Publications
This page presents a list, in reverse chronological order, of published peer-reviewed Conference and Journal works along with the Thesis written through the course of study.
The full papers are accessible on my ResearchGate profile while information pertaining to my citations and H-index can be found on my Google Scholar profile. Links to these profiles can be found here.
Conference Papers
Adolphus Lye, and Luca Marino (2023). An investigation into an alternative transition criterion of the Transitional Markov Chain Monte Carlo method for Bayesian model updating. In Proceedings of the 33rd European Safety and Reliability Conference, Southampton. doi: 10.3850/978-981-18-8071-1_P331-cd
Adolphus Lye, Ander Gray, Marco de Angelis, and Scott Ferson (2023). Robust Probability Bounds Analysis for Failure Analysis under Lack of Data and Model Uncertainty. In Proceedings of the 5th International Conference on Uncertainty Quantication in Computational Sciences and Engineering, Athens. doi: 10.7712/120223.10345.19797
Adolphus Lye, Alice Cicirello, and Edoardo Patelli (2022). On-line Bayesian Model Updating and Model Selection of a Piece-wise model for the Creep-growth rate prediction of a Nuclear component. In Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, Hannover. doi: 10.3850/978-981-18-5184-1_MS-02-208-cd
Adolphus Lye, Nawal Prinja, and Edoardo Patelli (2022). Probabilistic Artificial Intelligence Prediction of Material Properties for Nuclear Reactor Designs. In Proceedings of the 32nd European Safety and Reliability Conference, Dublin. doi: 10.3850/978-981-18-5183-4_S24-02-306-cd
Adolphus Lye, Ander Gray, and Edoardo Patelli (2021). Identication of Time-varying Parameters using Variational Bayes - Sequential Ensemble Monte Carlo Sampler. In Proceedings of the 31st European Safety and Reliability Conference, Angers. doi: 10.3850/978-981-18-2016-8_081-cd
Adolphus Lye, Alice Cicirello, and Edoardo Patelli (2020). Bayesian Model Updating of Reliability Parameters using Transitional Markov Chain Monte Carlo with Slice Sampling. In Proceedings of the 30th European Safety and Reliability Conference, Venice. doi: 10.3850/978-981-14-8593-0_4374-cd
Adolphus Lye, Alice Cicirello, and Edoardo Patelli (2019). A Review of Stochastic Sampling Methods for Bayesian Inference Problems. In Proceedings of the 29th European Safety and Reliability Conference, Hannover. doi: 10.3850/978-981-11-2724-3_1087-cd
Adolphus Lye, Alice Cicirello, and Edoardo Patelli (2019). Uncertainty Quantication of Optimal Threshold Failure Probability for Predictive Maintenance using Confidence Structures. In Proceedings of the 3rd International Conference on Uncertainty Quantication in Computational Sciences and Engineering, Crete. doi: 10.7712/120219.6364.18502
Adolphus Lye, Hector Diego Estrada-Lugo, and Edoardo Patelli (2019). Conversion of Fault Tree into Credal Network for Probabilistic Safety Assessment of a Nuclear Power Plant. In Proceedings of the 3rd International Conference on Nuclear Power Plants: Structures, Risk and Decommissioning, London.
Journal Papers
Adolphus Lye, Scott Ferson, Sicong Xiao (2024). Comparison between distance functions for Approximate Bayesian Computation towards Stochastic model updating and Model validation under limited data. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A: Civil Engineering, 10, 03124001. doi: 10.1061/AJRUA6.RUENG-1223
Michael McGurk, Adolphus Lye, Ludovic Renson, and Jie Yuan (2024). Data-Driven Bayesian Inference for Stochastic Model Identification of Nonlinear Aeroelastic Systems. AIAA Journal. doi: 10.2514/1.J063611
Adolphus Lye, Luca Marino, Alice Cicirello, and Edoardo Patelli (2023). Sequential Ensemble Monte Carlo Sampler for On-Line Bayesian Inference of Time-Varying Parameter In Engineering Applications. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B: Mechanical Engineering, 9, 031202. doi: 10.1115/1.4056934
Adolphus Lye, Masaru Kitahara, Matteo Broggi, and Edoardo Patelli (2022). Robust optimisation of a dynamic Black-box system under severe uncertainty: A Distribution-free framework. Mechanical Systems and Signal Processing, 167, 108522. doi: 10.1016/j.ymssp.2021.108522
Adolphus Lye, Alice Cicirello, and Edoardo Patelli (2022). An efficient and robust sampler for Bayesian inference: Transitional Ensemble Markov Chain Monte Carlo. Mechanical Systems and Signal Processing, 167, 108471. doi: 10.1016/j.ymssp.2021.108471
Adolphus Lye, Alice Cicirello, and Edoardo Patelli (2021). Sampling methods for solving Bayesian model updating problems: A tutorial. Mechanical Systems and Signal Processing, 159, 107760. doi: 10.1016/j.ymssp.2021.107760
Thesis
Adolphus Lye (2023). Robust and Efficient Probabilistic Approaches towards Parameter Identification and Model Updating. University of Liverpool Repository. doi: 10.17638/03170546
Adolphus Lye (2018). Core Meltdown Simulation in Nuclear Power Plants. National University of Singapore, Faculty of Science, Department of Physics Undergraduate Thesis Repository. Download here.