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Based on Fourier neural operator, this study proposes VINO (Vehicle\u2013Bridge Interaction Neural Operator) to serve as a surrogate model of bridge structures. VINO learns mappings between structural response fields and damage fields. In this study, vehicle\u2013bridge interaction (VBI)\u2013finite element (FE) data set was established by running parametric FE simulations of the VBI system, considering a random distribution of the structural initial damage field. Subsequently, vehicle\u2010bridge interaction (VB)\u2013experimental (EXP) dataset was produced by conducting an experimental study under four damage scenarios. After VINO was pretrained by VBI\u2010FE and fine\u2010tuned by VBI\u2010EXP from the bridge at the healthy state, the model achieved the following two improvements. First, forward VINO can predict structural responses from damage field inputs more accurately than the FE model. Second, inverse VINO can determine, localize, and quantify damages in all scenarios, validating the accuracy and efficiency of data\u2010driven approaches.<\/jats:p>","DOI":"10.1111\/mice.13105","type":"journal-article","created":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T04:15:20Z","timestamp":1696220120000},"page":"872-890","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Neural operator for structural simulation and bridge health monitoring"],"prefix":"10.1111","volume":"39","author":[{"given":"Chawit","family":"Kaewnuratchadasorn","sequence":"first","affiliation":[{"name":"Department of Civil and Earth Resources Engineering Kyoto University  Kyoto Japan"},{"name":"Department of Civil Engineering The University of Hong Kong  Pok Fu Lam Hong Kong"}]},{"given":"Jiaji","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering The University of Hong Kong  Pok Fu Lam Hong Kong"}]},{"given":"Chul\u2010Woo","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Civil and Earth Resources Engineering Kyoto University  Kyoto Japan"}]}],"member":"311","published-online":{"date-parts":[[2023,10]]},"reference":[{"key":"e_1_2_8_2_1","unstructured":"Abeykoon D. 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