Rui Zhang¹, Lixiang Wang^2,*, Jing Li^1,4, Chun Feng², Yiming Zhang^1,3,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 2103-2129, 2024, DOI:10.32604/cmes.2024.049885 - 20 May 2024

Abstract Perforation is a pivotal technique employed to establish main flow channels within the reservoir formation at the outset of hydraulic fracturing operations. Optimizing perforation designs is critical for augmenting the efficacy of hydraulic fracturing and boosting oil or gas production. In this study, we employ a hybrid finite-discrete element method, known as the continuous–discontinuous element method (CDEM), to simulate the initiation of post-perforation hydraulic fractures and to derive enhanced design parameters. The model incorporates the four most prevalent perforation geometries, as delineated in an engineering technical report. Real-world perforations deviate from the ideal cylindrical shape, More >

Sujithra Sankar^1,*, S. Sathyalakshmi²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3111-3138, 2024, DOI:10.32604/cmc.2024.048408 - 15 May 2024

Abstract In the era of advanced machine learning techniques, the development of accurate predictive models for complex medical conditions, such as thyroid cancer, has shown remarkable progress. Accurate predictive models for thyroid cancer enhance early detection, improve resource allocation, and reduce overtreatment. However, the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and transparency. This paper proposes a novel association-rule based feature-integrated machine learning model which shows better classification and prediction accuracy than present state-of-the-art models. Our study also focuses on the application of SHapley Additive exPlanations (SHAP) values as… More >

Di Qiu^1,3,4, Rongpei Shi^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1017-1028, 2024, DOI:10.32604/cmes.2024.048797 - 16 April 2024

Abstract For media with inclusions (e.g., precipitates, voids, reinforcements, and others), the difference in lattice parameter and the elastic modulus between the matrix and inclusions cause stress concentration at the interfaces. These stress fields depend on the inclusions’ size, shape, and distribution and will respond instantly to the evolving microstructure. This study develops a phase-field model concerning modulus heterogeneity. The effect of modulus heterogeneity on the growth process and equilibrium state of the α plate in Ti-6Al-4V during precipitation is evaluated. The α precipitate exhibits strong anisotropy in shape upon cooling due to the interplay of the… More >

Zhuo Huang, Ye Tian, Yifan Zhang, Tielin Shi, Qi Xia^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 711-733, 2024, DOI:10.32604/cmes.2024.045411 - 16 April 2024

Abstract Stiffened structures have great potential for improving mechanical performance, and the study of their stability is of great interest. In this paper, the optimization of the critical buckling load factor for curved grid stiffeners is solved by using the level set based density method, where the shape and cross section (including thickness and width) of the stiffeners can be optimized simultaneously. The grid stiffeners are a combination of many single stiffeners which are projected by the corresponding level set functions. The thickness and width of each stiffener are designed to be independent variables in the More >

Chein-Shan Liu¹, Chung-Lun Kuo¹, Chih-Wen Chang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3189-3208, 2024, DOI:10.32604/cmes.2023.046002 - 11 March 2024

Abstract To solve the Laplacian problems, we adopt a meshless method with the multiquadric radial basis function (MQ-RBF) as a basis whose center is distributed inside a circle with a fictitious radius. A maximal projection technique is developed to identify the optimal shape factor and fictitious radius by minimizing a merit function. A sample function is interpolated by the MQ-RBF to provide a trial coefficient vector to compute the merit function. We can quickly determine the optimal values of the parameters within a preferred rage using the golden section search algorithm. The novel method provides the More >

Di Zhou¹, Jianxun Zhang^1,*, Chao Li², Yifan Guo¹, Bowen Li¹

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1821-1842, 2024, DOI:10.32604/cmc.2023.047236 - 27 February 2024

Abstract Text perception is crucial for understanding the semantics of outdoor scenes, making it a key requirement for building intelligent systems for driver assistance or autonomous driving. Text information in car-mounted videos can assist drivers in making decisions. However, Car-mounted video text images pose challenges such as complex backgrounds, small fonts, and the need for real-time detection. We proposed a robust Car-mounted Video Text Detector (CVTD). It is a lightweight text detection model based on ResNet18 for feature extraction, capable of detecting text in arbitrary shapes. Our model efficiently extracted global text positions through the Coordinate Attention Threshold Activation… More >

Yu Cheng^1,2,5, Yajun Huang³, Shuai Li⁴, Zhongbin Zhou⁵, Xiaohui Yuan^1,2,*, Yanming Xu^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1935-1960, 2024, DOI:10.32604/cmes.2023.045668 - 29 January 2024

Abstract A new approach for flexoelectric material shape optimization is proposed in this study. In this work, a proxy model based on artificial neural network (ANN) is used to solve the parameter optimization and shape optimization problems. To improve the fitting ability of the neural network, we use the idea of pre-training to determine the structure of the neural network and combine different optimizers for training. The isogeometric analysis-finite element method (IGA-FEM) is used to discretize the flexural theoretical formulas and obtain samples, which helps ANN to build a proxy model from the model shape to More >

Afraz Hussain Majeed¹, Rashid Mahmood², Sayed M. Eldin³, Imran Saddique^4,5,*, S. Saleem⁶, Muhammad Jawad⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1505-1519, 2024, DOI:10.32604/cmes.2023.030255 - 29 January 2024

Abstract This study explains the entropy process of natural convective heating in the nanofluid-saturated cavity in a heated fin and magnetic field. The temperature is constant on the Y-shaped fin, insulating the top wall while the remaining walls remain cold. All walls are subject to impermeability and non-slip conditions. The mathematical modeling of the problem is demonstrated by the continuity, momentum, and energy equations incorporating the inclined magnetic field. For elucidating the flow characteristics Finite Element Method (FEM) is implemented using stable FE pair. A hybrid fine mesh is used for discretizing the domain. Velocity and More >

Chuang Lu¹, Leilei Chen^2,3, Jinling Luo⁴, Haibo Chen^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 847-872, 2024, DOI:10.32604/cmes.2023.044446 - 30 December 2023

Abstract We propose a combined shape and topology optimization approach in this research for 3D acoustics by using the isogeometric boundary element method with subdivision surfaces. The existing structural optimization methods mainly contain shape and topology schemes, with the former changing the surface geometric profile of the structure and the latter changing the material distribution topology or hole topology of the structure. In the present acoustic performance optimization, the coordinates of the control points in the subdivision surfaces fine mesh are selected as the shape design parameters of the structure, the artificial density of the sound… More >

Raveena Selvanarayanan¹, Surendran Rajendran^1,*, Youseef Alotaibi²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 759-782, 2024, DOI:10.32604/cmes.2023.044084 - 30 December 2023

Abstract Colletotrichum kahawae (Coffee Berry Disease) spreads through spores that can be carried by wind, rain, and insects affecting coffee plantations, and causes 80% yield losses and poor-quality coffee beans. The deadly disease is hard to control because wind, rain, and insects carry spores. Colombian researchers utilized a deep learning system to identify CBD in coffee cherries at three growth stages and classify photographs of infected and uninfected cherries with 93% accuracy using a random forest method. If the dataset is too small and noisy, the algorithm may not learn data patterns and generate accurate predictions.… More >