Model of rough surfaces with Gaussian processes

Arsalan, Jawaid,; Seewig, Joerg

doi:10.1088/2051-672x/acbe55

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…A numerical technique based on the fast Fourier transform, widely used in mechanical engineering [40][41][42], is used to create the composite rough surface. The roughness of the surfaces is assumed to follow a Gaussian distribution [43]. By specifying a roughness σ and an autocorrelation length T, the height distribution matrix of the rough surface can be obtained by a linear transformation of a Gaussian random matrix:…”

Section: Numerical Reconstruction Of Interfacial Leakage Passagesmentioning

confidence: 99%

Study on interfacial leakage characteristics of rubber sealing under temperature cycle conditions in PEM fuel cell

et al. 2023

Modelling Simul. Mater. Sci. Eng.

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The amount of leakage is the only direct indicator of the sealing performance of a Proton Exchange Membrane Fuel Cell (PEMFC). In this work, a predictive model is developed to quantitatively evaluate the variation of leakage for a PEMFC under temperature cycling conditions. The method first uses the Lattice-Boltzmann Method (LBM) to simulate the gas flow within the contact interfacial gap at various heights. Then the Finite Element Method is used to analyze the local and macroscale contact state of the sealing interface and to clarify the effect of contact stresses on the interfacial gap height. Finally, the generalized Maxwell model, which considers time-temperature transfer and stiffness growth, is used to calculate the interfacial contact stresses under temperature cycling. The validity of the model was verified by comparison with experimental data from the available literature. Further analysis showed that reduced start-up temperature exacerbated the stress relaxation effect and decreased the service life of the seal material. When the start-up temperature is reduced from 25°C to -20°C, the model predicts that the service life of the PEMFC will be reduced by 100 temperature cycles or more. The leakage variation in a cycle was also discussed, and it was found that the leakage fluctuation became more and more significant as the number of cycles increased, weakening system reliability.

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Section: Numerical Reconstruction Of Interfacial Leakage Passagesmentioning

confidence: 99%

Study on interfacial leakage characteristics of rubber sealing under temperature cycle conditions in PEM fuel cell

et al. 2023

Modelling Simul. Mater. Sci. Eng.

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Model‐based analysis of the influence of surface roughness on fatigue processes

Yan,

Jawaid,

Kerscher

et al. 2024

Proc Appl Math and Mech

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In the last decade, the phase field method was developed to simulate fatigue fracture processes. The biggest advantage of phase field modeling is its unified framework, in which the entire fracture evolution from nucleation to propagation is covered. Even though it is known that surface roughness has an essential impact on fatigue life, it has rarely been considered directly in phase field models for fatigue processes due to the required computational effort. In this work, we provide a simulation setup to incorporate roughness profiles into a phase field model for fatigue cracks. We have used a roughness model for our studies and also present initial results that show agreement between simulation and experiments.

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Discrete Filter and Non-Gaussian Noise for Fast Roughness Simulations with Gaussian Processes

Jawaid

Seewig

2023

Proceedings of the 3rd Conference on Physical Modeling for Virtual Manufacturing Systems and Processes

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Rough surface simulations result in tight feedback loops in research procedures, such that they speed up studies for example about roughness’ impact on tribology or fluid dynamics. To model and simulate a broad spectrum of rough surfaces, Gaussian processes (GP) have been suggested recently. However, these models are limited on surfaces with small sizes since computational time-costs and memory-costs of simulations with standard procedures scale cubically and quadratically, respectively. In this paper, we apply the discrete filter approach which is a special case of GPs. We use the discrete filter with the fast Fourier transform (FFT) algorithm to efficiently sample from a high-dimensional Gaussian distribution and we compare its computational costs with the contour integral quadrature algorithm. Our experiments show that GPs benefit from FFT and allow stationary rough surfaces with sizes as large as 30, 000 × 30, 000 to be efficiently sampled. Since this approach is complementary to the GP and noise model approach, we also show simulations of rough surfaces with underlying non-Gaussian noise models that can reduce computational complexity.

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Model of rough surfaces with Gaussian processes

Cited by 3 publications

References 38 publications

Study on interfacial leakage characteristics of rubber sealing under temperature cycle conditions in PEM fuel cell

Study on interfacial leakage characteristics of rubber sealing under temperature cycle conditions in PEM fuel cell

Model‐based analysis of the influence of surface roughness on fatigue processes

Discrete Filter and Non-Gaussian Noise for Fast Roughness Simulations with Gaussian Processes

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