Reliability assessment of civil structures under seismic loads requires probabilistic evaluation considering the uncertainty of input ground motion and material properties due to deterioration. However, Monte Carlo calculation for the structural …
This study developed a framework for real-time dynamic analysis of structural members using physics-informed neural networks (PINN). The interest in the use of augmented reality (AR) and virtual reality (VR) technologies to visualize the results of …
Monte Carlo simulation is often adopted for the structural reliability analysis of civil structures that considers the parameter uncertainties, such as uncertainties of structural properties and input loads in the structural analysis. However, as the …
This study proposes the surrogate modeling by the Gaussian process regression with the transfer learning (TL-GPRSM). The TL-GPRSM can reduce the computational cost by using data with input-output relationships close to those of the target analysis …
This study proposes the surrogate modeling by the Gaussian process regression with the transfer learning (TL-GPRSM). The TL-GPRSM can reduce the computational cost by using data with input-output relationships close to those of the target analysis …
Monte Carlo calculation is used in the seismic risk analysis of infrastructures that consider various parameter uncertainties; however, the calculation cost increases as the parameters become higher in the non-linear time history analysis with …
Monte Carlo calculation is used in the seismic risk analysis of infrastructures that consider various parameter uncertainties; however, the calculation cost increases as the parameters become higher in the non-linear time history analysis with …