02436nas a2200277 a 450000500170000000800410001703500150005810000300007324501080010326000670021130000420027849000270032050001330034750200590048052011690053965000240170865000260173265000280175870000370178670000470182370000460187070000530191671000570196981000590202685600730208520260818085742.0260202s20259999th u  ms t    000   eng d  a.b124740951 aPeerawut Watsaratiyanont 10aData-driven numerical model updating of reinforced concrete structures using artificial neural networks  aPathum Thani, Thailand :bAsian Institute of Technology,c2025  a79 leaves :bill.+e1 online resource1 aThesis ;vno. ST-25-12  aA thesis submitted in partial fulfillment of the requirements for the  degree of Master of Engineering in Structural Engineering  aThesis (M. Eng.) - Asian Institute of Technology, 2025  aThis research develops and evaluates a data-driven model updating framework for reinforced  concrete (RC) building structures using Artificial Neural Networks (ANN) and the 3D Applied  Element Method (AEM). The proposed method aims to improve the accuracy of gradient-based  model updating by providing more realistic initial estimates of material properties based on  measured modal parameters.Databases were generated by varying Young{u2019}s modulus in 3D AEM models and recording  corresponding modal responses. ANN models trained on these databases achieved high  predictive accuracy in low- and moderate-resolution configurations. Verification on a  controlled numerical model demonstrated improved convergence and robustness compared to  conventional random-initial-guess approaches. Validation on two experimental case studies  showed that the method produces updated models with plausible material properties and  improved agreement with measured modal data.The results confirm that the proposed framework effectively integrates data-driven prediction  with numerical updating, providing a practical and efficient approach for RC building model  updating. 0aReinforced concrete 0aConcrete construction 0aArtificial Intelligence1 aKrishna, Chaitanya,eChairperson0 aPennung Warnitchai,eExamination Committee0 aPanon Latcharote,eExamination Committee 0 aRaktipong Sahamitmongkol,eExamination Committee2 aRoyal Thai Government Fellowship,eScholarship Donor2 aAsian Institute of Technology.tThesis ;vno. ST-25-12403Full-Textuhttp://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B23418