Jiang Mi¹, Zhijian Gan¹, Pengliu Tan^2,*, Xin Chang², Zhi Wang², Haisheng Xie²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-22, 2026, DOI:10.32604/cmc.2025.069348 - 10 November 2025

Abstract In response to the challenges in highway pavement distress detection, such as multiple defect categories, difficulties in feature extraction for different damage types, and slow identification speeds, this paper proposes an enhanced pavement crack detection model named Star-YOLO11. This improved algorithm modifies the YOLO11 architecture by substituting the original C3k2 backbone network with a Star-s50 feature extraction network. The enhanced structure adjusts the number of stacked layers in the StarBlock module to optimize detection accuracy and improve model efficiency. To enhance the accuracy of pavement crack detection and improve model efficiency, three key modifications to… More >

Božo Damjanović^*, Pejo Konjatić, Marko Katinić

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1735-1753, 2025, DOI:10.32604/cmes.2025.072256 - 26 November 2025

Abstract Ensuring the structural integrity of piping systems is crucial in industrial operations to prevent catastrophic failures and minimize shutdown time. This study investigates a transportation-damaged pipe exposed to high-temperature conditions and cyclic loading, representing a realistic challenge in plant operation. The objective was to evaluate the service life and integrity assessment parameters of the damaged pipe, subjected to 22,000 operational cycles under two daily charge and discharge conditions. The flaw size in the damaged pipe was determined based on a failure assessment procedure, ensuring a conservative and reliable input. The damage was characterized as a… More >

Kavita Bodke^1,*, Sunil Bhirud¹, Keshav Kashinath Sangle²

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1547-1562, 2025, DOI:10.32604/sdhm.2025.069239 - 17 November 2025

Abstract Structural Health Monitoring (SHM) systems play a key role in managing buildings and infrastructure by delivering vital insights into their strength and structural integrity. There is a need for more efficient techniques to detect defects, as traditional methods are often prone to human error, and this issue is also addressed through image processing (IP). In addition to IP, automated, accurate, and real- time detection of structural defects, such as cracks, corrosion, and material degradation that conventional inspection techniques may miss, is made possible by Artificial Intelligence (AI) technologies like Machine Learning (ML) and Deep Learning… More > Graphic Abstract

Yating Xu¹, Mansheng Xiao^1,*, Mengxing Gao¹, Zhenzhen Liu¹, Zeyu Xiao²

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1635-1656, 2025, DOI:10.32604/sdhm.2025.068822 - 17 November 2025

Abstract During the operation, maintenance and upkeep of concrete buildings, surface cracks are often regarded as important warning signs of potential damage. Their precise segmentation plays a key role in assessing the health of a building. Traditional manual inspection is subjective, inefficient and has safety hazards. In contrast, current mainstream computer vision–based crack segmentation methods still suffer from missed detections, false detections, and segmentation discontinuities. These problems are particularly evident when dealing with small cracks, complex backgrounds, and blurred boundaries. For this reason, this paper proposes a lightweight building surface crack segmentation method, HL-YOLO, based on… More >

Abdulnaser M. Alshoaibi^*, Yahya Ali Fageehi

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 189-214, 2025, DOI:10.32604/cmes.2025.071583 - 30 October 2025

Abstract Fatigue crack growth is a critical phenomenon in engineering structures, accounting for a significant percentage of structural failures across various industries. Accurate prediction of crack initiation, propagation paths, and fatigue life is essential for ensuring structural integrity and optimizing maintenance schedules. This paper presents a comprehensive finite element approach for simulating two-dimensional fatigue crack growth under linear elastic conditions with adaptive mesh generation. The source code for the program was developed in Fortran 95 and compiled with Visual Fortran. To achieve high-fidelity simulations, the methodology integrates several key features: it employs an automatic, adaptive meshing… More >

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

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 215-239, 2025, DOI:10.32604/cmes.2025.070846 - 30 October 2025

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 >

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 >

Meng Wang¹, Jay Fineberg², Alan Needleman^3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-1, 2025, DOI:10.32604/icces.2025.011000

Abstract Brittle materials fail by means of rapid cracks. At their tips, tensile cracks dissipate elastic energy stored in the surrounding material to create newly fractured surfaces, precisely maintaining 'energy balance' by exactly equating the energy flux with dissipation. Using energy balance, fracture mechanics perfectly describes crack motions; accelerating from nucleation to their maximal speed of cR, the Rayleigh wave speed. A tensile crack speed greater than cR is generally considered impossible [1]. Recently, a new mode of tensile crack propagation faster than cR that is not incorporated in classical fracture mechanics has been predicted in… More >

Chenghuan Liu, Xiangbo Hu, Xiaogang Wang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.010910

Abstract Digital image correlation (DIC) is an emerging non-contact optical measurement method that tracks speckle patterns on the specimen surface to obtain the deformation, providing an advanced methodology for the quantitative evaluation of full-field strain. The present work focuses on the quantitative assessment of deformation from micro to macro scales based on the DIC method and examines damage evolution in metal materials under static and cyclic loading conditions. First, an SEM-based DIC method allowing high-resolution strain measurement at subgrain scales is developed for investigating strain partitioning in dual-phase steel. The results reveal that the strain distribution… More >

Shifa Fan^1,*, Yuanwen Gao^2,3, Zhiqiang Li¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-2, 2025, DOI:10.32604/icces.2025.010668

Abstract In recent years, wearable technology has burst onto the scene as a game-changer, completely transforming multiple facets of our daily lives—from keeping tabs on our health to facilitating communication for staying connected. It has found its way into diverse fields such as healthcare, education, the military, engineering, and sports. However, a major challenge hindering the popularization of wearable devices is the need for a reliable power source. Conventional batteries, though widely used, have limitations, including the need for frequent recharging or replacement, which hinder the seamless integration of wearable technology into everyday life [1]. To… More >