activity
20202023
most citedMachine Learning Approach to Model Order Reduction of Nonlinear Systems via Autoencoder and LSTM Networks

68 citations · 70 across the 4 of their papers we have counts for

collaborators

6 papers

math.NA2023

VpROM: A novel Variational AutoEncoder-boosted Reduced Order Model for the treatment of parametric dependencies in nonlinear systems

Thomas Simpson, Konstantinos Vlachas, Anthony Garland +2

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-…

cs.CE2022

Nonlinear Reduced Order Modelling of Soil Structure Interaction Effects via LSTM and Autoencoder Neural Networks

Thomas Simpson, Nikolaos Dervilis, Philippe Couturier +2

In the field of structural health monitoring (SHM), inverse problems which require repeated analyses are common. With the increase in the use of nonlinear models, the development o…

cs.CE2021★ 68 cited

Machine Learning Approach to Model Order Reduction of Nonlinear Systems via Autoencoder and LSTM Networks

Thomas Simpson, Nikolaos Dervilis, Eleni Chatzi

In analyzing and assessing the condition of dynamical systems, it is necessary to account for nonlinearity. Recent advances in computation have rendered previously computationally…

math.NA2020★ 2 cited

On the use of Nonlinear Normal Modes for Nonlinear Reduced Order Modelling

Thomas Simpson, Nikolaos Dervilis, Eleni Chatzi

In many areas of engineering, nonlinear numerical analysis is playing an increasingly important role in supporting the design and monitoring of structures. Whilst increasing comput…

cs.CE2020

On Dynamic Substructuring of Systems with Localised Nonlinearities

Thomas Simpson, Dimitrios Giagopoulos, Vasilis Dertimanis +1

Dynamic substructuring (DS) methods encompass a range of techniques to decompose large structural systems into multiple coupled subsystems. This decomposition has the principle ben…

cs.CE2020

On the Potential of Dynamic Substructuring Methods for Model Updating

Thomas Simpson, Vasilis Dertimanis, Costas Papadimitriou +1

While purely data-driven assessment is feasible for the first levels of the Structural Health Monitoring (SHM) process, namely damage detection and arguably damage localization, th…