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07/16/2023
POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenance
Partially Observable Markov Decision Processes (POMDPs) can model comple...
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06/28/2023
Assessment of alternative covariance functions for joint input-state estimation via Gaussian Process latent force models in structural dynamics
Digital technologies can be used to gather accurate information about th...
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06/06/2023
A metric for assessing and optimizing data-driven prognostic algorithms for predictive maintenance
Prognostic Health Management aims to predict the Remaining Useful Life (...
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04/11/2023
VpROM: A novel Variational AutoEncoder-boosted Reduced Order Model for the treatment of parametric dependencies in nonlinear systems
Reduced Order Models (ROMs) are of considerable importance in many areas...
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01/09/2023
Graph Neural Networks for Aerodynamic Flow Reconstruction from Sparse Sensing
Sensing the fluid flow around an arbitrary geometry entails extrapolatin...
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12/15/2022
Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems
Structural Health Monitoring (SHM) describes a process for inferring qua...
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10/09/2022
Neural Extended Kalman Filters for Learning and Predicting Dynamics of Structural Systems
Accurate structural response prediction forms a main driver for structur...
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07/16/2022
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures
The order/dimension of models derived on the basis of data is commonly r...
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05/06/2022
On off-line and on-line Bayesian filtering for uncertainty quantification of structural deterioration
Data-informed predictive maintenance planning largely relies on stochast...
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03/03/2022
Nonlinear Reduced Order Modelling of Soil Structure Interaction Effects via LSTM and Autoencoder Neural Networks
In the field of structural health monitoring (SHM), inverse problems whi...
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02/03/2022
A framework for quantifying the value of vibration-based structural health monitoring
The difficulty in quantifying the benefit of Structural Health Monitorin...
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11/17/2021
An adapted deflated conjugate gradient solver for robust extended/generalised finite element solutions of large scale, 3D crack propagation problems
An adapted deflation preconditioner is employed to accelerate the soluti...
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10/25/2021
Which Model To Trust: Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms for Continuous Control Tasks
The need for algorithms able to solve Reinforcement Learning (RL) proble...
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10/16/2021
Physics-guided Deep Markov Models for Learning Nonlinear Dynamical Systems with Uncertainty
In this paper, we propose a probabilistic physics-guided framework, term...
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09/23/2021
Machine Learning Approach to Model Order Reduction of Nonlinear Systems via Autoencoder and LSTM Networks
In analyzing and assessing the condition of dynamical systems, it is nec...
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08/09/2021
Moment fitted cut spectral elements for explicit analysis of guided wave propagation
In this work, a method for the simulation of guided wave propagation in ...
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06/30/2021
Relational VAE: A Continuous Latent Variable Model for Graph Structured Data
Graph Networks (GNs) enable the fusion of prior knowledge and relational...
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03/12/2021
Value of information from vibration-based structural health monitoring extracted via Bayesian model updating
Quantifying the value of the information extracted from a structural hea...
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03/05/2021
Foundations of Population-Based SHM, Part IV: The Geometry of Spaces of Structures and their Feature Spaces
One of the requirements of the population-based approach to Structural H...
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11/23/2020
Remaining Useful Life Estimation Under Uncertainty with Causal GraphNets
In this work, a novel approach for the construction and training of time...
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06/30/2020
On the use of Nonlinear Normal Modes for Nonlinear Reduced Order Modelling
In many areas of engineering, nonlinear numerical analysis is playing an...
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06/30/2020
On Dynamic Substructuring of Systems with Localised Nonlinearities
Dynamic substructuring (DS) methods encompass a range of techniques to d...
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06/30/2020
On the Potenital of Dynamic Substructuring Methods for Model Updating
While purely data-driven assessment is feasible for the first levels of ...
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03/16/2020
A local basis approximation approach for nonlinear parametric model order reduction
The efficient condition assessment of engineered systems requires the co...
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07/11/2017
