2 citations · 7 across the 8 of their papers we have counts for
8 papers
Uncertainty quantification in model discovery by distilling interpretable material constitutive models from Gaussian process posteriors
David Anton, Henning Wessels, Ulrich Römer +2
Constitutive model discovery refers to the task of identifying an appropriate model structure, usually from a predefined model library, while simultaneously inferring its material…
Unsupervised Constitutive Model Discovery from Sparse and Noisy Data
Vahab Knauf Narouie, Jorge-Humberto Urrea-Quintero, Fehmi Cirak +1
Recently, unsupervised constitutive model discovery has gained attention through frameworks based on the Virtual Fields Method (VFM), most prominently the EUCLID approach. However,…
Automated Constitutive Model Discovery by Pairing Sparse Regression Algorithms with Model Selection Criteria
Jorge-Humberto Urrea-Quintero, David Anton, Laura De Lorenzis +1
The automated discovery of constitutive models from data has recently emerged as a promising alternative to the traditional model calibration paradigm. In this work, we present a f…
Physics-Informed Surrogates for Temperature Prediction of Multi-Tracks in Laser Powder Bed Fusion
Hesameddin Safari, Henning Wessels
Modeling plays a critical role in additive manufacturing (AM), enabling a deeper understanding of underlying processes. Parametric solutions for such models are of great importance…
Drivetrain simulation using variational autoencoders
Pallavi Sharma, Jorge-Humberto Urrea-Quintero, Bogdan Bogdan +4
This work proposes variational autoencoders (VAEs) to predict a vehicle's jerk signals from torque demand in the context of limited real-world drivetrain datasets. We implement bot…
Model-based reinforcement corrosion prediction: Continuous calibration with Bayesian optimization and corrosion wire sensor data
A. Potnis, M. Macier, T. Leusmann +3
Chloride-induced corrosion significantly contributes to the degradation of reinforced concrete structures, making accurate predictions of chloride migration and its effects on mate…
Gaussian Processes enabled model calibration in the context of deep geological disposal
Lennart Paul, Jorge-Humberto Urrea-Quintero, Umer Fiaz +5
Deep geological repositories are critical for the long-term storage of hazardous materials, where understanding the mechanical behavior of emplacement drifts is essential for safet…
Parameter identification and uncertainty propagation of hydrogel coupled diffusion-deformation using POD-based reduced-order modeling
Gopal Agarwal, Jorge-Humberto Urrea-Quintero, Henning Wessels +1
This study explores reduced-order modeling for analyzing the time-dependent diffusion-deformation of hydrogels. The full-order model describing hydrogel transient behavior consists…