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"id" : "https://puma.ub.uni-stuttgart.de/bibtex/24864ccb34c23f7f35e3e6456d91df837/lmandl",
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"label" : "Physics-informed time-integrated DeepONet: Temporal tangent space operator learning for high-accuracy inference",
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"journal": "Computer Methods in Applied Mechanics and Engineering",
"year": "2026",
"url": "https://www.sciencedirect.com/science/article/pii/S0045782526001908",
"author": [
"Luis Mandl","Dibyajyoti Nayak","Tim Ricken","Somdatta Goswami"
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"authors": [
{"first" : "Luis", "last" : "Mandl"},
{"first" : "Dibyajyoti", "last" : "Nayak"},
{"first" : "Tim", "last" : "Ricken"},
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"volume": "455","pages": "118917","abstract": "Accurately modeling and inferring solutions to time-dependent partial differential equations (PDEs) over extended temporal horizons remains a core challenge in scientific machine learning. Traditional full rollout (FR) methods, predicting entire trajectories in a single pass, often fail to capture the causal dependencies inherent to dynamical systems and exhibit poor generalization outside the training time horizon. In contrast, autoregressive (AR) approaches, which evolve the system step by step, are prone to error accumulation, as predictions at each time step depend on potentially erroneous prior outputs. These shortcomings limit the long-term accuracy and reliability of both strategies. To overcome these issues, we introduce Physics-Informed Time-Integrated Deep Operator Network (PITI-DeepONet), an operator learning framework designed for stable and accurate long-term time evolution, well beyond the training time horizon. PITI-DeepONet employs a dual-output DeepONet architecture trained via either fully physics-informed or hybrid physics- and data-driven objectives. The training enforces consistency between the learned temporal derivative and its counterpart obtained via automatic differentiation. Rather than directly forecasting future states, the network learns the time-derivative operator from the current state, which is then integrated using classical time-stepping schemes - such as explicit Euler, fourth-order Runge-Kutta, second-order Adams-Bashforth-Moulton, or implicit Euler - to advance the solution sequentially in time. Additionally, the framework supports residual monitoring during inference to estimate prediction quality and flags when the learned temporal tangent becomes unreliable, e.g., outside the training domain. Applied to benchmark problems, PITI-DeepONet demonstrates enhanced accuracy and stability over extended inference time horizons when compared to traditional methods. Mean relative L2 errors reduced by 84% (versus FR) and 79% (versus AR) for the one-dimensional heat equation; by 87% (versus FR) and 98% (versus AR) for the one-dimensional Burgers equation; by 42% (versus FR) and 89% (versus AR) for the two-dimensional Allen-Cahn equation; and by 58% (vs. FR) and 61% (vs. AR) for the one-dimensional Kuramoto-Sivashinsky equation. By moving beyond classic FR and AR schemes, PITI-DeepONet paves the way for more reliable, long-term integration of complex, time-dependent PDEs.",
"issn" : "0045-7825",
"doi" : "https://doi.org/10.1016/j.cma.2026.118917",
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"label" : "Modelling basal\u2010cell carcinoma behaviour in avascular skin",
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"date" : "2025-02-05 01:12:54",
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"journal": "PAMM",
"year": "2021",
"url": "http://dx.doi.org/10.1002/pamm.202000283",
"author": [
"M. Suditsch","P. Schröder","L. Lambers","T. Ricken","W. Ehlers","A. Wagner"
],
"authors": [
{"first" : "M.", "last" : "Suditsch"},
{"first" : "P.", "last" : "Schröder"},
{"first" : "L.", "last" : "Lambers"},
{"first" : "T.", "last" : "Ricken"},
{"first" : "W.", "last" : "Ehlers"},
{"first" : "A.", "last" : "Wagner"}
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"abstract": "AbstractMalignant neoplasms are one of the most dangerous diseases. Within the framework of the well\u2010established Theory of Porous Media (TPM), a multi\u2010constituent model is derived. The model is mathematically formulated by a set of coupled partial differential equations which are solved within the well\u2010known framework of the finite\u2010element method. The general TPM model is applied to basal\u2010cell carcinoma in the avascular skin and representative numerical examples show the capabilities of the model.",
"issn" : "1617-7061",
"doi" : "10.1002/pamm.202000283",
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"label" : "Patient\u2010specific simulation of brain tumour growth and regression",
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"date" : "2025-02-05 01:12:54",
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"journal": "PAMM",
"year": "2023",
"url": "http://dx.doi.org/10.1002/pamm.202200213",
"author": [
"Marlon Suditsch","Tim Ricken","Arndt Wagner"
],
"authors": [
{"first" : "Marlon", "last" : "Suditsch"},
{"first" : "Tim", "last" : "Ricken"},
{"first" : "Arndt", "last" : "Wagner"}
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"abstract": "AbstractThe medical relevance of brain tumours is characterised by its locally invasive and destructive growth. With a high mortality rate combined with a short remaining life expectancy, brain tumours are identified as highly malignant. A continuum\u2010mechanical model for the description of the governing processes of growth and regression is derived in the framework of the Theory of Porous Media (TPM). The model is based on medical multi\u2010modal magnetic resonance imaging (MRI) scans, which represent the gold standard in diagnosis. The multi\u2010phase model is described mathematically via strongly coupled partial differential equations. This set of governing equations is transformed into their weak formulation and is solved with the software package FEniCS. A proof\u2010of\u2010concept simulation based on one patient geometry and tumour pathology shows the relevant processes of tumour growth and the results are discussed.",
"issn" : "1617-7061",
"doi" : "10.1002/pamm.202200213",
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"label" : "Application of a continuum\u2010mechanical tumour model to brain tissue",
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"year": "2021",
"url": "http://dx.doi.org/10.1002/pamm.202100204",
"author": [
"M. Suditsch","L. Lambers","T. Ricken","A. Wagner"
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"authors": [
{"first" : "M.", "last" : "Suditsch"},
{"first" : "L.", "last" : "Lambers"},
{"first" : "T.", "last" : "Ricken"},
{"first" : "A.", "last" : "Wagner"}
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"abstract": "AbstractBrain tumours are among the most serious diseases of our time. A continuum\u2010mechanical model is proposed to represent the basic processes of growth and regression. The physical multi\u2010constituent approach is derived in the framework of the Theory of Porous Media (TPM). This modelling approach can be expressed mathematically via strongly coupled partial differential equations (PDEs), that are solved using the well\u2010known Finite Element Method with the software toolkit FEniCS. A realistic initial\u2010boundary\u2010value problem is used to demonstrate the workflow with the used software and the capabilities of the model.",
"issn" : "1617-7061",
"doi" : "10.1002/pamm.202100204",
"bibtexKey": "suditsch2021application"
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"imported","myOwn","atlas","isd","rg-compbio","exc2075"
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"intraHash" : "4ae7a45e0782c222f771846c5ff3b2d3",
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"label" : "Onco*: An umbrella Python framework for modelling and simulation of oncological scenarios",
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"date" : "2025-02-05 01:12:54",
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"pub-type": "article",
"journal": "Journal of Computational Science",
"year": "2025",
"url": "https://doi.org/10.1016/j.jocs.2025.102533",
"author": [
"Marlon Suditsch","Arndt Wagner","Tim Ricken"
],
"authors": [
{"first" : "Marlon", "last" : "Suditsch"},
{"first" : "Arndt", "last" : "Wagner"},
{"first" : "Tim", "last" : "Ricken"}
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"doi" : "10.1016/j.jocs.2025.102533",
"bibtexKey": "suditsch2025umbrella"
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"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/2915ec72a4630733b0802d8bb2cd98609/marlonsuditsch",
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"imported","myOwn","isd","rg-compbio"
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"intraHash" : "915ec72a4630733b0802d8bb2cd98609",
"interHash" : "835491832a8cfd63910d9978944c7e0a",
"label" : "A Multiscale and Multiphase Model of Function\u2010Perfusion Growth Processes in the Human Liver",
"user" : "marlonsuditsch",
"description" : "",
"date" : "2025-02-05 01:12:54",
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"pub-type": "article",
"journal": "PAMM",
"year": "2021",
"url": "http://dx.doi.org/10.1002/pamm.202000290",
"author": [
"Lena Lambers","Marlon Suditsch","Arndt Wagner","Tim Ricken"
],
"authors": [
{"first" : "Lena", "last" : "Lambers"},
{"first" : "Marlon", "last" : "Suditsch"},
{"first" : "Arndt", "last" : "Wagner"},
{"first" : "Tim", "last" : "Ricken"}
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"abstract": "AbstractDue to an ageing society and unhealthy living conditions, liver diseases like non\u2010alcoholic fatty liver disease (NAFLD) or liver cancer will account for an increasing proportion of deaths in the coming years. Using a mathematical model, the underlying function\u2010perfusion processes of both diseases are investigated. We developed a multiscale and multiphase model for the simulation of hepatic processes on the lobular and cell scale. The lobular scale is described with partial differential equations (PDEs) based on the Theory of Porous Media (TPM), whereas on the cellular scale the metabolic processes are calculated using ordinary differential equations (ODEs). Since NAFLD and the development of a liver tumor lead to tissue growth as well as changes in the blood perfusion, growth and remodelling processes in the human liver are evaluated.",
"issn" : "1617-7061",
"doi" : "10.1002/pamm.202000290",
"bibtexKey": "lambers2021multiscale"
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"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/220635225c87f4eb66d8a3a0b3d38d392/marlonsuditsch",
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"myown","atlas","isd","rg-compbio"
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"label" : "Growth in biphasic tissue",
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"date" : "2024-12-19 00:29:44",
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"journal": "International Journal of Engineering Science",
"year": "2025",
"url": "https://doi.org/10.1016/j.ijengsci.2024.104183",
"author": [
"Marlon Suditsch","Franziska S. Egli","Lena Lambers","Tim Ricken"
],
"authors": [
{"first" : "Marlon", "last" : "Suditsch"},
{"first" : "Franziska S.", "last" : "Egli"},
{"first" : "Lena", "last" : "Lambers"},
{"first" : "Tim", "last" : "Ricken"}
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"doi" : "10.1016/j.ijengsci.2024.104183",
"bibtexKey": "suditsch2025growth"
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"myown","isd","rg-compbio"
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"intraHash" : "2516a17a401590393c0c6e682ac9191a",
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"label" : "Phase transition in porous materials: effects of material parameters and deformation regime on mass conservativity",
"user" : "marlonsuditsch",
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"date" : "2024-12-07 00:05:38",
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"pub-type": "article",
"journal": "Computational Mechanics",
"year": "2024",
"url": "https://doi.org/10.1007/s00466-024-02557-2",
"author": [
"Maximilian Brodbeck","Marlon Suditsch","Seyed Morteza Seyedpour","Tim Ricken"
],
"authors": [
{"first" : "Maximilian", "last" : "Brodbeck"},
{"first" : "Marlon", "last" : "Suditsch"},
{"first" : "Seyed Morteza", "last" : "Seyedpour"},
{"first" : "Tim", "last" : "Ricken"}
],
"abstract": "Phase transition in porous materials is relevant within different engineering applications, such as freezing in saturated soil or pancake sea ice. Mathematical descriptions of such processes can be derived based on Biot\u2019s consolidation theory or the Theory of Porous Media. Depending on parameters such as density ratio, permeability or compressibility of the solid matrix, either small or finite deformations occur. Numerical solution procedures for the general, finite deformation case, suffers from instabilities and high computational costs. Simplifications, assuming small deformations, increases stability and computational efficiency. Within this work shortcomings of simplified theories based on Biot and linearisations of the Theory of Porous Media (TPM) are systematically studied. In order to determine the interaction of the different model parameters a non-dimensional model for poro-elasticity is presented. Based on a characteristic test-case including phase-transition and consolidation, the simplified models are compared to the fully non-linear TPM, focusing on mass errors as well as the time behaviour of the solution. Taking further into account the efficiency of discretisation based on different primal variables and finite-element-spaces, a guideline for selecting an appropriate combination of model, kinematic assumption and discretisation scheme is presented.",
"issn" : "14320924",
"refid" : "Brodbeck2024",
"doi" : "10.1007/s00466-024-02557-2",
"bibtexKey": "brodbeck2024phase"
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"id" : "https://puma.ub.uni-stuttgart.de/bibtex/272373d9bb43e24b26199f605ed22c33f/lmandl",
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"qualiperf","rg-ml","myown","hybrid-mor","PN2","PN2-2","atlas","isd","updated","exc2075"
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"label" : "Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning",
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"date" : "2024-12-03 13:57:51",
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"journal": "Computer Methods in Applied Mechanics and Engineering",
"year": "2025",
"url": "https://www.sciencedirect.com/science/article/pii/S0045782524008405",
"author": [
"Luis Mandl","Somdatta Goswami","Lena Lambers","Tim Ricken"
],
"authors": [
{"first" : "Luis", "last" : "Mandl"},
{"first" : "Somdatta", "last" : "Goswami"},
{"first" : "Lena", "last" : "Lambers"},
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"volume": "434","pages": "117586","abstract": "The deep operator network (DeepONet) has shown remarkable potential in solving partial differential equations (PDEs) by mapping between infinite-dimensional function spaces using labeled datasets. However, in scenarios lacking labeled data, the physics-informed DeepONet (PI-DeepONet) approach, which utilizes the residual loss of the governing PDE to optimize the network parameters, faces significant computational challenges, particularly due to the curse of dimensionality. This limitation has hindered its application to high-dimensional problems, making even standard 3D spatial with 1D temporal problems computationally prohibitive. Additionally, the computational requirement increases exponentially with the discretization density of the domain. To address these challenges and enhance scalability for high-dimensional PDEs, we introduce the Separable physics-informed DeepONet (Sep-PI-DeepONet). This framework employs a factorization technique, utilizing sub-networks for individual one-dimensional coordinates, thereby reducing the number of forward passes and the size of the Jacobian matrix required for gradient computations. By incorporating forward-mode automatic differentiation (AD), we further optimize computational efficiency, achieving linear scaling of computational cost with discretization density and dimensionality, making our approach highly suitable for high-dimensional PDEs. We demonstrate the effectiveness of Sep-PI-DeepONet through three benchmark PDE models: the viscous Burgers\u2019 equation, Biot\u2019s consolidation theory, and a parameterized heat equation. Our framework maintains accuracy comparable to the conventional PI-DeepONet while reducing training time by two orders of magnitude. Notably, for the heat equation solved as a 4D problem, the conventional PI-DeepONet was computationally infeasible (estimated 289.35 h), while the Sep-PI-DeepONet completed training in just 2.5 h. These results underscore the potential of Sep-PI-DeepONet in efficiently solving complex, high-dimensional PDEs, marking a significant advancement in physics-informed machine learning.",
"issn" : "0045-7825",
"preprinturl" : "https://arxiv.org/abs/2407.15887",
"doi" : "https://doi.org/10.1016/j.cma.2024.117586",
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"label" : "On the influence of non-linearity within two-phase poro-elasticity: Numerical examples and counterexamples",
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"date" : "2024-11-05 14:23:31",
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"journal": "Examples and Counterexamples","booktitle": "Examples and Counterexamples","publisher":"Elsevier",
"year": "2024",
"url": "https://doi.org/10.1016/j.exco.2024.100167",
"author": [
"Maximilian Brodbeck","Franziska S. Egli","Marlon Suditsch","Seyed Morteza Seyedpour","Tim Ricken"
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"authors": [
{"first" : "Maximilian", "last" : "Brodbeck"},
{"first" : "Franziska S.", "last" : "Egli"},
{"first" : "Marlon", "last" : "Suditsch"},
{"first" : "Seyed Morteza", "last" : "Seyedpour"},
{"first" : "Tim", "last" : "Ricken"}
],
"volume": "6",
"issn" : "2666657X",
"comment" : "doi: 10.1016/j.exco.2024.100167",
"doi" : "10.1016/j.exco.2024.100167",
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{
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"id" : "https://puma.ub.uni-stuttgart.de/bibtex/23ebccdce9fddc93484ee48096a113de2/lmandl",
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"label" : "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",
"user" : "lmandl",
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"date" : "2024-10-02 17:42:07",
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"pub-type": "article",
"journal": "European Journal of Environmental and Civil Engineering","publisher":"Taylor & Francis",
"year": "2024",
"url": "",
"author": [
"O. Arasteh-Khoshbin","Seyed Morteza Seyedpour","Luis Mandl","Lena Lambers","Tim Ricken"
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"authors": [
{"first" : "O.", "last" : "Arasteh-Khoshbin"},
{"first" : "Seyed Morteza", "last" : "Seyedpour"},
{"first" : "Luis", "last" : "Mandl"},
{"first" : "Lena", "last" : "Lambers"},
{"first" : "Tim", "last" : "Ricken"}
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"pages": "1\u201320",
"issn" : "2116-7214",
"doi" : "10.1080/19648189.2024.2393881",
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"id" : "https://puma.ub.uni-stuttgart.de/bibtex/2bf594299a1e67aece40891441082661a/lmandl",
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"label" : "SimLivA\u2013Modeling ischemia\u2010reperfusion injury in the liver: A first step towards a clinical decision support tool",
"user" : "lmandl",
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"date" : "2024-02-16 10:35:52",
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"journal": "GAMM-Mitteilungen","publisher":"Wiley",
"year": "2024",
"url": "http://dx.doi.org/10.1002/gamm.202370003",
"author": [
"Hans\u2010Michael Tautenhahn","Tim Ricken","Uta Dahmen","Luis Mandl","Laura Bütow","Steffen Gerhäusser","Lena Lambers","Xinpei Chen","Elina Lehmann","Olaf Dirsch","Matthias König"
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"authors": [
{"first" : "Hans\u2010Michael", "last" : "Tautenhahn"},
{"first" : "Tim", "last" : "Ricken"},
{"first" : "Uta", "last" : "Dahmen"},
{"first" : "Luis", "last" : "Mandl"},
{"first" : "Laura", "last" : "Bütow"},
{"first" : "Steffen", "last" : "Gerhäusser"},
{"first" : "Lena", "last" : "Lambers"},
{"first" : "Xinpei", "last" : "Chen"},
{"first" : "Elina", "last" : "Lehmann"},
{"first" : "Olaf", "last" : "Dirsch"},
{"first" : "Matthias", "last" : "König"}
],
"issn" : "1522-2608",
"doi" : "10.1002/gamm.202370003",
"bibtexKey": "Tautenhahn_2024"
}
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{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/264dcef425b67715336c4460f2e9d7475/lenalambers",
"tags" : [
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"intraHash" : "64dcef425b67715336c4460f2e9d7475",
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"label" : "Quantifying Fat Zonation in Liver Lobules: An IntegratedMultiscale In-silico Model Combining DisturbedMicroperfusion and Fat Metabolism via aContinuum-Biomechanical Bi-scale, Tri-phasic Approach",
"user" : "lenalambers",
"description" : "",
"date" : "2023-11-15 18:23:16",
"changeDate" : "2024-06-06 16:19:28",
"count" : 6,
"pub-type": "article",
"publisher":"Research Square Platform LLC",
"year": "2023",
"url": "http://dx.doi.org/10.21203/rs.3.rs-3348101/v1",
"author": [
"Lena Lambers","Navina Waschinsky","Jana Schleicher","Matthias König","Hans-Michael Tautenhahn","Mohamed Albadry","Uta Dahmen","Tim Ricken"
],
"authors": [
{"first" : "Lena", "last" : "Lambers"},
{"first" : "Navina", "last" : "Waschinsky"},
{"first" : "Jana", "last" : "Schleicher"},
{"first" : "Matthias", "last" : "König"},
{"first" : "Hans-Michael", "last" : "Tautenhahn"},
{"first" : "Mohamed", "last" : "Albadry"},
{"first" : "Uta", "last" : "Dahmen"},
{"first" : "Tim", "last" : "Ricken"}
],
"doi" : "10.21203/rs.3.rs-3348101/v1",
"bibtexKey": "Lambers_2023"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/2f7c0b2bd77f733abed52e18571941fe4/lenalambers",
"tags" : [
"qualiperf","myown","pn2","for5151","isd","rg-compbio","exc2075"
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"intraHash" : "f7c0b2bd77f733abed52e18571941fe4",
"interHash" : "63230bcc4a25b112c6e64e460107c7e1",
"label" : "Mathematical modelling of the dynamic response of an implantable enhanced capacitive glaucoma pressure sensor",
"user" : "lenalambers",
"description" : "",
"date" : "2023-11-15 18:20:01",
"changeDate" : "2024-06-06 16:20:21",
"count" : 9,
"pub-type": "article",
"journal": "Measurement: Sensors",
"year": "2023",
"url": "https://www.sciencedirect.com/science/article/pii/S2665917423002726",
"author": [
"Seyed Morteza Seyedpour","Lena Lambers","Ghader Rezazadeh","Tim Ricken"
],
"authors": [
{"first" : "Seyed Morteza", "last" : "Seyedpour"},
{"first" : "Lena", "last" : "Lambers"},
{"first" : "Ghader", "last" : "Rezazadeh"},
{"first" : "Tim", "last" : "Ricken"}
],
"pages": "100936","abstract": "Glaucoma as an eye disease influences the optic nerve, resulting in progressive vision loss and, thus, blindness. For this disease, the most important risk factor is high intraocular pressure. Therefore, it is important to accurately measure the intraocular pressure. The present work aimes to present a mathematical description of a capacitive pressure sensor based on a Micro-Electro-Mechanical-Systems (MEMS) to measure intraocular pressure (IOP). The relatively high working bias voltage of MEMS capacitive pressure sensors restricts their potential applications as implantable sensors. Hence, Polydimethylsiloxane (PDMS) is employed as a porous elastomeric substance between the deformable and fixed electrodes of the capacitor. With a low young modulus and a higher dielectric constant, it reduces the sensor's working bias voltage. The PDMS's permittivity and young modulus are a function of the porosity volume fraction based on displacement in terms of a power law with fractional power constant. The dynamic equation of the microplate's transversal motion is used in the developed model, taking mid-plane stre-tching into account along with the generated force owing to the PDMS film squeezing. To decompose the governing nonlinear equation, a weak formulation is used with appropriate basis functions, thus integrating the attained ordinary differential equations over time. The sensor response to static pressure and step-wise alteration of the applied pressure is examined by dynamic and static analysis. The results of pull-in voltage reveal that using the PDMS as a dielectric causes a considerable reduction. Additionally, the effect of the PDMS elasticity on the capacitance and displacement was assessed along with the effects of the geometrical parameters on the sensor response.",
"issn" : "2665-9174",
"doi" : "https://doi.org/10.1016/j.measen.2023.100936",
"bibtexKey": "SEYEDPOUR2023100936"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/27d2174d8d45f7342a5dd5a442e3429ba/lenalambers",
"tags" : [
"qualiperf","myown","pn2","for5151","isd","rg-compbio","exc2075"
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"interHash" : "82bfe94abd19b52edb72c3b61d8ae2db",
"label" : "One-dimensional thermomechanical bio-heating analysis of viscoelastic tissue to laser radiation shapes",
"user" : "lenalambers",
"description" : "",
"date" : "2023-11-15 18:13:18",
"changeDate" : "2024-06-06 16:20:52",
"count" : 9,
"pub-type": "article",
"journal": "International Journal of Heat and Mass Transfer","publisher":"Elsevier",
"year": "2024",
"url": "",
"author": [
"Seyed Morteza Seyedpour","Mohammad Azhdari","Lena Lambers","Tim Ricken","Ghader Rezazadeh"
],
"authors": [
{"first" : "Seyed Morteza", "last" : "Seyedpour"},
{"first" : "Mohammad", "last" : "Azhdari"},
{"first" : "Lena", "last" : "Lambers"},
{"first" : "Tim", "last" : "Ricken"},
{"first" : "Ghader", "last" : "Rezazadeh"}
],
"volume": "218","pages": "124747",
"doi" : "https://doi.org/10.1016/j.ijheatmasstransfer.2023.124747",
"bibtexKey": "seyedpour2024one"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/23d4f476ebe3785666ff01ad58f9b878a/lenalambers",
"tags" : [
"myown","pn2","isd","rg-compbio","exc2075"
],
"intraHash" : "3d4f476ebe3785666ff01ad58f9b878a",
"interHash" : "173fb49a1dcdfa9efd0f172ba03cce80",
"label" : "Non-local three phase lag bio thermal modeling of skin tissue and experimental evaluation",
"user" : "lenalambers",
"description" : "",
"date" : "2023-11-15 18:11:17",
"changeDate" : "2024-06-06 16:21:12",
"count" : 9,
"pub-type": "article",
"journal": "International Communications in Heat and Mass Transfer",
"year": "2023",
"url": "https://www.sciencedirect.com/science/article/pii/S0735193323005353",
"author": [
"Mohammad Azhdari","Seyed Morteza Seyedpour","Lena Lambers","Hans-Michael Tautenhahn","Franziska Tautenhahn","Tim Ricken","Ghader Rezazadeh"
],
"authors": [
{"first" : "Mohammad", "last" : "Azhdari"},
{"first" : "Seyed Morteza", "last" : "Seyedpour"},
{"first" : "Lena", "last" : "Lambers"},
{"first" : "Hans-Michael", "last" : "Tautenhahn"},
{"first" : "Franziska", "last" : "Tautenhahn"},
{"first" : "Tim", "last" : "Ricken"},
{"first" : "Ghader", "last" : "Rezazadeh"}
],
"volume": "149","pages": "107146","abstract": "In this paper, the thermal behavior of living tissue has been modeled using a non-local three-phase lag approach. The simulation results of this model- ing have been compared with experimental results of alternating radiation with different periods on human skin, yielding satisfactory alignments. Ad- ditionally, it has been investigated that the TPL model, which is an equation with an integral term, can simulate energy accumulation within the dermal tissue. Moreover, the non-local nature of the modeling has been explored to alter the influence of phase lag terms. Furthermore, apart from numer- ically solving the equation, an analytical solution has been derived for the frequency equation, demonstrating the effects of simulation parameters on the frequency equation and simulation results. The obtained results indi cate that these parameters not only independently affect the outcomes but also interact with other parameters, leading to variations beyond their direct impacts.",
"issn" : "0735-1933",
"doi" : "https://doi.org/10.1016/j.icheatmasstransfer.2023.107146",
"bibtexKey": "AZHDARI2023107146"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/20252f0b3fb5a37ee4a3c234a3791b9f3/lmandl",
"tags" : [
"qualiperf","rg-ml","neural-network","myown","hybrid-mor","simliva","machine-learning","atlas","isd","physics-informed"
],
"intraHash" : "0252f0b3fb5a37ee4a3c234a3791b9f3",
"interHash" : "8596788f2da4f14c756f36923e0be9f2",
"label" : "Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem",
"user" : "lmandl",
"description" : "",
"date" : "2023-10-23 11:04:28",
"changeDate" : "2024-09-25 11:21:43",
"count" : 11,
"pub-type": "article",
"journal": "Scientific Reports",
"year": "2023",
"url": "https://doi.org/10.1038/s41598-023-42141-x",
"author": [
"Luis Mandl","André Mielke","Seyed Morteza Seyedpour","Tim Ricken"
],
"authors": [
{"first" : "Luis", "last" : "Mandl"},
{"first" : "André", "last" : "Mielke"},
{"first" : "Seyed Morteza", "last" : "Seyedpour"},
{"first" : "Tim", "last" : "Ricken"}
],
"volume": "13","pages": "15566","abstract": "Physics-informed neural networks (PINNs) leverage data and knowledge about a problem. They provide a nonnumerical pathway to solving partial differential equations by expressing the field solution as an artificial neural network. This approach has been applied successfully to various types of differential equations. A major area of research on PINNs is the application to coupled partial differential equations in particular, and a general breakthrough is still lacking. In coupled equations, the optimization operates in a critical conflict between boundary conditions and the underlying equations, which often requires either many iterations or complex schemes to avoid trivial solutions and to achieve convergence. We provide empirical evidence for the mitigation of bad initial conditioning in PINNs for solving one-dimensional consolidation problems of porous media through the introduction of affine transformations after the classical output layer of artificial neural network architectures, effectively accelerating the training process. These affine physics-informed neural networks (AfPINNs) then produce nontrivial and accurate field solutions even in parameter spaces with diverging orders of magnitude. On average, AfPINNs show the ability to improve the \\$\\$\\\\backslashmathscr Ł\\\\\\_2\\$\\$relative error by \\$\\$64.84\\backslash\\%\\$\\$after 25,000 epochs for a one-dimensional consolidation problem based on Biot's theory, and an average improvement by \\$\\$58.80\\backslash\\%\\$\\$with a transfer approach to the theory of porous media.",
"issn" : "2045-2322",
"doi" : "10.1038/s41598-023-42141-x",
"bibtexKey": "Mandl2023"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/271ba3d65f853a2bf0b4739aa83450314/marlonsuditsch",
"tags" : [
"myown","pn2","simtech","mib_ls2","isd","exc2075"
],
"intraHash" : "71ba3d65f853a2bf0b4739aa83450314",
"interHash" : "4d4ae8fbdeb29d94671e62b5d3ef8f42",
"label" : "Patient-specific simulation of brain tumour growth and regression",
"user" : "marlonsuditsch",
"description" : "",
"date" : "2023-06-07 07:36:29",
"changeDate" : "2023-06-07 07:36:29",
"count" : 6,
"pub-type": "article",
"journal": "PAMM","publisher":"Wiley",
"year": "2023",
"url": "https://doi.org/10.1002%2Fpamm.202200213",
"author": [
"Marlon Suditsch","Tim Ricken","Arndt Wagner"
],
"authors": [
{"first" : "Marlon", "last" : "Suditsch"},
{"first" : "Tim", "last" : "Ricken"},
{"first" : "Arndt", "last" : "Wagner"}
],
"volume": "23","number": "1",
"doi" : "10.1002/pamm.202200213",
"bibtexKey": "Suditsch_2023"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/23a9df66447921dfe31d3723c1d8901a3/lenalambers",
"tags" : [
"qualiperf","myown","pn2","for5151","isd","rg-compbio","exc2075"
],
"intraHash" : "3a9df66447921dfe31d3723c1d8901a3",
"interHash" : "e158a3480455513ffb6b087efe708b27",
"label" : "Semi-automated Data-driven FE Mesh Generation and Inverse Parameter Identification for a Multiscale and Multiphase Model of Function-Perfusion Processes in the Liver",
"user" : "lenalambers",
"description" : "",
"date" : "2021-12-15 09:47:36",
"changeDate" : "2024-06-06 16:22:00",
"count" : 9,
"pub-type": "article",
"journal": "PAMM",
"year": "2021",
"url": "",
"author": [
"Lena Lambers","André Mielke","Tim Ricken"
],
"authors": [
{"first" : "Lena", "last" : "Lambers"},
{"first" : "André", "last" : "Mielke"},
{"first" : "Tim", "last" : "Ricken"}
],
"volume": "21","number": "1",
"issn" : "1617-7061",
"doi" : "10.1002/pamm.202100190",
"bibtexKey": "Lambers.2021"
}
,
{
"type" : "Publication",
"id" : "https://puma.ub.uni-stuttgart.de/bibtex/2f539da2c8354ef34f26ae34bd8371aef/katharinafuchs",
"tags" : [
"myown","pn2","from:lenalambers","isd","EXC2075"
],
"intraHash" : "f539da2c8354ef34f26ae34bd8371aef",
"interHash" : "4d72b7eff2282d9ac8dec12295b4c5f3",
"label" : "Modelling basal-cell carcinoma behaviour in avascular skin",
"user" : "katharinafuchs",
"description" : "",
"date" : "2021-12-08 17:10:08",
"changeDate" : "2021-12-08 16:10:08",
"count" : 9,
"pub-type": "article",
"journal": "PAMM","publisher":"Wiley",
"year": "2021",
"url": "https://doi.org/10.1002%2Fpamm.202000283",
"author": [
"M. Suditsch","P. Schröder","L. Lambers","T. Ricken","W. Ehlers","A. Wagner"
],
"authors": [
{"first" : "M.", "last" : "Suditsch"},
{"first" : "P.", "last" : "Schröder"},
{"first" : "L.", "last" : "Lambers"},
{"first" : "T.", "last" : "Ricken"},
{"first" : "W.", "last" : "Ehlers"},
{"first" : "A.", "last" : "Wagner"}
],
"volume": "20","number": "1",
"doi" : "10.1002/pamm.202000283",
"bibtexKey": "Suditsch_2021"
}
]
}