Road Network Layout Planning based on Evaluation of Connectivity and Asset Criticality

State of the art research in ensuring transport infrastructure resilience focuses on adopting a network perspective. However, there is no comprehensive, widespread method for evaluating connectivity and proposing alternative routes to improve it. Presented herein is a framework that: assesses road network connectivity, using a “closeness” measure and focusing on routes passing by the vulnerable asset of bridges; and proposes the development of optimal alternative routes, using a genetic algorithm. The results showed a significant improvement of network connectivity and the potential of the method to serve as the basis for updated transport infrastructure planning practices.H2020 Programme MG7-1-2017 Resilience to extreme (natural and man-made) events, under Grant [769255] ‘‘GIS-based infrastructure management system for optimized response to extreme events of terrestrial transport networks (SAFEWAY)’’

COST Action TU 1406 quality specifications for roadway bridges (BridgeSpec)

Roadway bridges, being one of the most critical road infrastructures components, require regular maintenance actions. Therefore, it becomes important to define strategies to maximize societal benefits, derived from the investment made in these assets. Consequently, this investment should be planned, effectively managed and technically supported by appropriate management systems, supported in quality control plans. For this purpose, authorities need to produce an asset management plan which should, not only define the goals to be achieved by exploiting the roadway bridge network, but also identify the investment needs and priorities based on a life cycle cost criteria. Additionally, a proper condition assessment of these assets must be conducted to support the decision-making process regarding their preservation. A COST Action recently started in Europe with the aim of standardizing the establishment of quality control plans for roadway bridges. This paper describes this Action and, particularly, its most recent developments. MaintenanceThis article is based upon work from COST Action TU-1406, Quality specifications for roadway bridges, standardization at a European level (BridgeSpec), supported by COST (European Cooperation in Science and Technology)

A Review of Probabilistic Methods of Assessment of Load Effects in Bridges

This paper reviews a range of statistical approaches to illustrate the influence of data quality and quantity on the probabilistic modelling of traffic load effects. It also aims to demonstrate the importance of long-run simulations in calculating characteristic traffic load effects. The popular methods of Peaks Over Threshold and Generalized Extreme Value are considered but also other methods including the Box-Cox approach, fitting to a Normal distribution and the Rice formula. For these five methods, curves are fitted to the tails of the daily maximum data. Bayesian Updating and Predictive Likelihood are also assessed, which require the entire data for fittings. The accuracy of each method in calculating 75-year characteristic values and probability of failure, using different quantities of data, is assessed. The nature of the problem is first introduced by a simple numerical example with a known theoretical answer. It is then extended to more realistic problems, where long-run simulations are used to provide benchmark results, against which each method is compared. Increasing the number of data in the sample results in higher accuracy of approximations but it is not able to completely eliminate the uncertainty associated with the extrapolation. Results also show that the accuracy of estimations of characteristic value and probabilities of failure are more a function of data quality than extrapolation technique. This highlights the importance of long-run simulations as a means of reducing the errors associated with the extrapolation process

A bridge network maintenance framework for Pareto optimization of stakeholders/users costs

For managing highway bridges, stakeholders require efficient and practical decision making techniques. In a context of limited bridge management budget, it is crucial to determine the most effective breakdown of financial resources over the different structures of a bridge network. Bridge management systems (BMSs) have been developed for such a purpose. However, they generally rely on an individual approach. The influence of the position of bridges in the transportation network, the consequences of inadequate service for the network users, due to maintenance actions or bridge failure, are not taken into consideration. Therefore, maintenance strategies obtained with current BMSs do not necessarily lead to an optimal level of service (LOS) of the bridge network for the users of the transportation network. Besides, the assessment of the structural performance of highway bridges usually requires the access to the geometrical and mechanical properties of its components. Such information might not be available for all structures in a bridge network for which managers try to schedule and prioritize maintenance strategies. On the contrary, visual inspections are performed regularly and information is generally available for all structures of the bridge network. The objective of this paper is threefold (1) propose an advanced network-level bridge management system considering the position of each bridge in the transportation network, (2) use information obtained at visual inspections to assess the performance of bridges, and (iii) compare optimal maintenance strategies, obtained with a genetic algorithm, when considering interests of users and bridge owner either separately as conflicting criteria, or simultaneously as a common interest for the whole community. In each case, safety and serviceability aspects are taken into account in the model when determining optimal strategies. The theoretical and numerical developments are applied on a French bridge network

Artificial Neural Networks, Non Linear Auto Regression Networks (NARX) and Causal Loop Diagram Approaches for Modelling Bridge Infrastructure Conditions

The quality of highway bridge infrastructure in United States is of major concern. One in every four bridges in the US is deficient. This research applied Artificial Intelligence, Systems Dynamics and linear modeling techniques to investigate the causes and effects of bridge deterioration and to forecast bridge infrastructure condition and improvement costs. The main contribution of the research is the development and demonstration of these methods within the context of highway bridges. These methods provide bridge designers and policy makers new tools for maintaining, improving, and delivering high quality bridge infrastructure. To start with, a comprehensive review of the current state of bridge deficiency in US was conducted. Through extensive data mining of the National Bridge Inventory (NBI), the causes and trends in bridge deficiency were identified. This exercise addressed questions such as: What is the current extent of bridge deficiency? Is deficiency getting better or worse? What are the biggest problems causing deficiencies? It was observed that though the general condition of bridges is improving, additional work needs to be done in fixing bridge deficiency and bridge functionally obsolescence in particular. Subsequent to the review of bridge deficiency, four distinct but related modeling studies were conducted. These phases are: 1) Capacity Obsolescence/Sustainability assessment, 2) Causal Loop Diagram (CLD) and linear modeling for bridge improvement costs, 3) Artificial Neural Network (ANN) model for bridge condition ratings and bridge variable effects, 4) Non-linear auto regression (NARX) model for bridge inventory condition prediction. In the first phase, a conceptual model was developed to minimize capacity obsolescence, one face of functional obsolescence. A framework was developed to minimize bridge capacity obsolescence while optimizing the use of embodied energy over the service life of bridges. The research demonstrated how design phase consideration of bridge obsolescence can contribute to sustainability of bridge infrastructure. As a novel approach for studying bridge improvement costs, the second phase used a Causal Loop Diagram (CLD), a tool used in the field of System Dynamics. Using a CLD, the causes and effects for bridge deterioration were qualitatively described. A segment of the qualitative relationships described through the CLD were then analyzed quantitatively for the South Carolina bridge inventory. The quantitative model was based on linear modeling and was developed and validated using NBI data. The model was then applied to estimate future bridge inventory sufficiency ratings and improvement costs under possible funding scenarios. For effective mitigation of bridge deficiency, it is important to identify the effects of different variables on bridge conditions and forecast bridge condition. In the third phase of modeling, Artificial Neural Networks (ANN) models were used to study the effects of bridge variables on bridge deck and superstructure condition ratings. The models considered prestressed concrete bridges in South Eastern United States. Simulations based on Full Factorial Design (FFD) were conducted using the developed ANN models. The simulations highlighted the effects of skew, span and age on bridge condition ratings. Given sufficient source data, the approach can be broadly applied to consider other bridge types and design variables. In the last phase, time based ANN learning algorithms were used to forecast bridge condition ratings and bridge improvement costs. Non Linear Auto Regression with Exogenous Inputs (NARX) model was developed using NBI data for South Carolina bridges over the last decade. The study estimated bridge condition ratings as a function of bridge geometry, age, structural, traffic attributes and bridge improvement spending. This doctoral research contributed to the development of multiple qualitative and mathematical models for forecasting bridge inventory condition and improvement costs by applying ANN, CLD, and linear regression techniques. While the conclusions of these studies are bound by the scope of the data and methodical constraints of the research, the methods can be more generally applied to aid in better bridge management policies and contribute to sustainable bridge infrastructure in United States

Network Maintenance and Capacity Management with Applications in Transportation

abstract: This research develops heuristics to manage both mandatory and optional network capacity reductions to better serve the network flows. The main application discussed relates to transportation networks, and flow cost relates to travel cost of users of the network. Temporary mandatory capacity reductions are required by maintenance activities. The objective of managing maintenance activities and the attendant temporary network capacity reductions is to schedule the required segment closures so that all maintenance work can be completed on time, and the total flow cost over the maintenance period is minimized for different types of flows. The goal of optional network capacity reduction is to selectively reduce the capacity of some links to improve the overall efficiency of user-optimized flows, where each traveler takes the route that minimizes the traveler’s trip cost. In this dissertation, both managing mandatory and optional network capacity reductions are addressed with the consideration of network-wide flow diversions due to changed link capacities. This research first investigates the maintenance scheduling in transportation networks with service vehicles (e.g., truck fleets and passenger transport fleets), where these vehicles are assumed to take the system-optimized routes that minimize the total travel cost of the fleet. This problem is solved with the randomized fixed-and-optimize heuristic developed. This research also investigates the maintenance scheduling in networks with multi-modal traffic that consists of (1) regular human-driven cars with user-optimized routing and (2) self-driving vehicles with system-optimized routing. An iterative mixed flow assignment algorithm is developed to obtain the multi-modal traffic assignment resulting from a maintenance schedule. The genetic algorithm with multi-point crossover is applied to obtain a good schedule. Based on the Braess’ paradox that removing some links may alleviate the congestion of user-optimized flows, this research generalizes the Braess’ paradox to reduce the capacity of selected links to improve the efficiency of the resultant user-optimized flows. A heuristic is developed to identify links to reduce capacity, and the corresponding capacity reduction amounts, to get more efficient total flows. Experiments on real networks demonstrate the generalized Braess’ paradox exists in reality, and the heuristic developed solves real-world test cases even when commercial solvers fail.Dissertation/ThesisDoctoral Dissertation Industrial Engineering 201

Évaluation multiéchelle de l'état des réseaux vieillissants de ponts routiers

Les ouvrages vieillissent et leur état se détériore. Compte tenu de leur importance sociale et économique, ils constituent des vecteurs de transports construits dans le but d'assurer un service alliant un haut niveau de qualité, de sécurité et de fiabilité. Des budgets d'investissement, le plus souvent déficitaires, sont octroyés pour la construction d'infrastructures et d'ouvrages de génie civil. La fermeture des ouvrages pour les activités d'entretien ou de réparation, même temporaire, et, dans le cas de leur démolition, perturbe fortement la mobilité des usagers, en particulier, le mouvement des marchandises, social humain au niveau des activités de service et récréative, entraînant des répercussions économiques à différentes échelles et secteurs. La gestion des ouvrages permet l'auscultation des détériorations, la surveillance, et l'évaluation régulière d'un parc d'infrastructure en vue d'assurer un meilleur service aux utilisateurs. Nous aborderons pour cela, le contexte du projet, les besoins de recherche et ses objectifs. Par la suite, nous nous intéresserons plus en détail à la méthodologie qui décrit le modèle de gestion qui sera développé dans ce travail de recherche pour évaluer et gérer le parc d'ouvrages et les résultats attendus du projet de recherche. Une revue de la littérature est abordée afin d'identifier et analyser les modèles de gestions existants dans ce domaine de gestion des infrastructures. Le rapport s'articule autour de trois grandes parties : (1) Évaluation de la condition d'état d'un pont (2) Variation temporelle de la condition d'état d'un pont (3) Gestion intégrée du réseau routier. Ce rapport conclut sur les apports de la recherche et ouvre la perspective de développement à venir. Ce qui contribuera à maintenir et à en rétablir de façon optimale l'état des ouvrages ainsi qu'à stimuler l'économie.The structures grow old, and their condition deteriorates. Given their social and economic importance,they are transporting vectors built to ensure a service combining a high level of quality, safety and reliability. Investment budgets, most often in the deficit, are allocated for infrastructure and civil engineering structures construction. The closure of structures for maintenance or repair activities, even temporarily, and, in the case of their demolition, strongly disrupts the mobility of users, in particular, the movement of goods, human social at the level of service and recreational activities, entailing economic impacts at different scales and sectors. The structure management allows the monitoring of deterioration,the surveillance and the regular assessment of an infrastructure fleet in order to ensure a better service to the users. We will cover the context of the project, the research necessities and its goals. Afterwards, we will focus in more detail on the methodology that describes the management model that will be developed in this research work to evaluate and manage the structure fleet and the expected outcomes of the research project. A literature review is performed to identify and analyse existing management models in this field of infrastructure management. The report is structured around three main parts: (1) Bridge state condition assessment (2) Temporal variation of the bridge state condition (3) Integrated Road network management. This thesis concludes on the research contributions and opens the perspective of future development. This will help to maintain and optimally restore the structures state condition and stimulate the economy

Étude de la durabilité des ouvrages dans un contexte de développement durable (application aux ponts mixtes)

La pratique courante de la conception des ouvrages d'art est fortement orientée par la phase de construction. Traditionnellement, la conception des ouvrages consiste à retenir un dimensionnement qui permet d'atteindre un coût initial de construction le plus faible possible tout en respectant des exigences prescrites pour une durée de fonctionnement donnée. Cette approche est aujourd'hui revisitée pour chercher à intégrer tout le cycle de vie de l'ouvrage, c'est-à-dire à considérer toutes les étapes de sa vie depuis la conception jusqu'à la fin de vie en service. En effet, les activités liées au cycle de vie de l'ouvrage durant les phases d'exploitation, de maintenance/réhabilitation, et de fin de vie génèrent des impacts tant sur le plan économique que sur les plans environnementaux et sociétaux, bien plus importants que la simple phase de conception/construction. Chaque option de dimensionnement peut être associée à un cycle de vie différent et donc à des impacts différents. Pour cette raison et dans une approche de développement durable, cette thèse propose d'analyser les ouvrages dans leur cycle de vie selon trois axes : économique, environnemental et sociétal. Pour cela, une famille d'ouvrage particulière a été retenue : les ponts mixtes acier-béton. Une analyse performantielle est également effectuée pour permettre de prendre en compte différents scénarios de maintenance. Finalement, une procédure d'optimisation et une analyse multicritère sont proposées pour évaluer l'ensemble des variantes de conception et permettre d'avoir une vision globale qui aide les maîtres d'ouvrage et les gestionnaires lors de la prise de décisionThe current practice in structural design is strongly impacted by the construction stage. Traditionally, the design process aims at selecting the solution with the lowest initial construction cost while fulfilling prescribed requirements during a fixed service life. This approach is now revisited to integrate the whole life-cycle of the structure, i.e to consider the structure from the design step to the end of the service life. Indeed, activities related to the structure life-cycle such as operation, maintenance/rehabilitation and end-of-life generate economic, environmental and societal impacts, which may be more significant than those at the design/construction of the structure. Each design solution might be associated with a different life-cycle, and then with differents impacts. For this reason and within an approach of sustainable development, this PhD work proposes to analyze structures during the overall life-cycle of the structure in accordance with three axes : economic, environmental and social. A performance-based analysis is also performed to take into account different maintenance strategies. Finally, a multi-objective optimization process and a multi-criteria analysis are proposed to assess all design solutions and have a global vision that helps bridge owners and managers in the decision making processPARIS-EST-Université (770839901) / SudocSudocFranceF