Search results
Results: 13
Number of items: 13
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Kakhaia, S., Zun, P., Ye, D., & Krzhizhanovskaya, V. (2023). Inverse uncertainty quantification of a mechanical model of arterial tissue with surrogate modelling. Reliability Engineering & System Safety, 238, Article 109393. https://doi.org/10.1016/j.ress.2023.109393 -
Ye, D., Zun, P., Krzhizhanovskaya, V., & Hoekstra, A. G. (2022). Uncertainty quantification of a three-dimensional in-stent restenosis model with surrogate modelling. Journal of the Royal Society Interface, 19(187), Article 20210864. https://doi.org/10.1098/rsif.2021.0864
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Ye, D., Zun, P., & Veen, L. (2021). ISR3D other inputs file for UQ tutorial paper [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4603912
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Suleimenova, D., Arabnejad, H., Edeling, W. N., Coster, D., Luk, O. O., Lakhlili, J., Jancauskas, V., Kulczewski, M., Veen, L., Ye, D., Zun, P., Krzhizhanovskaya, V., Hoekstra, A., Crommelin, D., Coveney, P. V., & Groen, D. (2021). Tutorial applications for Verification, Validation and Uncertainty Quantification using VECMA toolkit. Journal of Computational Science, 53, Article 101402. https://doi.org/10.1016/j.jocs.2021.101402
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Ye, D., Nikishova, A., Veen, L., Zun, P., & Hoekstra, A. G. (2021). Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model. Reliability Engineering and System Safety, 214, Article 107734. https://doi.org/10.1016/j.ress.2021.107734
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Zun, P., Svitenkov, A., & Hoekstra, A. (2021). Effects of local coronary blood flow dynamics on the predictions of a model of in-stent restenosis. Journal of Biomechanics, 120, Article 110361. https://doi.org/10.1016/j.jbiomech.2021.110361
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Zun, P. S., Narracott, A. J., Evans, P. C., van Rooij, B. J. M., & Hoekstra, A. G. (2020). A particle-based model for endothelial cell migration under flow conditions. Biomechanics and Modeling in Mechanobiology, 19(2), 681-692. https://doi.org/10.1007/s10237-019-01239-w
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Nikishova, A., Veen, L., Zun, P., & Hoekstra, A. G. (2019). Semi-intrusive multiscale metamodelling uncertainty quantification with application to a model of in-stent restenosis. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 377(2142), Article 2018154. https://doi.org/10.1098/rsta.2018.0154
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Zun, P. S., Narracott, A. J., Chiastra, C., Gunn, J., & Hoekstra, A. G. (2019). Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine In Vivo Experiments. Cardiovascular Engineering and Technology, 10(4), 568–582. https://doi.org/10.1007/s13239-019-00431-4
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