Journal of Infrastructure Systems

The highway alignment optimization (HAO) process is a complex combinatorial optimization problem in which several conflicting factors, such as highway costs, user preferences, and environmentally sensitive factors, must be simultaneously considered. In previous studies, single-level and bi-level optimization approaches were developed to optimize three-dimensional highway alignments. One drawback of previous approaches is that environmental factors, such as vehicular emissions, were not adequately considered in conjunction with other factors (such as user preferences and highway costs) in the optimization process. This paper builds on our previous studies and proposes two separate approaches for considering environmental emissions in the HAO process. The first approach involves a separate analysis of user and decision-maker preferences, in which a conceptual formulation of various environmental factors is presented. In the second approach, a novel tri-level optimization framework is proposed for optimizing highway alignments. At the upper level, optimization is performed using the traditional criteria of cost minimization. At the intermediate level, total systems emission is calculated. Finally, at the lower level, the user equilibrium traffic flow is optimized. The developed approaches are illustrated through case study examples. The proposed approaches will be beneficial for designing highway alignments when considering environmental emissions. Future studies may make additional refinements to the formulation and sensitivity analyses.

Oil and gas pipelines transport millions of dollars of goods worldwide every day. Even though they are the safest way to transport petroleum products, pipelines do still sometimes fail, generating hazardous and irreparable environmental damages. Many models have been developed in the last decade to predict pipeline failures and conditions. However, most of these models were limited to one failure type, such as corrosion failure, or relied mainly on expert opinions. The objective of this paper is to develop a fuzzy-based model to predict the failure type of oil pipelines using historical data of pipeline accidents. The model was able to satisfactorily predict pipeline failures due to mechanical, operational, corrosion, third-party, and natural hazards with an average percent validity of 83%. This research contributes to the body of knowledge by developing a robust failure type prediction model for oil pipelines using a fuzzy approach. The model will assist pipeline operators to predict the expected failure type(s) in order to take the necessary preventive actions.

In accordance with European Policy, management, maintenance, upgrading, and repair of existing infrastructures play a very important role in their optimal use. Availability and access to information regarding the track-support structure, switches, crossings, and rails may efficiently lead to timely identification of the needs for maintenance and/or renewal. In the context of the previously mentioned considerations, a monitoring and assessing performance-quality (MAP-Q) framework has been developed for railway infrastructure, which aims to provide the railway operators and managers with global and complete knowledge on the condition of infrastructure and enable the maintenance process in the most effective way to achieve a three-fold objective, as follows: (1) increase performance of the component or te network overall, (2) achieve a coherent and consistent network with a harmonized level of performance, and (3) prevent deterioration in the short-term or long-term as a result of its usage. The framework is structured in six criteria, as follows: (1) performance/speed, (2) safety, (3) comfort, (4) maintenance cost, (5) operability/reliability, and (6) overall condition, and allocates to them 54 primary and 112 basic indicators, associated to the track, structure, and equipment. The methodology for quality assessment of the railway infrastructure was implemented on the railway network of Greece (Hellenic Railways). Analysis of the results showed that (1) the central division network has the highest performance indices in almost all criteria, and (2) the southern division network is inferior to those of central and northern Greece in speed/performance, comfort, maintenance cost, and general condition, owing to the older age of the three elements that compose the infrastructure (i.e., track, structures, and equipment). Such a comparison provides useful information towards harmonized upgrading and development of the network, minimizing the disadvantages of remote regions, and assuring the interoperability of the network throughout the area under analysis. If adjusted to the specific requirements and priorities of a railway authority, the framework can be merged to the decision-support mechanism, which is responsible for the maintenance of a high-quality-performance network.

This study compares the cradle-to-gate greenhouse gas emissions (GHGs), energy use, water use, and potential environmental toxicity of conventional (Conv), glass powder (GP), and alkali-activated slag (AAS) concrete and mortar. The comparison is based on $1{\mathrm{m}}^3$ of concrete/mortar with similar 28-day compressive strength, so the same concrete/mortar member with same dimensions may be manufactured from Conv, GP, or AAS materials and used for same applications. The result shows that compared to a 35-MPa Conv concrete, a 35-MPa GP concrete has, on average, 19% lower GHGs, 17% less energy, 14% less water, and 14–21% lower environmental toxicity. A 35-MPa AAS concrete has 73% lower GHGs, 43% less energy, 25% less water, and 22–94% lower effects for all environmental toxicity categories except an 72% higher ecotoxicity effect. Environmental impact reductions are also found for using GP as a cement replacement in concrete with lower strengths and replacing cement with GP or AAS in mortars with different strengths. The paper concludes that using alternative cementitious materials GP and AAS as cement replacements could significantly reduce the environmental impacts of cement-based products.

The costs of acquiring parcels by condemnation are usually significantly higher than those of property acquired by negotiation, suggesting that right-of-way (R/W) acquisition costs may best be described by two different regression equations. This paper develops a switching regression model of acquisition cost to simultaneously predict the probability of whether a parcel will go to condemnation rather than be acquired through negotiation and the corresponding acquisition costs under these two regimes. The error terms of the selection equation and the two cost equations follow a trivariate normal distribution to reflect codependence on unobserved factors (such as a land owner’s tenacity or a site’s view value). When applied to the properties acquired across the state of Texas for transportation probjects between 2008 and 2011, the results of this switching regression model suggest that R/W appraisers and staff should pay special attention to parcels in commercial use involving a partial taking with a relatively small remainder and located in more urbanized areas. Comparison of cost estimates between the two regimes (condemnation versus negotiation) suggests that condemned parcels will have, on average, 78% higher acquisition costs and 51% greater price variation across the 1,710 acquired properties. These results suggest that it is much more costly to acquire a property and more difficult to accurately predict its costs if it cannot be acquired through negotiation. The application of model estimates to an example corridor highlights the value of simulation to capture all modeling uncertainties.

This paper presents a cost-benefit analysis of mobile terrestrial laser scanning (MTLS), specifically in highway infrastructure (HI) applications using data and requirements from the western United States. MTLS can be used for rapid data collection in a digital point-cloud format. This data can then be analyzed for mapping and feature inventory in several applications including asset management, preservation, maintenance, and operational planning performed by State Department of Transportation agencies. In this paper, data and requirements related to some of the operations of Washington State Department of Transportation and the California Department of Transportation are used as the basis for this cost-benefit analysis.