Year: 2024
Type: conference-paper
Abstract: This paper presents a nonlinear finite element analysis (FEA) of RC beams by adopting material models based on machine learning (ML).The Gaussian Process Regression (GPR) approach is considered for constructing concrete and steel material models.However, a GPR material model has an increased computational load, so it is difficult to use in the nonlinear analysis of RC structures composed of numerous members.To solve this limitation, GPU acceleration is based on the constitution of the parallelized computing structure.GPU-accelerated Python-based FEA program is developed to trace the nonlinear behaviour of RC beams.The FEA and experimental data for two representative RC beams are compared.The results obtained from the developed program confirm that the solution procedure using GPU acceleration with GPR material models can effectively be used in the nonlinear analysis of large RC structures with nonlinear behaviours.
Source: Civil-comp conferences
DOI: 10.4203/ccc.9.14.1
Authors: H. Chung, H.-G. Kwak
Institution: Korea Advanced Institute of Science and Technology
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Award: G2922544013
OpenAlex ID: W4401884469
