Transportation Infrastructure Resilience Research Articles

A Data-Driven Seismic Fragility Model for Post-Earthquake Repairable Performance of Highway Curved Bridge Portfolios

The rapid assessment of seismic fragility for highway curved bridges is crucial for enhancing the seismic resilience of transportation infrastructure. However, commonly used performance limit states fail to fully capture post-earthquake rehabilitation requirements. To address this, this paper proposes a data-driven, system-level seismic fragility assessment method for post-earthquake repairable performance of highway curved bridge portfolios. A sample database of curved bridge portfolios is generated using uniform design (UD) and a parametric finite element program, which then drives machine learning (ML) algorithms to develop a seismic fragility prediction model for post-earthquake repairable performance. The model is used to analyze the influence of various structural attributes on the median values of fragility curves (mR) for curved bridges. Additionally, a simplified fragility estimation method is developed based on the analysis results, and its reliability is validated through typical case studies. The results show that the central discrepancy of the UD sampling method is 0.0649, providing reliable and comprehensive data support for the ML prediction model. The fragility prediction model based on an artificial neural network (ANN) exhibits favorable fidelity and robustness. Curved bridges with central angles (α) in the range of 00.5rad show significant variations in mR, with a coupling effect observed between α and column height (H). The median absolute percentage error (MAPE) of the simplified fragility parameter calculation formula is below 11%, offering a preliminary reference for assessing the post-earthquake repairable performance of curved bridges.

Statistical and machine learning models for predicting spalling in CRCP

Continuously reinforced concrete pavement (CRCP), crucial for the resilience of transportation infrastructure owing to its continuous steel reinforcement, confronts a critical challenge in the form of spalling—a distress phenomenon posing a threat to pavement durability and overall structural integrity. The detachment or breakage of concrete from the surface compromises CRCP’s functionality and raises safety concerns and escalating maintenance costs. To address this pressing issue, our study investigates the multifaceted factors influencing spalling, employing a comprehensive approach that integrates statistical and machine learning techniques for predictive modeling. Descriptive statistics meticulously profile the dataset, emphasizing age, thickness, precipitation, temperature, and traffic parameters. Regression analysis unveils key relationships, emphasizing the significance of age, annual temperature, annual precipitation, maximum humidity, and the initial International Roughness Index (IRI) as influential factors. The correlation matrix heatmap guides feature selection, elucidating intricate interdependencies. Simultaneously, feature importance analysis identifies age, Average Annual Daily Traffic (AADT), and total pavement thickness as crucial contributors to spalling. In machine learning, adopting models, including Gaussian Process Regression and ensemble tree models, is grounded in their diverse capabilities and suitability for the complex task at hand. Their varying predictive accuracies underscore the importance of judicious model selection. This research advances pavement engineering practices by offering nuanced insights into factors influencing spalling in CRCP, refining our understanding of spalling influences. Consequently, the study not only opens avenues for developing improved predictive methodologies but also enhances the durability of CRCP infrastructure, addressing broader implications for informed decision-making in transportation infrastructure management. The selection of Gaussian Process Regression and ensemble tree models stems from their adaptability to capture intricate relationships within the dataset, and their comparative performance provides valuable insights into the diverse predictive capabilities of these models in the context of CRCP spalling.

Natural and natural-anthropogenic measures for adapting transport infrastructure to climate change

The purpose of the study is to analyze and develop natural and natural-anthropogenic measures for adapting transport infrastructure to climate change. The analysis was based on national and international regulations, best practices in the development and implementation of technical, organizational, natural and natural-anthropogenic measures for adapting transport infrastructure facilities to a changing climate. Although technical adaptation measures can be seen as the basis for ensuring safety against climate risks, the adoption of complementary or alternative nature-based measures will allow effective adaptation to be achieved more cost-effectively based on sustainable and long-term solutions. In some cases, technical adaptation measures are clearly determined, which largely deprives decision makers of flexibility when choosing a set of measures for a specific territory. Thus, hybrid solutions combining natural and technical measures can provide an optimal level of safety, taking into account the environmental impact, the area required to accommodate adaptation means, and the magnitude of costs.Current engineering adaptation measures used at transport infrastructure facilities have been identified. With the exception of a number of procedural changes to current practice, most current measures are technical solutions. It has been established that complementing technical and organizational measures with natural and natural-human adaptation measures has the potential not only to provide ecosystem services that could increase biodiversity and ecological connectivity, but also to ensure the resilience of transport infrastructure to climate change. The widespread use of these adaptation measures will make it possible to position railway transport as a reliable, sustainable and environmentally friendly mode of transport.

Quantifying the vulnerability of road networks to flood-induced closures using traffic simulation

Disruptions in road networks can significantly impact traffic flow, necessitating the identification and mitigation of vulnerable components. This study presents a methodology to assess the vulnerability and robustness of road networks, addressing the research gap in comprehensive approaches that effectively evaluate both controlled intersections and uncontrolled/free-flow highway segments. The proposed framework employs traffic simulation tools to model road closures within designated study areas, focusing on networks in Qatar. Performance measures such as average control delay and volume to capacity ratios are utilized to calculate vulnerability indices for network components. The two-pronged approach quantifies the impact of simulated closures at both the component and network levels, revealing critical intersections and road segments that markedly affect network performance during disruptions. The findings contribute to the field by providing transportation engineers with an effective quantitative tool to detect vulnerabilities in their road network, guiding design plans and actions to mitigate the potential harmful impacts of disruptive events on transportation infrastructure. The methodology's scalability ensures its applicability to various operational contexts, offering significant insights for transportation planning and infrastructure resilience. By establishing a comprehensive vulnerability analysis framework, this study enhances the understanding and management of road network vulnerabilities in complex urban environments. Further research on integrating dynamic traffic assignment and real-time data is recommended to further enhance the predictive accuracy and applicability of the proposed framework, ultimately improving transportation infrastructure resilience.

Seepage interaction mechanism of crossing tunnels and existing tunnels: Model test and numerical analysis

High-density urban tunnel engineering produces strong spatial seepage and stability interactions of newly built and existing operational tunnels, which is critical to the safety and resilience of transport infrastructure. Previous research mainly focused on the mechanical response of adjacent tunnel construction and the active deformation control of surrounding rock, while little consideration is given to the influence of spatial intersecting tunnels on the seepage field distribution, especially in water-rich regions. This paper investigates the seepage interaction of crossing tunnels and existing tunnels using dedicated seepage tests and corresponding numerical analysis under different hydrodynamic head heights and spatial crossing forms. The schemes are designed based on the Kexuecheng Tunnel in Chongqing City, China, which is a typical small spacing highway tunnel that crosses five existing railway tunnels in complex hydrogeological environment. According to the results, the seepage funnels generated by intersecting tunnels will overlap each other in space, causing significant changes in the seepage field within the impact area. When the newly built tunnel above-crossing the existing tunnels, the water pressure on lining structure of the small interval tunnel can be reduced by 20 ∼ 30 %. While the impact of the existing tunnel on the seepage field of the new tunnel is mainly reflected in its upper part. The construction of new tunnels is equivalent to adding seepage paths to the upper or bottom of an existing tunnel, reducing its water pressure by 10 ∼ 30 %. The spatial overlap effect will significantly reduce the water pressure at the intersection of tunnels, but also exacerbates the asymmetric distribution of water pressure in small spacing tunnel. According to the W-shaped spatial distribution of the seepage field in small spacing tunnels, the predicted seepage influence range may exceed 80 ∼ 100 m. When the newly built tunnel above-crossing or under-crossing the existing railway tunnels, the water inflow of the small interval tunnel and the overlying tunnel can be decreased by 10 ∼ 30 % compared to the situation without crossing. However, the overall groundwater discharge further increases by 53.9 %. The seepage interactions of newly built tunnels and existing tunnels could provide support for both alignment design and construction of newly built tunnel, and service performance improvement of existing tunnels.

Optimizing Tsunami Evacuation Routes in Padang City, Indonesia: A Transportation Infrastructure Resilience Approach

Optimizing Tsunami Evacuation Routes in Padang City, Indonesia: A Transportation Infrastructure Resilience Approach

A framework for decarbonisation for bridge owners, engineers and designers

The Net Zero Bridges Group brings together bridge specialists concerned to lower the carbon dioxide footprint of their work, and to understand collectively how best to do so. Achieving net zero carbon dioxide by 2050 is the best way to mitigate the severity of the climate emergency. In addition to social consequences, failure will make ensuring the climate resilience of transport infrastructure increasingly difficult. Bridge engineers must rapidly develop new knowledge and skills, and commit to gradual but steady decarbonisation compatible with agreed climate pathways and timelines. Prioritising decarbonisation requires making different decisions to those traditionally made. The carbon dioxide reduction hierarchy asks that measures be prioritised to ‘avoid, switch and improve’. Applying these to bridge engineering requires bold choices, while managing risk effectively. The project life cycle must be rethought to allocate sufficient time at the right time. Above all, the challenge requires collaborative, collective action, to share data and best practice, rather than working in isolation. This paper sets the above in an overriding framework for action, and provides an overview of current thinking for decarbonising bridge construction and maintenance. It identifies priorities for the industry to tackle within the next few years.

A probabilistic framework for the resilience assessment of transport infrastructure systems via structural health monitoring and control based on a cost function approach

The essential role of transport infrastructure systems for economic development, territorial cohesion and social transformation is widely recognized. However, key structural components of this systems, such as bridges, are rapidly aging, while the loading conditions to which they are subjected are evolving to become increasingly severe, for instance, due to changes in vehicle loads, climate crisis, etc. These circumstances contribute to reduce the level of reliability and safety of these vital infrastructure systems. Therefore, assessing the current state and predicting the future condition of transportation infrastructure, and protecting it against external hazards, proves essential. This paper focuses on an in-depth study of the role of structural control and monitoring in improving the structural resilience of transportation infrastructure as a life-cycle indicator. Subsequently, a novel framework based on a cost function approach is introduced, recognizing that the benefits of enhanced resilience come with associated investments. This enables stakeholders to assess the balance between initial investments and long-term gains, facilitating informed decisions on control and monitoring to ensure structural resilience.

Lower-bound shakedown solutions for transportation infrastructures subjected to moving harmonic loads: A focus on saturated subgrade support

As a valuable tool, the shakedown analysis technique can be used to evaluate the long-term resilience of transportation infrastructures subjected to dynamic vehicular loads. In this paper, we introduce a 3-D analytical model that faithfully replicates the geometric complexities inherent in real-world transportation systems. Rather than utilizing the total stress field, modifications to the existing shakedown limit determination methods are executed by focusing on the effective stress field within saturated subsoil. This refined methodology is specifically designed for multi-layered transportation infrastructures like road pavements and rail tracks built over saturated subgrade soils. Upon validation of both the analytical model and the enhanced method for calculating shakedown limits, a systematic investigation into the role of various parameters is conducted. These include the strength ratio, embankment height, and dynamic loading characteristics such as speed and frequency. Subsequent numerical analyses reveal that both the strength ratio and embankment height markedly influence shakedown limits within defined boundaries. Additionally, a comprehensive consideration of load speed and frequency is imperative for an accurate shakedown behavior assessment of the infrastructure in question. The findings validate that the proposed approach offers a more rigorous framework for the optimized design and safety evaluation of transportation systems comprising saturated soil layers.

Inclusive climate resilient transport challenges in Africa

Delivering sustainable and inclusive low-carbon transport is a critical to reducing greenhouse gas emissions and achieving the United Nations Sustainable Development Goals. Yet transport infrastructure is vulnerable to the effects of climate change in low-income countries in Africa. This paper explores the status of inclusive mobility and climate-resilient transportation in Africa, focusing on the perceptions and importance amongst key stakeholders, their incorporation into existing practices, and the priority given to making transport more inclusive and climate resilient. A nested scale approach was used that included an online continental survey of 136 respondents from 17 African countries; 2 country-level Focus Group Discussions in Uganda and Zambia; and city-level semi-structured interviews with key stakeholders in Lusaka and Kampala using the Delphi method. In addition, an online spatial questionnaire (Maptionnaire) was used to locate where infrastructure improvements were needed, and two city workshops held in Lusaka and Kampala. Providing more active travel infrastructure was a priority for both government and non-governmental groups. This is not connected to climate resilience but to immediate priorities of road safety and health. Our surveys highlighted that climate resilience and inclusive mobility policies are in place, but poor implementation and lack of transparency were undermining outcomes. Upgrading existing infrastructure was more cost-effective and workable than developing new robust alternatives. Lack of knowledge exchange was limiting agencies efforts to tackle this growing challenge. The paper underscores the need to raise awareness of relevant options to improve the climate resilience of transport infrastructure and expand accessible mobility solutions to tackle issues of inclusion and equity in African cities.

Performance Measure–Based Framework for Evaluating Transportation Infrastructure Resilience

Despite many organizations recognizing the need for more comprehensive resilience planning for transportation infrastructure, the United States still lacks a standardized planning framework to guide these decisions and prioritize improvements. Therefore, this paper develops and demonstrates the application of a flexible resilience framework that supports transportation resilience decision-making across multiple operational and infrastructure systems. This Performance-based Resilience Evaluation Procedure (PREP) framework calculates comparable resilience scores and can be implemented for any type of transportation infrastructure to assist transportation agencies and community stakeholders in making informed decisions in relation to project prioritization, risk mitigation, asset management, and design for more reliable infrastructure. The PREP framework, comprised of 12 steps organized in five phases, calculates resilience as a weighted probability of hazard events and the impacts of such hazards on measures of performance. Having such a framework is crucial because it allows stakeholders to develop the data-driven knowledge necessary to deliver informed management and planning of the entire transportation infrastructure system against disruptive events.

Resilience surface for quantifying hazard resiliency of transportation infrastructure

Resilience assessment of transportation infrastructure is a crucial aspect of ensuring the continued functionality of a city or region in the face of various disruptions. However, these infrastructures are also vulnerable to various types of disruptions, such as natural disasters. The ability of transportation infrastructures to withstand and recover from such disruptions is referred to as their resilience. This research presents a comprehensive framework to develop the resilience surface for assessing the resilience of transportation infrastructure such as bridges, roads, and tunnels. The framework involves the identification of the unique damage configurations through performing the fragility analysis, and the restoration of the infrastructures through developing recovery curves for each damage configuration by considering the relevant restoration data. The framework also considers the inherent uncertainty in the hazard intensity, modeling uncertainty, and restoration process. The framework is illustrated through the application to a case study of a highway bridge in Canada. The aim of this paper is to provide a useful tool for decision-makers to evaluate and improve the resilience of transportation infrastructures.

Development of decision-making system measuring the resilience level of highway projects

AbstractThe recent increase in the frequency and intensity of disasters has damaged and disrupted transportation infrastructures, thereby significantly increasing the economic losses and slowing the pace of recovery. Resilient infrastructures ensure functionality with minimal discontinuity, but there currently exists rarely a tool for assessing the resilience level of existing transportation infrastructures so that the information can be used to make future constructions more resilient. This study aims to identify the significant dimensions for measuring the resilience of transportation infrastructures and to utilize the dimensions to develop a decision-making tool that can be used to assess the level of resilience. A survey supported by a comprehensive literature review was conducted, and statistical tests were performed on the collected data. It was found that network characteristics (length of the link, number of lanes, number of optional routes, etc.), organizational characteristics (time to start reconstruction work, knowledge of the employee, resilience measurement experience, etc.), and information related to data (previous data availability and data accessibility, etc.) have major impacts on the resilience of transportation infrastructures. Based on the impact of statistically significant indicators, a resilience measurement tool was developed that provides a relative resilience score for projects and reveals how each statistically significant dimension affects the resilience. The outcome of this study will help decision-makers and practitioners prioritize their projects for resilience enhancement activities and provide funding accordingly.

Evaluation of Flood-Vulnerable Pavement Network in Support of Resilience in Pavement System Management

Transportation systems play a pivotal role in the nation’s economic and societal development. Transportation assets, such as pavements and bridges, are inevitably subject to the effects of climate and environment. These stressors mainly include flood, precipitation, heat, wildfire, and wind. Specifically, more extreme weather events, such as hurricanes and snowstorms, have occurred in recent years. This requires stakeholders to better prepare transportation infrastructure resilience in planning, design, construction, and management. Its importance is manifested through nationwide policy and state-level practice. For example, in Bipartisan Infrastructure Law, the FHWA directs all state DOTs to incorporate resilience in their transportation asset management plans. A critical element in resilience is to evaluate the effect of climatic or environmental stressors on facilities’ performance. This study examines the impact of flood on the TxDOT-managed pavement network. It proposes a method to evaluate the flood-vulnerable pavement network in the context of resilience. First, the GIS tool is used to overlap a 100-year frequency flood with the road network to identify weak pavement sections subject to flood risk. Second, a simulation is run to determine sections affected by flood over a 10-year analysis horizon. Then, different deterioration models are used to predict the network-level pavement performance, to reflect (1) normal deterioration without flood, (2) optimistic accelerated deterioration under flooding, and (3) pessimistic accelerated deterioration under flooding. It is found that the network-level pavement will experience varying levels of performance reduction, owing to a 100-year flood impact. The quantified performance change can serve to enhance infrastructure resilience preparation for more reliable pavement system management.

Framework for assessing infrastructure resilience and prioritizing resilience enhancing measures

This work presents a framework for assessing the resilience of transport infrastructures and prioritizing resilience enhancing interventions. This framework has been developed in the context of the FORESEE project which is funded by the European Union's H2020 Programme and aims to provide reliable tools to improve the resilience of transport infrastructure. The developed framework is intended to help, at the strategic level, infrastructure owners and operators to assess the resilience of transport infrastructures, identify opportunities to enhance resilience, and inform policy and investment decisions. It is structured as a set of sequential steps through which supporting methods and tools are provided to assist users.

Using Big Data Analysis in increasing transportation infrastructure resilience

Transportation infrastructure plays a vital role in supporting economic activity and ensuring the resilience of communities. This study examines the interconnection of socio-economic effects and the transportation infrastructure resilience in a country in the context of possible disruptions. The results of the study suggest that exploring the relevant socio-economic indicators and monitoring them might help increasing transportation infrastructure resilience by reducing the impact of disruptions on economic activity and improving access to essential goods and services. Additionally, the study finds that the socio-economic effects of transportation infrastructure are complex and multifaceted, and that a comprehensive approach is needed to fully understand and address the challenges posed by disruptions to transportation systems. Overall, the study emphasizes the importance of transportation infrastructure for community resilience and highlights the need for continued investment in this critical infrastructure.

A Systematic Review: To Increase Transportation Infrastructure Resilience to Flooding Events

This study investigated literature databases of Google Scholar and Scopus from 1900 to 2021 and reviewed relevant studies conducted to increase transportation infrastructure resilience to flood events. This review has three objectives: (1) determine which natural hazard or natural disaster had the most vulnerability studies; (2) identify which infrastructure type was most prevalent in studies related to flood resilience infrastructure; and (3) investigate the current stage of research. This review was conducted with three stages. Based on stage one, floods have been extremely present in research from 1981 to 2021. Based on stage two, transportation infrastructure was most studied in studies related to flood resilience. Based on stage three, this systematic review focused on a total of 133 peer-reviewed, journal articles written in English. In stage three, six research categories were identified: (1) flood risk analysis; (2) implementation of real-time flood forecasting and prediction; (3) investigation of flood impacts on transportation infrastructure; (4) vulnerability analysis of transportation infrastructure; (5) response and preparatory measures towards flood events; and (6) several other studies that could be related to transportation infrastructure resilience to flood events. Current stage of studies for increasing transportation resilience to flood events was investigated within these six categories. Current stage of studies shows efforts to advance modeling systems, improve data collections and analysis (e.g., real-time data collections, imagery analysis), enhance methodologies to assess vulnerabilities, and more.

A GIS-based approach for estimating community transportation exposure and capacity in the context of disaster resilience

Transportation is a critical sector for communities. It is, however, particularly vulnerable to climate change, and a disruption in its infrastructure impacts the whole community. Enhancing the resilience of transportation infrastructure is vital for reliable and sustainable functionalities, and subsequently, to more resilient communities. There are indices and frameworks that assess and evaluate transportation resilience and performance, ranging from component-based, to network and system metrics. The existing approaches, however, usually overlook location and capacity of critical transportation components. These two characteristics possess significant effects on the resilience and performance of the transportation sector. Moreover, the stress type and its magnitude should be incorporated in the resilience assessment. In this work, we leverage a recent resilience quantification framework to compute the Exposure and Capacity-based Transportation Resilience Index (EC-TRI), describing the resilience of the transportation infrastructure, focusing on the location and capacity of certain assets. We argue for the adoption of this index as a complement to existing frameworks, and we develop a web-based GIS framework to evaluate EC-TRI for communities within New Jersey (NJ). The novelty of EC-TRI lies in its consideration for the stress level, the exposure and capacity characteristics of transportation assets, as well as in its practicality and scalability. Users can leverage EC-TRI to locate the weak and vulnerable components within the transportation network, and to provide a community-based assessment of the resilience level of the transportation infrastructure. In addition, we provide EC-TRI as a highly scalable GIS framework, providing users with the ability to adjust the quantification components as per local needs and priorities.

Resilience measurement in highway and roadway infrastructures: Experts' perspectives

This study aims to identify the factors that affect level of resilience of transportation infrastructure from different points of view, including construction, and managemfent as well as factors of resilience related to resources, investment, and funding. To fulfill the purpose of the study, a survey was developed. Results indicated that not only the physical characteristics of a roadway segment but also the characteristics of the construction and management of the roadway influence the level of resilience of transportation infrastructures. Also, knowledge and experience of the management team responsible for the roadway will influence the level of resilience of transportation infrastructures.

Evaluation of Structural Performance of Pavements under Extreme Events: Flooding and Heatwave Case Studies

The recent increase in the frequency of extreme weather events has raised awareness and interest in the need for transportation infrastructure resilience. In this paper, the issue of pavement resilience is discussed with the goal of refining the idea for its use in pavement design. It is argued that one critical knowledge gap to advancing the state of the art in this area is distinguishing between functional and structural resiliency. The arguments here are framed using floods and heatwaves to demonstrate the importance of structural resilience. Under extreme event disruptions, structural damage is inevitable. The case study simulations in this paper suggest, depending on the pavement structure, intensity, and frequency of flooding events over the analysis period, that pavement rutting performance can decrease by 15.5% in the case of a structure with sand subgrade and 18.8% in the case of a structure with clay subgrade. In the case of heatwaves, the increase in rutting was found to be 2.9% in a structure with sand subgrade. To move toward more resilient pavement infrastructure, it is important to continuously monitor pavements after extreme events, develop methodologies to predict their performance, incorporate the findings in the current pavement management systems, and adapt design and management strategies accordingly. Future design and management of pavement systems should consider both structural and functional resiliency. This study shows that pavement performance simulations predict a long-term decrease in structural performance as a result of extreme events.