activity
20202026
most citedUnsupervised discovery of interpretable hyperelastic constitutive laws

264 citations · 926 across the 20 of their papers we have counts for

collaborators
Showing 2025Show all

5 papers · 1 filter

physics.comp-ph2025

Discovery of Hyperelastic Constitutive Laws from Experimental Data with EUCLID

Arefeh Abbasi, Maurizio Ricci, Pietro Carrara +4

We assess the performance of EUCLID, Efficient Unsupervised Constitutive Law Identification and Discovery, a recently proposed framework for automated discovery of constitutive law…

cs.RO2025

Shape-Space Graphs: Fast and Collision-Free Path Planning for Soft Robots

Carina Veil, Moritz Flaschel, Ellen Kuhl

Soft robots, inspired by elephant trunks or octopus arms, offer extraordinary flexibility to bend, twist, and elongate in ways that rigid robots cannot. However, their motion plann…

cs.CE2025

Material Fingerprinting: A shortcut to material model discovery without solving optimization problems

Moritz Flaschel, Denisa Martonová, Carina Veil +1

We propose Material Fingerprinting, a new method for the rapid discovery of mechanical material models from direct or indirect data that avoids solving potentially non-convex optim…

cs.CE2025

Non-smooth optimization meets automated material model discovery

Moritz Flaschel, Trevor Hastie, Ellen Kuhl

Automated material model discovery disrupts the tedious and time-consuming cycle of iteratively calibrating and modifying manually designed models. Non-smooth L1-norm regularizatio…

cs.CE2025★ 12 cited

A topology optimisation framework to design test specimens for one-shot identification or discovery of material models

Saeid Ghouli, Moritz Flaschel, Siddhant Kumar +1

The increasing availability of full-field displacement data from imaging techniques in experimental mechanics is determining a gradual shift in the paradigm of material model calib…