Comparative Analysis of Various Hyperelastic Models for Neoprene Gasket at Ranging Strains

Latif, Rana Fahad; Khan, Nadeem Shafi

doi:10.1109/ibcast.2019.8667253

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…Optimising rubber roll hardness and configuration in embossing operations can enhance the critical properties of tissue paper products, providing valuable insights for the industry. In [32], the study presents a comparative analysis of 16 hyperelastic models for neoprene gaskets under uniaxial tensile loading. The selection of an appropriate model is essential for accurately predicting gasket behaviour when limited experimental data is available.…”

Section: Introductionmentioning

confidence: 99%

FEA Assessment of Contact Pressure and Von Mises Stress in Gasket Material Suitability for PEMFCs in Electric Vehicles

Park,

Kareem,

Joo

et al. 2023

Inventions

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Ensuring the safety of electric vehicles is paramount, and one critical concern is the potential for hazardous hydrogen fuel leaks caused by the degradation of Proton-Exchange Membrane Fuel Cell (PEMFC) gasket materials. This study employs advanced techniques to address this issue. We leverage Finite Element Analysis (FEA) to rigorously assess the suitability of gasket materials for PEMFC applications, focusing on two crucial conditions: ageing and tensile stress. To achieve this, we introduce a comprehensive “dual degradation framework” that considers the effects of contact pressure and von Mises stress. These factors are instrumental in evaluating the performance and durability of Liquid Silicon Rubber (LSR) and Ethylene Propylene Diene Monomer (EPDM) materials. Our findings reveal the Yeoh model as the most accurate and efficient choice for ageing simulations, boasting a minimal Mean Absolute Percentage Error (MAPE) and computational time of just 0.27 s. In contrast, the Ogden model, while accurate, requires more computational resources. In assessing overall model performance using MAE, Root Mean Square Error (RMSE), and R-squared metrics, both LSR and EPDM materials proved promising, with LSR exhibiting superior performance in most areas. Furthermore, our study incorporates uniaxial tensile testing, which yields RMSE and MAE values of 0.30% and 0.40%, respectively. These results provide valuable insights into material behaviour under tensile stress. Our research underscores the pivotal role of FEA in identifying optimal gasket materials for PEMFC applications. Notably, LSR is a superior choice, demonstrating enhanced FEA modelling performance under ageing and tensile conditions. These findings promise to significantly contribute to developing safer and more reliable electric vehicles by advancing gasket material design.

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Section: Introductionmentioning

confidence: 99%

FEA Assessment of Contact Pressure and Von Mises Stress in Gasket Material Suitability for PEMFCs in Electric Vehicles

Park,

Kareem,

Joo

et al. 2023

Inventions

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A Novel Approach for Optimization of Soft Material Constitutive Model Parameters Based on a Genetic Algorithm and Drucker's Stability Criterion

Cruz-Terán,

Ruiz-Huerta,

Elias-Zuñiga

et al. 2023

Soft Robotics

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Integrating Experimental Strain Functions and Machine Learning for Enhanced Finite Element Analysis of PEMFC Gasket Materials

Park,

Kareem,

Zoo

et al. 2023

Preprint

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The degradation of Proton-exchange membrane fuel cell (PEMFC) gasket materials is crucial in electric vehicles as it can cause hazardous hydrogen fuel leaks, which are usually due to high temperatures, pressures, and hydrogen fuel exposure. Degradation of gasket materials in PEMFC presents a critical concern for electric vehicle safety due to potential hydrogen fuel leaks. This study utilizes finite element analysis (FEA) to assess the suitability of gasket materials for PEMFC applications, focusing on aging and tensile conditions. The dual degradation framework, incorporating contact pressure and von Mises stress, is employed to evaluate Liquid Silicon Rubber (LSR) and Ethylene Propylene Diene Monomer (EPDM) materials. Under aging techniques, the Yeoh model exhibits the least Mean Absolute Percentage Error (MAPE) and computational cost of 0.27 seconds, while the Ogden model records the highest computational cost of 0.89 seconds. In evaluating MAE, Root Mean Square Error (RMSE), and R-squared metrics, LSR and EPDM materials demonstrate respective averages of 0.25%, 0.275%, 0.945%, and 0.815%, 0.685%, 0.77%. Tensile testing (Uniaxial) reveals RMSE and MAE values of 0.30%, 0.40%, and 0.50%, 0.40%, respectively. FEA proves instrumental in identifying suitable gasket materials for PEMFC applications. LSR emerges as the superior choice, demonstrating enhanced FEA modelling performance under aging and tensile conditions. These findings contribute valuable insights to the design and development of improved gasket materials, bolstering the safety and reliability of electric vehicles.

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Comparative Analysis of Various Hyperelastic Models for Neoprene Gasket at Ranging Strains

Cited by 3 publications

References 24 publications

FEA Assessment of Contact Pressure and Von Mises Stress in Gasket Material Suitability for PEMFCs in Electric Vehicles

FEA Assessment of Contact Pressure and Von Mises Stress in Gasket Material Suitability for PEMFCs in Electric Vehicles

A Novel Approach for Optimization of Soft Material Constitutive Model Parameters Based on a Genetic Algorithm and Drucker's Stability Criterion

Integrating Experimental Strain Functions and Machine Learning for Enhanced Finite Element Analysis of PEMFC Gasket Materials

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