Zefu Li¹, Weidong Yang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011671

Abstract For composite materials incorporating porous structures with multi-walled carbon nanotubes (MWCNTs), the effects of pores and MWCNT agglomeration significantly impact electrical conductivity. Theoretical modeling of the piezoresistive behavior is crucial for understanding the electromechanical response of porous MWCNT/polymer nanocomposites. Currently, there is limited theoretical modeling that considers the combined effects of porosity and MWCNT agglomeration on the electrical conductivity and piezoresistive performance of porous MWCNT/polymer composites. Addressing this gap, this paper presents a multiscale modeling approach for the strain-dependent piezoresistive behavior of porous MWCNT/polymer nanocomposites. The model considers the influence of porosity and MWCNT agglomeration, More >

Yanhui Zhang¹, Lianhua Ma¹, Hailiang Su^1,2,3,*, Jirong Qin², Zhining Chen², Kaibiao Deng¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1961-1980, 2024, DOI:10.32604/cmes.2023.045570 - 29 January 2024

Abstract In this paper, to present a lightweight-developed front underrun protection device (FUPD) for heavy-duty trucks, plain weave carbon fiber reinforced plastic (CFRP) is used instead of the original high-strength steel. First, the mechanical and structural properties of plain carbon fiber composite anti-collision beams are comparatively analyzed from a multi-scale perspective. For studying the design capability of carbon fiber composite materials, we investigate the effects of TC-33 carbon fiber diameter (D), fiber yarn width (W) and height (H), and fiber yarn density (N) on the front underrun protective beam of carbon fiber composite materials. Based on… More >

Lifan Chen^1,*, Ning Guo¹, Zhongxuan Yang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09709

Abstract A multiscale approach [1] that couples the finite-element method (FEM) and the discrete-element method (DEM) is employed to model and analyse the earthquake fault rupture-soil-foundation interaction (FR-SFI) problem. In the approach, the soil constitutive responses are obtained from DEM solutions of representative volume elements (RVEs) embedded at the FEM integration points so as to effectively bypass the phenomenological hypotheses in conventional FEM simulations. The fault rupture surfaces and shear localization patterns under normal faults with or without foundation atop have been well captured by the multiscale approach and verified with available centrifuge experimental [2] and More >

Pandi Zhao¹, Zebang Zheng^1,*, Mei Zhan¹, Hongwei Li¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09508

Abstract Metallic sealing rings made from nickel-based superalloys are critical components of aero engines that prevent the leakage of high-pressure liquid or gas fuel. As one of the main failure modes, fatigue cracking has been a concern for the aerospace industries because the formation of even a micro-crack may cause an aviation accident. For the purpose of manufacturing fatigue-resisting sealing rings, much effort has been spent on the lifetime predicting under fatigue loadings. However, the fatigue analysis of metallic sealing rings is challenging due to several aspects. On the one hand, the diameter of the rings… More >

Xiaoding Wei^1,*, Wenqing Zhu¹, Junjie Liu²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09998

Abstract Fiber-reinforced polymer composites with excellent impact energy absorption properties play a pivotal role in the safety of spacecraft, protection of military personnel and equipment, as well as high-speed transportation. Research on the impact performance of composite materials has always relied mainly on expensive experiments and large-scale simulations. In this talk, we will introduce the “dynamic shear-lag model” by extending the classical shear-lag model to the dynamic domain. The dynamic shear-lag model reveals the transfer characteristics of impact energy in the microstructure scale of composite materials, and establishes a quantitative relationship between the " composition-microstructure-performance" of More >

Shiwei Zhao^1,*, Hao Chen², Jidong Zhao¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09965

Abstract With global warming, thaw-induced landslides occur more frequently in permafrost, which not only threaten the safety of infrastructures as general geohazards but also worsen global warming due to carbon release. This work presents a novel computational framework to model thaw-induced landslides from a multiscale perspective. The proposed approach can capture the thermal-mechanical (TM) response of frozen soils at the particulate scale by using discrete element method (DEM). The micromechanics-based TM model is superior to capturing the sudden crash of soil skeletons caused by thaw-induced cementation loss between soil grains. The DEM-simulated TM response is then More >

Ye Lu¹, Hengyang Li¹, Sourav Saha², Satyajit Mojumder², Abdullah Al Amin¹, Derick Suarez¹, Yingjian Liu³, Dong Qian³, Wing Kam Liu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.3, pp. 1351-1371, 2021, DOI:10.32604/cmes.2021.017719 - 25 November 2021

Abstract This paper presents the concept of reduced order machine learning finite element (FE) method. In particular, we propose an example of such method, the proper generalized decomposition (PGD) reduced hierarchical deeplearning neural networks (HiDeNN), called HiDeNN-PGD. We described first the HiDeNN interface seamlessly with the current commercial and open source FE codes. The proposed reduced order method can reduce significantly the degrees of freedom for machine learning and physics based modeling and is able to deal with high dimensional problems. This method is found more accurate than conventional finite element methods with a small portion More >

Rina Okuyama¹, Naoto Mitsume², Hideki Fujii¹, Hideaki Uchida^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 949-965, 2021, DOI:10.32604/cmes.2021.015773 - 11 August 2021

Abstract As the number of automobiles continues to increase year after year, the associated problem of traffic congestion has become a serious societal issue. Initiatives to mitigate this problem have considered methods for optimizing traffic volumes in wide-area road networks, and traffic-flow simulation has become a focus of interest as a technique for advance characterization of such strategies. Classes of models commonly used for traffic-flow simulations include microscopic models based on discrete vehicle representations, macroscopic models that describe entire traffic-flow systems in terms of average vehicle densities and velocities, and mesoscopic models and hybrid (or multiscale)… More >

Jingfa Li¹, Bo Yu^1,*, Qianqian Shao², Dongliang Sun¹

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 541-563, 2020, DOI:10.32604/cmes.2020.011835 - 12 October 2020

Abstract In this work, the drag-reducing mechanism of high-Reynoldsnumber turbulent channel flow with surfactant additives is investigated by using large eddy simulation (LES) method. An N-parallel finitely extensible nonlinear elastic model with Peterlin’s approximation (FENE-P) is used to describe the rheological behaviors of non-Newtonian fluid with surfactant. To close the filtered LES equations, a hybrid subgrid scale (SGS) model coupling the spatial filter and temporal filter is applied to compute the subgrid stress and other subfilter terms. The finite difference method and projection algorithm are adopted to solve the LES governing equations. To validate the correctness More >

Padmini Rangamani^1,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 22-22, 2019, DOI:10.32604/mcb.2019.08513

Abstract Endocytosis is the process of uptake of cargo and fluid from the extracellular space to inside the cell; defects in endo- cytosis contribute to a wide spectrum of diseases including cancer, neurodegeneration, and heart disease. Clathrin- mediated endocytosis (CME) is an archetypal example of a membrane deformation process where multiple variables such as pre-existing membrane curvature, membrane bending due to the protein machinery, membrane tension regulation, and actin-mediated forces govern the progression of vesiculation. My group has been working for the past few years on deciphering the biophysical determinants of CME using multiscale modeling. We… More >