ATLAS

AI and Simulation for Tumor Liver ASsessment (ATLAS)

Liver cancer is the second leading cause of cancer-related death. Diagnosis and treatment are time-critical and require highly patient-specific diagnostic and treatment pathways. Medical decision-making is based on a multitude of interdependent factors related to various medical disciplines, past experiences and clinical guidelines. The consideration of all decision factors in combination with the possible therapy approaches is a major challenge for the physicians and often cannot be solved in an optimal way even in the interdisciplinary tumor board. In this project, we develop ATLAS, a decision support tool, which will significantly assist clinicians with this challenge. Based on AI methods, ATLAS processes all relevant patient data from databases, systems medicine and continuum biomechanical in silico prognoses modeling data as well as individual patient data. The tool will be developed in a co-design approach by experts in surgical oncology, mathematical modeling, and machine learning. Chosen technologies integrate the automated understanding of a highly complex patient situation through the simulation of liver functions with expert knowledge and ontology-guided learning with knowledge graphs from retrospective cases of liver tumors. ATLAS will be based on detailed historical data cohort from over 6,000 patients with liver tumors and will be evaluated on case studies at the Jena University Hospital. The integration of medical expert knowledge, mathematical modeling and artificial intelligence constitutes a highly original and most promising approach for high-quality diagnoses and treatments of liver tumors resulting in patient-specific prognosis improvement. Scientific insights from this projects will offer exploitation possibilities for the transfer to malignancies in other organs, such as lungs, kidneys or the brain. Tool and demonstrator development will provide for sustainable exploitation pathways for future commercial applications.

Clinical integration of AI and Simulation for Tumor Liver ASsessment (ATLAS) in the treatment of liver tumors. As the central decision-making element, the tumor board will empowered by ATLAS in the diagnostics and treatment decisions of liver tumors. Currently, the treatment decision is based primarily on the patient’s clinical data, image data, histological reports and the current state of scientific evidence. In the future, ATLAS will support the physicians as a decision support in the clinical process by additionally using In Silico Data and AI. Already in the outpatient clinic, ATLAS will provide recommendations on the necessary diagnostics with regard to the specific tumor and the patient’s condition. In the tumor board, ATLAS will then support the physicians by predicting the outcome of the therapy. ATLAS also contributes to save resources in the structured oncological follow-up by recommending patient-specific examination intervals and diagnostics. As a clinical decision support tool, ATLAS will personalize the therapy and improve patient specific outcome.

This work is supported/funded by the German Federal Ministry of Education and Research (BMBF) under grant numbers 031L0304A, 031L0304B and 031L0304C (ATLAS)

This project is part of CompLS.

News

ATLAS Kick-off Meeting in Stuttgart!

We had an awesome time with the ATLAS team at our first in-person meeting in Stuttgart! We covered a lot - checking our progress, brainstorming how to blend AI, simulation, and clinical data, and enjoying swabian dinner together. It's exciting to see how we're all working together towards an AI- and simulation-based clinical decision supporting tool for liver tumor assessment. 

Project Information

Project Partners:

Tim Ricken
Institute of Structural Mechanics and Dynamics in Aerospace Structures
University of Stuttgart, Pfaffenwaldring 27, 70569 Stuttgart, Germany
tim.ricken@isd.uni-stuttgart.de, +40 711 685 63612
https://www.isd.uni-stuttgart.de/

Steffen Staab
Institute for Artificial Intelligence (KI) – Analytic Computing
University of Stuttgart, Universitätsstraße 32, 70569 Stuttgart, Germany 
steffen.staab@ipvs.uni-stuttgart.de, +49 711 685 88100
https://www.ki.uni-stuttgart.de/departments/ac/

Matthias König
Institute for Theoretical Biology (ITB)
Humboldt-University Berlin, Phillipstraße 13, 10115 Berlin, Germany 
koenigmx@hu-berlin.de, +49 30 2093 98435
https://livermetabolism.com/

Hans-Michael Tautenhahn
Department of Visceral, Transplantation, Thoracic and Vascular Surgery
University Hospital Leipzig, Leipzig, Liebigstr. 20, 04103 Leipzig 
hans-michael.tautenhahn@medizin.uni-leipzig.de, +49 341 9719966
https://www.uniklinikum-leipzig.de/einrichtungen/vttg/%C3%A4rztliche-mitarbeiter-innen

 

Publications

  1. 2025

    1. Pathak, R., Seyedpour, S. M., Kutschan, B., Thoms, S., & Ricken, T. (2025). A coupled multiscale description of seasonal Physical--BioGeoChemical dynamics in Southern Ocean Marginal Ice Zone. Environmental Modelling & Software, 185, 106270. https://doi.org/10.1016/j.envsoft.2024.106270
    2. Armiti-Juber, A., & Ricken, T. (2025). A multigrid two-scale modeling approach for nonlinear multiphysical systems. Computer Methods in Applied Mechanics and Engineering, 433, 117523. https://doi.org/10.1016/j.cma.2024.117523
    3. Mandl, L., Goswami, S., Lambers, L., & Ricken, T. (2025). Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning. Computer Methods in Applied Mechanics and Engineering, 434, 117586. https://doi.org/10.1016/j.cma.2024.117586
    4. Suditsch, M., Egli, F. S., Lambers, L., & Ricken, T. (2025). Growth in biphasic tissue. International Journal of Engineering Science, 208, 104183. https://doi.org/10.1016/j.ijengsci.2024.104183

  2. 2024

    1. Arasteh-Khoshbin, O., Seyedpour, S. M., Mandl, L., Lambers, L., & Ricken, T. (2024). Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA. European Journal of Environmental and Civil Engineering, 1–20. https://doi.org/10.1080/19648189.2024.2393881
    2. Albadry, M., Küttner, J., Grzegorzewski, J., Dirsch, O., Kindler, E., Klopfleisch, R., Liska, V., Moulisova, V., Nickel, S., Palek, R., Rosendorf, J., Saalfeld, S., Settmacher, U., Tautenhahn, H.-M., König, M., & Dahmen, U. (2024). Cross-species variability in lobular geometry and cytochrome P450 hepatic zonation: insights into CYP1A2,  CYP2D6,  CYP2E1 and CYP3A4. Frontiers in Pharmacology, 15. https://doi.org/10.3389/fphar.2024.1404938
    3. Tautenhahn, H., 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
    4. Pathak, R., Seyedpour, S. M., Kutschan, B., Thom, A., Thoms, S., & Ricken, T. (2024). Modeling freezing and BioGeoChemical processes in Antarctic sea ice. PAMM, 24(2), Article 2. https://doi.org/10.1002/pamm.202400047
    5. Maike, S., Schröder, J., Bluhm, J., & Ricken, T. (2024). A mesh--in--element method for the theory of porous media. International Journal for Numerical Methods in Engineering. https://doi.org/10.1002/nme.7565
    6. 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
    7. 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
    8. 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. https://doi.org/10.1007/s10237-023-01797-0
    9. Pi Savall, B., Seyedpour, S. M., & Ricken, T. (2024). Experimental Analysis of Strain and Thermal Behaviour on 3D Printed Flexible Auxetic Structures. In H. Altenbach, L. Hitzler, M. Johlitz, M. Merkel, & A. Öchsner (Eds.), Lectures Notes on Advanced Structured Materials 2 (pp. 85--102). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-49043-95
    10. 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
    11. 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
    12. 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(7), Article 7. https://doi.org/10.1021/acsbiomaterials.4c00417

  3. 2023

    1. 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
    2. Arasteh-Khoshbin, O., Seyedpour, S. M., Brodbeck, M., Lambers, L., & Ricken, T. (2023). On effects of freezing and thawing cycles of concrete containing nano-Formula: see text: experimental study of material properties and crack simulation. Scientific Reports, 13(1), Article 1. https://doi.org/10.1038/s41598-023-48211-4
    3. Soltani, K., Seyedpour, S. M., Ricken, T., & Rezazadeh, G. (2023). Transient high-frequency spherical wave propagation in porous medium using fractional calculus technique. Acta Mechanica. https://doi.org/10.1007/s00707-023-03780-3
    4. 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
    5. Seyedpour, S. M., Thom, A., & Ricken, T. (2023). Simulation of Contaminant Transport through the Vadose Zone: A Continuum Mechanical Approach within the Framework of the Extended Theory of Porous Media (eTPM). Water, 15(2), Article 2. https://doi.org/10.3390/w15020343
    6. Trivedi, Z., Gehweiler, D., Wychowaniec, J. K., Ricken, T., Gueorguiev-Rüegg, B., Wagner, A., & Röhrle, O. (2023). Analysing the bone cement flow in the injection apparatus during vertebroplasty. PAMM, 23(1), Article 1. https://doi.org/10.1002/pamm.202200295
    7. Suditsch, M., Ricken, T., & Wagner, A. (2023). Patient--specific simulation of brain tumour growth and regression. PAMM, 23(1), Article 1. https://doi.org/10.1002/pamm.202200213
    8. 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, 30, 100936. https://doi.org/10.1016/j.measen.2023.100936
    9. Seyedpour, S. M., Henning, C., Kirmizakis, P., Herbrandt, S., Ickstadt, K., Doherty, R., & Ricken, T. (2023). Uncertainty with Varying Subsurface Permeabilities Reduced Using Coupled Random Field and Extended Theory of Porous Media Contaminant Transport Models. Water, 15(1), Article 1. https://doi.org/10.3390/w15010159
    10. 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
    11. Völter, J.-S. L., Ricken, T., & Röhrle, O. (2023). About the applicability of the theory of porous media for the modelling of non--isothermal material injection into porous structures. PAMM, 23(1), Article 1. https://doi.org/10.1002/pamm.202200070
    12. Trivedi, Z., Gehweiler, D., Wychowaniec, J. K., Ricken, T., Gueorguiev, B., Wagner, A., & Röhrle, O. (2023). A continuum mechanical porous media model for vertebroplasty: Numerical simulations and experimental validation. Biomechanics and Modeling in Mechanobiology, 22(4), Article 4. https://doi.org/10.1007/s10237-023-01715-4
    13. Paul, F., Schwarz, C., Audh, R. R., Bluhm, J., Johnson, S., MacHutchon, K., Mielke, T., Mishra, A., Rampai, T., Ricken, T., Schwarz, A., Skatulla, S., Thom, A., Verrinder, R., Schrder, J., Vichi, M., & Lupascu, D. C. (2023). Sea ice mechanics. Computer Methods in Material Science, 23(3), Article 3. https://doi.org/10.7494/cmms.2023.3.0816

  4. 2022

    1. Arasteh-Khoshbin, O., Seyedpour, S., & Ricken, T. (2022). The effect of Caspian Sea water on mechanical properties and durability of concrete containing rice husk ash, nano SiO2, and nano Al2O3. Scientific Reports, 12, 20202. https://doi.org/10.1038/s41598-022-24304-4
    2. Seyedpour, S. M., Nafisi, S., Nabati, M., Pierce, D. M., Reichenbach, J. R., & Ricken, T. (2022). Magnetic Resonance Imaging--based biomechanical simulation of cartilage: A systematic review. Journal of the Mechanical Behavior of Biomedical Materials, 126, 104963. https://doi.org/10.1016/j.jmbbm.2021.104963
    3. Bertrand, F., Brodbeck, M., & Ricken, T. (2022). On robust discretization methods for poroelastic problems: Numerical examples and counter-examples. Examples and Counterexamples, 2, 100087. https://doi.org/10.1016/j.exco.2022.100087
    4. Ricken, T., Schröder, J., Bluhm, J., Maike, S., & Bartel, F. (2022). Theoretical formulation and computational aspects of a two-scale homogenization scheme combining the TPM and FE 2 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
    5. 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

  5. 2021

    1. 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(1), Article 1. https://doi.org/10.1002/pamm.202000290
    2. 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(1), Article 1. https://doi.org/10.1002/pamm.202100188
    3. Mielke, A., & Ricken, T. (2021). Finite element analysis of a 2D cantilever on a noisy intermediate-scale quantum computer. PAMM, 21(1), Article 1. https://doi.org/10.1002/pamm.202100246
    4. Trivedi, Z., Bleiler, C., Gehweiler, D., Gueorguiev-Rüegg, B., Ricken, T., Wagner, A., & Röhrle, O. (2021). Simulating vertebroplasty: A biomechanical challenge. PAMM, 20(1), Article 1. https://doi.org/10.1002/pamm.202000313
    5. Bertrand, F., Lambers, L., & Ricken, T. (2021). Least Squares Finite Element Method for Hepatic Sinusoidal Blood Flow. PAMM, 20(1), Article 1. https://doi.org/10.1002/pamm.202000306
    6. Pi Savall, B., Mielke, A., & Ricken, T. (2021). Data--Driven Stress Prediction for Thermoplastic Materials. PAMM, 21(1), Article 1. https://doi.org/10.1002/pamm.202100225
    7. Seyedpour, S. M., Valizadeh, I., Kirmizakis, P., Doherty, R., & Ricken, T. (2021). Optimization of the Groundwater Remediation Process Using a Coupled Genetic Algorithm-Finite Difference Method. Water, 13(3), Article 3. https://doi.org/10.3390/w13030383
    8. Suditsch, M., Lambers, L., Ricken, T., & Wagner, A. (2021). Application of a continuum--mechanical tumour model to brain tissue. PAMM, 21(1), Article 1. https://doi.org/10.1002/pamm.202100204
    9. 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, 579. https://doi.org/10.3389/fphys.2021.733868
    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 in Liver Biomechanics: A Systematic Review. Frontiers in Physiology, 12, 733393. https://doi.org/10.3389/fphys.2021.733393
    11. Keller, K., Wallmersperger, T., & Ricken, T. (2021). Sensitivity Analysis of a Simulated Hydrogel. PAMM, 20(1), Article 1. https://doi.org/10.1002/pamm.202000317
    12. Mielke, A., & Ricken, T. (2021). Solving linear equation systems on noisy intermediate--scale quantum computers. PAMM, 20(1), Article 1. https://doi.org/10.1002/pamm.202000266
    13. Suditsch, M., Schröder, P., Lambers, L., Ricken, T., Ehlers, W., & Wagner, A. (2021). Modelling basal--cell carcinoma behaviour in avascular skin. PAMM, 20(1), Article 1. https://doi.org/10.1002/pamm.202000283
    14. Thom, A., & Ricken, T. (2021). In Silico Modeling of Coupled Physical--Biogeochemical (P--BGC) Processes in Antarctic Sea Ice. PAMM, 20(1), Article 1. https://doi.org/10.1002/pamm.202000308
    15. 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(1), Article 1. https://doi.org/10.1002/pamm.202100190
    16. Henning, C., Brodbeck, M., Koch, C., Staudacher, S., & Ricken, T. (2021). Phase--field model for erosion processes. PAMM, 20(1), Article 1. https://doi.org/10.1002/pamm.202000282

  6. 2020

    1. Hopkins, G., Skatulla, S., Moj, L., Ricken, T., Ntusi, N., & Meintjes, E. (2020). A biphasic model for full cycle simulation of the human heart aimed at rheumatic heart disease. Computers & Structures, 232, 105920. https://doi.org/10.1016/j.compstruc.2018.02.012
    2. Ricken, T., Thom, A., Gehrke, T., Denecke, M., Widmann, R., Schulte, M., & Schmidt, T. C. (2020). Biological Driven Phase Transitions in Fully or Partly Saturated Porous Media: A Multi-Component FEM Simulation Based on the Theory of Porous Media. In P. Giovine, P. M. Mariano, & G. Mortara (Eds.), Views on Microstructures in Granular Materials (Vol. 44, pp. 157--183). Springer International Publishing. https://doi.org/10.1007/978-3-030-49267-08

  7. 2019

    1. Seyedpour, S. M., Janmaleki, M., Henning, C., Sanati-Nezhad, A., & Ricken, T. (2019). Contaminant transport in soil: A comparison of the Theory of Porous Media approach with the microfluidic visualisation. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2019.05.095
    2. Drieschner, M., Matthies, H. G., Hoang, T.-V., v. Rosić, B., Ricken, T., Henning, C., Ostermeyer, G.-P., Müller, M., Brumme, S., Srisupattarawanit, T., Weinberg, K., & Korzeniowski, T. F. (2019). Analysis of polymorphic data uncertainties in engineering applications. GAMM-Mitteilungen, 42(2), Article 2. https://doi.org/10.1002/gamm.201900010
    3. Nisters, C., Schröder, J., Niekamp, R., & Ricken, T. (2019). The Taylor-least-squares time integrator scheme applied to tracer equations of a sea ice model. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900473
    4. Thom, A., & Ricken, T. (2019). Towards a physical model of Antarctic sea ice microstructure including biogeochemical processes using the extended Theory of Porous Media. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900285
    5. 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(1), Article 1. https://doi.org/10.1002/pamm.201900429
    6. 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.
    7. 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
    8. Egli, F., & Ricken, T. (2019). On Osmotic Pressure in Hyperelastic Biphasic Fiber--Reinforced Articular Cartilage. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900355
    9. Keller, K., Wallmersperger, T., & Ricken, T. (2019). An Overview of Simulated Hydrogel Behaviour under Various Kinds of Stimulation. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900487
    10. 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
    11. Mielke, A., & Ricken, T. (2019). Evaluating Artificial Neural Networks and Quantum Computing for Solving Mechanical Boundary Value Problems. In Zingoni, A (Ed.), Advances in Engineering Materials, Structures and Systems: Innovations, Mechanics and Applications (pp. 537–542). CRC Press-Balkema.
    12. Seyedpour, S. M., Kirmizakis, P., Brennan, P., Doherty, R., & Ricken, T. (2019). Optimal remediation design and simulation of groundwater flow coupled to contaminant transport using genetic algorithm and radial point collocation method (RPCM). Science of The Total Environment, 669, 389--399. https://doi.org/10.1016/j.scitotenv.2019.01.409
    13. Ricken, T., & Lambers, L. (2019). On computational approaches of liver lobule function and perfusion simulation. GAMM-Mitteilungen, 42(4), Article 4. https://doi.org/10.1002/gamm.201900016
    14. Pivovarov, D., Willner, K., Steinmann, P., Brumme, S., Müller, M., Srisupattarawanit, T., Ostermeyer, G.-P., Henning, C., Ricken, T., Kastian, S., Reese, S., Moser, D., Grasedyck, L., Biehler, J., Pfaller, M., Wall, W., Kohlsche, T., von Estorff, O., Gruhlke, R., … Leyendecker, S. (2019). Challenges of order reduction techniques for problems involving polymorphic uncertainty. GAMM-Mitteilungen, 42(2), Article 2. https://doi.org/10.1002/gamm.201900011
    15. Bartel, F., Ricken, T., Schröder, J., & Bluhm, J. (2019). Application of Artificial Neural Network accelerating a porous media FE2 homogenization scheme. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900381
    16. Mielke, A., & Ricken, T. (2019). Evaluating Artificial Neural Networks and Quantum Computing for Mechanics. PAMM, 19(1), Article 1. https://doi.org/10.1002/pamm.201900470

  8. 2018

    1. Moj, L., Ricken, T., Foppe, M., & Deike, R. (2018). Numerical simulation and validation of a solidification experiment using a continuum mechanical two--phase/--scale model. PAMM, 17(1), Article 1. https://doi.org/10.1002/pamm.201710275
    2. Hopkins, G., Skatulla, S., Moj, L., Ricken, T., Ntusi, N., & Meintjes, E. (2018). A biphasic model for full cycle simulation of the human heart aimed at rheumatic heart disease. Computers & Structures. https://doi.org/10.1016/j.compstruc.2018.02.012
    3. Bartel, F., Ricken, T., Schröder, J., & Bluhm, J. (2018). On efficient computation of 3-d simulation within TPM 2 -Framework. PAMM, 18(1), Article 1. https://doi.org/10.1002/pamm.201800332
    4. Lambers, L., Waschinsky, N., & Ricken, T. (2018). On a Multi-Scale and Multi-Phase Model of Paracetamol-induced Hepatotoxicity for Human Liver. PAMM, 18(1), Article 1. https://doi.org/10.1002/pamm.201800454
    5. Bongert, M., Wüst, J., Geller, M., Schlömicher, M., Ricken, T., Nicolas, V., & Strauch, J. (2018). Comparison of two biological aortic valve prostheses inside patient-specific aorta model by bi-directional fluid-structure interaction. Current Directions in Biomedical Engineering, 4(1), Article 1. https://doi.org/10.1515/cdbme-2018-0015
    6. Henning, C., & Ricken, T. (2018). 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
    7. Bartel, F., Ricken, T., Schröder, J., & Bluhm, J. (2018). Microstructural influence on macroscopic response regarding fluid flow through porous media applying TPM2--Method. PAMM, 17(1), Article 1. https://doi.org/10.1002/pamm.201710258
    8. Ricken, T., Waschinsky, N., & Werner, D. (2018). Simulation of Steatosis Zonation in Liver Lobule---A Continuummechanical Bi-Scale, Tri-Phasic, Multi-Component Approach. In Peter Wriggers, Prof. Thomas Lenarz (Ed.), Biomedical Technology. Springer International Publishing. https://doi.org/10.1007/978-3-319-59548-12
    9. Waschinsky, N., Werner, D., Ricken, T., Dahmen, U., & Dirsch, O. (2018). 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. https://doi.org/10.1002/pamm.201710083
    10. Schröder, J., Nisters, C., & Ricken, T. (2018). On a least-squares finite element formulation for sea ice dynamics. PAMM, 18(1), Article 1. https://doi.org/10.1002/pamm.201800156
    11. Wang, X., Eriksson, T. S. E., Ricken, T., & Pierce, D. M. (2018). On incorporating osmotic prestretch/prestress in image-driven finite element simulations of cartilage. Journal of the Mechanical Behavior of Biomedical Materials, 86, 409--422. https://doi.org/10.1016/j.jmbbm.2018.06.014
    12. Pierce, D. M., Ricken, T., & Neu, C. P. (2018). Chapter 4 - Image-Driven Constitutive Modeling for FE-Based Simulation of Soft Tissue Biomechanics. In M. Cerrolaza, S. J. Shefelbine, & D. Garzón-Alvarado (Eds.), Numerical Methods and Advanced Simulation in Biomechanics and Biological Processes (pp. 55--76). Academic Press and Elsevier/AP Academic Press an imprint of Elsevier. https://doi.org/10.1016/B978-0-12-811718-7.00004-6
    13. Thom, A., Ricken, T., Koßler, M., Gehrke, T., Denecke, M., Widmann, R., Schulte, M., & Schmidt, T. C. (2018). Numerical investigations of diffusion coefficients in the context of multi-component gas transport within the Theory of Porous Media. PAMM, 18(1), Article 1. https://doi.org/10.1002/pamm.201800446

  9. 2017

    1. Moj, L., Foppe, M., Deike, R., & Ricken, T. (2017). Micro-macro modelling of steel solidification: A continuum mechanical, bi-phasic, two-scale model including thermal driven phase transition. GAMM--Mitteilungen, 40(2), Article 2. https://doi.org/10.1002/gamm.201720004
    2. Schulte, M., Jochmann, M. A., Gehrke, T., Thom, A., Ricken, T., Denecke, M., & Schmidt, T. C. (2017). Characterization of methane oxidation in a simulated landfill cover system by comparing molecular and stable isotope mass balances. Waste Management, 69, 281--288. https://doi.org/10.1016/j.wasman.2017.07.032
    3. 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. https://doi.org/10.3389/fphys.2017.00906

  10. 2016

    1. Henning, C., Moj, L., & Ricken, T. (2016). A ternary phase bi-scale FE-model for diffusion-driven dendritic alloy solidification processes. PAMM, 16(1), Article 1. https://doi.org/10.1002/pamm.201610213
    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(1), Article 1. https://doi.org/10.1002/pamm.201610043
    3. Pierce, D. M., Unterberger, M. J., Trobin, W., Ricken, T., & Holzapfel, G. A. (2016). A microstructurally based continuum model of cartilage viscoelasticity and permeability incorporating measured statistical fiber orientations. Biomechanics and Modeling in Mechanobiology, 15(1), Article 1. https://doi.org/10.1007/s10237-015-0685-x
    4. Bartel, F., Ricken, T., Schröder, J., & Bluhm, J. (2016). Remarks on coupled multi-scale simulations and high performance computation. PAMM, 16(1), Article 1. https://doi.org/10.1002/pamm.201610244
    5. Seyedpour, S. M., & Ricken, T. (2016). Modeling of contaminant migration in groundwater: A continuum mechanical approach using in the theory of porous media. PAMM, 16(1), Article 1. https://doi.org/10.1002/pamm.201610232

  11. 2015

    1. Werner, D., Ricken, T., Dahmen, U., Dirsch, O., Holzhütter, H.-G., & König, M. (2015). On the Influence of Growth in Perfusion Dependent Biological Systems - at the Example of the Human Liver. PAMM, 15(1), Article 1. https://doi.org/10.1002/pamm.201510050
    2. Ricken, T., Werner, D., Holzhütter, H. G., König, M., Dahmen, U., & Dirsch, O. (2015). Modeling function-perfusion behavior in liver lobules including tissue, blood, glucose, lactate and glycogen by use of a coupled two-scale PDE-ODE approach. Biomech Model Mechanobiol, 14(3), Article 3. https://doi.org/10.1007/s10237-014-0619-z
    3. Thom, A., Ricken, T., Bluhm, J., Widmann, R., Denecke, M., & Gehrke, T. (2015). Validation of a coupled FE-model for the simulation of methane oxidation via thermal imaging. PAMM, 15(1), Article 1. https://doi.org/10.1002/pamm.201510207
    4. Bartel, F., Ricken, T., Schröder, J., & Bluhm, J. (2015). A two-scale homogenisation approach for fluid saturated porous media based on TPM and FE 2 -Method. PAMM, 15(1), Article 1. https://doi.org/10.1002/pamm.201510214
    5. Moj, L., Ricken, T., & Steinbach, I. (2015). A continuum mechanical, bi-phasic, two-scale model for thermal driven phase transition during solidification. PAMM, 15(1), Article 1. https://doi.org/10.1002/pamm.201510195

  12. 2014

    1. Bluhm, J., Bloßfeld, W. M., & Ricken, T. (2014). Energetic effects during phase transition under freezing-thawing load in porous media -- a continuum multiphase description and FE-simulation. ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift Für Angewandte Mathematik Und Mechanik, 94(7–8), Article 7–8. https://doi.org/10.1002/zamm.201200154
    2. Albrecht, D., Ricken, T., & Pierce, D. M. (2014). A Multi-Component Description of Osmotic Driven Deformations in Articular Cartilage. PAMM, 14(1), Article 1. https://doi.org/10.1002/pamm.201410042
    3. Ricken, T., Sindern, A., Bluhm, J., Widmann, R., Denecke, M., Gehrke, T., & Schmidt, T. C. (2014). Concentration driven phase transitions in multiphase porous media with application to methane oxidation in landfill cover layers. ZAMM--Journal of Applied Mathematics and Mechanics/Zeitschrift Für Angewandte Mathematik Und Mechanik, 94(7), Article 7.
    4. Werner, D., Ricken, T., Holzhütter, H.-G., König, M., Dahmen, U., & Dirsch, O. (2014). On growth effects in the human liver. PAMM, 14(1), Article 1. https://doi.org/10.1002/pamm.201410040
    5. Moj, L., Ricken, T., & Steinbach, I. (2014). Multi-Scale and Multi-Component Approach for Solidification Processes. PAMM, 14(1), Article 1. https://doi.org/10.1002/pamm.201410220
    6. Sindern, A., Ricken, T., Bluhm, J., Widmann, R., Denecke, M., & Gehrke, T. (2014). A coupled multi-component approach for bacterial methane oxidation in landfill cover layers. PAMM, 14(1), Article 1. https://doi.org/10.1002/pamm.201410222
    7. Ricken, T., & Bluhm, J. (2014). Modeling of liquid and gas saturated porous solids under freezing and thawing cycles. In T. Schanz & A. Hettler (Eds.), Aktuelle Forschung in der Bodenmechanik 2013 (pp. 23--42). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-37542-22

  13. 2013

    1. Pierce, D. M., Ricken, T., & Holzapfel, G. A. (2013). A hyperelastic biphasic fibre-reinforced model of articular cartilage considering distributed collagen fibre orientations: continuum basis, computational aspects and applications. Computer Methods in Biomechanics and Biomedical Engineering, 16(12), Article 12.
    2. Ricken, T., Dahmen, U., Dirsch, O., & Werner, D. Q. (2013). A Biphasic 3D-FEM Model for the Remodeling of Microcirculation in Liver Lobes. In Computer Models in Biomechanics (pp. 277--292). Springer.
    3. Sindern, A., Ricken, T., Bluhm, J., Widmann, R., & Denecke, M. (2013). Bacterial methane oxidation in landfill cover layers--a coupled FE multiphase description. PAMM, 13(1), Article 1.
    4. Werner, D., Ricken, T., & Ferreira Pfeiffer, A. (2013). On a FEM model for isotropic and transversely isotropic growth in biphasic materials. PAMM, 13(1), Article 1.
    5. Pierce, D. M., Ricken, T., & Holzapfel, G. A. (2013). Modeling sample/patient--specific structural and diffusional responses of cartilage using DT--MRI. International Journal for Numerical Methods in Biomedical Engineering, 29(8), Article 8.
    6. Albrecht, D., Ricken, T., Pierce, D. M., & Holzapfel, G. A. (2013). A hyperelastic biphasic fiber reinforced model for articular cartilage considering the distribution and orientation of collagen fibers. PAMM, 13(1), Article 1.

  14. 2012

    1. Sindern, A., Ricken, T., Bluhm, J., Denecke, M., & Schmidt, T. C. (2012). Phase transition in methane oxidation layers--a coupled FE multiphase description. PAMM, 12(1), Article 1.
    2. Albrecht, D., Ricken, T., Pierce, D. M., & Holzapfel, G. A. (2012). A biphasic transverse isotropic FEM model for cartilage. PAMM, 12(1), Article 1.
    3. Werner, D., Ricken, T., Dahmen, U., & Dirsch, O. (2012). A Biphasic FEM Model for the Microperfusion in Liver Lobules. PAMM, 12(1), Article 1.
    4. Bloßfeld, W. M., Bluhm, J., & Ricken, T. (2012). Simulation of Freezing and Thawing Processes with Capillary Effects in fluid filled porous media. PAMM, 12(1), Article 1.

  15. 2011

    1. Bluhm, J., Bloßfeld, W. M., & Ricken, T. (2011). Simulation of Capillary Effects and Phase Transition under Freezing and Thawing Load in Liquid and Gas Saturated Porous Media. PAMM, 11(1), Article 1.
    2. Robeck, M., Ricken, T., & Widmann, R. (2011). A finite element simulation of biological conversion processes in landfills. Waste Management, 31(4), Article 4. https://doi.org/10.1016/j.wasman.2010.08.007
    3. Lilledahl, M. B., Pierce, D. M., Ricken, T., Holzapfel, G. A., & de Lange Davies, C. (2011). Extracting quantitative biomechanical parameters for cartilage from second harmonic generation images. In A. Periasamy, K. König, & P. T. C. So (Eds.), SPIE BiOS (p. 79033A). SPIE. https://doi.org/10.1117/12.888087
    4. Bluhm, J., Ricken, T., & Bloßfeld, M. (2011). Ice Formation in Porous Media. In Advances in Extended and Multifield Theories for Continua (pp. 153--174). Springer.
    5. Lilledahl, M. B., Pierce, D. M., Ricken, T., Holzapfel, G. A., & de Lange Davies, C. (2011). Structural analysis of articular cartilage using multiphoton microscopy: input for biomechanical modeling. Medical Imaging, IEEE Transactions On, 30(9), Article 9.
    6. Ricken, T., Widmann, R., & Schmidt, T. C. (2011). On the Modeling and Simulation of Biological Methane Oxidation in porous media-A Multiphase Continuum Approach.

  16. 2010

    1. Bluhm, J., Ricken, T., & Bloßfeld, W. M. (2010). Simulation of freeze--thaw--cycles in liquid--and gas saturated porous media. PAMM, 10(1), Article 1.
    2. Ricken, T., & Bluhm, J. (2010). Remodeling and growth of living tissue: a multiphase theory. Archive of Applied Mechanics, 80(5), Article 5.
    3. Ricken, T., Dahmen, U., & Dirsch, O. (2010). A biphasic model for sinusoidal liver perfusion remodeling after outflow obstruction. Biomechanics and Modeling in Mechanobiology, 9(4), Article 4. https://doi.org/10.1007/s10237-009-0186-x
    4. Ricken, T., & Bluhm, J. (2010). Modeling fluid saturated porous media under frost attack. GAMM--Mitteilungen, 33(1), Article 1.
    5. Pierce, D. M., Lilledahl, M. B., Ricken, T., de Lange Davies, C., & Holzapfel, G. A. (2010). Morphological Analysis of Articular Cartilage Using Multiphoton Microscopy as Input for Constitutive Modeling: Experiment and Mathematical Implementation. In 6th World Congress of Biomechanics (WCB 2010). August 1-6, 2010 Singapore (pp. 895--898). Springer.
    6. Ateshian, G. A., & Ricken, T. (2010). Multigenerational interstitial growth of biological tissues. Biomechanics and Modeling in Mechanobiology, 9(6), Article 6. https://doi.org/10.1007/s10237-010-0205-y

  17. 2009

    1. Ricken, T., & Bluhm, J. (2009). Evolutional growth and remodeling in multiphase living tissue. Computational Materials Science, 45(3), Article 3. https://doi.org/10.1016/j.commatsci.2008.10.016
    2. Ricken, T., Bluhm, J., Epple, M., Wehmöller, M., & Annen, T. (2009). An Enriched Biphasic Model for Solute Driven Degradation. PAMM, 9(1), Article 1.
    3. Bluhm, J., Ricken, T., & Bloßfeld, W. M. (2009). Freezing and thawing processes in porous media--Experiment and Simulation. PAMM, 9(1), Article 1.
    4. Ricken, T., Robeck, M., & Widmann, R. (2009). A multiphase finite element simulation of biological conversion processes in landfills. PAMM, 9(1), Article 1.

  18. 2008

    1. Bluhm, J., Ricken, T., & Bloßfeld, W. M. (2008). Energetische Aspekte zum Gefrierverhalten von Wasser in porösen Strukturen. PAMM, 8(1), Article 1.
    2. Schrefler, B. A. (Ed.). (2008). Modeling of porous functionally graded biodegradable implants for bone replacement.
    3. Bluhm, J., Ricken, T., & Bloßfeld, M. (2008). MODELING OF FREEZING AND THAWING CYCLES OF SATURATED POROUS MEDIA.

  19. 2007

    1. Ricken, T., Schwarz, A., & Bluhm, J. (2007). A triphasic model of transversely isotropic biological tissue with applications to stress and biologically induced growth. Computational Materials Science, 39(1), Article 1. https://doi.org/10.1016/j.commatsci.2006.03.025
    2. Bluhm, J., & Ricken, T. (2007). Modeling of freezing and thawing processes in liquid filled thermo-elastic porous solids. Transport in Concrete: Nano-to Macrostructure, Edited by M. Setzer (Aedificatio Publishers, Freiburg, 2007), 41--57.
    3. Ricken, T. (2007). Transverse isotropic flow in biphasic materials. PAMM, 7(1), Article 1.

  20. 2006

    1. Ustohalova, V., Ricken, T., & Widmann, R. (2006). Estimation of landfill emission lifespan using process oriented modeling. Waste Management, 26(4), Article 4. https://doi.org/10.1016/j.wasman.2005.11.012
    2. Ricken, T. (2006). On the Description of Growth in Saturated Living Tissues. PAMM, 6(1), Article 1.
    3. Ricken, T., Schwarz, A., & Bluhm, J. (2006). A Triphasic Theory for Growth in Biological Tissue--Basics and Applications. Materialwissenschaft Und Werkstofftechnik, 37(6), Article 6.

  21. 2005

    1. Ricken, T., & de Boer, R. (2005). Two Phase Flow in Capillary Porous Thermo-Elastic Materials. In IUTAM Symposium on Physicochemical and Electromechanical Interactions in Porous Media (pp. 359--364). Springer.
    2. Ricken, T. (2005). On Biological Activities in Organic Materials. PAMM, 5(1), Article 1.
    3. Ricken, T., & Ustohalova, V. (2005). Modeling of thermal mass transfer in porous media with applications to the organic phase transition in landfills. Computational Materials Science, 32(3), Article 3. https://doi.org/10.1016/j.commatsci.2004.09.015

  22. 2004

    1. Ricken, T. (2004). Mass Transfer in Porous Media. PAMM, 4(1), Article 1.
    2. Ricken, T., de Boer, R., Ustohalova, V., & Widmann, R. (2004). Biodegradation in Porous Landfill Bodies.
    3. Ricken, T., de Boer, R., de Boer, R., & de Boer, R. (2004). Kapillar induzierte Mehrphasenströmung in porösen Medien. Universität Duisburg-Essen.

  23. 2003

    1. Ricken, T., & de Boer, R. (2003). Transport in a capillary thermo--elastic porous material. PAMM, 3(1), Article 1.
    2. Ricken, T. (2003). Transport of fluids in capillary porous solids. PAMM, 2(1), Article 1.
    3. Ricken, T., & de Boer, R. (2003). Multiphase flow in a capillary porous medium. Computational Materials Science, 28(3–4), Article 3–4. https://doi.org/10.1016/j.commatsci.2003.08.032

  24. 2002

    1. Ricken, T. (2002). Kapillarität in porösen Medien: theoretische Untersuchung und numerische Simulation [PhD-Thesis]. Universität Essen.

  25. 1994

    1. de Boer, R., Bluhm, J., Waehling, M., Ricken, T., & Essen Univ.. Fachbereich 10-Bauwesen. (1994). Phase transition in porous media.

Responsible Person:

This image shows Tim Ricken

Tim Ricken

Univ.-Prof. Dr.-Ing.

Head of Department

This image shows Franziska Egli

Franziska Egli

M.Sc.

Research Assistant

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