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

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.072089

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 >

Ihab Taleb, Guillaume Guerard^*, Frédéric Fauberteau, Nga Nguyen, Pascal Clain

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.070517

Abstract Isolated power systems, such as those on islands, face acute challenges in balancing energy demand with limited generation resources, making them particularly vulnerable to disruptions. This paper addresses these challenges by proposing a novel control and simulation framework based on a holonic multi-agent architecture, specifically developed as a digital twin for the Mayotte island grid. The primary contribution is a multi-objective optimization model, driven by a genetic algorithm, designed to enhance grid resilience through intelligent, decentralized decision-making. The efficacy of this architecture is validated through three distinct simulation scenarios: (1) a baseline scenario establishing nominal… More >

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

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.069177

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 >

Hojun Moon, Donghyun You^*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.071648

Abstract A numerical method is presented to simulate bubble–particle interaction phenomena in particle-laden flows. The bubble surface is represented in an Eulerian framework by a volume-of-fluid (VOF) method, while particle motions are predicted in a Lagrangian framework. Different frameworks for describing bubble surfaces and particles make it difficult to predict the exact locations of collisions between bubbles and particles. An effective bubble, defined as having a larger diameter than the actual bubble represented by the VOF method, is introduced to predict the collision locations. Once the collision locations are determined, the attachment of particles to the More >

Xing Lin¹, Junning Wu¹, Shixue Liang^1,2,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.070846

Abstract Random media like concrete and ceramics exhibit stochastic crack propagation due to their heterogeneous microstructures. This study establishes a Conditional Generative Adversarial Network (CGAN) combined with random field modeling for the efficient prediction of stochastic crack patterns and stress-strain responses. A total dataset of 500 samples, including crack propagation images and corresponding stress-strain curves, is generated via random Finite Element Method (FEM) simulations. This dataset is then partitioned into 400 training and 100 testing samples. The model demonstrates robust performance with Intersection over Union (IoU) scores of 0.8438 and 0.8155 on training and testing datasets, More >

Binu Sudhakaran Pillai¹, Raghavendra Kulkarni², Venkata Satya Suresh kumar Kondeti², Surendran Rajendran^3,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.070348

Abstract Future 6G communications will open up opportunities for innovative applications, including Cyber-Physical Systems, edge computing, supporting Industry 5.0, and digital agriculture. While automation is creating efficiencies, it can also create new cyber threats, such as vulnerabilities in trust and malicious node injection. Denial-of-Service (DoS) attacks can stop many forms of operations by overwhelming networks and systems with data noise. Current anomaly detection methods require extensive software changes and only detect static threats. Data collection is important for being accurate, but it is often a slow, tedious, and sometimes inefficient process. This paper proposes a new… More >

Nadia Gouider¹, Mohammed Benzerara^2,*, Yazid Hadidane¹, S. M. Anas^3,*, Oulfa Harrat¹, Hamda Guedaoura^2,4, Anfel Chaima Hadidane⁵, Messaoud Saidani⁶

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.071600

Abstract In recent years, cold-formed steel (CFS) built-up sections have gained a lot of attention in construction. This is mainly because of their structural efficiency and the design advantages they offer. They provide better load-bearing strength and show greater resistance to elastic instability. This study looks at both experimental and numerical analysis of built-up CFS columns. The columns were formed by joining two C-sections in different ways: back-to-back, face-to-face, and box arrangements. Each type was tested with different slenderness ratios. For the experiments, the back-to-back and box sections were connected using two rows of rivets. The… More > Graphic Abstract

Alex Segura^*, Joaquim Meléndez

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.070954

Abstract The increasing use of renewable energy sources, combined with the increase in electricity demand, has highlighted the importance of energy flexibility management in electrical grids. Energy flexibility is the capacity that generators and consumers have to change production and/or consumption to support grid operation, ensuring the stability and efficiency of the grid. Thus, Local Flexibility Markets (LFMs) are market-oriented mechanisms operated at different time horizons that support flexibility provision and trading at the distribution level, where the Distribution System Operators (DSOs) are the flexibility-demanding actors, and prosumers are the flexibility providers. This paper investigates the… More >

Nguyen Dong Phuong¹, Nanthakumar Srivilliputtur Subbiah¹, Yabin Jin², Xiaoying Zhuang^1,3,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.067100

Abstract Traditional inverse neural network (INN) approaches for inverse design typically require auxiliary feedforward networks, leading to increased computational complexity and architectural dependencies. This study introduces a standalone INN methodology that eliminates the need for feedforward networks while maintaining high reconstruction accuracy. The approach integrates Principal Component Analysis (PCA) and Partial Least Squares (PLS) for optimized feature space learning, enabling the standalone INN to effectively capture bidirectional mappings between geometric parameters and mechanical properties. Validation using established numerical datasets demonstrates that the standalone INN architecture achieves reconstruction accuracy equal or better than traditional tandem approaches while More >

Hsiao-Chun Han¹, Der-Chen Huang^1,*, Chin-Ling Chen^2,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.070944

Abstract This study presents a systematic review of applications of artificial intelligence (abbreviated as AI) and blockchain in supply chain provenance traceability and legal forensics cover five sectors: integrated circuits (abbreviated as ICs), pharmaceuticals, electric vehicles (abbreviated as EVs), drones (abbreviated as UAVs), and robotics—in response to rising trade tensions and geopolitical conflicts, which have heightened concerns over product origin fraud and information security. While previous literature often focuses on single-industry contexts or isolated technologies, this review comprehensively surveys these sectors and categorizes 116 peer-reviewed studies by application domain, technical architecture, and functional objective. Special attention More >