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  • Open Access

    ARTICLE

    A Novel Localized Meshless Method for Solving Transient Heat Conduction Problems in Complicated Domains

    Chengxin Zhang1, Chao Wang1, Shouhai Chen2,*, Fajie Wang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2407-2424, 2023, DOI:10.32604/cmes.2023.024884

    Abstract This paper first attempts to solve the transient heat conduction problem by combining the recently proposed local knot method (LKM) with the dual reciprocity method (DRM). Firstly, the temporal derivative is discretized by a finite difference scheme, and thus the governing equation of transient heat transfer is transformed into a non-homogeneous modified Helmholtz equation. Secondly, the solution of the non-homogeneous modified Helmholtz equation is decomposed into a particular solution and a homogeneous solution. And then, the DRM and LKM are used to solve the particular solution of the non-homogeneous equation and the homogeneous solution of More >

  • Open Access

    ARTICLE

    Fast Mesh Reconstruction from Single View Based on GCN and Topology Modification

    Xiaorui Zhang1,2,3,*, Feng Xu2, Wei Sun3,4, Yan Jiang2, Yi Cao5

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1695-1709, 2023, DOI:10.32604/csse.2023.031506

    Abstract 3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one perspective. When existing methods reconstruct the mesh surface of complex objects, the surface details are difficult to predict and the reconstruction visual effect is poor because the mesh representation is not easily integrated into the deep learning framework; the 3D topology is easily limited by predefined templates and inflexible, and unnecessary mesh self-intersections and connections will be generated when reconstructing complex topology, thus destroying the surface details; the training of the reconstruction network is limited by the… More >

  • Open Access

    ARTICLE

    Explicit Isogeometric Topology Optimization Method with Suitably Graded Truncated Hierarchical B-Spline

    Haoran Zhu, Xinhao Gao, Aodi Yang, Shuting Wang, Xianda Xie, Tifan Xiong*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1435-1456, 2023, DOI:10.32604/cmes.2022.023454

    Abstract This work puts forward an explicit isogeometric topology optimization (ITO) method using moving morphable components (MMC), which takes the suitably graded truncated hierarchical B-Spline based isogeometric analysis as the solver of physical unknown (SGTHB-ITO-MMC). By applying properly basis graded constraints to the hierarchical mesh of truncated hierarchical B-splines (THB), the convergence and robustness of the SGTHB-ITOMMC are simultaneously improved and the tiny holes occurred in optimized structure are eliminated, due to the improved accuracy around the explicit structural boundaries. Moreover, an efficient computational method is developed for the topological description functions (TDF) of MMC under More > Graphic Abstract

    Explicit Isogeometric Topology Optimization Method with Suitably Graded Truncated Hierarchical B-Spline

  • Open Access

    ARTICLE

    A Deep Learning Approach to Mesh Segmentation

    Abubakar Sulaiman Gezawa1, Qicong Wang1,2, Haruna Chiroma3, Yunqi Lei1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1745-1763, 2023, DOI:10.32604/cmes.2022.021351

    Abstract In the shape analysis community, decomposing a 3D shape into meaningful parts has become a topic of interest. 3D model segmentation is largely used in tasks such as shape deformation, shape partial matching, skeleton extraction, shape correspondence, shape annotation and texture mapping. Numerous approaches have attempted to provide better segmentation solutions; however, the majority of the previous techniques used handcrafted features, which are usually focused on a particular attribute of 3D objects and so are difficult to generalize. In this paper, we propose a three-stage approach for using Multi-view recurrent neural network to automatically segment… More > Graphic Abstract

    A Deep Learning Approach to Mesh Segmentation

  • Open Access

    ARTICLE

    Numerical Assessment of Nanofluid Natural Convection Using Local RBF Method Coupled with an Artificial Compressibility Model

    Muneerah Al Nuwairan1,*, Elmiloud Chaabelasri2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 133-154, 2023, DOI:10.32604/cmes.2022.022649

    Abstract In this paper, natural heat convection inside square and equilateral triangular cavities was studied using a meshless method based on collocation local radial basis function (RBF). The nanofluids used were Cu-water or -water mixture with nanoparticle volume fractions range of . A system of continuity, momentum, and energy partial differential equations was used in modeling the flow and temperature behavior of the fluids. Partial derivatives in the governing equations were approximated using the RBF method. The artificial compressibility model was implemented to overcome the pressure velocity coupling problem that occurs in such equations. The main goal… More > Graphic Abstract

    Numerical Assessment of Nanofluid Natural Convection Using Local RBF Method Coupled with an Artificial Compressibility Model

  • Open Access

    ARTICLE

    Analysis of the Microstructure of a Failed Cement Sheath Subjected to Complex Temperature and Pressure Conditions

    Zhiqiang Wu1,2, Yi Wu2, Renjun Xie2, Jin Yang1, Shujie Liu3, Qiao Deng4,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.2, pp. 399-406, 2023, DOI:10.32604/fdmp.2022.020402

    Abstract One of the main obstacles hindering the exploitation of high-temperature and high-pressure oil and gas is the sealing integrity of the cement sheath. Analyzing the microstructure of the cement sheath is therefore an important task. In this study, the microstructure of the cement sheath is determined using a CT scanner under different temperature and pressure conditions. The results suggest that the major cause of micro-cracks in the cement is the increase in the casing pressure. When the micro-cracks accumulate to a certain extent, the overall structure of the cement sheath is weakened, resulting in gas More >

  • Open Access

    REVIEW

    Deep Learning-Based 3D Instance and Semantic Segmentation: A Review

    Siddiqui Muhammad Yasir1, Hyunsik Ahn2,*

    Journal on Artificial Intelligence, Vol.4, No.2, pp. 99-114, 2022, DOI:10.32604/jai.2022.031235

    Abstract The process of segmenting point cloud data into several homogeneous areas with points in the same region having the same attributes is known as 3D segmentation. Segmentation is challenging with point cloud data due to substantial redundancy, fluctuating sample density and lack of apparent organization. The research area has a wide range of robotics applications, including intelligent vehicles, autonomous mapping and navigation. A number of researchers have introduced various methodologies and algorithms. Deep learning has been successfully used to a spectrum of 2D vision domains as a prevailing A.I. methods. However, due to the specific… More >

  • Open Access

    REVIEW

    Anomaly Detection in Textured Images with a Convolutional Neural Network for Quality Control of Micrometric Woven Meshes

    Pierre-Frédéric Villard1,*, Maureen Boudart2, Ioana Ilea3, Fabien Pierre1

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.6, pp. 1639-1648, 2022, DOI:10.32604/fdmp.2022.021726

    Abstract Industrial woven meshes are composed of metal materials and are often used in construction, industrial and residential activities or applications. The objective of this work is defect detection in industrial fabrics in the quality control stage. In order to overcome the limitations of manual methods, which are often tedious and time-consuming, we propose a strategy that can automatically detect defects in micrometric steel meshes by means of a Convolutional Neural Network. The database used for such a purpose comes from real problem data for anomaly detection in micrometric woven meshes. This detection is performed through More >

  • Open Access

    ARTICLE

    Simulation of Oil-Water Flow in a Shale Reservoir Using a Radial Basis Function

    Zenglin Wang1, Liaoyuan Zhang1, Anhai Zhong2, Ran Ding2, Mingjing Lu2,3,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.6, pp. 1795-1804, 2022, DOI:10.32604/fdmp.2022.020020

    Abstract Due to the difficulties associated with preprocessing activities and poor grid convergence when simulating shale reservoirs in the context of traditional grid methods, in this study an innovative two-phase oil-water seepage model is elaborated. The modes is based on the radial basis meshless approach and is used to determine the pressure and water saturation in a sample reservoir. Two-dimensional examples demonstrate that, when compared to the finite difference method, the radial basis function method produces less errors and is more accurate in predicting daily oil production. The radial basis function and finite difference methods provide More >

  • Open Access

    ARTICLE

    High Efficiency Crypto-Watermarking System Based on Clifford-Multiwavelet for 3D Meshes Security

    Wajdi Elhamzi1,2,*, Malika Jallouli3, Yassine Bouteraa1,4

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4329-4347, 2022, DOI:10.32604/cmc.2022.030954

    Abstract Since 3D mesh security has become intellectual property, 3D watermarking algorithms have continued to appear to secure 3D meshes shared by remote users and saved in distant multimedia databases. The novelty of our approach is that it uses a new Clifford-multiwavelet transform to insert copyright data in a multiresolution domain, allowing us to greatly expand the size of the watermark. After that, our method does two rounds of insertion, each applying a different type of Clifford-wavelet transform. Before being placed into the Clifford-multiwavelet coefficients, the watermark, which is a mixture of the mesh description, source… More >

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