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Lye, Adolphus ORCID: 0000-0002-1803-8344, Cicirello, Alice and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2020)
Bayesian Model Updating of Reliability Parameters using Transitional Markov Chain Monte Carlo with Slice Sampling.
In: Proceedings of the 29th European Safety and Reliability Conference (ESREL), 2020-11-1 - 2020-11-5, Venice.
Lye, Adolphus ORCID: 0000-0002-1803-8344, De Angelis, Marco ORCID: 0000-0001-8851-023X and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2020)
Bayesian Regression over Sparse Fatigue Crack Growth Data for Nuclear Piping.
[Poster]
Lye, Adolphus ORCID: 0000-0002-1803-8344, Gray, Ander ORCID: 0000-0002-1585-0900 and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2021)
Identification of Time-varying Parameters using Variational Bayes -- Sequential Ensemble Monte Carlo Sampler.
In: Proceedings of the 31st European Safety and Reliability Conference, 2021-9-19 - 2021-9-23, Angers, France.
Lye, Adolphus ORCID: 0000-0002-1803-8344, Cicirello, Alice and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2022)
On-line Bayesian Inference for Structural Health Monitoring under Model Uncertainty using Sequential Ensemble Monte Carlo.
In: 13th International Conference on Structural Safety and Reliability, 2022-9-13 - 2022-9-17, Shanghai, China.
Lye, Adolphus, Cicirello, Alice and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(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: 8th International Symposium on Reliability Engineering and Risk Management, 2022-9-4 - 2022-9-7, Hannover, Germany.
Lye, Adolphus ORCID: 0000-0002-1803-8344, Prinja, Nawal and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2022)
Probabilistic AI for Prediction of Material Properties (PROMAP).
[Poster]
Lye, Adolphus, Prinja, Nawal and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2022)
Probabilistic Artificial Intelligence Prediction of Material Properties for Nuclear Reactor Designs.
In: 32nd European Safety and Reliability Conference, 2022-8-28 - 2022-9-7, Dublin, Ireland.
Lye, Adolphus, Cicirello, Alice and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2019)
A Review of Stochastic Sampling Methods for Bayesian Inference Problems.
In: Proceedings of the 29th European Safety and Reliability Conference (ESREL), 2019-9-22 - 2019-9-26.
Lye, Adolphus ORCID: 0000-0002-1803-8344, Kitahara, Masaru, Broggi, Matteo and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2022)
Robust optimization of a dynamic Black-box system under severe uncertainty: A distribution-free framework.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 167.
p. 108522.
Lye, Adolphus ORCID: 0000-0002-1803-8344, Cicirello, Alice and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2021)
Sampling methods for solving Bayesian model updating problems: A tutorial.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 159.
p. 107760.
Lye, Adolphus ORCID: 0000-0002-1803-8344, Marino, Luca, Cicirello, Alice and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(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 (3).
pp. 1-13.
Lye, Adolphus ORCID: 0000-0002-1803-8344, Prinja, Nawal and Patelli, Edoardo
(2022)
Towards a Robust Prediction of Material Properties by Artificial Intelligence and Probabilistic Methods.
In: International Conference on Topical Issues in Nuclear Installation Safety: Strengthening Safety of Evolutionary and Innovative Reactor Designs, 2022-10-18 - 2022-10-21, Vienna.
Lye, Adolphus ORCID: 0000-0002-1803-8344, Cicrello, Alice and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2019)
UNCERTAINTY QUANTIFICATION OF OPTIMAL THRESHOLD FAILURE PROBABILITY FOR PREDICTIVE MAINTENANCE USING CONFIDENCE STRUCTURES.
In: 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, 2019-6-24 - 2019-6-26, Crete, Greece.
Lye, Adolphus ORCID: 0000-0002-1803-8344, Cicirello, Alice and Patelli, Edoardo ORCID: 0000-0002-5007-7247
(2022)
An efficient and robust sampler for Bayesian inference: Transitional Ensemble Markov Chain Monte Carlo.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 167.
p. 108471.