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4 results on '"Department of Civil and Environmental Engineering, ATLSS Center"'

1. Author Correction: El Niño–Southern Oscillation complexity

Author

Wenju Cai, Karl Stein, Pamela R. Grothe, Sang-Wook Yeh, Jin-Ho Yoon, Tim Li, WonMoo Kim, Yann Planton, Sunyong Kim, Xuebin Zhang, Hong Li Ren, Agus Santoso, Ken Takahashi, Yoshimitsu Chikamoto, Scott B. Power, Sarah Ineson, Fei-Fei Jin, Matthieu Lengaigne, Kyung-Sook Yun, Daehyun Kang, Han Ching Chen, Woo Hyun Yang, Alexander Todd, Boris Dewitte, Andrew T. Wittenberg, June-Yi Lee, Eric Guilyardi, Shayne McGregor, Kim M. Cobb, Michiya Hayashi, Dietmar Dommenget, Tobias Bayr, Jong-Seong Kug, Axel Timmermann, Malte F. Stuecker, Ruihuang Xie, Soon Il An, Antonietta Capotondi, Michael J. McPhaden, Elke Zeller, Harun Rashid, Guomin Wang, Guojian Wang, Jing-Jia Luo, Yoo-Geun Ham, Institute of Basic Science (IBS), International Pacific Research Center (IPRC), School of Ocean and Earth Science and Technology (SOEST), University of Hawai‘i [Mānoa] (UHM)-University of Hawai‘i [Mānoa] (UHM), Department of Atmospheric Sciences [Seoul], Yonsei University, Pohang University of Science and Technology (POSTECH), Unité de Mathématiques Pures et Appliquées (UMPA-ENSL), Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon), CSIRO Marine and Atmospheric Research [Aspendale], Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), School of Earth and Atmospheric Sciences [Atlanta], Georgia Institute of Technology [Atlanta], Océan et variabilité du climat (VARCLIM), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), Department of Atmospheric Sciences [Seattle], University of Washington [Seattle], NOAA Geophysical Fluid Dynamics Laboratory (GFDL), Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), National Taiwan University [Taiwan] (NTU), Department of Plants, Soils and Climate, Utah State University (USU), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), School of Earth, Atmosphere and Environment, Monash University, Monash University [Clayton], University of Hawai‘i [Mānoa] (UHM), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Department of Civil and Environmental Engineering, ATLSS Center, Lehigh University, Centre for Australian Weather and Climate Research (CAWCR), University of Sussex, University of South Wales (USW), University of Occupational and Environmental Health [Kitakyushu] (UEOH), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Center for Ocean-Land-Atmosphere Studies (COLA), Gwangju Institute of Science and Technology (GIST), CSIRO Marine and Atmosphere Research [Hobart], École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), and School of Earth, Atmosphere and Environment

Subjects
Multidisciplinary, El Niño Southern Oscillation, Climatology, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], CobB, Mathematics
Abstract

In this Review, the middle initial of author Kim M. Cobb was omitted. The original Review has been corrected online.

Published
2019
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2. Optimization of Bridge Management under Budget Constraints

Author

André Orcesi, Dan M. Frangopol, Département Structures et Ouvrages d'Art (LCPC/SOA), Laboratoire Central des Ponts et Chaussées (LCPC)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), and Department of Civil and Environmental Engineering, ATLSS Center, Lehigh University

Subjects
Event tree, Engineering, Operations research, Process (engineering), Event tree analysis, 0211 other engineering and technologies, 020101 civil engineering, 02 engineering and technology, Bridge (nautical), 0201 civil engineering, [PHYS.MECA.STRU]Physics [physics]/Mechanics [physics]/Structural mechanics [physics.class-ph], INCERTITUDE, 021105 building & construction, Budget constraint, Civil and Structural Engineering, Strategic planning, business.industry, OPTIMISATION, Mechanical Engineering, PROCESSUS DE DECISION, [SPI.MECA.STRU]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Structural mechanics [physics.class-ph], Management system, [SHS.GESTION]Humanities and Social Sciences/Business administration, Structural health monitoring, business, GESTION DES PONTS
Abstract

Bridge management is a complex engineering issue with public safety and financial implications. It is a challenge to provide efficient bridge management systems, taking into account uncertainties in the structural degradation process, the loads and resistance of the structure, the decisions that are made concerning assessment strategies—such as inspections or structural health monitoring (SHM)—and maintenance and rehabilitation strategies. It is important to determine optimal management strategies that satisfy budget constraints, because efficient use of available financial funds is a primary objective of stakeholders. The purpose of this paper is to provide a probabilistic framework based on SHM results for optimization of management strategies under multiple criteria, including budget availability. To take into account uncertainties in the decision process, an event tree–based approach is used. This enables quantification of the expected inspection, SHM, maintenance and failure costs, and accuracy of the decision process according to the occurrence and duration of future SHM programs. To include budget constraints, the probability distribution of management cost—defined as the sum of inspection, SHM, and maintenance costs—is determined at each decision time and compared with an ideal budget distribution. The proposed approach is applied to an existing bridge.

Published
2010
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3. Optimization of bridge maintenance strategies based on structural health monitoring information

Author

Dan M. Frangopol, André D. Orcesi, Département Structures et Ouvrages d'Art (LCPC/SOA), Laboratoire Central des Ponts et Chaussées (LCPC)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Department of Civil and Environmental Engineering, ATLSS Center, and Lehigh University

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, Engineering, Operations research, Process (engineering), 0211 other engineering and technologies, Optimal maintenance, 020101 civil engineering, 02 engineering and technology, CYCLE DE VIE, Bridge (nautical), 0201 civil engineering, MODELE, 021105 building & construction, SURVEILLANCE, Safety, Risk, Reliability and Quality, Reliability (statistics), ENTRETIEN, Civil and Structural Engineering, FIABILITE DES STRUCTURES, business.industry, COUT, OPTIMISATION, Building and Construction, DEGRADATION, Monitoring program, Reliability engineering, PREVISION, Bridge maintenance, Structural health monitoring, business, GESTION DES PONTS, Predictive modelling
Abstract

Highway bridges are subjected to strength degradation processes. Under budget constraints, it is important to determine the best maintenance strategies. Optimized strategies, based on prediction models, are already considered for the maintenance and operation of highway bridges. Prediction models are updated both in space and time by using non-destructive testing methods. Nevertheless, there is an urgent need for the efficient inclusion of structural health monitoring (SHM) data in structural assessment and prediction models. Indeed, SHM allows keeping strength degradation processes under control and should be included in life-cycle cost models. The lifetime reliability of structures is characterized by survivor functions. The SHM data enable to update the probability density function of time to failure through a Bayesian process. The aim of this paper is threefold: (a) to include SHM data in a bridge life-cycle cost analysis, (b) to determine optimal maintenance strategies based on monitoring information, and (c) to show the benefits of SHM. Optimal strategies are determined considering the cases without and with including monitoring results; the benefit of monitoring is then highlighted. The proposed concepts are applied to the I-39 Northbound Bridge over the Wisconsin River in Wisconsin, USA. A monitoring program of that bridge was performed by the ATLSS Engineering Research Center at Lehigh University.

Published
2011
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4. Optimization of bridge maintenance strategies based on multiple limit states and monitoring

Author

Sunyong Kim, André D. Orcesi, Dan M. Frangopol, Département Structures et Ouvrages d'Art (LCPC/SOA), Laboratoire Central des Ponts et Chaussées (LCPC)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Department of Civil and Environmental Engineering, ATLSS Center, and Lehigh University

Subjects
[SPI.OTHER]Engineering Sciences [physics]/Other, Engineering, Serviceability (structure), 0211 other engineering and technologies, Structural reliability, Optimal maintenance, 020101 civil engineering, 02 engineering and technology, 0201 civil engineering, Discrete points, Girder, 021105 building & construction, SURVEILLANCE, ENTRETIEN, Civil and Structural Engineering, FIABILITE DES STRUCTURES, business.industry, OPTIMISATION, ETAT LIMITE DE SERVICE, Structural engineering, Intervention planning, Reliability engineering, Bridge maintenance, PONT, Structural health monitoring, business, GESTION DES PONTS
Abstract

Visual inspections, diagnostic instrumentation and monitoring of bridges are essential for determination of intervention planning. Nowadays, a great challenge is to use bridge monitoring to determine optimal maintenance strategies. Indeed, monitoring data allow updating the knowledge on the structural performance and can significantly affect the intervention strategy. A methodology for structural reliability analysis of superstructures of steel girder bridges incorporating monitoring results is presented. Component reliability indices are computed for the slab and the girders and a time-variant performance analysis is conducted by considering corrosion. This allows dealing with structural capacity and serviceability with respect to permanent deformation under overload. Continuous and simultaneous measurements at discrete points of the bridge superstructure, provided by monitoring, allow to update some parameters of the serviceability limit state function and to perform a fatigue reliability analysis for several bridge components. The consideration of multiple limit states can lead to different optimal maintenance solutions, if taken individually or simultaneously. The aim of this paper is to show the impact of considering a global approach rather than an individual one when determining optimal maintenance strategies associated with several bridge limit states. The approach is illustrated on an existing highway bridge.

Published
2010
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