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Efficient Bridging of Temporal Scales for Fatigue Simulations via a Compressive Sensing ApproachFatigue damage simulations are computationally demanding due to the high number of simulated load cycles (up to 10^9 for high-cycle fatigue, HCF) and the non-linear nature of the system of equations in the context of finite element analysis (FEA). [...]Leitung: Prof. Dr. David Néron, Prof. Dr.-Ing. Udo NackenhorstTeam:Jahr: 2025
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Computational multiphysics modelling of Proton Exchange Membrane Water Electrolysis systems (PEMWE)The climate crisis demands a rapid global shift from fossil-based systems to carbon-neutral technologies, with renewable energy and green hydrogen playing central roles. Proton Exchange Membrane Water Electrolysis (PEMWE) is one of the most promising technologies for high-purity hydrogen production thanks to its high efficiency, fast response, and ability to operate at elevated current densities and pressures. However, challenges remain, including high material costs, limited durability, and the need for performance optimization. [...]Leitung: Prof. Dr.-Ing. Fadi AldakheelTeam:Jahr: 2025
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Multiphysics modeling framework for corrosion-fatigue degradation in reinforced concrete structuresIn this project, we plan to develop a comprehensive multiphysics phase-field framework that simulates the full spectrum of processes governing corrosion–fatigue degradation in RC structures. The framework will incorporate chloride ingress, chloride binding, and carbonation-induced depassivation in concrete; reactive transport of corrosion products; pressure buildup and cracking caused by rust formation; corrosion diffusion and dissolution-driven weakening of steel; fatigue degradation in reinforcing steel; and fatigue crack propagation and splitting fracture in concrete. Degradation-dependent transport properties will be included to capture the bidirectional coupling between mechanical cracking and ionic transport, allowing corrosion, fracture, and fatigue to evolve simultaneously throughout the service life. The interaction between steel and concrete will further be modeled through corrosion- and fatigue-induced bond deterioration, enabling realistic simulation of slip, confinement loss, and load-transfer degradation. [...]Leitung: Prof. Fadi Aldakheel, Dr.-Ing. Abedulgader BaktheerTeam:Jahr: 2025
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Phase-field modeling for corrosion-fatigue degradation in metallic materialsIn this project, we plan to develop a new corrosion–fatigue modeling framework capable of mechanistically describing dissolution-driven corrosion in metals, including processes such as pitting, stress corrosion cracking, and the pit-to-crack transition. The approach will couple mechanical straining with electrochemical kinetics and employ a phase-field formulation to represent the evolving metal–electrolyte interface, enabling the model to reproduce both activation-controlled and diffusion-controlled corrosion regimes. As part of this development, we will introduce an additional phase-field variable to represent fracture and fatigue, making it possible to simulate fatigue crack initiation and propagation under cyclic loading. Furthermore, a dedicated fatigue degradation mechanism will be formulated to capture cyclic damage accumulation, localized plasticity effects, and electrochemically assisted material weakening. [...]Leitung: Prof. Fadi Aldakheel, Dr.-Ing. Abedulgader BaktheerTeam:Jahr: 2025
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Deciphering the effect of load sequence in concrete fatigue: An interleaved numerical-experimental methodologyThe primary objective of the proposed project is to develop a comprehensive experimental-numerical methodology for understanding fatigue behavior in concrete structures, with a specific focus on the influence of loading sequence. The research centers on exploring fatigue-induced degradation in critical zones of structural elements across various loading scenarios, including systematic loading blocks and realistic random loading sequences. Moreover, the project is actively testing a new hypothesis that suggests the stabilization of cumulative fatigue life in highly nonuniform loading scenarios, showcasing a deviation from the predictions of the widely used Palmgren-Miner (P-M) damage accumulation rule. [...]Leitung: Dr.-Ing. Abedulgader Baktheer, Prof. Fadi AldakheelTeam:Jahr: 2025Förderung: Deutsche Forschungsgemeinschaft (DFG) - Project number 544805481
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Machine learning modelling to design micro-structured concrete absorber of carbon dioxide (CO2)This work introduces the key aspects involved in optimizing binder-based microstructures using machine-learning techniques, with the primary goal of enhancing their uptake properties—particularly their capacity to absorb carbon dioxide (CO₂). [...]Leitung: Prof. Dr.-Ing. Fadi AldakheelTeam:Jahr: 2024
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Physics-based machine learning for inverse design of porous metamaterialsEmerging as a paradigmatic material system, porous metamaterials have the potential to deliver highly adaptable and unique properties across a wide range of applications. This project focuses on establishing a physics-based machine learning framework to design porous metamaterials based on desired properties...Leitung: Prof. Dr.-Ing. Fadi AldakheelTeam:Jahr: 2024
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A Numerical Investigation of Granular Structure Influences on Battery PerformancesThis project aims to establish a comprehensive computational framework for examining the influence of granular heterogeneity within lithium-ion battery cathode electrodes on macroscopic performance. [...]Leitung: Prof. Dr.-Ing. Yupeng Jiang, Prof. Dr. Pierre-Alain BoucardTeam:Jahr: 2024
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Numerically Efficient Simulation of Inelastic Material Properties within the Framework of ALE Formulation for Rolling BodiesThe aim of this project is to develop an efficient and reliable finite-element framework for rolling bodies by combining advanced inelastic material modelling with the ALE formulation. While the ALE setting enables a quasi-steady description of rolling contact by keeping the mesh fixed in the contact region, it also requires a consistent strategy for handling history-dependent internal variables as they are convected through the mesh. [...]Leitung: Prof. Dr.-Ing. Udo NackenhorstTeam:Jahr: 2024
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Artificial Intelligence and Material Modeling in BiomechanicsThis research focuses on the development and implementation of advanced material models as User-Defined Elements (UEL) in Abaqus, based on Finite Strain Theory and incorporating Hyperelasticity, Plasticity, Nonlinear Hardening, Phase-Field Fracture, Fatigue, Chemical Reactions, and Anisotropy...Leitung: Prof. Dr.-Ing. Fadi AldakheelTeam:Jahr: 2023
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Physics-based machine learning for computational fracture mechanicsIn this project, we plan to develop a physics-based machine learning framework that embeds core physical principles directly into the neural network architecture. Using a feedforward neural network designed to satisfy governing equations and thermodynamic constraints, the framework will integrate mechanics, constitutive behavior, and energy balance at the architectural level. Synthetic data generated from finite element–based phase-field fracture simulations will be used to train the model, initially focusing on homogeneous one-dimensional responses for both brittle and ductile materials. Special emphasis will be placed on learning the evolution of elastic energy, dissipated work, and fracture characteristics in a way that preserves physical interpretability and consistency, addressing key limitations of classical ML approaches that rely purely on data and lack embedded physical guarantees. [...]Leitung: Prof. Dr.-Ing. Fadi Aldakheel, Dr.-Ing. Abedulgader BaktheerTeam:Jahr: 2023
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Surrogate modelling for the monitoring of implantsHigh-fidelity computational simulations can be used to predict the long-term stability and possible failure of implants. Furthermore, the patient’s individual conditions can be considered to optimise the monitoring of the implantation. However, these models require a high computational effort due to...Leitung: Prof. Dr.-Ing. Udo NackenhorstTeam:Jahr: 2021Förderung: DFG-funded collaborative research centre/transregio 298 “Safety-Integrated and Infection-Reactive Implants” (SIIRI)
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Aktuelle Forschungsprojekte am IBNM
Letzte Änderung: 20.11.25; Webredaktion IBNM
