Academic Journal
Convolutional neural network for identifying effective seismic force at a DRM layer for rapid reconstruction of SH ground motions
| العنوان: | Convolutional neural network for identifying effective seismic force at a DRM layer for rapid reconstruction of SH ground motions |
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| المؤلفون: | Maharjan, Shashwat, Guidio, Bruno, Jeong, Chanseok |
| المساهمون: | National Science Foundation |
| المصدر: | Earthquake Engineering & Structural Dynamics ; volume 53, issue 2, page 894-923 ; ISSN 0098-8847 1096-9845 |
| بيانات النشر: | Wiley |
| سنة النشر: | 2023 |
| المجموعة: | Wiley Online Library (Open Access Articles via Crossref) |
| الوصف: | We introduce a novel data‐informed convolutional neural network (CNN) approach that utilizes sparse ground motion measurements to accurately identify effective seismic forces in a truncated two‐dimensional (2D) domain. Namely, this paper presents the first prototype of a CNN capable of inferring domain reduction method (DRM) forces, equivalent to incident waves, across all nodes in the DRM layer. It achieves this from sparse measurement data in a multidimensional setting, even in the presence of incoherent incident waves. The method is applied to shear (SH) waves propagating into a domain truncated by a wave‐absorbing boundary condition (WABC). By effectively training the CNN using input‐layer features (surface sensor measurements) and output‐layer features (effective forces at a DRM layer), we achieve significant reductions in processing time compared to PDE‐constrained optimization methods. The numerical experiments demonstrate the method's effectiveness and robustness in identifying effective forces, equivalent to incoherent incident waves, at a DRM layer. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.1002/eqe.4049 |
| الاتاحة: | http://dx.doi.org/10.1002/eqe.4049 https://onlinelibrary.wiley.com/doi/am-pdf/10.1002/eqe.4049 https://onlinelibrary.wiley.com/doi/pdf/10.1002/eqe.4049 |
| Rights: | http://onlinelibrary.wiley.com/termsAndConditions#vor |
| رقم الانضمام: | edsbas.57AA76E |
| قاعدة البيانات: | BASE |
| DOI: | 10.1002/eqe.4049 |
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