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Thomas Simpson
Thomas Simpson
Phd Student, ETH Zurich
Verified email at ibk.baug.ethz.ch
Title
Cited by
Cited by
Year
Machine learning approach to model order reduction of nonlinear systems via autoencoder and LSTM networks
T Simpson, N Dervilis, E Chatzi
Journal of Engineering Mechanics 147 (10), 04021061, 2021
422021
Nonlinear modal analysis via non‐parametric machine learning tools
N Dervilis, TE Simpson, DJ Wagg, K Worden
Strain 55 (1), e12297, 2019
252019
Machine learning for energy load forecasting
D Scott, T Simpson, N Dervilis, T Rogers, K Worden
Journal of Physics: Conference Series 1106 (1), 012005, 2018
222018
Model order reduction for real-time hybrid simulation: Comparing polynomial chaos expansion and neural network methods
N Tsokanas, T Simpson, R Pastorino, E Chatzi, B Stojadinović
Mechanism and Machine Theory 178, 105072, 2022
82022
On the use of variational autoencoders for nonlinear modal analysis
T Simpson, G Tsialiamanis, N Dervilis, K Worden, E Chatzi
Nonlinear Structures & Systems, Volume 1: Proceedings of the 40th IMAC, A …, 2022
8*2022
Towards data-driven real-time hybrid simulation: adaptive modeling of control plants
T Simpson, VK Dertimanis, EN Chatzi
Frontiers in Built Environment 6, 570947, 2020
82020
On the use of nonlinear normal modes for nonlinear reduced order modelling
T Simpson, N Dervilis, E Chatzi
arXiv preprint arXiv:2007.00466, 2020
82020
On dynamic substructuring of systems with localised nonlinearities
T Simpson, D Giagopoulos, V Dertimanis, E Chatzi
Dynamic Substructures, Volume 4: Proceedings of the 38th IMAC, A Conference …, 2021
52021
VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems
T Simpson, K Vlachas, A Garland, N Dervilis, E Chatzi
Scientific Reports 14 (1), 6091, 2024
12024
A Machine Learning Framework for Alleviating Bottlenecks of Projection-Based Reduced Order Models
K Vlachas, T Simpson, C Martinez, AR Brink, E Chatzi
International Design Engineering Technical Conferences & Computers and …, 2021
12021
On the implementation of adaptive inverse control to virtual transfer systems
T Simpson, VK Dertimanis, E Chatzi
EURODYN 2020. Proceedings of the XI International Conference on Structural …, 2020
12020
On the Potential of Dynamic Sub-structuring Methods for Model Updating
T SIMPSON, V DERTIMANIS, C PAPADIMITRIOU, E CHATZI
Structural Health Monitoring 2019, 2019
12019
Reduced order modeling of non-linear monopile dynamics via an AE-LSTM scheme
T Simpson, N Dervilis, P Couturier, N Maljaars, E Chatzi
Frontiers in Energy Research 11, 1128201, 2023
2023
Variational AutoEncoder (VAE) Boosted Parametric Reduced Order Modelling (pROM).
K Vlachas, T Simpson, A Garland, C Martinez, D Quinn, E Chatzi
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022
2022
Nonlinear Reduced Order Modelling of Soil Structure Interaction Effects via LSTM and Autoencoder Neural Networks
T Simpson, N Dervilis, P Couturier, N Maljaars, E Chatzi
arXiv preprint arXiv:2203.01842, 2022
2022
A MACHINE LEARNING FRAMEWORK FOR ALLEVIATING BOTTLENECKS OF PROJECTION-BASED REDUCED ORDER MODELS.
V Konstantinos, T Simpson, C Martinez, A Brink, E Chatzi
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021
2021
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