Computational Biomechanics

Mechanical simulations of biological tissue systems.

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Why Biomechanics?

Biomechanics is a modern topic and offers an enormous range of interesting and challenging problems. Common to many biomechanical problems is a strong scale-dependent behaviour. It is important to analyze the behaviour of material at all scales and adjust models accordingly.

Almost all tissue in the human body contains collagen fibers. A typical example is articular cartilage, where collagen fibers distribute stress optimally for minimizing wear. The Theory of Porous Media (TPM) presents a framework for handling these, as well as other typical properties of biological material. Combining this framwork with the medical knowledge of research partners offers deep insight into vital biological processes in the human body.

Current projects

Articular Cartilage Simulation

Modeling and simulation of articular cartilage

Brain Tumour Modelling

Data-integrated simulation of tumour growth and regression in brain tissue

Digital Liver Lab

Multiscale and Multiphase Modeling of the Human Liver

Modelling of material injection processes into porous structures applied to vertebroplasty

Research Project C03

Publications

  1. 2025

    1. Suditsch, M., Egli, F. S., Lambers, L., & Ricken, T. (2025). Growth in biphasic tissue. International Journal of Engineering Science. https://doi.org/10.1016/j.ijengsci.2024.104183
    2. Azhdari, M., Rezazadeh, G., Ricken, T., Pathak, R., Tautenhahn, H.-M., Tautenhahn, F., & Seyedpour, S. M. (2025). Temperature distribution in multi-layered skin tissue during laser irradiation considering epidermis sublayers: Virtual Element Method approach. Thermal Science and Engineering Progress, 59, 103297. https://doi.org/10.1016/j.tsep.2025.103297
    3. Ali Mirza, Z., Azhdari, M., Kolomenskiy, D., Rezazadeh, G., Ricken, T., Pathak, R., Tautenhahn, H.-M., Tautenhahn, F., & Seyedpour, S. M. (2025). Enhancing laser therapy procedure through surface temperature control in multi-layered skin tissue. Journal of Thermal Biology, 129, 104106. https://doi.org/10.1016/j.jtherbio.2025.104106
    4. Suditsch, M., Wagner, A., & Ricken, T. (2025). Onco*: An umbrella Python framework for modelling and simulation of oncological scenarios. Journal of Computational Science. https://doi.org/10.1016/j.jocs.2025.102533

  2. 2024

    1. Seyedpour, S. M., Azhdari, M., Lambers, L., Ricken, T., & Rezazadeh, G. (2024). One-dimensional thermomechanical bio-heating analysis of viscoelastic tissue to laser radiation shapes. International Journal of Heat and Mass Transfer, 218, 124747. https://doi.org/10.1016/j.ijheatmasstransfer.2023.124747
    2. Tautenhahn, H.-M., Ricken, T., Dahmen, U., Mandl, L., Bütow, L., Gerhäusser, S., Lambers, L., Chen, X., Lehmann, E., Dirsch, O., & König, M. (2024). SimLivA–Modeling ischemia‐reperfusion injury in the liver: A first step towards a clinical decision support tool. GAMM-Mitteilungen. https://doi.org/10.1002/gamm.202370003
    3. Suditsch, M., Egli, F., Lambers, L., Wagner, A., & Ricken, T. (2024). biphasic-kinematic-growth. https://doi.org/10.18419/darus-4361
    4. Brodbeck, M., Suditsch, M., Seyedpour, S. M., & Ricken, T. (2024). Data for: Phase transition in porous materials - Effects of material parameters and deformation regime on mass conservativity. DaRUS. https://doi.org/10.18419/darus-4460
    5. Azhdari, M., Rezazadeh, G., Lambers, L., Ricken, T., Tautenhahn, H.-M., Tautenhahn, F., & Seyedpour, S. M. (2024). Refining thermal therapy: Temperature distribution modeling with distinct absorption in multi-layered skin tissue during infrared laser exposure. International Communications in Heat and Mass Transfer, 157, 107818. https://doi.org/10.1016/j.icheatmasstransfer.2024.107818
    6. Brodbeck, M., Suditsch, M., Seyedpour, S. M., & Ricken, T. (2024). Phase transition in porous materials: effects of material parameters and deformation regime on mass conservativity. Computational Mechanics. https://doi.org/10.1007/s00466-024-02557-2
    7. Tautenhahn, H.-M., Ricken, T., Dahmen, U., Mandl, L., Bütow, L., Gerhäusser, S., Lambers, L., Chen, X., Lehmann, E., Dirsch, O., & König, M. (2024). SimLivA-Modeling ischemia-reperfusion injury in the liver: A first step towards a clinical decision support tool. GAMM-Mitteilungen. https://doi.org/10.1002/gamm.202370003
    8. Trivedi, Z., Wychowaniec, J. K., Gehweiler, D., Sprecher, C. M., Boger, A., Gueorguiev, B., D’Este, M., Ricken, T., & Röhrle, O. (2024). Rheological Analysis and Evaluation of Measurement Techniques for Curing Poly(Methyl Methacrylate) Bone Cement in Vertebroplasty. ACS Biomaterials Science & Engineering, 10, Article 7. https://doi.org/10.1021/acsbiomaterials.4c00417

  3. 2023

    1. Lambers, L., Waschinsky, N., Schleicher, J., König, M., Tautenhahn, H.-M., Albadry, M., Dahmen, U., & Ricken, T. (2023). Quantifying Fat Zonation in Liver Lobules: An IntegratedMultiscale In-silico Model Combining DisturbedMicroperfusion and Fat Metabolism via aContinuum-Biomechanical Bi-scale, Tri-phasic Approach. https://doi.org/10.21203/rs.3.rs-3348101/v1
    2. Seyedpour, S. M., Lambers, L., Rezazadeh, G., & Ricken, T. (2023). Mathematical modelling of the dynamic response of an implantable enhanced capacitive glaucoma pressure sensor. Measurement: Sensors, 100936. https://doi.org/10.1016/j.measen.2023.100936
    3. Azhdari, M., Seyedpour, S. M., Lambers, L., Tautenhahn, H.-M., Tautenhahn, F., Ricken, T., & Rezazadeh, G. (2023). Non-local three phase lag bio thermal modeling of skin tissue and experimental evaluation. International Communications in Heat and Mass Transfer, 149, 107146. https://doi.org/10.1016/j.icheatmasstransfer.2023.107146
    4. Suditsch, M., Ricken, T., & Wagner, A. (2023). Patient‐specific simulation of brain tumour growth and regression. Pamm. https://doi.org/10.1002/pamm.202200213
    5. Azhdari, M., Seyedpour, S. M., Ricken, T., & Rezazadeh, G. (2023). On the thermo-vibrational response of multi-layer viscoelastic skin tissue to laser irradiation. International Journal of Thermal Sciences, 187, 108160. https://doi.org/10.1016/j.ijthermalsci.2023.108160

  4. 2021

    1. Suditsch, M., Lambers, L., Ricken, T., & Wagner, A. (2021). Application of a continuum-mechanical tumour model to brain tissue. Pamm, 21, Article 1. https://doi.org/10.1002/pamm.202100204
    2. Seyedpour, S. M., Nabati, M., Lambers, L., Nafisi, S., Tautenhahn, H.-M., Sack, I., Reichenbach, J. R., & Ricken, T. (2021). Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review. Frontiers in Physiology, 12. https://doi.org/10.3389/fphys.2021.733393
    3. Suditsch, M., Schröder, P., Lambers, L., Ricken, T., Ehlers, W., & Wagner, A. (2021). Modelling basal-cell carcinoma behaviour in avascular skin. Pamm, 20, Article 1. https://doi.org/10.1002/pamm.202000283
    4. Bertrand, F., Lambers, L., & Ricken, T. (2021). Least Squares Finite Element Method for Hepatic Sinusoidal Blood Flow. Pamm, 20, Article 1. https://doi.org/10.1002/pamm.202000306
    5. Christ, B., Collatz, M., Dahmen, U., Herrmann, K.-H., Höpfl, S., König, M., Lambers, L., Marz, M., Meyer, D., Radde, N., Reichenbach, J. R., Ricken, T., & Tautenhahn, H.-M. (2021). Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function. Frontiers in Physiology, 12. https://doi.org/10.3389/fphys.2021.733868
    6. Lambers, L., Mielke, A., & Ricken, T. (2021). Semi-automated Data-driven FE Mesh Generation and Inverse Parameter Identification for a Multiscale and Multiphase Model of Function-Perfusion Processes in the Liver. Pamm, 21, Article 1. https://doi.org/10.1002/pamm.202100190
    7. Lambers, L., Suditsch, M., Wagner, A., & Ricken, T. (2021). A Multiscale and Multiphase Model of Function-Perfusion Growth Processes in the Human Liver. Pamm, 20, Article 1. https://doi.org/10.1002/pamm.202000290
    8. Seyedpour, S. M., Nafisi, S., Nabati, M., Pierce, D. M., Reichenbach, J. R., & Ricken, T. (2021). Magnetic Resonance Imaging–based biomechanical simulation of cartilage: A systematic review. Journal of the Mechanical Behavior of Biomedical Materials, 104963. https://doi.org/10.1016/j.jmbbm.2021.104963
    9. Egli, F. S., Straube, R. C., Mielke, A., & Ricken, T. (2021). Surrogate Modeling of a Nonlinear, Biphasic Model of Articular Cartilage with Artificial Neural Networks. Pamm, 21, Article 1. https://doi.org/10.1002/pamm.202100188
    10. Seyedpour, S. M., Nabati, M., Lambers, L., Nafisi, S., Tautenhahn, H.-M., Sack, I., Reichenbach, J. R., & Ricken, T. (2021). Application of Magnetic Resonance Imaging (MRI) in liver biomechanics: a systematic review. Frontiers in Physiology, 12, 1563. https://doi.org/10.3389/fphys.2021.733393

  5. 2019

    1. Egli, F., & Ricken, T. (2019). On Osmotic Pressure in Hyperelastic Biphasic Fiber--Reinforced Articular Cartilage. Pamm, 19, Article 1. https://doi.org/10.1002/pamm.201900355
    2. Lambers, L., Ricken, T., & König, M. (2019). A multiscale and multiphase model for the description of function-perfusion processes in the human liver. 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, 304.
    3. Lambers, L., Ricken, T., & König, M. (2019). Model Order Reduction (MOR) of Function--Perfusion--Growth Simulation in the Human Fatty Liver via Artificial Neural Network (ANN). Pamm, 19, Article 1. https://doi.org/10.1002/pamm.201900429
    4. Ricken, T., & Lambers, L. (2019). On computational approaches of liver lobule function and perfusion simulation. GAMM-Mitteilungen, 9, Article 3. https://doi.org/10.1002/gamm.201900016
    5. Egli, F., Ricken, T., Wang, X., & Pierce, D. M. (2019). A hyperelastic biphasic fiber reinforced model of articular cartilage incorporating the influences of osmotic pressure and damage. 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, 308.

  6. 2018

    1. Lambers, L., Waschinsky, N., & Ricken, T. (2018). On a Multi-Scale and Multi-Phase Model of Paracetamol-induced Hepatotoxicity for Human Liver. Pamm, 18, Article 1. https://doi.org/10.1002/pamm.201800454
    2. 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.

  7. 2017

    1. 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.
    2. 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, Article 1.
    3. Lambers, L., Waschinsky, N., Werner, D., & Ricken, T. (2017). A Multi-scale and Multi-phase Model for the Description of Toxicity caused by Paracetamol in Biological Tissue using the Example of the Human Liver. Pamm, 17, 199–200. https://doi.org/10.1002/pamm.201710069

  8. 2016

    1. Taranejoo, S., Janmaleki, M., Pachenari, M., Seyedpour, S. M., Chandrasekaran, R., Cheng, W., & Hourigan, K. (2016). Dual effect of F-actin targeted carrier combined with antimitotic drug on aggressive colorectal cancer cytoskeleton: Allying dissimilar cell cytoskeleton disrupting mechanisms. International Journal of Pharmaceutics, 513, Article 1–2.
    2. 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, Article 1.
    3. Janmaleki, M., Pachenari, M., Seyedpour, S. M., Shahghadami, R., & Sanati-Nezhad, A. (2016). Impact of simulated microgravity on cytoskeleton and viscoelastic properties of endothelial cell. Scientific Reports, 6, Article 1.

  9. 2015

    1. Seyedpour, S. M., Pachenari, M., Janmaleki, M., Alizadeh, M., & Hosseinkhani, H. (2015). Effects of an antimitotic drug on mechanical behaviours of the cytoskeleton in distinct grades of colon cancer cells. Journal of Biomechanics, 48, Article 6.

  10. 2014

    1. Pachenari, M., Seyedpour, S. M., Janmaleki, M., Babazadeh Shayan, S., Taranejoo, S., & Hosseinkhani, H. (2014). Mechanical properties of cancer cytoskeleton depend on actin filaments to microtubules content: investigating different grades of colon cancer cell lines. Journal of Biomechanics, 47, Article 2.

  11. 2012

    1. Alizadeh, M., Seyedpour, S. M., Mozafari, V., & Babazadeh Shayan, S. (2012). Calculation and analysis of velocity and viscous drag in an artery with a periodic pressure gradient. Chinese Journal of Mechanical Engineering, 25, Article 4.

  12. 2011

    1. Seyedpour, S. M., Pachenari, M., Alizadeh, M., سیدپور, س. م., پاچناری, م., & علیزاده, م. (2011). محاسبه‌ی الاستیسیته‌ی حجمی جهت تعیین میزان تاثیر دیابت بر روی تصلب شریان. مجله دانشکده پزشکی اصفهان, 29, Article 174.

Head of Research Group

Researchers

This image shows Marlon Suditsch

Marlon Suditsch

M.Sc.

Head of Computational Biomechanics Group, Research Assistant

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