FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)
To quickly evaluate the safety of damaged bridge structures in the service process of cranes, a real-time prediction method for the fatigue life of bridge structures based on the optimal additive agent model is proposed. Based on the measured load data, the randomness of the relevant parameters of t...
Main Authors: | , , , |
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Format: | Article |
Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2023-01-01
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Series: | Jixie qiangdu |
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Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.03.031 |
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author | DONG Qing CHEN YuHao LIU YongGang QI QiSong |
author_facet | DONG Qing CHEN YuHao LIU YongGang QI QiSong |
author_sort | DONG Qing |
collection | DOAJ |
description | To quickly evaluate the safety of damaged bridge structures in the service process of cranes, a real-time prediction method for the fatigue life of bridge structures based on the optimal additive agent model is proposed. Based on the measured load data, the randomness of the relevant parameters of the service conditions is characterized by the combination of the working cycle process. In line with the most unfavorable service conditions, the stress weak position of the bridge structure is determined through finite element statics analysis and failure case statistics. And the structure finite element model is established for fatigue damage and life prediction. The MSC. Fatigue′s S-N module and crack propagation module are employed to simulate the residual life of the structure under random working conditions, and the influence of different crack depths on the residual life of the structure is analyzed. The Kriging model for the life prediction of the bridge structure that is optimized by the Pelican Optimization Algorithm and additive point criterion is created by the Latin Hypercube Sampling method and the black box theory. The real-time fatigue life prediction of bridge structures during trolley movement with load by Miner linear cumulative damage theory. The bridge structure of QD20/10 t × 43 m × 12 m general bridge crane is taken as an example to verify the feasibility of the proposed method. Comparing the proposed method with the traditional fatigue life calculation method based on finite element simulation, the results show that it can accurately assess the remaining life of the damaged bridge structure with fewer simulation calls and shorter simulation time, which can provide some reference significance for crane maintenance cycle formulation and scrapping decisions. |
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issn | 1001-9669 |
language | zho |
last_indexed | 2024-03-12T20:41:39Z |
publishDate | 2023-01-01 |
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series | Jixie qiangdu |
spelling | doaj.art-eaa8059b105a43f9b4b533dfa54ccf5d2023-08-01T07:55:48ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692023-01-0172974240373624FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT)DONG QingCHEN YuHaoLIU YongGangQI QiSongTo quickly evaluate the safety of damaged bridge structures in the service process of cranes, a real-time prediction method for the fatigue life of bridge structures based on the optimal additive agent model is proposed. Based on the measured load data, the randomness of the relevant parameters of the service conditions is characterized by the combination of the working cycle process. In line with the most unfavorable service conditions, the stress weak position of the bridge structure is determined through finite element statics analysis and failure case statistics. And the structure finite element model is established for fatigue damage and life prediction. The MSC. Fatigue′s S-N module and crack propagation module are employed to simulate the residual life of the structure under random working conditions, and the influence of different crack depths on the residual life of the structure is analyzed. The Kriging model for the life prediction of the bridge structure that is optimized by the Pelican Optimization Algorithm and additive point criterion is created by the Latin Hypercube Sampling method and the black box theory. The real-time fatigue life prediction of bridge structures during trolley movement with load by Miner linear cumulative damage theory. The bridge structure of QD20/10 t × 43 m × 12 m general bridge crane is taken as an example to verify the feasibility of the proposed method. Comparing the proposed method with the traditional fatigue life calculation method based on finite element simulation, the results show that it can accurately assess the remaining life of the damaged bridge structure with fewer simulation calls and shorter simulation time, which can provide some reference significance for crane maintenance cycle formulation and scrapping decisions.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.03.031Fatigue life;Kriging agent model;Finite element simulation;Bridge structures;Work cycle |
spellingShingle | DONG Qing CHEN YuHao LIU YongGang QI QiSong FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT) Jixie qiangdu Fatigue life;Kriging agent model;Finite element simulation;Bridge structures;Work cycle |
title | FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT) |
title_full | FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT) |
title_fullStr | FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT) |
title_full_unstemmed | FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT) |
title_short | FATIGUE LIFE PREDICTION METHOD OF BRIDGE STRUCTURE BASED ON OPTIMIZED ADDITIVE POINT AGENT MODEL (MT) |
title_sort | fatigue life prediction method of bridge structure based on optimized additive point agent model mt |
topic | Fatigue life;Kriging agent model;Finite element simulation;Bridge structures;Work cycle |
url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2023.03.031 |
work_keys_str_mv | AT dongqing fatiguelifepredictionmethodofbridgestructurebasedonoptimizedadditivepointagentmodelmt AT chenyuhao fatiguelifepredictionmethodofbridgestructurebasedonoptimizedadditivepointagentmodelmt AT liuyonggang fatiguelifepredictionmethodofbridgestructurebasedonoptimizedadditivepointagentmodelmt AT qiqisong fatiguelifepredictionmethodofbridgestructurebasedonoptimizedadditivepointagentmodelmt |