Tao Liu¹, Yang Liu², Jianbin Du^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-2, 2025, DOI:10.32604/icces.2025.011595

Abstract Currently, the application of the Boundary Penalty (BP) method in acoustic-structural coupled multiphysics optimization problems remains unexplored. Within the theoretical framework of BP developed previously, we address acoustic-structural coupled topology optimization problems by proposing a BP-based acoustic-structural coupled topology optimization model. A systematic solution strategy is developed to tackle the challenges encountered during model solving.
The proposed model employs a mixed u/p formulation for finite element analysis and the adjoint method for sensitivity analysis to minimize the acoustic pressure within a specified region (Fig.1 A). During optimization iterations, issues such as topological discretization and iteration oscillations… 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 >

Haoyun Fan¹, Soon Poh Yap^1,*, Shengkang Zhang¹, Ahmed El-Shafie^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 17-65, 2025, DOI:10.32604/cmes.2025.070880 - 30 October 2025

Abstract Data-driven research on recycled aggregate concrete (RAC) has long faced the challenge of lacking a unified testing standard dataset, hindering accurate model evaluation and trust in predictive outcomes. This paper reviews critical parameters influencing mechanical properties in 35 RAC studies, compiles four datasets encompassing these parameters, and compiles the performance and key findings of 77 published data-driven models. Baseline capability tests are conducted on the nine most used models. The paper also outlines advanced methodological frameworks for future RAC research, examining the principles and challenges of physics-informed neural networks (PINNs) and generative adversarial networks (GANs), More >

Heping Wang^1,*, Ying Lu¹, Yanggui Li²

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 391-410, 2025, DOI:10.32604/cmes.2025.069763 - 30 October 2025

Abstract With oily wastewater treatment emerging as a critical global issue, porous media and shear forces have received significant attention as environmentally friendly methods for oil–water separation. This study systematically simulates the dynamics of oil-in-water emulsion demulsification under porous media and shear forces using a color-gradient Lattice Boltzmann model. The morphological evolution and demulsification efficiency of emulsions are governed by porous media and shear forces. The effects of porosity and shear velocity on demulsification are quantitatively analyzed. (1) The presence of porous media enhances the ability of the flow field to trap oil droplets, with lower More >

Nurlan Zhangabay^1,*, Marco Bonopera^2,*, Konstantin Avramov³, Maryna Chernobryvko³, Svetlana Buganova⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 241-261, 2025, DOI:10.32604/cmes.2025.069544 - 30 October 2025

Abstract This research extends ongoing efforts to develop methods for reinforcing damaged main gas pipelines to prevent catastrophic failure. This study establishes the use of scaled-down experimental models for assessing the dynamic strength of damaged pipeline sections reinforced with wire wrapping or composite sleeves. A generalized dynamic model is introduced for numerical simulation to evaluate the effectiveness of reinforcement techniques. The model incorporates the elastoplastic behavior of pipe and wire materials, the influence of temperature on mechanical properties, the contact interaction between the pipe and the reinforcement components (including pretensioning), and local material failure under transient… More >

Rehman Ali Shah^1,2, Zeeshan Asghar^3,*, Chenji Li², Arezoo Ardekani², Nasir Ali¹

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 753-778, 2025, DOI:10.32604/cmes.2025.069177 - 30 October 2025

Abstract The objective of this work is to investigate the dynamics of a self-propelled undulating sheet in a non-Newtonian electrolyte solution inside a wavy channel under the electroosmotic effect. The electrolyte solution, which is non-Newtonian, is modeled as a Carreau-Yasuda fluid. The flow generated by a combination of an undulating sheet and electroosmotic effect is obtained by solving the continuity and momentum equations. The electroosmotic body force term is derived using the Poisson-Boltzmann equation for the electric potential. A fourth-order ordinary differential equation for the stream function is solved under the Stokes flow regime. The dynamics More >

Yumeng Kong^*, Xuesong Guo, Yifei Wang

International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1577-1594, 2025, DOI:10.32604/ijmhp.2025.069985 - 31 October 2025

Abstract Background: Anxiety and depression are prevalent among university students, calling for effective non-pharmacological interventions. Tai Chi shows potential in reducing these symptoms, but research on its effects at different frequencies in younger populations is limited. This study compared the impacts of high-(5 sessions/week), medium-(3 sessions/week), and low-frequency (2 sessions/week) 24-form Tai Chi on college students’ anxiety/depression, versus a control group. Methods: A randomized controlled trial (RCT) included 120 university students with mild-to-moderate anxiety/depression, randomly assigned to 4 groups (30 each). The 8-week intervention used the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) for… More >

Liu Pan, Lei Xu^*, Bin Yan

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.012221

Abstract To address the issue of computational inefficiency arising from the large dimensionality of dynamic matrices in the train-track-tunnel-soil (TTTS) dynamic model, this study integrates the spectral element method (SEM) and finite element method (FEM) to develop a highly efficient dynamic model for the TTTS system. The model leverages the distinct vibration characteristics of the near- and far- field regions of TTTS system, employing different modelling approaches: the FEM, known for its superior shape adaptability and precise high-frequency dynamic response computation, is applied to the tunnel and near-field soil; the SEM, recognized for its rapid convergence… More >

Dan Wang¹, Zhoubin Li¹, Yuze Xia^1,2,*, Zhenhua Yu^1,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5823-5845, 2025, DOI:10.32604/cmc.2025.071656 - 23 October 2025

Abstract Multimodal Aspect-Based Sentiment Analysis (MABSA) aims to detect sentiment polarity toward specific aspects by leveraging both textual and visual inputs. However, existing models suffer from weak aspect-image alignment, modality imbalance dominated by textual signals, and limited reasoning for implicit or ambiguous sentiments requiring external knowledge. To address these issues, we propose a unified framework named Gated-Linear Aspect-Aware Multimodal Sentiment Network (GLAMSNet). First of all, an input encoding module is employed to construct modality-specific and aspect-aware representations. Subsequently, we introduce an image–aspect correlation matching module to provide hierarchical supervision for visual-textual alignment. Building upon these components, More >

Nada Alasbali^*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4943-4958, 2025, DOI:10.32604/cmc.2025.068330 - 23 October 2025

Abstract Intelligent Traffic Management (ITM) has progressively developed into a critical component of modern transportation networks, significantly enhancing traffic flow and reducing congestion in urban environments. This research proposes an enhanced framework that leverages Deep Q-Learning (DQL), Game Theory (GT), and Stochastic Optimization (SO) to tackle the complex dynamics in transportation networks. The DQL component utilizes the distribution of traffic conditions for epsilon-greedy policy formulation and action and choice reward calculation, ensuring resilient decision-making. GT models the interaction between vehicles and intersections through probabilistic distributions of various features to enhance performance. Results demonstrate that the proposed More >