Navina Waschinsky

Lambers, L., Waschinsky, N., Schleicher, J., König, M., Tautenhahn, H.-M., Albadry, M., Dahmen, U., & Ricken, T. (2024). Quantifying fat zonation in liver lobules : an integrated multiscale in silico model combining disturbed microperfusion and fat metabolism via a continuum biomechanical bi-scale, tri-phasic approach. Biomechanics and Modeling in Mechanobiology, 23(2), Article 2. https://doi.org/10.1007/s10237-023-01797-0

Grünfelder, N., Savall, B. P., Seyedpour, S. M., Waschinsky, N., & Ricken, T. (2024). Exploring the dependencies of Poisson’s ratio in auxetic structures. PAMM. https://doi.org/10.1002/pamm.202400073

Mandl, L., Mielke, A., Seyedpour, S. M., & Ricken, T. (2023). Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem. Scientific Reports, 13, 15566. https://doi.org/10.1038/s41598-023-42141-x

Ricken, T., Schroeder, J., Bluhm, J., Maike, S., & Bartel, F. (2022). Theoretical formulation and computational aspects of a two-scale homogenization scheme combining the TPM and FE2 method for poro-elastic fluid-saturated porous media. International Journal of Solids and Structures, 241, 111412. https://doi.org/10.1016/j.ijsolstr.2021.111412

Armiti-Juber, A., & Ricken, T. (2022). Model order reduction for deformable porous materials in thin domains via asymptotic analysis. Archive of Applied Mechanics, 92(2), Article 2. https://doi.org/10.1007/s00419-021-01907-3

Waschinsky, N., Barthold, F.-J., & Menzel, A. (2021). Structural optimisation of diffusion driven degradation processes. Structural and Multidisciplinary Optimization, 64, 889--903. https://doi.org/10.1007/s00158-021-02900-8

Drieschner, M., Matthies, H. G., Hoang, T.-V., Rosić, B. V., Ricken, T., Henning, C., Ostermeyer, G.-P., Müller, M., Brumme, S., Srisupattarawanit, T., & others. (2019). Analysis of polymorphic data uncertainties in engineering applications. GAMM-Mitteilungen, e201900010. https://doi.org/10.1002/gamm.201900010

Waschinsky, N., Barthold, F.-J., & Menzel, A. (2019). Optimisation of Diffusion Driven Degradation Processes. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900182

Henning, C., & Ricken, T. (2019). Polymorphic Uncertainty Quantification of Computational Soil and Earth Structure Simulations via the Variational Sensitivity Analysis. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900289

Schmidt, A., Henning, C., Herbrandt, S., Könke, C., Ickstadt, K., Ricken, T., & Lahmer, T. (2019). Numerical studies of earth structure assessment via the theory of porous media using fuzzy probability based random field material descriptions. GAMM-Mitteilungen, 42(1), Article 1. https://doi.org/10.1002/gamm.201900007

Pivovarov, D., Willner, K., Steinmann, P., Brumme, S., Müller, M., Srisupattarawanit, T., Ostermeyer, G.-P., Henning, C., Ricken, T., Kastian, S., & others. (2019). Challenges of order reduction techniques for problems involving polymorphic uncertainty. GAMM-Mitteilungen, 42(2), Article 2. https://doi.org/10.1002/gamm.201900011

Henning, C., & Ricken, T. (2019). Transition of the variational sensitivity analysis to polymorphic uncertainty quantification to soil investigations. Advances in Engineering Materials, Structures and Systems: Innovations, Mechanics and Applications: Proceedings of the 7th International Conference on Structural Engineering, Mechanics and Computation (SEMC 2019), September 2-4, 2019, Cape Town, South Africa, 297–302. https://doi.org/10.1201/9780429426506

Henning, C., Herbrandt, S., Ickstadt, K., & Ricken, T. (2018). Combining Finite Elements and Random Fields to Quantify Uncertainty in a Multi-phase Structural Analysis. PAMM, 18(1), Article 1. https://doi.org/10.1002/pamm.201800333

Ricken, T., Waschinsky, N., & Werner, D. (2018). Simulation of steatosis zonation in liver lobule—a continuummechanical bi-scale, tri-phasic, multi-component approach. Biomedical Technology: Modeling, Experiments and Simulation, 15--33.

Christ, B., Dahmen, U., Herrmann, K.-H., König, M., Reichenbach, J. R., Ricken, T., Schleicher, J., Ole Schwen, L., Vlaic, S., & Waschinsky, N. (2017). Computational modeling in liver surgery. Frontiers in Physiology, 8, 906.

Waschinsky, N., Werner, D., Ricken, T., Dahmen, U., & Dirsch, O. (2017). On a Tri-Scale and Multiphase Model for the Description of Perfusion coupled to Fat Growth Effects in Liver Tissue. PAMM, 17(1), Article 1.

Henning, C., & Ricken, T. (2017). Polymorphic uncertainty quantification for stability analysis of fluid saturated soil and earth structures. PAMM, 17(1), Article 1. https://doi.org/10.1002/pamm.201710018

Waschinsky, N., Werner, D., Ricken, T., Dahmen, U., & Dirsch, O. (2016). On a bi-scale and tri-phasic model for the description of growth in biological tissue using the example of the human liver. PAMM, 16(1), Article 1.