The Experts below are selected from a list of 18687 Experts worldwide ranked by ideXlab platform
Dan M. Frangopol - One of the best experts on this subject based on the ideXlab platform.
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optimizing Bridge network Maintenance management under uncertainty with conflicting criteria life cycle Maintenance failure and user costs
Journal of Structural Engineering-asce, 2006Co-Authors: Margaret Liu, Dan M. FrangopolAbstract:During the past decade, a variety of Bridge Maintenance management methodologies have been developed to cost-effectively allocate limited budgets to deteriorating highway Bridges for performance enhancement and lifespan extension. In most existing research and practice, however, Bridges are treated individually rather than collectively as integral parts of a transportation network. In addition to safety issues, failure of Bridges renders a highway network inaccessible, either partially or completely. This may lead to considerable economic consequences, ranging from agency costs caused by repair/reconstruction to user costs as a result of disrupted network service (e.g., congestion and detour). Therefore, it is both natural and important to maintain the satisfactory long-term performance of not only individual Bridges but the highway network. In this paper, a novel analytical/computational framework for network-level Bridge Maintenance management using optimization is presented. This framework integrates time-dependent structural reliability prediction, highway network performance assessment, and life-cycle cost analysis. Failure occurrences of individual Bridges and their effects on the overall performance of the highway network are evaluated probabilistically. The Maintenance resources are prioritized to deteriorating Bridges through simultaneous and balanced minimization of three objective functions, i.e., Maintenance cost, Bridge failure cost, and user cost. Each of these cost metrics is computed as the present value of the expected economic expenditure accrued over the specified time horizon. The resulting multiobjective optimization problem is solved by a genetic algorithm. An application example is provided for Maintenance management of deteriorating reinforced concrete deck slabs of an existing Bridge highway network in Colorado. It is shown that the proposed methodology is effective for enhancing the Bridge Maintenance management practice at network-level through probabilistic quantification and preferred balance of various life-cycle costs.
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optimal Bridge Maintenance planning using improved multi objective genetic algorithm
Structure and Infrastructure Engineering, 2006Co-Authors: Hitoshi Furuta, Takahiro Kameda, Koichiro Nakahara, Yuji Takahashi, Dan M. FrangopolAbstract:In order to establish a rational Bridge management program, it is necessary to develop a cost-effective decision-support system for the Maintenance of Bridges. In this paper, an attempt is made to develop a Bridge management system that can provide practical Maintenance plans by using an improved multi-objective genetic algorithm. A group of Bridges is analyzed to demonstrate the applicability and efficiency of the proposed method.
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service life prediction of structural systems using lifetime functions with emphasis on Bridges
Reliability Engineering & System Safety, 2004Co-Authors: Seungie Yang, Dan M. Frangopol, Luis C NevesAbstract:Abstract In order to adequately handle the huge increase in traffic over the past three decades, most North American and European countries invested enormous funds in building highway networks. Nowadays, most of these networks are complete or close to completion. The biggest challenge highway agencies and departments of transportation face is the Maintenance of these networks, keeping them safe and serviceable, with limited funds. The use of consistent measures of safety is fundamental for the development of optimum strategies for Bridge Maintenance. The analysis of safety on a component basis is a gross approximation of the real system performance of a Bridge. In this paper, a model using lifetime functions to evaluate the overall system probability of survival of existing Bridges, under Maintenance or no Maintenance, is proposed. In this model, Bridges are modeled as systems of independent and/or correlated components. The proposed model is applied to an existing Bridge located in Denver, Colorado, and the optimal Maintenance strategy of this Bridge is obtained in terms of service life extension and cumulative Maintenance cost.
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service life prediction of structural systems using lifetime functions with emphasis on Bridges
Reliability Engineering & System Safety, 2004Co-Authors: Seungie Yang, Dan M. Frangopol, Luis C NevesAbstract:Abstract In order to adequately handle the huge increase in traffic over the past three decades, most North American and European countries invested enormous funds in building highway networks. Nowadays, most of these networks are complete or close to completion. The biggest challenge highway agencies and departments of transportation face is the Maintenance of these networks, keeping them safe and serviceable, with limited funds. The use of consistent measures of safety is fundamental for the development of optimum strategies for Bridge Maintenance. The analysis of safety on a component basis is a gross approximation of the real system performance of a Bridge. In this paper, a model using lifetime functions to evaluate the overall system probability of survival of existing Bridges, under Maintenance or no Maintenance, is proposed. In this model, Bridges are modeled as systems of independent and/or correlated components. The proposed model is applied to an existing Bridge located in Denver, Colorado, and the optimal Maintenance strategy of this Bridge is obtained in terms of service life extension and cumulative Maintenance cost.
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optimal Bridge Maintenance planning based on probabilistic performance prediction
Engineering Structures, 2004Co-Authors: Min Liu, Dan M. FrangopolAbstract:Current automated Maintenance planning procedures for deteriorating Bridges are usually based on deterministic prediction of Bridge performance and whole-life Maintenance costing. In these procedures, uncertainties associated with the deterioration process under no Maintenance and under Maintenance are not taken into consideration. In this paper, such uncertainties are confined to the parameters that define the selected computational models and their effects are evaluated by means of Monte Carlo simulations. A multiobjective genetic algorithm based numerical procedure is used to locate, in the Pareto optimal sense, the best possible tradeoff Maintenance planning solutions with respect to three objective functions, namely, condition index, safety index, and cumulative life-cycle Maintenance cost. By computing these objectives in terms of either sample mean or sample percentile values, Bridge managers’ specific confidence levels on the performance of Maintenance solutions can therefore be conveniently incorporated into the optimization process.
Masaru Miyake - One of the best experts on this subject based on the ideXlab platform.
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optimal network level Bridge Maintenance planning based on minimum expected cost
Transportation Research Record, 2000Co-Authors: Dan M. Frangopol, Emhaidy S. Gharaibeh, Jun Sik G Kong, Masaru MiyakeAbstract:The goal of Bridge management is to determine and implement the best possible strategy that ensures an adequate level of safety at the lowest possible life-cycle cost. Although this is generally recognized, the integration of life-cycle cost analysis with Bridge reliability analysis has been very limited. Moreover, this has been formulated and illustrated only for individual Bridges. A framework for optimal network-level Bridge Maintenance planning based on minimum expected cost is presented. The goal is the minimization of the expected Maintenance cost of a Bridge stock with Maintenance of the lifetime reliability of each Bridge above an acceptable (target) level. The approach is illustrated for a stock of realistic highway Bridges. Individual Bridges in this stock have different ages, and their reliabilities are time dependent. The framework offers a rational basis for optimizing the resource allocation for management of a stock of gradually deteriorating Bridges based on balancing life-cycle maintenanc...
Samer Madanat - One of the best experts on this subject based on the ideXlab platform.
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reliability based system level optimization of Bridge Maintenance and replacement decisions
Transportation Science, 2008Co-Authors: Charlesantoine Robelin, Samer MadanatAbstract:This paper addresses the problem of optimizing Bridge Maintenance and replacement (M&R) decisions for a heterogeneous system of facilities. The objective is to determine optimal M&R policies for each facility over a finite planning horizon based on the knowledge of the current facilities conditions and on the prediction of future conditions. The system-level problem is based on the results of an M&R optimization problem for each facility. The results of the facility-level optimization are incorporated in a reliability-based, bottom-up, system-level formulation that provides recommendations for each individual facility. We derive sufficient conditions for optimality and prove the result for the continuous case. A parametric study shows that the results obtained in the discrete-case implementation of the solution are valid approximations of the continuous case results. The computational efficiency of the system-level solution makes the formulation suitable for systems of realistic sizes.
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History-Dependent Bridge Deck Maintenance and Replacement Optimization with Markov Decision Processes
Journal of Infrastructure Systems, 2007Co-Authors: Charlesantoine Robelin, Samer MadanatAbstract:Bridge Maintenance and replacement optimization methods use deterioration models to predict the future condition of Bridge components. The purpose of this paper is to develop a framework for Bridge Maintenance optimization using a deterioration model that takes into account aspects of the history of the Bridge condition and Maintenance, while allowing the use of efficient optimization techniques. Markovian models are widely used to represent Bridge component deterioration. In existing Markovian models, the state is the Bridge component condition, and the history of the condition is not taken into account, which is seen as a limitation. This paper describes a method to formulate a realistic history-dependent model of Bridge deck deterioration as a Markov chain, while retaining aspects of the history of deterioration and Maintenance as part of the model. This model is then used to formulate and solve a reliability-based Bridge Maintenance optimization problem as a Markov decision process. A parametric study is conducted to compare the policies obtained in this research with policies derived using a simpler Markovian model.
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dynamic programming based Maintenance and replacement optimization for Bridge decks using history dependent deterioration models
Applications of Advanced Technology in Transportation - Proceedings of the Ninth International Conference on Applications of Advanced Technology in Tr, 2006Co-Authors: Charlesantoine Robelin, Samer MadanatAbstract:In this research, a reliability-based optimization model of Bridge Maintenance and replacement decisions is developed. Bridge Maintenance optimization models use deterioration models to predict the future condition of Bridges. Some current optimization models use physically-based deterioration models taking into account the history of deterioration. However, due to the complexity of the deterioration models, the number of decision variables in these optimization models is limited. Some other optimization models consist of a full set of decision variables; however, they use simpler deterioration models. Namely, these deterioration models are Markovian, and the state of the Markov chain is limited to the condition of the facility. In this research, a facility level optimization model of Bridge Maintenance and decisions is developed, using a Markov chain whose state includes part of the history of deterioration and Maintenance. The main advantage of this formulation is that it allows the use of standard optimization techniques (dynamic programming), while using realistic, history-dependent deterioration models. This research presents a method to formulate a realistic history-dependent model of Bridge deck deterioration as a Markov chain, while retaining relevant parts of the history of deterioration, using state augmentation. This deterioration model is then used to formulate and solve a reliability-based Bridge Maintenance optimization problem as a Markov decision process. In a numerical example, the policies derived using the augmented Markov chain are applied to a realistic Bridge deck, and compared to the policies derived using a simpler Markov chain.
Charlesantoine Robelin - One of the best experts on this subject based on the ideXlab platform.
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reliability based system level optimization of Bridge Maintenance and replacement decisions
Transportation Science, 2008Co-Authors: Charlesantoine Robelin, Samer MadanatAbstract:This paper addresses the problem of optimizing Bridge Maintenance and replacement (M&R) decisions for a heterogeneous system of facilities. The objective is to determine optimal M&R policies for each facility over a finite planning horizon based on the knowledge of the current facilities conditions and on the prediction of future conditions. The system-level problem is based on the results of an M&R optimization problem for each facility. The results of the facility-level optimization are incorporated in a reliability-based, bottom-up, system-level formulation that provides recommendations for each individual facility. We derive sufficient conditions for optimality and prove the result for the continuous case. A parametric study shows that the results obtained in the discrete-case implementation of the solution are valid approximations of the continuous case results. The computational efficiency of the system-level solution makes the formulation suitable for systems of realistic sizes.
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History-Dependent Bridge Deck Maintenance and Replacement Optimization with Markov Decision Processes
Journal of Infrastructure Systems, 2007Co-Authors: Charlesantoine Robelin, Samer MadanatAbstract:Bridge Maintenance and replacement optimization methods use deterioration models to predict the future condition of Bridge components. The purpose of this paper is to develop a framework for Bridge Maintenance optimization using a deterioration model that takes into account aspects of the history of the Bridge condition and Maintenance, while allowing the use of efficient optimization techniques. Markovian models are widely used to represent Bridge component deterioration. In existing Markovian models, the state is the Bridge component condition, and the history of the condition is not taken into account, which is seen as a limitation. This paper describes a method to formulate a realistic history-dependent model of Bridge deck deterioration as a Markov chain, while retaining aspects of the history of deterioration and Maintenance as part of the model. This model is then used to formulate and solve a reliability-based Bridge Maintenance optimization problem as a Markov decision process. A parametric study is conducted to compare the policies obtained in this research with policies derived using a simpler Markovian model.
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dynamic programming based Maintenance and replacement optimization for Bridge decks using history dependent deterioration models
Applications of Advanced Technology in Transportation - Proceedings of the Ninth International Conference on Applications of Advanced Technology in Tr, 2006Co-Authors: Charlesantoine Robelin, Samer MadanatAbstract:In this research, a reliability-based optimization model of Bridge Maintenance and replacement decisions is developed. Bridge Maintenance optimization models use deterioration models to predict the future condition of Bridges. Some current optimization models use physically-based deterioration models taking into account the history of deterioration. However, due to the complexity of the deterioration models, the number of decision variables in these optimization models is limited. Some other optimization models consist of a full set of decision variables; however, they use simpler deterioration models. Namely, these deterioration models are Markovian, and the state of the Markov chain is limited to the condition of the facility. In this research, a facility level optimization model of Bridge Maintenance and decisions is developed, using a Markov chain whose state includes part of the history of deterioration and Maintenance. The main advantage of this formulation is that it allows the use of standard optimization techniques (dynamic programming), while using realistic, history-dependent deterioration models. This research presents a method to formulate a realistic history-dependent model of Bridge deck deterioration as a Markov chain, while retaining relevant parts of the history of deterioration, using state augmentation. This deterioration model is then used to formulate and solve a reliability-based Bridge Maintenance optimization problem as a Markov decision process. In a numerical example, the policies derived using the augmented Markov chain are applied to a realistic Bridge deck, and compared to the policies derived using a simpler Markov chain.
Changsu Shim - One of the best experts on this subject based on the ideXlab platform.
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development of a Bridge Maintenance system for prestressed concrete Bridges using 3d digital twin model
Structure and Infrastructure Engineering, 2019Co-Authors: Changsu Shim, Ngoc Son Dang, Sokanya Lon, Chiho JeonAbstract:AbstractPreventive Maintenance is increasingly becoming an essential strategy in the Bridge industry owing to its proactive advantage of maintaining the structural sustainability during its entire ...
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development of a Bridge Maintenance system for prestressed concrete Bridges using 3d digital twin model
Structure and Infrastructure Engineering, 2019Co-Authors: Changsu Shim, Ngoc Son Dang, Chiho JeonAbstract:Preventive Maintenance is increasingly becoming an essential strategy in the Bridge industry owing to its proactive advantage of maintaining the structural sustainability during its entire service ...
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development of bim based Bridge Maintenance system for cable stayed Bridges
Smart Structures and Systems, 2017Co-Authors: Changsu Shim, Hwirang Kang, Ngoc Son Dang, Deokkeun LeeAbstract:Maintenance plays a critical role in the Bridge industry, but actual practices show many limitations because of traditional, 2D-based information systems. It is necessary to develop a new generation of Maintenance information management systems for more reliable decision making in Bridge Maintenance. Enhancing current work processes requires a BIM-based 3D digital model that can use information from the whole lifecycle of a project (design, construction, operation, and Maintenance) through continuous exchanges and updates from each stakeholder. This study describes the development of a data scheme for Maintenance of cable-stayed Bridges. We implemented the proposed system for a cable-stayed Bridge and discussed its effectiveness.
