Xinyu studied at the department of mechanical engineering in Hunan University (HNU), China for his Bachelor’s degree from 2011-2015 and Master’s degree from 2015-2018. He was working in the field of uncertainty and reliability analysis in engineering for his Master’s studies, particularly on the topic of uncertainty quantification and propagation based on probabilistic methods. He has published 3 international papers for those studies in Journals ‘Reliability Engineering & System Safety (RESS)’, ‘Applied Mathematical Modelling (APM)’ and ‘Frontiers of Mechanical Engineering (FME)’.
After his graduation, he joined the Marie Curie DyVirt program for his PhD in 2018. Currently his research interests focus on Bayesian tools for uncertainty quantification and propagation (UQP) in structural dynamics simulations. The objective of the project (his PhD thesis) is to develop a Bayesian probabilistic framework for UQP in engineering simulations based on complex physics-based models of dynamic systems, component test data and measurements collected during system operation. A data-driven framework will also be developed to update predictions of safety and risk taking into account the uncertainties in future loads. High performance computing techniques will be integrated into the framework to efficiently handle large-order models of hundreds of thousands or millions of degree of freedoms (DOF), including distributed or localized nonlinear actions activated during operation and uncertain/stochastic loads. The framework will be based on the process of assembling the structure from its individual components and substructures.