In silico exploration of post-burn contraction using uncertainty quantification

G. Egberts

Numerical Analysis

Research output: Thesis › Dissertation (TU Delft)

48 Downloads (Pure)

6 Article
1 Conference contribution

7 results

2023
High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations
Egberts, G., Vermolen, F. & van Zuijlen, P., 2023, In: Frontiers in Applied Mathematics and Statistics. 9, p. 1-9 9 p., 1098242.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
77 Downloads (Pure)
Stability of a two-dimensional biomorphoelastic model for post-burn contraction
Egberts, G., Vermolen, F. & van Zuijlen, P., 2023, In: Journal of Mathematical Biology. 86, 4, 37 p., 59.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
55 Downloads (Pure)
2022
A Bayesian finite-element trained machine learning approach for predicting post-burn contraction
Egberts, G., Schaaphok, M., Vermolen, F. & Zuijlen, P. V., 2022, In: Neural Computing and Applications. 34, 11, p. 8635-8642 8 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
2 Citations (Scopus)

55 Downloads (Pure)
Sensitivity of a two-dimensional biomorphoelastic model for post-burn contraction
Egberts, G., Desmoulière, A., Vermolen, F. & van Zuijlen, P., 2022, In: Biomechanics and Modeling in Mechanobiology. 22, 1, p. 105-121 17 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
2 Citations (Scopus)

55 Downloads (Pure)
2021
Sensitivity and feasibility of a one-dimensional morphoelastic model for post-burn contraction
Egberts, G., Vermolen, F. & van Zuijlen, P., 2021, In: Biomechanics and Modeling in Mechanobiology. 20, 6, p. 2147-2167 21 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
3 Citations (Scopus)

46 Downloads (Pure)
Some Mathematical Properties of Morphoelasticity
Egberts, G., Smits, D., Vermolen, F. & van Zuijlen, P., 2021, Numerical Mathematics and Advanced Applications, ENUMATH 2019 - European Conference. Vermolen, F. J. & Vuik, C. (eds.). Cham: Springer, p. 1119-1127 9 p. (Lecture Notes in Computational Science and Engineering; vol. 139).
Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review
2 Citations (Scopus)
Stability of a one-dimensional morphoelastic model for post-burn contraction
Egberts, G., Vermolen, F. & van Zuijlen, P., 2021, In: Journal of Mathematical Biology. 83, 3, p. 1-24 35 p., 24.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
7 Citations (Scopus)

62 Downloads (Pure)

In silico exploration of post-burn contraction using uncertainty quantification

Research output

Search results

High-speed predictions of post-burn contraction using a neural network trained on 2D-finite element simulations

Stability of a two-dimensional biomorphoelastic model for post-burn contraction

A Bayesian finite-element trained machine learning approach for predicting post-burn contraction

Sensitivity of a two-dimensional biomorphoelastic model for post-burn contraction

Sensitivity and feasibility of a one-dimensional morphoelastic model for post-burn contraction

Some Mathematical Properties of Morphoelasticity

Stability of a one-dimensional morphoelastic model for post-burn contraction