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Estimation of fatigue S-N curves of welded joints using advanced probabilistic approach

This paper provides a new advanced probabilistic approach for reliable estimation of the fatigue characteristic S-N curves of welded joints both for constant amplitude (CA) and variable amplitude (VA) loading conditions. The presented approach, which is referred to as the ML-MCS approach, combines M...

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Detalles Bibliográficos
Autores principales: D’Angelo, Luca, Nussbaumer, Alain
Lenguaje:eng
Publicado: 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1016/j.ijfatigue.2016.12.032
http://cds.cern.ch/record/2270771
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author D’Angelo, Luca
Nussbaumer, Alain
author_facet D’Angelo, Luca
Nussbaumer, Alain
author_sort D’Angelo, Luca
collection CERN
description This paper provides a new advanced probabilistic approach for reliable estimation of the fatigue characteristic S-N curves of welded joints both for constant amplitude (CA) and variable amplitude (VA) loading conditions. The presented approach, which is referred to as the ML-MCS approach, combines Maximum Likelihood method (ML) and Monte-Carlo Simulations (MCS) method to estimate true p-quantiles of CA and VA S-N curves by using complete experimental data-sets. The ML-MCS approach includes a linearization method for use of S-N curves in combination with linear damage accumulation rule as well as for direct comparison with current standards. Application of the ML-MCS approach on two study cases and comparison with current standards shows that the use of the ML-MCS approach may have a significant impact in re-definition of CA and VA S-N curves of current standards and in particular of the CAFL, of the S-N curve second slope and of the critical value of accumulated damage at failure. The last section of the paper provides accurate guidelines for future experimental tests needed for re-definition of current standards. (C) 2016 Elsevier Ltd. All rights reserved.
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spelling oai-inspirehep.net-16050762019-09-30T06:29:59Zdoi:10.1016/j.ijfatigue.2016.12.032http://cds.cern.ch/record/2270771engD’Angelo, LucaNussbaumer, AlainEstimation of fatigue S-N curves of welded joints using advanced probabilistic approachEngineeringThis paper provides a new advanced probabilistic approach for reliable estimation of the fatigue characteristic S-N curves of welded joints both for constant amplitude (CA) and variable amplitude (VA) loading conditions. The presented approach, which is referred to as the ML-MCS approach, combines Maximum Likelihood method (ML) and Monte-Carlo Simulations (MCS) method to estimate true p-quantiles of CA and VA S-N curves by using complete experimental data-sets. The ML-MCS approach includes a linearization method for use of S-N curves in combination with linear damage accumulation rule as well as for direct comparison with current standards. Application of the ML-MCS approach on two study cases and comparison with current standards shows that the use of the ML-MCS approach may have a significant impact in re-definition of CA and VA S-N curves of current standards and in particular of the CAFL, of the S-N curve second slope and of the critical value of accumulated damage at failure. The last section of the paper provides accurate guidelines for future experimental tests needed for re-definition of current standards. (C) 2016 Elsevier Ltd. All rights reserved.oai:inspirehep.net:16050762017
spellingShingle Engineering
D’Angelo, Luca
Nussbaumer, Alain
Estimation of fatigue S-N curves of welded joints using advanced probabilistic approach
title Estimation of fatigue S-N curves of welded joints using advanced probabilistic approach
title_full Estimation of fatigue S-N curves of welded joints using advanced probabilistic approach
title_fullStr Estimation of fatigue S-N curves of welded joints using advanced probabilistic approach
title_full_unstemmed Estimation of fatigue S-N curves of welded joints using advanced probabilistic approach
title_short Estimation of fatigue S-N curves of welded joints using advanced probabilistic approach
title_sort estimation of fatigue s-n curves of welded joints using advanced probabilistic approach
topic Engineering
url https://dx.doi.org/10.1016/j.ijfatigue.2016.12.032
http://cds.cern.ch/record/2270771
work_keys_str_mv AT dangeloluca estimationoffatiguesncurvesofweldedjointsusingadvancedprobabilisticapproach
AT nussbaumeralain estimationoffatiguesncurvesofweldedjointsusingadvancedprobabilisticapproach