Sojin Shin¹, Guk Heon Kim², Seung Hwan Kim³, Jaemin Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.079127 - 30 March 2026

Abstract This study develops a surrogate super-resolution (SR) framework that accelerates finite element method (FEM)-based computational fluid dynamics (CFD) using deep learning. High-resolution (HR) FEM-based CFD remains computationally prohibitive for time-sensitive applications, including patient-specific aneurysm hemodynamics where rapid turnaround is valuable. The proposed pipeline learns to reconstruct HR velocity-magnitude fields from low-resolution (LR) FEM solutions generated under the same governing equations and boundary conditions. It consists of three modules: (i) offline pre-training of a residual network on representative vascular geometries; (ii) lightweight fine-tuning to adapt the pretrained model to geometric variability, including patient-specific aneurysm morphologies; and… More >

Azhar G. Hamad¹, Nasser Firouzi^2,*, Yousef S. Al Rjoub³

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075840 - 12 March 2026

Abstract The accurate mechanical analysis of thick-walled pressure vessel structures composed of advanced materials, such as hyperelastic and functionally graded materials (FGMs), is critical for ensuring their safety and optimizing their design. However, conventional numerical methods can face challenges with the non-linearities inherent in hyperelasticity and the complex spatial variations in FGMs. This paper presents a novel hybrid numerical approach combining Physics-Informed Neural Networks (PINNs) with Finite Element Method (FEM) derived data for the robust analysis of thick-walled, axisymmetric, heterogeneous, hyperelastic pressure vessels with elliptical geometries. A PINN framework incorporating neo-Hookean constitutive relations is developed in… More >

Yadong Xu¹, Weixing Hong², Mohammad Noori^3,6,*, Wael A. Altabey^4,*, Ahmed Silik⁵, Nabeel S.D. Farhan²

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 763-783, 2024, DOI:10.32604/sdhm.2024.053763 - 20 September 2024

Abstract This study introduces an innovative “Big Model” strategy to enhance Bridge Structural Health Monitoring (SHM) using a Convolutional Neural Network (CNN), time-frequency analysis, and fine element analysis. Leveraging ensemble methods, collaborative learning, and distributed computing, the approach effectively manages the complexity and scale of large-scale bridge data. The CNN employs transfer learning, fine-tuning, and continuous monitoring to optimize models for adaptive and accurate structural health assessments, focusing on extracting meaningful features through time-frequency analysis. By integrating Finite Element Analysis, time-frequency analysis, and CNNs, the strategy provides a comprehensive understanding of bridge health. Utilizing diverse sensor More >

Ankush Kapoor¹, Pradeep Kumar^2,*, Ranjan Mishra³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 341-361, 2023, DOI:10.32604/cmc.2023.028874 - 22 September 2022

Abstract Frequency selective surfaces (FSSs) play an important role in wireless systems as these can be used as filters, in isolating the unwanted radiation, in microstrip patch antennas for improving the performance of these antennas and in other 5G applications. The analysis and design of the double concentric ring frequency selective surface (DCRFSS) is presented in this research. In the sub-6 GHz 5G FR1 spectrum, a computational synthesis technique for creating DCRFSS based spatial filters is proposed. The analytical tools presented in this study can be used to gain a better understanding of filtering processes and… More >

Liangliang Chen¹, Madeeha Tahir^2,*, Sumeira Yasmin³, Taseer Muhammad⁴, Muhammad Imran^5,*, Fenghua Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1771-1788, 2022, DOI:10.32604/cmes.2022.017539 - 30 December 2021

Abstract The energy produced by the melting stretching disks surface has a wide range of commercial applications, including semi-conductor material preparation, magma solidification, permafrost melting, and frozen land refreezing, among others. In view of this, in the current communication we analyzed magnetohydrodynamic flow of Maxwell nanofluid between two parallel rotating disks. Nanofluids are important due to their astonishing properties in heat conduction flows and in the enhancement of electronic and manufacturing devices. Furthermore, the distinct tiny-sized particles and in the Maxwell water-based fluid for enhancing the heat transfer rate are analyzed. The heat equation is developed… More >

M. Razzaq¹, C. Tsotskas², S. Turek¹, T. Kipouros², M. Savill², J. Hron³

CMES-Computer Modeling in Engineering & Sciences, Vol.90, No.4, pp. 303-337, 2013, DOI:10.3970/cmes.2013.090.303

Abstract The integration and application of a new multi-objective tabu search optimization algorithm for Fluid Structure Interaction (FSI) problems are presented. The aim is to enhance the computational design process for real world applications and to achieve higher performance of the whole system for the four considered objectives. The described system combines the optimizer with a well established FSI solver which is based on the fully implicit, monolithic formuFlation of the problem in the Arbitrary Lagrangian-Eulerian FEM approach. The proposed solver resolves the proposed fluid-structure interaction benchmark which describes the self-induced elastic deformation of a beam More >

Shiqin He¹, Pengfei Li¹, Feng Shang²

CMES-Computer Modeling in Engineering & Sciences, Vol.73, No.4, pp. 387-394, 2011, DOI:10.3970/cmes.2011.073.387

Abstract A three-dimensional finite element (FE) and analytical approach for the simulation of the shear properties of steel-concrete composite beams are presented in this paper. To simulate the interfacial behavior between steel girders and concrete slabs, we apply an interface slip model in the simulation. This model has been used in analyzing the flexural properties of composite beams. Both simply supported beam and continuous composite beam experiments reported in literature are simulated. The load deflection and slip rule between steel girders and concrete slabs, as well as the crack pattern and contour at the ultimate load, More >

Paweł Dłotko¹, Ruben Specogna²

CMES-Computer Modeling in Engineering & Sciences, Vol.60, No.3, pp. 247-278, 2010, DOI:10.3970/cmes.2010.060.247

Abstract The systematic potential design is of high importance in computational electromagnetics. For example, it is well known that when the efficient eddy-current formulations based on a magnetic scalar potential are employed in problems which involve conductive regions with holes, the so-calledthick cutsare needed to make the boundary value problem well defined. Therefore, a considerable effort has been invested over the past twenty-five years to develop fast and general algorithms to compute thick cuts automatically. Nevertheless, none of the approaches proposed in literature meet all the requirements of being automatic, computationally efficient and general. In this More >

V. Minutolo¹, E. Ruocco¹, S. Ciaramella¹

CMES-Computer Modeling in Engineering & Sciences, Vol.41, No.1, pp. 27-48, 2009, DOI:10.3970/cmes.2009.041.027

Abstract A Field Boundary Element Method (FBEM) for Functionally Graded Materials (FGM) is presented and compared with Isoparametric Finite Element Method. The presented formulation, using the Kelvin's fundamental solution, is able to analyse structures although no fundamental solution is actually known. Isoparametric FGM Finite Element Method is a well established tool for FGM structural analysis. The comparison shows that both FBEM and FEM give accurate results. In the paper, the solution of some examples for 2D plates are reported both using FEM and FBEM. Some comparisons with analytical results are discussed and accuracy of the solutions More >

D. S. Liu¹, C.Y. Tsai¹

CMES-Computer Modeling in Engineering & Sciences, Vol.39, No.1, pp. 29-48, 2009, DOI:10.3970/cmes.2009.039.029

Abstract Utilizing a thin copper substrate for illustration purposes, this study presents a novel numerical method for extracting the thermo-mechanical properties of a thin-film. In the proposed approach, molecular dynamics (MD) simulations are performed to establish the load-displacement response of a thin copper substrate nanoindented at temperatures ranging from 300~1400 K. The load data are then input to an artificial neural network (ANN), trained using a finite element model (FEM), in order to extract the material constants of the copper substrate. The material constants are then used to construct the corresponding stress-strain curve, from which the… More >