Journal of Performance of Constructed Facilities

This research arises in the context of establishing a global inspection system based on previously developed individual expert systems for 12 types of elements used in the envelope of current buildings. It focuses on the rational homogenization of repair techniques in a global classification list. Twelve individual lists of repair techniques were the basis for the development of the proposed classification list, for which four harmonization criteria were considered. Those criteria include limits for merging and grouping repair techniques to reach a simultaneously concise and comprehensive list. Considering the proposed classification and the fieldwork data from the validation samples of the expert inspection systems, the frequency of the prescription of repair techniques is analyzed. Two techniques stood out: cleaning and the application of a new (adequate) cladding/finishing coat over the existent/replacement. Moreover, the relationship of repair techniques with defects in different types of building elements is also analyzed. Besides the previously mentioned techniques, two other repair works are highlighted: replacement or reapplication of the cladding/glazing and treatment of cracks or other holes in the cladding.

Long-span bridges face various threats every day due to their sophisticated operational environments. To investigate the operational state of bridges, a real-time dynamic warning method on the abnormity of cable-stayed bridges is proposed based on deflection measurements. The generalized Pareto distribution (GPD) model and finite-element (FE) calculation are used to determine the basic warning threshold. Considering the complicated components of the monitoring deflection signals (e.g., measurement noise, thermal effect, and vehicle load-induced effect), each signal component should be further modeled and investigated to improve the accuracy and effectiveness of the warning system. Because thermal effects are usually not the signal component of interest that may cover the signal fluctuation induced by abnormity, they should be separated from the raw signals. Then, in view of the variations of operational condition over time, the warning threshold is updated termly according to the operational period by using statistical approaches. Finally, the effectiveness of the proposed warning methodology is validated by analyzing the recorded deflection data from the third Nanjing Yangtze River Bridge. As a result, the proposed dynamic warning method is more effective than the conventional static one and will help bridge management departments identify emergencies in time and take inspection or maintenance decisions to ensure structural safety.

This paper presents design and installation details and full-scale test results for a prestressed mechanically fastened fiber-reinforced polymer (MF-FRP) retrofit solution that restores the original operating and inventory rating of prestressed concrete C-channel bridge superstructures with prestress losses due to concrete deterioration and steel corrosion. A retrofit solution that can be installed rapidly and immediately restores prestress losses is desired to minimize impacts on commerce, public transportation, and emergency services. Six 9.41-m (30-ft) long C-channel beams were tested for three-point bending to failure. The results of the experimental study indicate that the MF-FRP retrofit is capable of immediately restoring deteriorated C-channel beams with a 36% reduction in capacity from the original operating and inventory ratings. In this study, the reduction in the capacity of the C-channel beams was induced in the lab by cutting the bottom strand of each stem of the C-channel beam to simulate total prestress losses at the point of maximum internal moment. Further, the results of the experimental study indicate that the examined MF-FRP retrofit solution can be installed in 4.1 labor hours per retrofitted C-channel beam. Therefore, a four-worker DOT maintenance crew can install the retrofit on up to seven beams in a single eight-hour workday. A layered sectional analysis can be used to predict the flexural capacity of retrofitted C-channel beams with very good accuracy.

The failure of Shanghai Metro Line 4 in 2003 was one of the most striking accidents in the history of subway construction in China. It involved the first breach failure of a cross passage being mined by an artificial ground-freezing method, followed by a massive ingress of water and soil, dramatic ground subsidence, rapid sinking of existing structures, failure of the adjacent dike and floodwall along the Huang-Pu River, flooding of the site, and collapse of buildings and metro tunnels. The accident directly resulted from failure of the cross passage being excavated within a confined aquifer. In the beginning, artesian water broke the frozen mass; then, water and soil gushed into the cross passage and metro tunnels. As a result of massive ground loss, the ground level underwent significant subsidence up to 4 m and those preexisting structures were damaged. Inherently, this event was a typical project management failure, associated with a number of procedural and ethical blunders. To rebuild the destructive failure case, this paper outlines the design and construction for the cross passage along with the geological conditions, describes those preceding events incurring the failure, depicts the catastrophic scene, and introduces the postfailure emergency responses and disaster-relief measures. Finally, technical, procedural, and ethical factors leading to the failure are summarized.

Structural health monitoring represents an efficient way to diagnose the condition of cable-stayed bridges. Most studies assessing the condition of cable-stayed bridges and detecting damage to them have been developed to monitor the longitudinal performance of bridge bearings. However, few studies have aimed to detect the damage to tension pendulums, which are usually tie-down cables that resist girder uplift from auxiliary piers. This study aims to develop an effective method for detecting the damage of tension pendulums in cable-stayed bridges using structural modal frequencies. First, the sensitivity of the bridge frequency to tension pendulum damage is derived according to the Rayleigh method. Then, a finite-element simulation of a cable-stayed bridge is conducted to validate the rationality of the frequency index. Finally, a case study on tension pendulum damage is carried out for the cable-stayed Yonghe Bridge. The results indicate that the frequency change is far more sensitive to the damage of the tension pendulums than to the damage of the stay cables. The failure of tie-down cables will result in a substantial decrease in the bridge frequency, up to approximately 35% for the first vertical bending mode of the bridge. In practice, the damage of tension pendulums can be effectively detected by a sudden decrease in the measured frequency of cable-stayed bridges.

Enhanced flood hazard due to global warming and climate change imposes an additional threat to safety and serviceability of river crossing bridges. This study proposes an integrated approach to assess how climate change might affect bridge performance under multihazard conditions involving floods and earthquakes. The approach is used for an existing bridge spanning over the San Joaquin River, California. The multihazard impact considering climate change is evaluated in terms of risk and resilience of the bridge. Future flood projections under climate change are obtained from general circulation model simulations in conjunction with a macroscale hydrological model. Enhanced intensities of future design floods are observed to cause higher expected scour at around bridge piers. This resulted in significant rise in risk ($-21\%$) and drop in resilience ($-14\%$) of the bridge, when compared to no climate change scenario, at a specific seismic hazard level. To reduce possible consequences, ripraps are applied around piers as a climate change adaptation measure. Size of the riprap is determined based on the maximum expected design flood flow at the bridge site over the projection period. The applied adaptive measure is observed to be cost-effective through a cost-benefit analysis performed over the remaining bridge service life.

Precast concrete frames have been widely used, though little is known about their fragility under the combined influence of seismic excitation and corrosion. In this study, one four-story precast concrete frame with different corrosion levels is taken as an example, which is simulated by using a multiscale finite-element model consisting of solid elements for corroded beam-column joints and beam elements for beams and columns, respectively. A fiber model is proposed to simulate the hysteretic behavior of corroded steel bars by employing the user-defined material subroutine in Abaqus. The proposed multiscale finite-element model is validated through existing experiments, so that a balance between accuracy and computational costs is obtained. Based on the proposed finite-element model, the influence of corrosion on seismic fragility of the frames is investigated through incremental dynamic analysis. Four limit states regarding the maximum interstory drift ratio are defined to evaluate seismic fragility. The analysis results show that structural responses are highly random under different ground motions and corrosion levels. Meanwhile, the seismic fragility of the frame is significantly influenced by corrosion ratios, and the probabilities of exceedance show exponential growth with the increase of corrosion level for all four limit states.

The deterioration of reinforced concrete bridges due to environmental stressors is proven to adversely affect their strength and durability over time. This primarily originates from the penetration of aggressive ions, leading to the corrosion of steel rebars embedded in concrete. A range of factors, such as temperature, humidity, and precipitation, have a direct impact on this process and can greatly influence the corrosion initiation time. In the United States, the Midwest region is known to experience long winters, requiring multiple applications of deicing salts to keep the roadways open. The amount of deicing salts used on an annual basis has witnessed constant growth, while the climate change is believed to have intensified the exposure conditions. To investigate the deterioration of bridges serving the roads in the Midwest region, a computational framework is developed to predict the corrosion initiation time based on regional climate data obtained for the three major cities of Chicago, Minneapolis, and Des Moines. In addition, a rigorous sensitivity analysis is performed to evaluate the contribution of various input parameters based on the Sobol indices. In the absence of any similar studies on the bridges in the Midwest region, this investigation predicts the extent of vulnerability of the region’s bridges to deterioration based on historical climate data, as well as future forecasts. From the simulation results, the impact of climate conditions on the crack width and time duration to reach the durability thresholds has been quantified. With the possibility of an extension to other cold climate regions, the outcome of this study is expected to help transportation agencies optimize their maintenance and repair actions, which will not only improve the condition state of the bridges in service but also reduce the time, effort, and investment needed for the management of a large inventory of bridges.

In the fields of concrete structure maintenance and emergency demolition, high-pressure water jet breaking technology shows a multitude of advantages, having broad application in future. The propagation rule of internal cracks in concrete is the fundamental issue of the high-pressure water jet concrete-breaking mechanism because it is related to the accuracy and safety of the technology and can promote its further development. In order to observe the propagation of cracks in concrete intuitively, transparent concrete-like materials with precracks were built in this study, and the transient process of broken area evolution and crack propagation under water jet impact in time and space was recorded with the help of a high-speed camera system. The results show that the existence of precracks significantly increases the efficiency and degree of water jet fracture, which manifests increasing the number of cracks, promoting the development of cracks in all directions, and enhancing the penetration speed. The vertical precracks can guide more failure in the axial direction of the water jet, and the horizontal precracks are beneficial to the crack propagation in the radial direction. More secondary cracks can be generated from the precracks, which will consume much more energy in the initiation and propagation of these cracks, resulting in the inadequate development of erosion hole dimension, compared to the concrete without precracks.

There is a global research trend to enhance condition assessment of the concrete infrastructure by the development of advanced nondestructive testing (NDT) methods. Computer vision–based systems have been developed to detect different types of defects in both regular and thermographic images because these systems could offer a timely and cost-effective solution and are able to tackle the inconsistency issues of manual assessment. This paper investigates the performance of different deep neural network models to detect main concrete anomalies, including delamination, cracks, spalling, and patches in thermographic and regular images captured from a variety of distances and viewpoints. These models were trained and tested using images taken from a century-old buttress dam and validated in images captured from the decks of two concrete bridges. The results showed that the MobileNetV2 had promising performance in the identification of multiclass damages in the thermal images, identifying 79.7% of the total delamination, cracks, spalling, and patches on the test images of highly damaged concrete areas. The VGG 16 model showed better precision by reducing the number of false detections.

Existing bridges are aging and deteriorating rapidly, elevating concerns for public safety and preservation of these valuable assets. Large numbers of bridges exist in transportation networks, and the current budget limitations worsen the situation. This necessitates the development of an automated condition assessment and rating methods. Spalling is a common problem that majorly influences the health, safety, and structural integrity of bridges. The present study introduces a self-adaptive three-tier method for the automated detection and assessment of spalling using computer-vision technologies. The first model introduces a newly-developed segmentation model that adopts a multiobjective invasive weed optimization and information theory-based formalism of images for spalled concrete detection. In the second model, an integration of singular value decomposition and discrete wavelet transform are integrated for the efficient feature extraction of information in images. Additionally, the Elman neural network is coupled with the invasive weed optimization algorithm to enhance the accuracy of the evaluation of spalling severities by amplifying the exploration-exploitation trade-off mechanism of the Elman neural network. The third model is developed for the purpose of structuring a rating system of spalling severity based on its area and depth. A computerized platform is developed using C#.net language to facilitate the implementation of the developed method by the users. The results demonstrated that the developed multiobjective spalling segmentation model is capable of improving detection accuracy of spalling by 12.29% with respect to the region growing algorithm. It was also inferred that the developed quantification model outperformed other prediction models, such that it achieved a mean absolute percentage error, root mean-squared error, and root mean squared percentage error of 4.07%, 76.061, and 0.065, respectively, based on the original dataset. In this regard, it is expected that the developed computer-vision-based method can aid in establishing cost-effective bridge condition assessment models by transportation agencies.

Current strategies for prioritizing bridge preventive maintenance, rehabilitation, or replacement (MRR) include predicting future conditions by delineating depreciation rates from existing conditions and preventive MRR activities. Such predictions are overly conservative because element interactions, although present, are not considered in quantifying bridge deterioration. This study proposes a novel prioritization mechanism that leverages time-dependent element interactions, referred to as coactiveness, in predicting bridge performance resulting from MRR activities. The proposed coactive model hypothesizes that if one repairs one element, it should reduce the deterioration of other elements. The improved elements in turn reduce the deterioration of the repaired element, improving the overall health of a bridge. The element-level bridge inspection data from three southeastern US states (Alabama, Georgia, and Florida) are investigated to illustrate the capability of the proposed mechanism. In Georgia, the results show that changes in the condition of expansion joints are most critical to the long-term performance of bridge elements. Alabama’s bridge management strategy slows the depreciation of expansion joints when more MRR resources are allocated to its deck elements. It is concluded that early preventive maintenance implemented in Florida is effective and has a similar effect as leveraging the proposed prioritization mechanism in enhancing bridge long-term performance.

A live-load test was conducted on an in-service bridge containing flat precast concrete slabs. The purpose of the test was to evaluate transverse load distribution and efficiency of the longitudinal slab-to-slab joints. The precast slabs spanned $4.6\mathrm{m}$ (15 ft) and were $1.7\mathrm{m}$ (5.5 ft) wide. Slab-to-slab joints consisted of V-shaped interlocking shear keys. The live-load test measured vertical displacement of the slabs at several critical locations under a crawling ($<5\mathrm{mi}/\mathrm{h}$) loaded dump truck. From the deflection data, joint efficiency and experimental distribution factors for moments (DFMs) were calculated. The test results demonstrated that the joints were no longer capable of distributing loads transversely, and each slab acted independently. Based on the test results, it is recommended that 0.55 should be the minimum distribution factor used when calculating moment demand.

Deformations due to environmental and mechanical loads in curved bridges can lead to fairly complex long-term effects. Instead of the one-dimensional longitudinal movement that occur in straight bridges, in curved bridges two-dimensional movements, i.e., longitudinal and transverse, need to be considered in the design stage and throughout the structure’s life span. Both deformations are related to the curvature and construction materials used in the bridge. Currently, both guided and nonguided bearings commonly are deployed to accommodate the movement and stresses caused by thermal movements in curved bridges. Bearings usually are oriented along the chord from the fixed piers of the bridge in current design practice. However, this traditional orientation is not compatible with bridge movements at each pier, which can induce excessive stresses in both superstructure and substructure. This study monitored and investigated a steel twin-box girder bridge. The fracture-critical bridge analyzed in this study lies on four horizontal and three vertical curves. Guided and nonguided expansion pot bearings are utilized, except on the fixed pier. Extreme temperature changes caused transverse superstructure movements and damage to the bearing guiding system. The monitoring system outfitted on the bridge recorded the temperature distributions as well as the bridge movement. The structural movement behavior due to temperature variation was studied, and the investigation of existing damage showed that both transverse and longitudinal movement were excessive and that the resultant forces transferred from superstructure to substructure were significant. The results indicate that a refined analysis always is required to account for curved bridges’ deformations in order to prevent structural damage.

Many anomalies and problems in modern construction do not result in spectacular collapses but in other, more commonplace situations such as the entrance of water or certain dysfunctions of use. The reduction of these circumstances leads to an increase in service life and a decrease in expenses resulting from nonquality. This research resorted to a data source that was very difficult to access and compile (court sentences from complaints by private individuals) in order to better understand the reality in construction that leads building owners to resort to the courts of law. The study was carried out on roofs (both flat and pitched roofs) so as to determine their specific types of damages and underlying causes. Specifically, 100% of all cases existing in a European country in a complete period of six years were analyzed, allowing a complete X-ray of the situations that were reported. The complexity of the situation resulted in the identification of 84 different types of pathology processes.

Deflection and displacement in building components such as beams and roofs occur under imposed loads or element weight during constructing or operation of buildings, and should be less than allowable values. The detection and measurement of deflection predominantly are conducted based on visual inspection, which is known to be time-consuming, costly, and error-prone. The authors used image processing techniques to detect the location of maximum deflection and measure its value. The perspective of color images was eliminated, and then they were preprocessed using spatial domain filters. Afterward, image segmentation, in combination with nonlinear regression, was used to calculate the equation of the deflection curve of an element. Finally, the location and amount of maximum deflection were determined by calculating the derivative of the deflection curve. The proposed method was validated through two experiments. The method estimated the amount of maximum deflection with high accuracy—the relative errors of the two tests were 6.6% and 0.2%.

The goal of this research is to evaluate whether it is possible and effective to detect honeycombing of concrete pavement using a ground-penetrating radar (GPR) during construction. The motivation is that identifying honeycombing of concrete during construction would help avoid the spread of consolidation problems in large pavement sections, which are costly and time consuming to repair. GPR has been used as a tool for concrete quality control and detection of delamination in reinforced concrete elements since the 1980s, but it has not been used for the early detection of relatively small air voids. In this project, first, preliminary field testing was conducted to determine the possibility of detecting honeycombs in existing concrete pavement. Then, air voids of different sizes, shapes, and depths were artificially created using spray-foam in several laboratory specimens and detected using a high-frequency GPR antenna at different times after concrete placement. Cores were extracted to validate GPR readings and determine the capability of this technique. Another field testing was conducted to evaluate the efficiency and economy of using GPR as a nondestructive quality control tool. Field and lab test results indicated that GPR could be efficiently used to detect air voids as small as 32 mm (1.25 in.) and as deep as 102 mm (4 in.) from the surface of the concrete pavement as early as the initial set of concrete. These findings suggest that GPR is an effective, efficient, and economic quality control tool for this application.

Timber-based hybrid structures provide a prospective solution for utilizing environmentally friendly timber material in the construction of midrise or high-rise structures. This study mainly focuses on structural damage evaluation for a type of timber–steel hybrid structure that incorporates prefabricated light wood-frame shear walls into steel moment-resisting frames (SMRFs). The structural damage of such a hybrid structure was evaluated through shake table tests on a 4-story large-scale timber–steel hybrid structure. Four ground motion records (i.e., Wenchuan earthquake, Canterbury earthquake, El-Centro earthquake, and Kobe earthquake) were chosen for the tests, with the consideration of three different probability levels (i.e., minor, moderate, and major earthquakes) for each record. During the shake table tests, the hybrid structure performed quite well with visual damage only to wood shear walls. No visual damage in SMRFs and the frame-to-wall connections was observed. The correlation of visual damage to seismic intensity, modal-based damage index, and interstory drift is discussed. The reported work provides a basis of knowledge for performance-based seismic design (PBSD) for such timber-based hybrid structures.

In this study, the construction deficiencies affecting performance of hospitals during the 2017 Sarpol-e Zahab earthquake in Iran were studied through a field survey and numerical assessment. The inadequate bracing of infill walls, façades, and false ceilings, as well as the improper infill wall materials were the nonstructural deficiencies identified through the initial field survey. Improper spacing and anchoring of the reinforcement, unanticipated frame-infill interaction, and low concrete strength were also identified as the major drawbacks of structural members. In the numerical assessment, the results of the concrete coring tests were utilized to establish an as-built nonlinear model whose response was compared with the as-designed model for evaluation purposes. For this purpose, the models were initially pushed to a target roof drift and were then subjected to nonlinear response history analyses under various levels of the Sarpol-e Zahab earthquake. The ductility demands undergone by some members of the deficient as-built model were shown to surpass the counterpart values of the stronger as-designed model, while a nearly 17% reduction was observed in the maximum base shear due to the construction deficiencies.

Identifying and understanding potential nonconformities in different construction phases is key to ensuring the anticipated quality and performance of a building in its service period. Previous studies mostly focus on studying nonconformities in the handover or posthandover phases of building projects. There has been relatively less attention paid to the issue in the preconstruction and construction phases of building projects, particularly in densely populated South Asian countries. This study aims to identify the potential and critical nonconformity problems from the initiation to construction phases of building projects, with a particular focus on Bangladesh, where the quality and integrity of building construction works and practices are generally lacking. The study is informed by a comprehensive literature review of the topic, followed by a series of discussions and workshops with highly qualified and experienced experts to identify the potential nonconformities frequently encountered in building construction projects. Additionally, three building projects are studied to identify the instances of nonconformities and their root causes. The major nonconformities identified from this study are improper soil investigation, poor quality of materials, poor quality of concrete, improper alignment of structural members, insufficient concrete cover, lack of or no curing of concrete, defective formwork, and early removal of formwork. Subsequently, specific remedial actions are recommended for the individuals/organizations involved throughout the building construction phases in developing countries, such as Bangladesh, toward improving the quality and performance of buildings in their service lives.

Assessing the condition of sewer pipelines is essential for addressing associated problems as a result of deterioration to maintain functionality and avoid additional social costs. This paper presents the development of a defect-based condition assessment model for sewer pipelines. The model aims to cover the structural, operational, and rehabilitation defects that are associated with the pipeline, joints, and maintenance holes on pipe segments. The analytic network process (ANP), which considers the interdependencies between pipeline components and defect types, was used to deduce the relative importance weights through questionnaires and interviews with infrastructure experts and professionals. The model employs the defects’ severities to develop fuzzy membership functions based on a predefined linguistic condition grading scale that would precisely indicate the degree of distress. Hierarchical evidential reasoning (HER) and the Dempster-Shafer (D-S) theory were used to integrate the defects’ conditions and to evaluate the overall condition of sewer pipelines, which is represented as a crisp value calculated by the weighted average defuzzification method. A validation dataset was used in the model validation and protocol verification. This model is expected to minimize the inaccuracy of sewer condition assessment through the application of severity, uncertainty mitigation, and robust aggregation. It could also benefit asset managers by providing a precise condition overview for maintenance, rehabilitation, and budget allocation purposes.

Infrared thermography is a cost-effective nonintrusive testing approach to assess surface and near-surface distresses, such as asphalt pavement surface cracks. However, the raw data collected by thermal cameras cannot be directly used for pavement surface distress inspection. Thus, advanced thermal image processing methods are desirable for extracting indicators of hidden flaws. The objective of this research was to develop an integrated system that combines infrared imaging, high-resolution visual imaging, real-time image processing, and data-rich analytics for automated inspection to support decision making for pavement preservative maintenance. This work developed a code that can integrate the characteristics captured by both thermal and visual images to provide a quantitative identification of the surface cracks and their severity. Field-test data were collected and a statistical analysis was conducted to correlate temperature gradient to the surface crack profile of asphalt pavement. It was found that the surface temperature distribution pattern has a direct correlation with pavement crack profile, and can be used as an indicator of crack depth. The proposed real-time thermal imaging-based system was found to be feasible for field inspection, and the three-dimensional (3D) crack profiling method can help produce fairly accurate measurements to enable fast and easy decision support for pavement preservation practices.

The limited efficiency of current supports has led to serious support system problems in loess tunnel construction, which are mainly noted in arch distortion, shotcrete cracking, surface subsidence, and even total structural failure. A novel type of support, called the steel-concrete composite support system (SCCS), is proposed in the present study via an in-depth analysis of support failure cases in China’s loess tunnels. Additionally, it places emphasis on the enhancement of the primary lining, which consists of three bearing layers: (1) the arch layer, (2) the reinforcing skeleton layer, and (3) the concrete packed layer. The new type of support can provide greater supporting capacity by closing the excavated space immediately after the new arch has been installed, and it can then be strengthened by grouting and the installation of molded concrete. The hyperstatic reaction method (HRM) model and three-dimensional numerical model were established using ANSYS software, and the results demonstrate that the SCCS outperformed the conventional support system in terms of both structural safety and load-bearing capacity. It was also found to achieve superior practical worthiness with flexibility and efficiency during the tunneling process, which indicates that the new support system is much more reliable for bearing more variable loads and dealing with severe deformation in loess tunnel construction.

Train derailments caused by buckled or broken rail continue to be both a safety and economic concern for North America’s railway industry. These track failures are often attributed to excessive axial stresses in continuous welded rail (CWR) caused by thermal stresses under daily or seasonal variations in temperature. Improved monitoring systems, with the capability of detecting axial stress in CWR, are needed. The distributed nature and long-distance measurement ranges offered by fiber-optic sensors (FOS) may offer a potentially optimal solution for rail stress monitoring. This paper investigates the ability of two FOS systems (based on Rayleigh and Brillouin backscatter) to measure axial strain in rails under various boundary and environmental conditions. The performance of three alternative fiber types, differing based on ruggedness and installation effort, were also tested in the interest of creating an optimized field monitoring system. The effect of temperature on strain measurements led to the development of thermal correction factors for each analyzer/fiber combination. The application of this monitoring system in the field was then explored using both systems on a CWR track in Ottawa, Canada.