PSI - Issue 37

ScienceDirect Structural Integrity Procedia 00 (2019) 000 – 000 Structural Integrity Procedia 00 (2019) 000 – 000 Available online at www.sciencedirect.com Available online at www.sciencedirect.com ScienceD rect Available online at www.sciencedirect.com ScienceDirect

www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia

Procedia Structural Integrity 37 (2022) 6–16

© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira As proof-of-concept, a steel frame's model output is analyzed when Young's modulus E is reduced. The damaged member is successfully identified (a 60% E reduction showing a 94% change), and the most effective DI is Z-score resultant strain energy ZjR. Detection thresholds are found as a variation of 36% between the undamaged and damaged nodes and an average fitness value of 2.3%. Here, the limit of undetectable damage level was an E reduction of 0.001% due to the modeled time histories with 5% Gaussian noise. © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) This paper establ shes a genetic algorithm (GA)-based damage detection scheme to address current issues regarding damage indices. The us of d rectional index resul ants is also intro uced to provide inputs for a GA framework that optimizes detection accuracy of both location a d sev rity. Synchronou or asynchron us time histories of measu ed responses are acquire for wo states (e.g. baseline and subsequ nt inspections, pre- and post-event, a -built and ag d). Mod l analysis is independently perf rmed for both state , a d matched dynam c modal pro rties are us d to generate 51 dir ctional Damage Indices (DIs). These uni-axial DIs are u ed to generate t e 24 tri-axial resu tant DIs. Then th genetic algorithm (GA) fits the normalized resultant DI to a binary target vector t optimize the damage det ction result. The critical threshold is found by thre r unds of analysis, and the outputs are both best DI and optimize damage lo ations. As proof-of-conce , a steel frame's model output is analyzed when Young's modulus E is reduced. The damaged member is succe sfully identified (a 60% E eduction showing a 94% change), a d the most effective DI is Z-score r sultant strain en gy ZjR. Detection thresholds are found as a variati n of 36% between the u amaged and damaged nodes and an aver ge fitness value of 2 3%. Here, limit of undetect ble damage level was an E reduction of 0.001% ue to the modele time histories with 5% Gaussian noise. © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review u der re ponsibility of Pedro Miguel Guimara s Pires Moreira Keywords: Sturctural health evaluation; damage detection index; genetic algorithm 1. Introduction Damage is continuously accumulated during the service life of any load-carrying structure and may eventually cause system-level fail re with aging or abnormal loading. H alth i spections on civil engineering infrastructures ICSI 2021 The 4th International Conference on Structural Integrity Index combination for damage localization using genetic algorithm Elizabeth K. Ervin a *, Chuangshuo Zeng a a Civil Engineering, University of Mississippi,106 Carrier Hall, Box 1848, University, MS 38677 USA Abstract Inspection on infrastructure has a set return period to ensure structural integrity over time. In order to reduce time, cost, and error, vibration data can be analyzed to reveal internal changes, perhaps including defects. Modal properties extracted from acquired structural responses, such as acceleration or velocity, strongly correlate with structural health status. Literature has reported single quantitative measures that are useful for certain structures with particular damage, but publications rarely focus on using three dimensional data in their metrics. Due to the variety of civil infrastructures, damage mechanisms can vary widely such that a single index will be insufficient. This paper establishes a genetic algorithm (GA)-based damage detection scheme to address current issues regarding damage indices. The use of directional index resultants is also introduced to provide inputs for a GA framework that optimizes detection accuracy of both location and severity. Synchronous or asynchronous time histories of measured responses are acquired for two states (e.g. baseline and subsequent inspections, pre- and post-event, as-built and aged). Modal analysis is independently performed for both states, and matched dynamic modal properties are used to generate 51 directional Damage Indices (DIs). These uni-axial DIs are used to generate the 24 tri-axial resultant DIs. Then the genetic algorithm (GA) fits the normalized resultant DIs to a binary target vector to optimize the damage detection result. The critical threshold is found by three rounds of analysis, and the outputs are both best DI and optimized damage locations. ICSI 2021 The 4th International Conference on Structural Integrity Index combination for damage localization using genetic algorithm Elizabeth K. Ervin a *, Chuangshuo Zeng a a Civil Engineering, University of Mississippi,106 Carrier Hall, Box 1848, University, MS 38677 USA Abstract Inspection on infrastructure has a set return period to ensure structural integrity over time. In order to reduce time, cost, and error, vibration data can be analyzed to r veal internal changes, p rhaps including defects. Modal properties extract d from acquire st uctural responses, such as cceleration or velocity, stro ly co relate with structural health status. Lit rature has rep rted single quan itativ mea ure that are useful f r certain s ructures with particular damage, but public tions rarely focus on using three dimensional dat in their metrics. D e t th v riety of civil infrastructures, mechanisms ca vary widely uch that a single index will be insuffici nt. Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira Keywords: Sturctural health evaluation; damage detection index; genetic algorithm 1. Introduction Damage is continuously accumulated during the service life of any load-carrying structure and may eventually cause system-level failure with aging or abnormal loading. Health inspections on civil engineering infrastructures

2452-3216 © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira 2452-3216 © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review u der responsibility of Pedro Miguel Guimara s Pires Moreira

2452-3216 © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira 10.1016/j.prostr.2022.01.054