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author:

Strauss, Alfred (Strauss, Alfred.) [1] | Orcesi, André (Orcesi, André.) [2] | Lampropoulos, Andreas (Lampropoulos, Andreas.) [3] | Briseghella, Bruno (Briseghella, Bruno.) [4] | Frangopol, Dan M. (Frangopol, Dan M..) [5] | Sousa, Hélder S. (Sousa, Hélder S..) [6] | Casas, Joan (Casas, Joan.) [7] | Matos, José C. (Matos, José C..) [8] | Schellenberg, Kristian (Schellenberg, Kristian.) [9] | Valenzuela, Matias (Valenzuela, Matias.) [10] | Akiyama, Mitsuyoshi (Akiyama, Mitsuyoshi.) [11] | Linneberg, Poul (Linneberg, Poul.) [12] | Hajdin, Rade (Hajdin, Rade.) [13] | Moser, Thomas (Moser, Thomas.) [14]

Indexed by:

EI

Abstract:

Infrastructure systems, such as bridges, are a driver for the economic growth and sustainable development of countries. Similarly, the development of operation and maintenance strategies for infrastructure systems may aim at optimal management using Key Performance Indicators (KPIs) such as reliability, redundancy, availability, safety, economy, environmental performance and resilience. Recent research and development projects, such as COST TU1406, highlight that infrastructure managers make decisions based on a mix of qualitative and quantitative data from various sources paired with models of various levels of complexity as well as expert judgement. Similarly, recent state-of-the-art academia reports on a variety of different decision-making models applicable to the optimal management of infrastructure systems may be used. Within IABSE Commission 5 on Existing Structures, Task Group 5.4 has performed a survey on implemented decision-making models among 23 infrastructure managers from 20 countries. It highlights some similarities in relation to KPIs, condition rating and limit state checks. This has stimulated the standardisation of decision making. The application of risk-based methods, performance prediction and intervention modelling are somewhat more scattered and may call for further research and development as well as training. The need to bridge the gap between implemented decision-making models and research is of paramount importance. © 2023 International Association for Bridge and Structural Engineering (IABSE).

Keyword:

Benchmarking Decision making Economics Environmental management Maintenance Railroad transportation Redundancy Risk assessment Sustainable development

Community:

  • [ 1 ] [Strauss, Alfred]University of Natural Resources and Life Sciences, Vienna, Austria
  • [ 2 ] [Orcesi, André]Dr, Cerema, Research team ENDSUM, DTecITM/DTOA/GITEX, Champs-sur-Marne, France
  • [ 3 ] [Orcesi, André]Department MAST-EMGCU, Université Gustave Eiffel, IFSTTAR, Marne-la-Vallée, France
  • [ 4 ] [Lampropoulos, Andreas]University of Brighton, Brighton, United Kingdom
  • [ 5 ] [Briseghella, Bruno]Fuzhou University, Fujian, China
  • [ 6 ] [Frangopol, Dan M.]Lehigh University, Bethlehem, United States
  • [ 7 ] [Sousa, Hélder S.]University of Minho, Minho, Portugal
  • [ 8 ] [Casas, Joan]Universitat Politécnica de Catalunya, Barcelona, Spain
  • [ 9 ] [Matos, José C.]University of Minho, Minho, Portugal
  • [ 10 ] [Schellenberg, Kristian]Equi Bridges Ltd., Chur, Switzerland
  • [ 11 ] [Valenzuela, Matias]Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
  • [ 12 ] [Akiyama, Mitsuyoshi]Dr, Waseda University, Tokyo, Japan
  • [ 13 ] [Linneberg, Poul]COWI A/S, Kongens Lyngby, Denmark
  • [ 14 ] [Hajdin, Rade]Infrastructure Management Consultants GmbH, Zürich, Switzerland
  • [ 15 ] [Moser, Thomas]ASFiNAG GmbH, Vienna, Austria

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Source :

Structural Engineering International

ISSN: 1016-8664

Year: 2024

Issue: 1

Volume: 34

Page: 87-96

1 . 1 0 0

JCR@2023

CAS Journal Grade:4

Cited Count:

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SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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