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Journal of infrastructure systems
American Society of Civil Engineers
Journal of infrastructure systems

American Society of Civil Engineers

季刊

1076-0342

Journal of infrastructure systems/Journal Journal of infrastructure systemsEISCIISTP
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    Multisource Data-Driven Approach for Predicting the Deterioration of High Mast Light Poles along Highways

    Xin WangYun Bai
    1.1-1.14页
    查看更多>>摘要：Abstract Predicting the deterioration of high mast light poles (HMLPs) can support capital planning and asset management for highway agencies, such as inspection and maintenance prioritization decisions. This paper aims to develop a data-driven framework for predicting the performance of in-service HMLPs along highways by considering multiple factors including structural and environmental factors. The proposed framework consists of a pipeline of machine learning techniques including data cleaning, feature engineering and data integration, model development, and feature importance identification. Two data-driven models (XGBoost and logistic regression) are developed with the implementation of data oversampling to address imbalanced data issues. The importance level of selected factors is identified to provide insight into the underlying influential mechanism of various factors on the deterioration of HMLP elements because of both fatigue and corrosion effects. The proposed framework is implemented for one element of HMLP as an illustrative example using structural data from manual inspection reports, climatological data (e.g., wind and snow events) from the National Oceanic and Atmospheric Administration (NOAA), and geographical locations from the Geographical Information Systems (GIS) database. The results show that XGBoost with oversampling outperforms other methods. With the implementation of oversampling, the balanced accuracy of the XGBoost model increases from 0.69 to 0.74. The average precision of the best-fit model is 0.88, representing a high level of precision in predicting positive instances correctly across all classes. Feature importance analysis indicates that cumulative time of natural wind with speed from 5 to 15  m/s (days) is the most significant factor affecting the deterioration of HMLPs (797, 1,316, and 1,716 days on average in the data set for condition states 1, 2, 3+4 respectively), followed by the cumulative time of natural wind with speed over 15  m/s (days) and distance to the nearest coastline, suggesting the significance of considering these features from multisource data. The proposed data-driven approach can predict the deterioration of each in-service HMLP by considering the large variety and complex combination of influential factors, and is expected to constitute an important basis for inspection and maintenance decision making.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Journal of Infrastructure Systems: Thirty Years and an Opportunity to Refocus

    Sue McNeilBryan AdeyPanagiotis Ch. AnastasopoulosJames C. Chu...
    1.1-1.2页
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Sustainable Infrastructure Standard of Practice: Toward a Golden Age of Infrastructure

    Michael R. SanioWilliam E. KellyBrad C. McCoyCristina Contreras Casado...
    1.1-1.5页
    查看更多>>摘要：Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Impact of Conventional and Electric Delivery Vehicles on Road Wear in Residential Areas: A Case Study in Evanston, Illinois

    Callahan M. SkilesJing YuPablo L. Durango-Cohen
    1.1-1.8页
    查看更多>>摘要：Abstract Communications technologies and e-commerce have profound effects on travel behavior, including shopping trips. Such changes are, in turn, transforming operations associated with the delivery of goods and services, and consequently, the use of transportation infrastructure, including residential roads. As e-commerce continues to increase, including the spike from pandemic-era lockdowns, an effect of the growth of home deliveries is the potential impact on pavement performance from the increased number and weight of delivery vehicles. Delivery vehicles are heavier than personal vehicles, and thus they have an outsized impact on pavement wear, especially in the case of residential streets designed for limited traffic volumes. A method of accounting for the increased heavier traffic is presented as slightly changing the pavement design such that the maintenance schedule of these roads remains the same. A doubling of the number of delivery vehicles leads to a shorter useful life of the pavement, and a corresponding increase in the surface thickness of the pavement that allows for the maintenance schedule to remain unchanged was determined to be 6.35 mm (0.25 in.). Each 6.35-mm (0.25-in.) increase in pavement surface thickness has a material cost increase of $10,874/km ($17,500/mi) of roadway for an average residential street. The analysis was repeated for the increased weight of electric delivery vehicles, and it was determined that an even greater pavement surface thickness is needed to keep the maintenance frequency consistent.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Advanced Deep Learning–Based Hybrid Rail Extraction Algorithm Leveraging LiDAR Technology

    Yihao RenChengbo AiPan Lu
    1.1-1.13页
    查看更多>>摘要：Abstract In the United States, around 1/3 of the rail network is operated by short lines. These railroads play an important role in the nation’s transportation system by serving as the feeder and distributor for the rail network, but often lack a digitized rail track inventory for timely and efficient rail asset management due to limited resources. Much research has been conducted to develop automatic rail extraction methods, since it is a critical step toward a comprehensive digitized rail track inventory. However, existing methods strongly rely on high-density point cloud data sets, sensor property and configuration, and assumptions on global features; therefore, their applications in short lines are limited, since rail tracks will travel through different terrains with various global features, and data sets owned by short lines are mostly low-density data sets with unknown sensor property and configuration. To address these limitations, this study proposes an automatic rail extraction method that can be applied to low-density data sets and is independent of sensor properties/configurations, and global features. The proposed method is tested on the grade-crossing data sets collected by the Federal Railroad Administration (FRA) with a low point density around the track bed area. The performance shows an average completeness of 97.1%, correctness of 99.7%, and quality of 96.8%. This approach helps short lines to establish their own digitized rail track inventory, allowing for effective operation planning and investment strategy, and builds the foundation for future geometry measurements and infrastructure management, thereby improving operational safety and efficiency without significant investment in high-end sensors and high-density data sets.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Why a Framework to Engineer Infrastructure System Resilience Is Necessary

    Craig A. DavisSue McNeilBilal M. AyyubKiyoshi Kobayashi...
    1.1-1.4页
    查看更多>>摘要：Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Pavement Condition Prediction for Communities: A Low-Cost, Ubiquitous, and Network-Wide Approach

    Tao TaoSean Qian
    1.1-1.16页
    查看更多>>摘要：Abstract Effective prediction of pavement deterioration is critical to forecast infrastructure performance and make infrastructure investment decisions under escalating environmental and traffic change. However, most communities often struggle to undertake such predictive tasks due to limited sensing capacity and lack of granular data. With the pavement condition rating (PCR) data generated from artificial intelligence (AI)-powered computer vision technologies and multiple openly available data sets, we propose a low-cost and ubiquitous approach to predict system-level pavement conditions using nine communities across the US as an example. In addition to predicting absolute PCRs as was done in classical models, we develop another set of models to predict the change in PCRs over any time increment (i.e., time lapse between a PCR observation and retrofit decision point) and compare the results. The findings showed that the proposed low-cost prediction approach yields results comparable to existing studies, demonstrating its promising application in supporting pavement management. Furthermore, the PCR change model indicates that, besides current PCR, weather, road classification, socioeconomics, and built environment attributes are important to predicting PCR change. The interactive impacts also show salient interactive effects between variables and current PCR, offering suggestions on better allocating the limited resources in pavement maintenance projects. Finally, the proposed model could enhance climate resiliency and transportation equity during the pavement management process.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Green Project Finance for Infrastructure and Building Construction: Instruments and Benchmarks

    Yunping Liang
    1.1-1.7页
    查看更多>>摘要：Abstract It is counterintuitive that both the practice and research on green project finance for infrastructure and building construction are ascendant and still have limited precedents, considering that individually, the two parts (i.e., project finance and sustainability in the built environment) are both familiar to the communities. To narrow the gap and facilitate the financing of the built environment’s sustainable transformation, this study systematically reviews the common instruments for financing green infrastructure and building projects. Benchmarking questions distinguishing the profile of green project finance from common construction project finance are developed based on the literature review and then are used for empirical benchmarking with comprehensive financial data. In addition to yielding affirmative answers to the benchmarking questions, the benchmarking indicates that there is no evidence providing green project finance of infrastructure and building construction the immunity from the common critic, that is, greenwashing.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Resilience Assessment of Urban Water Distribution Networks under Disturbance Influence of Aftershocks

    Jiajia WuDonghui MaWei WangZhitao Fei...
    1.1-1.14页
    查看更多>>摘要：Abstract Water distribution networks (WDNs) are essential for urban water supply and postearthquake recovery. Conducting a seismic resilience assessment of a WDN and taking corresponding improvement measures can improve the disaster resistance capacity of the water system. A number of previous studies have evaluated the seismic resilience of WDNs, but seldom have taken into account the impact of aftershock disturbances. Aftershock disturbances may aggravate the damage to water distribution networks, prolong the repair time and reduce the recovery ability of WDNs. This study presents an improved framework for assessing WDN resilience considering aftershock disturbances. The stochastic principle and the elliptic ground vibration attenuation model were utilized to determine the spatial distribution of site ground vibration under the mainshock and aftershock. A superposition damage assumption was applied to incorporate aftershock effects in Monte Carlo simulations, and the pressure-driven analysis (PDA) and discrete-event simulation (DES) models were used to analyze the postearthquake hydraulic balance and model the restoration process. By constructing various scenarios, the probabilistic characteristic parameters of resilience indexes and the relationship between WDN resilience metrics and parameters related to aftershocks were investigated. A case study of a real WDN in China demonstrated that there is a correlation between aftershock-related parameters and resilience indexes. Moreover, relying solely on one resilience metric is insufficient for comprehensively understanding the seismic capacity of WDNs.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers

    Simulation-Based Evaluation of Resilience-Enhancing Measures for Transportation Systems Subject to Hydrometeorological Hazard Events

    Hossein NasrazadaniBryan T. AdeySaviz MoghtadernejadAlice Alipour...
    1.1-1.22页
    查看更多>>摘要：Abstract This paper identifies the essential requirements for simulation-based approaches such that these approaches serve as effective decision support tools for evaluating the effectiveness of climate-adaptation measures that enhance the resilience of transport systems against hydrometeorological events. These requirements include the ability to capture the effect of different types of measures, the spatial and temporal possibilities of their execution, their aggregate effect when executed together, and the effect of uncertainties in their evaluation. A novel simulation-based approach that meets the identified requirements is presented, and its application in a case study is showcased. The presented approach uses a set of interacting probabilistic models to generate numerous scenarios, each representing chains of cascading events from the occurrence of a possible hazard event, the impact on the assets and the network, restoration of the infrastructure, and the temporal evolution of its service. The models enable capturing the effect of resilience-enhancing measures on the intensity of hazard events and their ensuing consequences. The case study includes a road system in Switzerland comprising 605 km of roads and 121 bridges and subject to rainfall events leading to flooding and landslide. Twenty-one portfolios of measures combining four specific types are considered, and their effect on resilience was evaluated. Those include flood protection walls, stormwater retention basins, raising road embankments, and temporary flood barriers. The proposed approach enables infrastructure managers to engage in an appropriate quantitative evaluation to better devise and plan measures with the aim of cost efficiently improving resilience.
      原文链接:
    • NETL
    • NSTL
    • Asce-Amer Soc Civil Engineers