Hybrid method for full-field response estimation using sparse measurement data based on inverse analysis and static condensation

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dc.citation.articleNumber100017en_US
dc.citation.issueNumber2en_US
dc.citation.journalTitleJournal of Infrastructure Intelligence and Resilienceen_US
dc.citation.volumeNumber1en_US
dc.contributor.authorPal, Ashishen_US
dc.contributor.authorMeng, Weien_US
dc.contributor.authorNagarajaiah, Satishen_US
dc.contributor.orgSmalley-Curly Instituteen_US
dc.date.accessioned2024-05-08T18:56:09Zen_US
dc.date.available2024-05-08T18:56:09Zen_US
dc.date.issued2022en_US
dc.description.abstractIn structural health monitoring, measuring the accurate and spatially dense response near critical locations of the structure can be advantageous to estimate damage to the structure. Due to several physical restrictions or limitations of the sensing method, it may not always be possible to generate reliable data at critical locations. In this study, a hybrid method is presented that makes use of the measured displacement data and finite element (FE) model of the structure to predict dense full-field response. The presented method can incorporate unknown boundary conditions and unknown body forces by applying correction/fictitious forces to match predicted and measured responses. Using static condensation followed by inverse analysis, these additional forces are found by setting up a least square problem. Due to the problem being ill-posed, L2-penalty is used to control the prediction error. Numerical simulation of a plate subjected to body force showed an accurate prediction of full-field response except for a few boundary locations. To handle this, the proposed method is used in conjunction with linear interpolation near boundary locations. The method is validated in a laboratory experiment for a plate with a notch having displacement measured using Digital Image Correlation (DIC). On comparing strains calculated using predicted displacements, FEM, and DIC, the predicted strains show better agreement with the FEM than DIC. This affirms that the proposed hybrid technique can be used at critical locations where DIC fails to provide reliable strain data.en_US
dc.identifier.citationPal, A., Meng, W., & Nagarajaiah, S. (2022). Hybrid method for full-field response estimation using sparse measurement data based on inverse analysis and static condensation. Journal of Infrastructure Intelligence and Resilience, 1(2), 100017. https://doi.org/10.1016/j.iintel.2022.100017en_US
dc.identifier.digital1-s20-S2772991522000172-mainen_US
dc.identifier.doihttps://doi.org/10.1016/j.iintel.2022.100017en_US
dc.identifier.urihttps://hdl.handle.net/1911/115663en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.titleHybrid method for full-field response estimation using sparse measurement data based on inverse analysis and static condensationen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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