Chiao-Yang Kuan, Yung-Wei Chen^*, Jian-Hung Shen, Yen-Shen Chang

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079597 - 27 April 2026

Abstract This paper investigates the vibro-acoustic coupling behavior of high-speed ball bearings and the mechanisms driving vibration and radiated noise. Ball bearings consist of an inner ring, outer ring, cage, and rolling elements, whose complex interactions—impact, friction, and geometric non-uniformities—are difficult to capture experimentally. To address this challenge, a coupled numerical approach is developed by integrating the explicit nonlinear solver LS-DYNA with the acoustic module in LMS Virtual.Lab. Simultaneously, fixed boundary constraints and no-slip contact conditions are applied in the modal analysis to identify excitation sources of structural vibrations. First, a three-sphere collision simulation is employed More >

Peijun Xie^1,2, Shoulong Zhang^1,2,3,#,*, Pengfei Huang^1,2, Jintuan Zhang^4,#,*

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.072958 - 31 March 2026

Abstract To ensure the safety of the integral hoisting of precast pier boxes for sea-crossing bridges, this study focused on the sidewall height of the pier box and the width of the hoisting sling as core variables, established a finite element model using ABAQUS, and conducted a safety analysis of the hoisting process. The results showed that optimal structural safety and cost-effectiveness were achieved by first casting the concrete base plate of the pier box, then constructing the sidewalls to a height of 500 mm, and subsequently using REE-100T eye & eye round slings for hoisting. More >

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 >

Safwan Al-sayed¹, Xi Wang¹, Yijiang Peng^1,*, Esraa Hyarat², Ahmad Ali AlZubi³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.074068 - 12 January 2026

Abstract In modern construction, Lightweight Aggregate Concrete (LWAC) has been recognized as a vital material of concern because of its unique properties, such as reduced density and improved thermal insulation. Despite the extensive knowledge regarding its macroscopic properties, there is a wide knowledge gap in understanding the influence of microscale parameters like aggregate porosity and volume ratio on the mechanical response of LWAC. This study aims to bridge this knowledge gap, spurred by the need to enhance the predictability and applicability of LWAC in various construction environments. With the help of advanced numerical methods, including the… More >

Nikita Golovkin^1,2, Olesya Nikulenkova³, Vsevolod Pobezhimov¹, Alexander Nesmelov¹, Sergei Chvalun¹, Fedor Sorokin³, Arthur Krupnin^1,3,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073161 - 12 January 2026

Abstract This study presents and verifies a hybrid methodology for reliable determination of parameters in structural rheological models (Zener, Burgers, and Maxwell) describing the viscoelastic behavior of polyurethane specimens manufactured using extrusion-based 3D printing. Through comprehensive testing, including cyclic compression at strain rates ranging from 0.12 to 120 mm/min (0%–15% strain) and creep/relaxation experiments (10%–30% strain), the lumped parameters were independently determined using both analytical and numerical solutions of the models’ differential equations, followed by cross-verification in additional experiments. Numerical solutions for creep and relaxation problems were obtained using finite element analysis, with the three-parameter Mooney-Rivlin… More > Graphic Abstract

Yunjun Lee¹, Sanggyu Cheon², Woo Chul Chung^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3381-3403, 2025, DOI:10.32604/cmes.2025.073729 - 23 December 2025

Abstract The application of carbon capture systems on ships is technically constrained by limited onboard space and the weight of the conventional absorption tower. The rotating packed bed (RPB) has emerged as a promising alternative due to its small footprint and high mass transfer performance. However, despite its advantages, the structural and vibration stability of RPBs at high rotational speed remains insufficiently studied, and no international design standards currently exist for RPBs. To address this gap, this study performed a comprehensive finite element analysis (FEA) using ANSYS to investigate the structural and dynamic characteristics of an… More >

Adnan Ashique^1,#, Khalid Masood², Usman Afzal¹, Mati Ur Rahman², Maddina Dinesh Kumar³, Sohaib Abdal³, Nehad Ali Shah^1,#,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3627-3699, 2025, DOI:10.32604/cmes.2025.072523 - 23 December 2025

Abstract This study outlines a quantitative and data-driven study of the mixed convection heat transfer processes that concern Cu-water nanofluids in a Γ-shaped enclosure with one to five rotating cylinders. The dimensionless equations of mass, momentum, and energy are solved using the finite element method as implemented in the COMSOL Multiphysics 6.3 software in different rotating Reynolds numbers and cylinder geometries. An artificial Neural Network that is trained using Bayesian Regularization on data produced by the COMSOL is utilized to estimate the average Nusselt numbers. The analysis is conducted for a wide range of rotational… More >

Faiza Benabdallah¹, Kaouther Ghachem¹, Walid Hassen², Haythem Baya², Hind Albalawi³, Lioua Kolsi^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1839-1861, 2025, DOI:10.32604/cmes.2025.071678 - 26 November 2025

Abstract Current developments in magnetohydrodynamic (MHD) convection and nanofluid engineering technology have have greatly enhanced heat transfer performance in process systems, particularly through the use of carbon nanotube (CNT)–based fluids that offer exceptional thermal conductivity. Despite extensive research on MHD natural convection in enclosures, the combined effects of complex obstacle geometries, magnetic fields, and CNT nanofluids in three-dimensional configurations remain insufficiently explored. This research investigates MHD natural convection of carbon nanotube (CNT)-water nanofluid within a three-dimensional cavity. The study considers an inclined cross-shaped hot obstacle, a configuration not extensively explored in previous works. The work aims… More >

Hanyu Tao^1,2, Dongye Sun^1,2, Tao Fang^1,2, Wenhu Zhao^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 521-536, 2025, DOI:10.32604/cmes.2025.072089 - 30 October 2025

Abstract Structural internal flaws often weaken the performance and integral stability, while traditional nondestructive testing or inversion methods face challenges of high cost and low efficiency in quantitative flaw identification. To quickly identify internal flaws within structures, a deep learning model for flaw detection is proposed based on the image quadtree scaled boundary finite element method (SBFEM) combined with a deep neural network (DNN). The training dataset is generated from the numerical simulations using the balanced quadtree algorithm and SBFEM, where the structural domain is discretized based on recursive decomposition principles and mesh refinement is automatically… More >