Roy, Atin and Chakraborty, Subrata and Adhikari, Sondipon (2024) Seismic reliability analysis of nonlinear structures by active learning-based adaptive sparse Bayesian regressions. International Journal of Non-Linear Mechanics, 165: 104817. ISSN 0020-7462
AI Summary:
The Monte Carlo simulation MCS technique is a simple and accurate approach for seismic reliability analysis SRA of structures involving nonlinear seismic response analysis. The proposed adaptive sparse Bayesian regression-based direct metamodeling approach is developed for SRA, which can avoid prior assumptions and provide better performance than traditional approaches.AI Topics:
The Monte Carlo simulation (MCS) technique is quite simple in concept and the most accurate for seismic reliability analysis (SRA) of structures involving nonlinear seismic response analysis, considering the effect of the stochastic nature of earthquakes and the uncertainty of various structural parameters. However, the approach needs to execute several repetitive nonlinear dynamic analyses of structures. The metamodeling technique has emerged as a practical alternative in such a scenario. In SRA, the dual metamodeling approach is typically adopted to deal with the stochastic nature of earthquakes following a lognormal seismic response assumption. In contrast, a direct metamodeling approach of SRA can avoid such prior assumptions. Adaptive training near the limit state is important in the metamodeling-based SRA. However, its implementation is quite challenging for SRA due to the record-to-record variation of earthquakes. In this context, an adaptive sparse Bayesian regression-based direct metamodeling approach is developed for SRA, where an active learning-based algorithm is proposed for adaptive training of metamodels for approximating nonlinear seismic responses. As the sparse Bayesian regression is computationally faster than Kriging due to the sparsity involved in sparse Bayesian learning, the overall performance of the proposed approach is expected to be better than the adaptive Kriging-based SRA approach. The effectiveness of the proposed approach is illustrated by numerical examples.
Roy, Atin
Author
Roy, Atin and Chakraborty, Subrata and Adhikari, Sondipon (2024) Seismic reliability analysis of nonlinear structures by active learning-based adaptive sparse Bayesian regressions. International Journal of Non-Linear Mechanics, 165: 104817. ISSN 0020-7462
Roy, Atin and Chatterjee, Tanmoy and Adhikari, Sondipon (2024) A physics-informed neural network enhanced importance sampling (PINN-IS) for data-free reliability analysis. Probabilistic Engineering Mechanics, 78: 103701. ISSN 0266-8920
Thapa, Axay and Roy, Atin and Chakraborty, Subrata (2024) A comparative study of various metamodeling approaches in tunnel reliability analysis. Probabilistic Engineering Mechanics, 75: 103553. ISSN 0266-8920
See full publications listChakraborty, Subrata
Author
Roy, Atin and Chakraborty, Subrata and Adhikari, Sondipon (2024) Seismic reliability analysis of nonlinear structures by active learning-based adaptive sparse Bayesian regressions. International Journal of Non-Linear Mechanics, 165: 104817. ISSN 0020-7462
Thapa, Axay and Roy, Atin and Chakraborty, Subrata (2024) A comparative study of various metamodeling approaches in tunnel reliability analysis. Probabilistic Engineering Mechanics, 75: 103553. ISSN 0266-8920
Roy, Atin and Chakraborty, Subrata (2024) Seismic reliability analysis of structures by an adaptive support vector regression based metamodel. Journal of Earthquake Engineering, 28 (6). pp. 1590-1614. ISSN 1363-2469
See full publications listAdhikari, Sondipon
Author
Chowdhury, Sudip and Adhikari, Sondipon (2025) Nonlinear inertial amplifier liquid column dampers. Applied Mathematical Modelling, 140: 115875. ISSN 0307-904X
Chowdhury, Sudip and Adhikari, Sondipon (2025) Nonlinear stiffened inertial amplifier tuned mass friction dampers. Soil Dynamics and Earthquake Engineering, 191: 109264. ISSN 0267-7261
Chowdhury, Sudip and Banerjee, Arnab and Adhikari, Sondipon (2024) From impact to control: inertially amplified friction bearings. ASCE - ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10 (4). ISSN 2376-7642
See full publications listAvailable under License Creative Commons Attribution Non-commercial No Derivatives.
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