and facility expense spending. This paper addresses the link between academic performance, categorized as return-on-assets, and facility management. The findings of this paper highlight the importance of establishing a process for prioritizing facility maintenance work orders. Moreover, the paper utilizes a process that can be used by other academic districts to assess the method by which decisions are made in support of academic facilities.

Cost is an important factor for owners and communities when considering the selection of pavement types for parking lots and sidewalks. Sustainabilty has also become an important factor. Permeable pavements, which have been shown to be more sustainable than traditional pavement types, are an attractive option given their advantages of reducing rainwater runoff, recharging ground water, and reducing the costs associated with treating storm water. A comprehensive study was conducted to analyze and compare the life-cycle costs of two conventional impermeable pavements (hot-mix asphalt and portland cement concrete) and two permeable pavements (porous asphalt and pervious concrete). The study analyzed the alternatives in 20-year, 30-year, and 40-year analysis periods. In addition to initial construction and maintenance costs, stormwater treatment costs were included in the life cycle cost analysis for all alternatives in areas that have combined sewer and storm systems. The results show that hot mix asphalt has the lowest initial construction costs, while permeable pavements are considerably more economical than impermeable pavements in terms of maintenance costs. If stormwater treatment costs are accounted for, permeable pavements are more economical for 20-year and 30-year period analysis. In the 40-year analysis period, portland cement concrete is the most economical followed by porous asphalt, hot-mix asphalt, and then pervious concrete.

Building evaluation is important part of the construction project delivery process. Through building evaluation, feedback is generated which can be utilized to improve construction of the next building. Currently, the most common building evaluation method is post-occupancy evaluation (POE). The POE is performed for a building (e.g., energy usage, building safety) and occupants (e.g., occupant satisfaction) after completion of construction. Because of that, it has time and cost limitations for the improvement of physical conditions. To reduce the limitations, recent research progress involves performance of building evaluation before the start of construction by using 3D simulation. This approach is called pre-occupancy evaluation (PrOE). This study presents an improved evaluation method to reduce the limitations of existing PrOE methods by performing the evaluation in advance. This study also categorizes the methodology and framework of existing studies in terms of building and human data and develops a comparison matrix for the various parameters used.

Analyzing performance of structural systems of bridges is necessary for optimizing maintenance cost including repair and replacement. Due to increasing number of deteriorating bridges reaching critical conditions because of age and lack of proper maintenance, advanced analytical methods are not only beneficial, but essential. The outcome of such methods leads to optimal decision-making regarding maintenance of the structure during its life-cycle. As a continuation of previous related work, which were mainly focused on replace strategies, this research pursues an approach for optimizing repair and replace in bridge maintenance in terms of schedule and type of action considering structural performance, cost uncertainty, system requirements, structure specifications, time constraints, as well as available budget. The aim of research described in this paper is to analyze condition state spectrum to determine appropriate action policies and strategies pertaining to each condition state and develop a multi-objective probabilistic method. The outcome reaches a set of efficient and effective solutions in order to minimize the cost for bridge management using a time-variant performance indicator—system reliability index. The outcome of this reliability-based optimization is a cost-action decision-making framework for the maintenance scheduling during the superstructure life-cycle. The advantage of the proposed methodology is incorporating comprehensive bridge maintenance actions into a probabilistic cost model and performing no-preference mathematical analysis. The proposed approach enables users to obtain reasonable scheduling options in order to avoid difficulties in maintenance decision-making regarding structural performance by focusing on failure and deterioration of the bridge structural components. To investigate the accuracy and validate the approach, a numerical experiment for an existing bridge structure is developed and the result is compared with similar efficient relevant methods.

Given the central role urban areas play in reducing worldwide carbon emissions, they are challenged with strategically assessing building performance and implementing optimal measures to meet carbon reduction targets on a city-scale. Current bottom-up approaches for assessing building performance are most applicable at the individual building level and challenging to implement at scale, while top-down benchmarking methods are limited in the insight they can offer to identify specific areas for building performance improvement. This paper leverages smart meter electricity data to examine an understudied component of energy use within benchmarking studies—temporal changes—to assess the potential of temporally segmented benchmarks in identifying underlying areas of building inefficiencies across a large scale of buildings. Top-down, data-driven strategies are applied to develop temporally segmented benchmarks across a community of buildings. Results show that benchmarks during various time periods are statistically distinct from annual benchmarks for the majority of buildings, indicating that for many buildings energy performance shifts temporally throughout the year. Such insights have the potential to inform energy efficiency decisions across a large number of buildings, which typically rely on annual performance data for prioritization decisions. Overall, these findings demonstrate the potential of building benchmarks segmented across time to support municipalities, building owners, and energy managers with systematically and continually identifying the most pressing areas for efficiency improvement to meet aggressive energy reduction targets.

According to the United Nations Environment Program (UNEP), by the increasing number of population in the urban area, there is an urgent need of city-level action on reducing environmental emissions. Based on the 2015 U.S. energy flow chart, buildings are responsible for around 20% of U.S. energy consumption and consequential environmental emissions. Therefore, there is a great need of a systematic national and regional observation and management plan for monitoring buildings’ life cycle energy portfolio and their environmental impacts. The objective of this research is to study the residential buildings (1-story and 2-stories) built over decades, in the City of Atlanta and observe the trend of embodied and operational energy usage and the consequential carbon emissions over building’s life cycle. In this research, embodied energy is the energy consumed by all the processes associated with the production of a building, from the mining and processing of natural resources to manufacturing, transport and product delivery. To this end, a process-based life cycle assessment (LCA) method has been utilized to calculate the embodied carbon and energy of buildings considering their construction methods and materials. For building operations, nationally averaged public datasets such as Department of Energy (DOE) and Residential Energy Consumption Survey (RECS) from U.S. Energy Information Administration (EIA) were utilized. The preliminary results indicate that there is around 26% more embodied carbon associated with newer buildings. Also, the results indicate that 2-story buildings have around 11% less embodied energy per square footage, in comparison to 1-story buildings. Additionally, newer residential buildings consume less energy per square footage over their operational life span. The result of this research, combined with the analysis of other building types and infrastructures of the city, can then be used by policy makers and city planners to improve the sustainability and energy-efficiency of this metropolitan area.

There are over 50 net zero energy (NZE) verified buildings in the U.S. in addition to approximately 280 NZE emerging buildings that have designed for and targeted net zero status, yet have not demonstrated achievement of that goal. Simply, a NZE building consumes only as much energy as can be produced from onsite renewable sources in the course of a year. With innovations in design, construction techniques, and advancement in technology, it is not surprising to see a dramatic increase in the number of NZE buildings. An additional force is the increasing number of U.S. States and local jurisdictions mandating net zero buildings. According to the New Building Institute (NBI), the number of verified and emerging NZE buildings in the U.S. has tripled since 2012. This paper aims to, first, present a summary of the definitions of NZE buildings and, second, to provide a qualitative and descriptive analysis for the factors that are essential in the development of NZE buildings. These include location, size, climate zone, energy use intensity, type of ownership, and local politics, to name a few. They are analyzed to evaluate and examine the key elements in the development of NZE buildings. The results of this study illustrate that a framework for the definition and evaluation of NZE buildings has gained more attention in certain locations than in others.

The Construction sector uses 40% of the earth’s resources, much of which ends up as “wastes” from our civilization. We can reduce resource use and eliminate demolition waste by simply reusing building materials. Some building components are easy to take apart and reuse while others require additional costs and effort. Some generate more environmental impacts during their recycling. The paper presents a study on understanding the lifecycle impact of recycling different building components and materials, thus allowing the industry to better understand the true lifecycle environmental impacts of reuse and recycling. The study compares the embodied energy, global warming potential, and water use of a wood frame and a steel frame for a manufactured home in the United States. The analysis assumes the wood frame would be demolished and rebuilt for three life cycles, while the steel frame was assumed to be continuously reused. The analysis is based on process-based life cycle analysis (LCA) and hybrid-LCA. Considerations on transportation distances and reuse rates were made. The analyses showed that, by using a cradle-to-cradle (C2C) framework, both methods generate conflicting results. The impact of the results to manufacturers, designers, policy-makers, building owners, and researchers are discussed.

Buildings worldwide contribute to around one third of carbon emissions. With the rapid urbanization process, high-rise buildings are almost the norm in high-density cities. Prefabrication will help not only reduce the carbon footprint of materials and products, but improve the efficiency of construction processes and quality of constructed facilities which should lead to substantial carbon reductions over the life cycle of the building. However, there is no consistent method of estimating life cycle carbon emissions from prefabricated buildings. The aim of this paper is to examine the implications of prefabrication for high-rise buildings’ life cycle carbon emissions (LCCa) in high-density urban environment. The research was carried out through the combination of a critical literature review, a systems survey of previous studies, and a case study with a typical high-rise building in Hong Kong. The review results suggest that, despite the burgeoning studies of life cycle carbon, inconsistent boundaries of life cycle exist with underexplored direct and indirect implications of prefabrication for carbon emissions. A systems framework of methodology is developed for examining the carbon emissions of high-rise buildings and the implications of prefabrication for the production and building process. This framework, for the first time in the life cycle literature, brings forward a multi-dimensional life cycle carbon methodology including temporal, spatial, functional and methodological variables. The case study results uncover carbon emission intensive components of the building and carbon emission intensive processes in the building’s life cycle. Several prefabrication scenarios are subsequently presented for reducing the LCCa of high-rise buildings in high-density urban environment, highlighting the aspects of utilizing low-carbon materials and adopting innovative design features.

Due to the high vulnerability of the concrete manholes to chemical corrosion, requiring a need for frequent maintenance and replacement, polymer concrete manholes are used as a substitute in water and wastewater pipelines. Polymer concrete manholes have a longer service life and more resistance to various chemical corrosives than normal concrete manholes. Despite the benefits from using polymer concrete manholes, the higher initial capital cost has been a barrier to wider application in public works. In this study, data was collected for the initial installation costs and replacement frequency to compare the life cycle costs for both types of manholes. The data was collected from the Clark County Water Reclamation District, the public entity responsible for constructing sewer pipelines in the Clark County. The scope of the cost analysis was limited to the initial capital cost of these two types of manholes used in sewer systems. An initial capital cost data (material, equipment, labor) and as well as replacement frequency data for both types of manholes were analyzed. The results showed that the life-cycle installation cost of polymer concrete manholes was significantly less than that of cement concrete manholes for this sample based on 50 years life cycle period. However, due to lack of data, a comprehensive life-cycle cost analysis of cement concrete manholes could not be conducted. The findings of this study will help water and wastewater engineers to identify the cost effectiveness of these two types of manholes.

Total emissions from the U.S. contribute 15% to the global emissions. The construction industry is a major source of the exhaust emissions produced. Use of light duty vehicles and heavy-duty trucks for various construction activities contributes 83% to the total greenhouse gases produced. Construction equipment comprises of on-road and non-road equipment. Non-road equipment is extensively used on buildings construction. Among the numerous pollutants identified on the construction site, this paper will focus on CO, CO₂, NO_x, SO_x, and PM because of their ill effects on human health and because they are produced in large amounts compared to the other pollutants. This paper summarizes the results of a research that used field data to estimate pollutant emissions from non-road equipment. The methodology for obtaining emissions using MOVES is presented. Basic information such as hours of operation per day, fuel used, and specifications of the engine are collected from a building construction site and are used for calculating total emissions. The output consists of emission rates for selected pollutants, model year, SCC number, and fuel type. The findings of this research are presented for excavators, mobile crane, and a forklift. Results indicate that CO₂ is produced in fairly large quantities when compared to other selected pollutants. The results from this study could be used by contractors and owners in the selection of the construction equipment in terms of reducing emissions.

Along with the sweeping adoption of prefabrication in the construction industry there has been increasing attention to and practice of exploring volumetric modular building technologies. While the modular approach has been reported with the benefits including shortened construction period, improved site health and safety, reduced construction waste, enhanced life cycle cost performance, lessons have also been learnt. More recently there have been cases of adopting modular construction for high-rise buildings that are a significant building type in cities. The aim of this paper is to review the 10-year journey of high-rise modular building and elicit learning for its future development. The research was carried out through a critical literature review, case studies with seven representative high-rise modular buildings constructed during the 10-year period from 2007 to 2017 selected worldwide from U.K., U.S., Singapore, Australia and China, and interviews with the project teams for verification and with industry stakeholders for consultation. The case studies together enabled a longitudinal examination of the adoption of high-rise modular buildings. Despite the available modular buildings in concrete and composite materials, steel framed solutions appear to be the norm for high-rise. Compared with the normal design decision criteria for prefabricated buildings, structural stability, wind load resistance, connection details emerge to be prominent considerations for high-rise modular solutions. While the many benefits claimed from prefabrication also apply to the use of modular building for high-rise, policy promotion, and client leadership are revealed to be the main drivers. Partnering between the client and its professional advisors and supply chains, particularly early contractors’ involvement, proves to be essential to secure project success. While there is in general premium direct building cost, cost neutrality can be demonstrated taking into account financial gains and operational savings. Learning for the future development of high-rise modular building is presented.

The concept of construction industrialization, first raised in the 1960s, refers to the transfer of on-site construction work to an off-site factory to improve quality and reduce cost, time, and safety issues. In some developing countries, industrialization of construction projects is highly recommended and generalized by governments and local construction institutions to minimize waste and pollution. However, there are concerns and constraints associated with applying this construction method. To test if industrialized construction projects have lower cost, shorter duration, fewer safety issues, and better quality, the first step is to determine how to calculate the industrialization rate. Up to now, there is no formal method available to calculate the rate of construction industrialization. The overall goal of the study is to develop such a method. To unite all of the units associated with the many construction operations and resources on a project, the researchers utilize energy consumption as a means for determining the percentages of human work and machine work. The researchers evaluate energy consumption of on-site construction workers based on surveys and literature reviews, and evaluate energy consumption of off-site concrete plants based on factory observations and data collection. The results of the analyses show that for construction activities operated on-site, construction workers consume different amounts of energy while processing different construction tasks. The findings from the research provide evidence and statistical measures to calculate the construction industrialization rate, and provide project owners/developers and construction contractors with quantitative means to evaluate and market their projects based on the extent of industrialization used to construct the projects.

Every construction project requires a continuous flow of communication between project stakeholders. However, complex project participants and team members who are responsible for regularly delivering multiple pieces of vital information to several people/entities face internal miscommunication challenges, which may ultimately lead to significant conflicts and disputes. Although incorrect and/or inaccurate transmission of data may cause major project delays and cost overruns, few researchers have focused on the prediction and analysis of communication quality in complex construction projects. Therefore, the aim of this study is to identify the contractor’s internal communication quality indicators throughout the project life-cycle. To achieve this objective, a comprehensive survey was developed and distributed among experienced practitioners. Depending on the collected type of data, appropriate statistical method was utilized. Through a factor analysis of these indicators, the number of significant variables was reduced, and the major components of the contractor’s internal communication were determined. Results indicated that there are six principal internal communication components for contractor entities: clarity, decision-making, financial support, technical issues, procurement, and execution. The contribution of this work lies in defining and improving the quality of the main elements of effective contractors’ internal communication (ECI) in complex construction projects, allowing practitioners to plan proactively, utilize project resources properly, and avoid costly miscommunications and conflicts.

Beyond the traditional economic dimension, improving energy efficiency through building energy retrofits could be also evaluated through the consideration of environmental and social dimensions. Integrating these three dimensions of sustainability—which is often called the triple bottom line (TBL) approach—for decision-making in energy retrofits could help evaluating the retrofitting project performance with a broader perspective. This study introduces the sustainable energy retrofit (SER) decision support system to select an optimum energy retrofitting strategy for a specific building, while maximizing the project’s TBL benefits. Economic, environmental and social indicators are defined and used in a multi-objective optimization model. The proposed SER decision support approach can be adapted and used in any energy retrofit project that wish to consider and optimize TBL criteria.

The economic viability of photovoltaic (PV) systems is subject to spatial and temporal uncertainties that can pose significant financial risks to the investors of such systems. This paper presents a decision-making model using Bayesian networks to assess the economic viability of PV systems, by considering the inherent spatial and temporal uncertainties and their impacts on the annual electricity generation of a PV system. The application of the proposed model is shown in a 6.5 kWh PV system installed on a house located in Corvallis, OR. Results show that by using the Bayesian networks, the probability of different states of electricity generation can be estimated and used for quantitative decision making. Furthermore, sensitivity analysis is performed to demonstrate how the key factors in the PV system can affect the annual electricity generation. The proposed model contributes to the body of knowledge in the valuation of renewable energy investments through the application of Bayesian networks. It is expected that the proposed model can help investors in PV systems make scientific and informed decisions.

Stakeholders in the construction industry continually strive to improve processes at all levels in order to achieve better performance while remaining competitive and meeting client demands. The recent and rapid level of industrialization in the construction industry necessitates stronger integration into the practice of design, planning, and management. Moreover, it is essential to understand the impact of management decisions on the performance of the systems in a building—such as architectural, structural, and mechanical—in order to achieve a high level of compatibility among the various systems in a building throughout the lifecycle of the project. However, such integration and understanding is not supported by the current practice of design in the construction industry. Thus, it is important to develop the concept of target-value design (TVD), an adaptation of Target Costing for the construction industry, in the following aspects: (1) extend the concept of values from a cost-centric system to a multiple-value system, such as incorporating cost, time, and energy consumption into the evaluation equation; (2) incorporate the performance of systems in the building, accounting for the interdependencies amongst the components of the systems, and the effect of the values on the performance; and (3) provide a method for design assessment that increases the likelihood of meeting client values, achieving a high level of performance for the building systems. Thus, this paper proposes a framework that consolidates these three aspects to provide a decision-support tool that helps decision makers in the construction industry to ensure that the end-product meets stakeholder requirements (e.g., cost), while at the same time the building systems reach more efficient performance as one holistic system.

One of the key issues in sustainable design and construction is the decision on the choice of building materials that meet the project objectives and standards, including cost, energy consumption, and environmental impacts. Decisions on the choice of building materials become more daunting because of the many available sustainable materials, and the interplay between their sustainable criteria. This paper provides a review of this problem and explores the current trends and opportunities for solving the problem. It proposes a more comprehensive framework for the integration of a decision support system (DSS) for materials selection into building information modeling (BIM). The unique component of the proposed framework is a holistic integration of cost, energy, carbon, and mechanical strength. The knowledge gap being addressed is twofold: (1) combination of sustainable design requirements with a principal mechanical property of materials, and (2) supplementing the existing limited studies on the subject. With the benefits that BIM offers in design and construction, its integration with a DSS can address the problem of materials selection while encouraging collaboration and coordination among project partners.

The California Environmental Protection Agency (CEPA) reported in 2014 that the transportation sector accounted for 26% of total reported greenhouse gas (GHG) emissions, representing one of the major contributors in all sectors. Passenger vehicles and light-duty trucks contribute more than 60% of transportation-related GHG emissions. Several guidelines are currently available by departments of transportation (DOTs) which pursue the goal of reducing single occupant vehicle travel in communities in order to reduce transportation-related GHG emissions. To date, however, these guidelines and approaches have had limited success. The California Environmental Quality Act (CEQA) has recently shifted its focus from driver delay to reduction of GHG emissions and the creation of multimodal systems. Furthermore, several states have explored policies intended to reduce GHG emissions. This research presents analysis and comparison of GHG emissions mitigation programs, including parking cash-out, employer-paid transit pass, and cap-and-trade. The present analysis is conducted for commuters with various commute travel distances and the impacts of implementing the aforementioned programs are generated from commuter and organization perspectives. Findings of implementing these programs showed promising results in reducing GHG emissions and transportation costs of students and universities. Findings also indicate that such policies can directly impact the bottom-line for businesses as well as best practices for DOTs.

In the United States, 18% of total primary energy consumes in commercial buildings. Windows in commercial buildings are responsible for 35 and 28% of heating and cooling loads respectively and 32% of the total building energy consumption. Geometrical design parameters of the window have significant impact on the building energy consumption since they define the window dimensions which interact with the light rays. Aspect ratio, the ratio of the width to the length of the window, is one of the geometrical parameters which needs more investigation in terms of their impact on building heating and cooling loads and light energy consumption. The objective of this study is to determine the optimum aspect ratio of the window in small commercial buildings in order to make balance between heating and cooling loads and lighting energy use in seven different climate zones in the United States. Small commercial buildings (i.e., less than 50,000 ft²) are selected for this study because they represent 94% of U.S. commercial buildings. To achieve this objective, first, the Hill Climbing algorithm is used to develop an optimization model. The developed model is coupled with the Energy Plus software to simulate energy performance of the building. An office building is modeled as a case study and is simulated in seven different climate zones (climate zone 1-7) in the United States. Finally, the results are analyzed and compared with the baseline model to show the energy loads and lighting energy use of the buildings having optimum window aspect ratio. In addition, based on the simulation results, recommendations are made for the designers for each of the seven climate zones.

For longevity, infrastructure (civil and building) needs to cope with any change in social and environmental states, and any change in technology that may occur in the future. Having infrastructure, with built-in flexibility, capable of addressing change and prolonging the point in time at which infrastructure becomes obsolete, would therefore appear to be sensible, provided that it can be shown to be viable, when compared with the more usual non-built-in flexibility case. The viability analysis is complicated with the necessary inclusion of the uncertainty surrounding future changes, their magnitude, timing, and costing. Heretofore, estimating the value of built-in flexibility has been done deterministically or qualitatively, or by analogy with methods derived from the financial options literature, even though it is generally acknowledged that there are shortcomings in such approaches. By contrast, this paper gives a general probabilistic treatment that overcomes these shortcomings and is generally applicable across all infrastructure types and across all change types. The uncertainty in costing as well as the economic uncertainty in intangibles related to social and environmental matters are addressed and incorporated into the calculations. With greater uncertainty, it is shown that the inclusion of flexibility becomes more viable, and flexibility leads to improved sustainability performance. Viability is examined through a comparative analysis of the built-in flexibility case versus the non-built-in flexibility case. The paper presents the background theory and illustrates this on road infrastructure examples.

The paper aims to tailor and ground the concept of systems engineering (SE) in the context of civil engineering practice. SE is a well-established discipline within other engineering fields, such as mechanics and aerospace. Compared to these fields, the civil engineering field is far more intricate. This complexity is mainly due to the following context: (1) civil systems have undefined boundaries, (2) the environment is an integrated part of the systems, (3) systems are influenced by and at the same time are influencing the users’ behavior, (4) systems are subject to a much longer lifespan, (5) future new systems need to be integrated with existing ones, (6) the current innovations in the area of technology continuously change the way the systems are designed, (7) systems are subject to public aspects, (8) systems are usually of a much larger scale, and moreover, (9) validation of designed systems is only possible through simulation of virtual prototypes and environments. In this context, we define civil SE as the acquisition of data and knowledge to support collaborative engineering through integrated modeling and simulation. It needs to focus on the holistic study of civil systems during their lifecycle by defining and identifying interfaces between the physical, social, and environmental sub-systems. The paper looks into the basic underlying concepts of SE, such as systems, interfaces, integration, modeling, simulation from the perspective of civil engineering. These concepts are not new, but the SE perspective combined with civil engineering context offers a different meaning over the one already in use. Consequently, different viewpoints over SE in civil engineering field have led to various ways of interpreting its concepts, which causes misapprehension among researchers and practitioners. Building on top of the limited existing literature this paper clarifies these concepts. Finally, the paper outlines a framework for adopting civil systems engineering.

Occupant behavior is the weakest link in the attainment of energy efficiency goals set during high-performance building designs. Environmentally responsible behavior (ERB) could be the answer to improving daily operations of these buildings. ERB is described as any action from an individual directed toward remediation of environmental issues. Previous studies suggest that ERB and perceived behavioral control (PBC) are positively correlated. This study aims to gain an understanding of energy efficient design features such as open floor designs, centralized temperature control, and radiant heating in an academic high-performance building and their relationship to building occupants’ personal comfort. A case study approach focusing on qualitative analysis was used in the present study. First, a survey, based on a pre-existing survey, containing both open- and close-ended questions was distributed to approximately 85 building occupants. Second, follow-up interviews were conducted with three facility managers to inquire about the original purposes behind building design features. The lack of control experienced by the building occupants over the thermostat posed challenges to adequately studying the correlation between ERB and PBC in this case study. The results indicate that the design features of the building were chosen to provide the highest operation capacity, but they fall short in maximizing the comfort level of building occupants in terms of temperature and acoustics. These findings confirm the complexity in combining various design features of a building into a harmonious unit for maximum functionality and comfort level of its occupants and reveal the even greater challenge when designing high-performance buildings.

Interest in and the use of permeable pavements has increased in recent years due to the potential for these systems to help alleviate storm water runoff and pollution. Communities and property owners are seeking ways to use these materials and other best management practices (BMPs) to improve sustainability. However, installation of permeable pavements has not always been successful and quality control test methods for the installer and quality assurance methods for the owner are very limited. In this study standard laboratory and field test methods for determining properties of pervious Portland cement concrete (PC) were investigated for use in design and quality control purposes. The test methods proposed in this study and the data obtained could be used by a team of designers, constructors, quality control personnel, and owners to evaluate, ensure performance, and to promote pervious concrete.

Early design decisions for complex projects are the result of a process comprising of a rotating cast of participants, decision making with imperfect information, and multiple communication paths. A change in the earliest decisions creates cascading impacts to the entire design process, for example, selecting a construction material early on restricts the balance of the design and construction process to materials and methods compatible with the construction material selected. Employing systems engineering methods assists in defining complex project processes and the potential impacts of a change to the established process. This paper explores how a system engineering tool, message sequence charts (MSC), can be used to document the early design decision process for building materials of sustainable building projects. The authors introduced MSC to two focus groups of experienced architecture and engineering professionals, and then asked the respondents to develop an MSC that documents the early design decision process for a recently designed project. The project types included higher education, private, and government clients, delivered via design-build or design-bid-build. Then, the focus group respondents were asked to consider the strategy they thought would be most effective to integrate a new sustainability requirement for building materials, such as environmental product declarations (EPD), into their project, and they documented the adjustments to their specific design process in a modified MSC. This paper elucidates how MSC support the study of complex design processes and identification of impacts that new sustainability requirements have on a standard design process. The paper specifically examines the changes required for private client design build projects to incorporate EPD. This research suggests the early engagement of a subject matter expert, either hired as a consultant, or trained in-house, is the strategy design teams will employ to effectively integrate EPD into this type of project.

Buildings account for a large amount of energy consumption in urban areas. Understanding the impacts of urban neighborhood characteristics on building energy consumption can help identify ways of how to improve neighborhood energy and environmental performance towards a more sustainable built environment. Despite the availability of many building energy consumption assessment/prediction models and tools, the majority of existing efforts mainly focus on the building scale; and the small number of neighborhood-scale analyses are typically conducted using building-scale simulations instead of taking a data-driven approach. To address these gaps, this paper proposes a hybrid machine-learning approach (Clus-SVR) that combines a support vector regression (SVR) algorithm with a clustering algorithm for predicting the building energy consumption at the building scale and the neighborhood scale based on the socioeconomic and building characteristics of the neighborhood (e.g., per capita income, average gross floor area, etc.). As a preliminary study, the proposed Clus-SVR algorithm was tested in predicting building-scale and neighborhood-scale consumption using the energy consumption data of the City of Chicago, and was evaluated in terms of mean absolute percentage of error (MAPE) and coefficient of variation (CV). The paper discusses the proposed algorithm and the performance results, and identifies the impacts of urban neighborhood features on building energy consumption levels.

Portland cement (PC) based concrete is the world’s most consumed man-made material and this consequently puts lots of demand on cement as a binder. The CO₂ gas emission during cement clinker production has placed this important material into non-environmental-friendly classification with quest for greener alternatives being on the rise. A recent study showed combination of pulverized calcined clay (PCC) and calcium carbide waste (CCW) as possible alternative for total PC replacement with resulting appreciable mortar strength but delayed setting times and lower strength than PC mortars. This paper reports on effects of PCC-CCW as alternative binder on strength properties of mortars. The mortar mixes had superplasticizers added to reduce water/binder ratio while the CCW was treated to reduce impurities with a view to improving the strength development and a bid to mitigate the observed setbacks of earlier study. The pozzolanic activity indices of the PCC was determined via x-ray fluorescence (XRF) and strength determination (strength activity index). The PCC was combined with Purified CCW to determine the binder’s strengths at varying PCC:CCW replacements to determine the prescribed mix combination for optimum strength. Improved optimised mortar strength of 13.11MPa was achieved compared to 11.89MPa in the previous study.

Stakeholder engagement has been identified as an integral element of sustainable construction projects. While the outputs for stakeholder engagement are being defined, the inputs required to, for example, “respond quickly to community concerns and perceptions” are still very vague. Building upon a recent framework for social sustainability developed by Rodolfo Valdes-Vasquez and Leidy Klotz, this case study presents social sustainability process details of a residential education center. To inform the social sustainability framework, stakeholder interviews, organization documents, and social media posts were analyzed to collect details which determine the inputs, cost, and time required to execute social sustainability processes. This case study focuses on a project led by Sustainability Inc., a non-profit dedicated to improving their local economic, social, and natural environment. Sustainability Inc. developed the Peggy’s House project to be a model for sustainable living in environmental justice neighborhoods. Through active engagement methods, over 30 local partners collaborated on the Peggy’s House project. Preliminary data has been collected, suggesting inputs, such as staff members focused on the community, can be leveraged to deliver thousands of dollars in value to a project. This paper outlines a process for developing case studies which can provide essential details about improving stakeholder engagement in construction projects.

While the literature on implementation of new technology is growing, the green attributes of the new technologies have not been fully investigated. This paper aims to present a clear gap in the literature, and present a novel model for implementation of green technologies, so called green construction technology adoption (GCTA). GCTA includes four main constructs including sustainability, innovation, user performance, and organizational facilitating condition. The structural equation modeling was utilized to analyze the data and measure the relationship of latent exogenous factors through significant constructs. The standardized regression weight of the results indicates that if the “organizational facilitating condition” construct increases for 1 standard deviation, perceived ease of use (PEU) will be increased by 0.62. In addition, if the four constructs increase for 1 standard deviation, perceived usefulness (PU) will be increased by 0.37, 0.33, 0.47, and 0.56 respectively. The results also show that 25% of PEU and 85% of PU is explained by four mentioned constructs. This paper develops a modified model to predict green technology adoption in construction projects, which is critical for manufacturers to predict the users’ perception toward their new technologies. Future work would examine the model in different contexts, such as industrial construction.

The ISO-registered industry foundation classes (IFC) data standard can facilitate building information modeling (BIM) interoperability by allowing a “one-to-many” software information flow pattern in the architecture, engineering, and construction (AEC) industry instead of the more complex “many-to-many” information flow pattern. However, even a full adoption of IFC cannot guarantee a seamless BIM interoperability, because of the flexibility allowed in adopting/using the IFC standard. Object classification in BIM is an important part of BIM interoperability. As part of an initial effort to pursue seamless BIM interoperability, the authors propose to use intrinsic geometric representations of IFC objects and geometric theorems to support the automated BIM object classification. A six-step method was proposed to develop automated IFC object classification algorithms using a data-driven approach. The method was preliminarily tested on classifying IFC objects into a cone frustum shape. The developed algorithm was successfully tested on three unseen bridge data. This shows an early promise of the proposed method to support error-free BIM object classification.

While regions like North America and Europe increasingly recognize environmentally sustainable buildings and infrastructure are financially beneficial because they offer increased property value and can improve human health and well-being, this awareness is still an obstacle in regions like the Middle East. In part, challenges stem from the high energy subsidization by governments. For example, in Kuwait, nearly 85% of electricity costs are subsidized. Another reason is education and training related to sustainability in the local construction industry. To identify how professionals in the Middle East view sustainable design and construction, preferences and values about sustainability were collected through a survey distributed to industry professionals in Kuwait (n = 131). The results indicate professionals in Kuwait, as a whole, undervalue design and construction practices that promote environmental sustainability but prioritize social sustainability principles and design features. Better aligning these preferences with the tools used during design and construction may lead to higher willingness to pursue greater sustainability achievement. For example, rating systems like LEED and Envision are filled with choice architecture, meaning the structure and presentation of options influences the decision outcome. By not aligning preferences with intent, these rating systems may inadvertently set goals that are too low thus discouraging the ambition needed to achieve sustainability performance that is technically and economically feasible. The next step of research is to bridge behavioral science and engineering by testing the effect of goal-framing, which proposes that attributes described as contrasting negative consequences of not engaging in a behavior inform choice. Based on prior goal-framing experiments, the expectation is goal-framing will help decision makers recognize environmental objectives that would otherwise be overlooked. The findings can be implemented in decision tools like rating systems that are designed by engineers who are often unaware of how the structure of choices influences behavior and decision outcomes.

Sustainability is a systems problem with interconnected socio-economic-ecological factors. To advance sustainable infrastructure, engineers are expected to more quickly think in systems from individual components to relationships between them. Until recently, understanding of cognition for sustainability was limited to investigating behavior and its outcomes. However, the emergence of neuroimaging techniques enables the collection of objective physiological data in the brain. By measuring the cognitive activation, we can construct a more detailed understanding of the mental processes during systems and linear thinking tasks related to engineering sustainability. Wearing a functional near infrared spectroscopy system, which measures changes in hemodynamic response, engineering students (n = 17) developed both lists and concept maps related to sustainability topics. The results show that systems thinking leads to more concepts generated and requires more cognitive activation in Brodmann area (BA) 46 (BA46 is associated with cognitive flexibility) while less activation in BA39 (associated with sequence and visuospatial processing). Moreover, the brain network analysis indicates the cognitive barriers for engineering students to think in systems for sustainability with lower global efficiency to cognitively integrate information and lower clustering coefficient to separately deal with information in the brain compared to linear thinking. This study is the first step in constructing a better cognition model and brain networks of systems thinking for sustainability. The next step can be how education training cognitively improves systems thinking among engineering students.

Advances in information technology (IT) have provided a continuous and reliable connection to the Internet for everyone. This factor, coupled with the widespread use of digital devices like laptops, cellphones, and tablets, have led to the emergence of “big data.” Nowadays, society is producing and using data at an unprecedented rate. Data centers are the primary place for storing, and processing data. Another important trend in IT is the emergence of cloud technology. The rapid rise of IT, the emergence of big data, and the shift to cloud technology have led to a high demand for newer and larger data centers. Data centers are industrial facilities that provide space for servers, hard drives, and batteries, where data is stored and processed. Having numerous servers that consume large quantities of energy makes heat management a critical issue. Heat, generated mostly by servers, needs to be controlled carefully and temperature needs to be maintained within a specified range. Removing excess heat means extensive use of energy resources by the HVAC systems. This constant high-cooling demand marks data centers as buildings that are especially problematic from an environmental standpoint. The LEED version 4 (v4) rating system now has a category for data centers. However, a review of LEED v4 reveals that it fails to address many sustainability factors related to data centers. By focusing only on specific issues, LEED attempts to make significant improvements to sustainability measures mainly in the sections of energy and atmosphere and indoor environmental quality. In other sections of LEED, such as Water and Site Selection, points are not allocated to specifically address data centers’ needs. In LEED v4, data centers have the same criteria as other building types. This paper identifies the potential areas for improvement in LEED v4 for data centers.

Sustainable practices have been on the rise during the last decade. From recycling to alternative energy sources, many studies have been conducted to incorporate green practices into people’s daily lives. However, cost efficiency can be a significant deterrent to begin or continue these practices. Homes are responsible for the consumption of a large portion of water in the United States. As such there is a need for more studies directed toward the assessment of the practical implementation of water efficiency. This study follows LEED v4 for homes guidelines to examine the feasibility of adopting green practices for water reduction. The paper presents a framework for a feasibility study on the utilization of efficient water fixtures in homes. The results show that the utilization of efficient water fixtures as recommended by LEED v4 for homes can be the most economic alternative on the long run.

Increased construction material demand has forced Singapore’s construction industry to turn towards DfD (design-for-disassembly) solutions. The current barriers to DfD adoption include a lack of information to ascertain the remaining structural integrity of reused DfD components. The implication is that regulatory requirements become difficult to meet. This paper addresses these challenges by leveraging on BIM (building information model) as a central data repository of component information. The contributions of the paper include identifying additional attributes to support DfD, as well as proposing a rule-based compatibility analysis. This will allow potential matches of DfD components between the current building and the future reuse to be automatically identified. A public housing project is analyzed using the proposed framework, and it is concluded that the optimal DfD strategy would be to overdesign the structural capacities by 1.25 times of a quarter (25%) of the largest columns.

The retrofit of buildings to improve energy performance represents a vast opportunity in the construction market with potential to create jobs, reduce energy demand, and achieve resultant environmental benefits. Multiple challenges need to be overcome to unleash this potential and realize the benefits of investments in improving building energy performance. While large facilities often have easily predictable energy saving potential at scales that are attractive to the financial industry, they are often pursued in a manner that achieves only “low hanging fruit” for short term economic return. As a consequence, they often fall short of their potential to be pursued as an integrative and long term solution. Small and medium sized buildings face even more challenges due to the lack of owners’ ability to manage and finance energy efficiency improvements. The goal of this research is to develop a framework that supports the continuous improvement of processes involved in energy retrofit project development for small/medium sized commercial buildings. Key elements of the framework are developed through case studies and process modeling and risk management techniques are utilized to inform decisions during the business development. Early research results examining the value of the framework in improving the business development process for energy retrofit projects are presented.

Value engineering (VE) methodology is a strategic systematic process that can bring together a multidisciplinary team of construction professionals in a workshop effort to conduct function analysis of systems to provide the owner with the best value of a project or service. Creativity is central to the success of the VE process. It aids in finding different ways to fulfill the functions of systems and in developing alternatives that are then evaluated to select better options suitable for a project. However, VE team leader may find it challenging to guide the team through VE creativity phase to produce valuable outcomes especially when sustainability goal is a requirement. Thus, this research analyzed the conventional VE methodology and proposed neuro-linguistic programming (NLP) approach to improve the VE creativity phase relative to green building design and construction. Specifically, the research aim was to remodel the conventional VE creativity phase to improve green building construction outcomes. VE course students were the research subjects. The research design was such that the control group used conventional creativity method while the experimental group used NLP method where they received training on the method before using it in creativity. Both the control and experimental groups were examined using a case study building. The students prepared VE final reports using the two methods that were then evaluated by faculty sustainability experts who rated the contribution of each of the recommended systems to building sustainability. Data analysis employed SAS v.9.4. The hypothesis was that the alternative creativity method would provide better sustainability outcomes. The results showed NLP method to be better than the conventional method and could be a useful inclusion in the VE methodology to provide better green building outcomes.