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  • Open Access

    ARTICLE

    A HYBRID CELLULAR AUTOMATON METHOD FOR STRUCTURAL TOPOLOGY OPTIMIZATION WITH MECHANICAL AND HEAT CONSTRAINTS

    Xiaolei Denga,b,c,*,† , Jin Wangd , Jinyu Zhoua, Hongcheng Shena, Zefeng Shenga, Jianglin Zhanga, Xiaowen La, Changxiong Xiea

    Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-6, 2019, DOI:10.5098/hmt.12.13

    Abstract A hybrid cellular automaton model combined with finite element method for structural topology optimization with mechanical and heat constraints is developed. The effect of thermal stress on structural optimization is taken into account. Higher order 8-node element and von Neumann strategy are employed for the finite element and the cellular element, respectively. The validating studies of standard testing structure for topological optimization are carried out. The structure evolution, stress evolution and thermal evolution of topology optimization with mechanical and heat constraints are investigated. The results show the developed hybrid method is more efficient for structural topology optimization. Meanwhile, the topology… More >

  • Open Access

    ARTICLE

    EVALUATION OF THE USE OF CONSTRAINTS IN STEP-BY-STEP ALGORITHMS FOR THE SOLUTION OF A 2D INVERSE HEAT TRANSFER PROBLEM

    Rodrigo Vidonscky Pintoa , Flávio Augusto Sanzovo Fiorellib,*

    Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-10, 2022, DOI:10.5098/hmt.19.30

    Abstract The present paper provides a discussion about the use of constraints in step-by-step optimization algorithms used for the solution of a twodimensional inverse heat transfer problem containing a modeling error. It is observed that the unrestricted algorithms provided better estimates to the power map and the introduction of constraints is harmful to the solution of the inverse heat transfer problem, reducing the area in which this solution approaches the actual heat sources distribution, due to the solution of the unrestricted problem adopting negative values in restricted areas, which compensate the high sensitivity of this problem and consequently provide improved solutions. More >

  • Open Access

    ARTICLE

    Virtual Synchronous Generator Adaptive Control of Energy Storage Power Station Based on Physical Constraints

    Yunfan Huang1, Qingquan Lv2, Zhenzhen Zhang2, Haiying Dong1,*

    Energy Engineering, Vol.120, No.6, pp. 1401-1420, 2023, DOI:10.32604/ee.2023.027365

    Abstract The virtual synchronous generator (VSG) can simulate synchronous machine’s operation mechanism in the control link of an energy storage converter, so that an electrochemical energy storage power station has the ability to actively support the power grid, from passive regulation to active support. Since energy storage is an important physical basis for realizing the inertia and damping characteristics in VSG control, energy storage constraints of the physical characteristics on the system control parameters are analyzed to provide a basis for the system parameter tuning. In a classic VSG control, its virtual inertia and damping coefficient remain unchanged. When the grid… More >

  • Open Access

    ARTICLE

    A New Prediction System Based on Self-Growth Belief Rule Base with Interpretability Constraints

    Yingmei Li, Peng Han, Wei He*, Guangling Zhang, Hongwei Wei, Boying Zhao

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3761-3780, 2023, DOI:10.32604/cmc.2023.037686

    Abstract Prediction systems are an important aspect of intelligent decisions. In engineering practice, the complex system structure and the external environment cause many uncertain factors in the model, which influence the modeling accuracy of the model. The belief rule base (BRB) can implement nonlinear modeling and express a variety of uncertain information, including fuzziness, ignorance, randomness, etc. However, the BRB system also has two main problems: Firstly, modeling methods based on expert knowledge make it difficult to guarantee the model’s accuracy. Secondly, interpretability is not considered in the optimization process of current research, resulting in the destruction of the interpretability of… More >

  • Open Access

    ARTICLE

    STPGTN–A Multi-Branch Parameters Identification Method Considering Spatial Constraints and Transient Measurement Data

    Shuai Zhang, Liguo Weng*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2635-2654, 2023, DOI:10.32604/cmes.2023.025405

    Abstract Transmission line (TL) Parameter Identification (PI) method plays an essential role in the transmission system. The existing PI methods usually have two limitations: (1) These methods only model for single TL, and can not consider the topology connection of multiple branches for simultaneous identification. (2) Transient bad data is ignored by methods, and the random selection of terminal section data may cause the distortion of PI and have serious consequences. Therefore, a multi-task PI model considering multiple TLs’ spatial constraints and massive electrical section data is proposed in this paper. The Graph Attention Network module is used to draw a… More > Graphic Abstract

    STPGTN–A Multi-Branch Parameters Identification Method Considering Spatial Constraints and Transient Measurement Data

  • Open Access

    ARTICLE

    Optimization Techniques in University Timetabling Problem: Constraints, Methodologies, Benchmarks, and Open Issues

    Abeer Bashab1, Ashraf Osman Ibrahim2,*, Ibrahim Abakar Tarigo Hashem3, Karan Aggarwal4, Fadhil Mukhlif5, Fuad A. Ghaleb5, Abdelzahir Abdelmaboud6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6461-6484, 2023, DOI:10.32604/cmc.2023.034051

    Abstract University timetabling problems are a yearly challenging task and are faced repeatedly each semester. The problems are considered non-polynomial time (NP) and combinatorial optimization problems (COP), which means that they can be solved through optimization algorithms to produce the aspired optimal timetable. Several techniques have been used to solve university timetabling problems, and most of them use optimization techniques. This paper provides a comprehensive review of the most recent studies dealing with concepts, methodologies, optimization, benchmarks, and open issues of university timetabling problems. The comprehensive review starts by presenting the essence of university timetabling as NP-COP, defining and clarifying the… More >

  • Open Access

    ARTICLE

    Shape and Size Optimization of Truss Structures under Frequency Constraints Based on Hybrid Sine Cosine Firefly Algorithm

    Ran Tao, Xiaomeng Yang, Huanlin Zhou*, Zeng Meng*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 405-428, 2023, DOI:10.32604/cmes.2022.020824

    Abstract Shape and size optimization with frequency constraints is a highly nonlinear problem with mixed design variables, non-convex search space, and multiple local optima. Therefore, a hybrid sine cosine firefly algorithm (HSCFA) is proposed to acquire more accurate solutions with less finite element analysis. The full attraction model of firefly algorithm (FA) is analyzed, and the factors that affect its computational efficiency and accuracy are revealed. A modified FA with simplified attraction model and adaptive parameter of sine cosine algorithm (SCA) is proposed to reduce the computational complexity and enhance the convergence rate. Then, the population is classified, and different populations… More >

  • Open Access

    ARTICLE

    Static Analysis of Doubly-Curved Shell Structures of Smart Materials and Arbitrary Shape Subjected to General Loads Employing Higher Order Theories and Generalized Differential Quadrature Method

    Francesco Tornabene*, Matteo Viscoti, Rossana Dimitri

    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 719-798, 2022, DOI:10.32604/cmes.2022.022210

    Abstract The article proposes an Equivalent Single Layer (ESL) formulation for the linear static analysis of arbitrarily-shaped shell structures subjected to general surface loads and boundary conditions. A parametrization of the physical domain is provided by employing a set of curvilinear principal coordinates. The generalized blending methodology accounts for a distortion of the structure so that disparate geometries can be considered. Each layer of the stacking sequence has an arbitrary orientation and is modelled as a generally anisotropic continuum. In addition, re-entrant auxetic three-dimensional honeycomb cells with soft-core behaviour are considered in the model. The unknown variables are described employing a… More > Graphic Abstract

    Static Analysis of Doubly-Curved Shell Structures of Smart Materials and Arbitrary Shape Subjected to General Loads Employing Higher Order Theories and Generalized Differential Quadrature Method

  • Open Access

    ARTICLE

    Regularised Layerwise Weight Norm Based Skin Lesion Features Extraction and Classification

    S. Gopikha*, M. Balamurugan

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2727-2742, 2023, DOI:10.32604/csse.2023.028609

    Abstract Melanoma is the most lethal malignant tumour, and its prevalence is increasing. Early detection and diagnosis of skin cancer can alert patients to manage precautions and dramatically improve the lives of people. Recently, deep learning has grown increasingly popular in the extraction and categorization of skin cancer features for effective prediction. A deep learning model learns and co-adapts representations and features from training data to the point where it fails to perform well on test data. As a result, overfitting and poor performance occur. To deal with this issue, we proposed a novel Consecutive Layerwise weight Constraint MaxNorm model (CLCM-net)… More >

  • Open Access

    ARTICLE

    Minimizing Total Tardiness in a Two-Machine Flowshop Scheduling Problem with Availability Constraints

    Mohamed Ali Rakrouki1,2,*, Abeer Aljohani1, Nawaf Alharbe1, Abdelaziz Berrais2, Talel Ladhari2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1119-1134, 2023, DOI:10.32604/iasc.2023.028604

    Abstract In this paper, we consider the problem of minimizing the total tardiness in a deterministic two-machine permutation flowshop scheduling problem subject to release dates of jobs and known unavailability periods of machines. The theoretical and practical importance of minimizing tardiness in flowshop scheduling environment has motivated us to investigate and solve this interested two-machine scheduling problem. Methods that solve this important optimality criterion in flowshop environment are mainly heuristics. In fact, despite the -hardness in the strong sense of the studied problem, to the best of our knowledge there are no approximate algorithms (constructive heuristics or metaheuristics) or an algorithm… More >

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