Chengya Hua¹, Leihua Yao^1,*, Chenguang Song¹, Qihang Ni¹, Dongfang Chen²

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 413-434, 2022, DOI:10.32604/cmes.2022.020260

Abstract A new variational method treating the system as a whole with rigorous mathematical and physical derivation was presented in this paper. Combined with classical and engineering examples, variational energy expressions of slopes were derived. In addition, the calculation programs were written in the FISH language set in FLAC3D (fast Lagrangian analysis of continua in three dimensions) software. Factors of safety (FOSs) of the models were determined by the variational method based on the strength reduction method (SRM) and then compared with other criteria or methods. The result showed that the variational method reflected the process of slope plasticity and failure… More >

Yongsong Li¹, Xiaomeng Yin², Yanming Xu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 471-488, 2022, DOI:10.32604/cmes.2022.020201

Abstract The isogeometric boundary element technique (IGABEM) is presented in this study for steady-state inhomogeneous heat conduction analysis. The physical unknowns in the boundary integral formulations of the governing equations are discretized using non-uniform rational B-spline (NURBS) basis functions, which are utilized to build the geometry of the structures. To speed up the assessment of NURBS basis functions, the B´ezier extraction approach is used. To solve the extra domain integrals, we use a radial integration approach. The numerical examples show the potential of IGABEM for dimension reduction and smooth integration of CAD and numerical analysis. More >

Rui Yong^1,2,*, Jun Ye^1,2, Shigui Du^1,2, Aqin Zhu¹, Yingying Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 569-584, 2022, DOI:10.32604/cmes.2022.019509

Abstract The simplified neutrosophic number (SNN) can represent uncertain, imprecise, incomplete, and inconsistent information that exists in scientific, technological, and engineering fields. Hence, it is a useful tool for describing truth, falsity, and indeterminacy information in multiple attribute decision-making (MADM) problems. To suit decision makers’ preference selection, the operational flexibility of aggregation operators shows its importance in dealing with the flexible decision-making problems in the SNN environment. To solve this problem, this paper develops the Aczel-Alsina aggregation operators of SNNs for MADM problems in view of the Aczel-Alsina operational flexibility. First, we define the Aczel-Alsina operations of SNNs. Then, the Aczel-Alsina… More >

Jinfu Wang¹, Shunyi Zhao^1,*, Fei Liu¹, Zhenyi Ma²

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 531-552, 2022, DOI:10.32604/cmes.2022.019521

Abstract In modern industry, process monitoring plays a significant role in improving the quality of process conduct. With the higher dimensional of the industrial data, the monitoring methods based on the latent variables have been widely applied in order to decrease the wasting of the industrial database. Nevertheless, these latent variables do not usually follow the Gaussian distribution and thus perform unsuitable when applying some statistics indices, especially the T2 on them. Variational AutoEncoders (VAE), an unsupervised deep learning algorithm using the hierarchy study method, has the ability to make the latent variables follow the Gaussian distribution. The partial least squares… More >

Adel Hamdan Mohammad^1,* , Sami Smadi², Tariq Alwada’n³

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 435-450, 2022, DOI:10.32604/cmes.2022.020088

Abstract Undoubtedly, spam is a serious problem, and the number of spam emails is increased rapidly. Besides, the massive number of spam emails prompts the need for spam detection techniques. Several methods and algorithms are used for spam filtering. Also, some emergent spam detection techniques use machine learning methods and feature extraction. Some methods and algorithms have been introduced for spam detecting and filtering. This research proposes two models for spam detection and feature selection. The first model is evaluated with the email spam classification dataset, which is based on reducing the number of keywords to its minimum. The results of… More >

Wenqian Zhang¹, Jingwen Chen^1,*, Saleem Riaz³, Naiwen Zheng¹, Li Li²

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 585-604, 2022, DOI:10.32604/cmes.2022.020523

Abstract Distributed collaborative control strategies for microgrids often use periodic time to trigger communication, which is likely to enhance the burden of communication and increase the frequency of controller updates, leading to greater waste of communication resources. In response to this problem, a distributed cooperative control strategy triggered by an adaptive event is proposed. By introducing an adaptive event triggering mechanism in the distributed controller, the triggering parameters are dynamically adjusted so that the distributed controller can communicate only at a certain time, the communication pressure is reduced, and the DC bus voltage deviation is effectively reduced, at the same time,… More >

Xiaoxin Yang¹, Saleem Riaz^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 605-626, 2022, DOI:10.32604/cmes.2022.020412

Abstract An iterative learning control algorithm based on error backward association and control parameter correction has been proposed for a class of linear discrete time-invariant systems with repeated operation characteristics, parameter disturbance, and measurement noise taking PD type example. Firstly, the concrete form of the accelerated learning law is presented, based on the detailed description of how the control factor is obtained in the algorithm. Secondly, with the help of the vector method, the convergence of the algorithm for the strict mathematical proof, combined with the theory of spectral radius, sucient conditions for the convergence of the algorithm is presented for… More >

Xiaona Fan, Qin Zhao, Guochen Sang, Yiyun Zhu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 627-660, 2022, DOI:10.32604/cmes.2022.020507

Abstract Indoor thermal comfort and passive solar heating technologies have been extensively studied. However, few studies have explored the suitability of passive solar heating technologies based on differentiated thermal comfort demands. This work took the rural dwellings in Northwest China as the research object. First, the current indoor and outdoor thermal environment in winter and the mechanism of residents’ differentiated demand for indoor thermal comfort were obtained through tests, questionnaires, and statistical analysis. Second, a comprehensive passive optimized design of existing buildings was conducted, and the validity of the optimized combination scheme was explored using DesignBuilder software. Finally, the suitability of… More >

Jun Zou^*, Haolei Mou

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 451-469, 2022, DOI:10.32604/cmes.2022.020111

Abstract The integration of topology optimization (TO) and additive manufacturing (AM) technologies can create significant synergy benefits, while the lack of AM-friendly TO algorithms is a serious bottleneck for the application of TO in AM. In this paper, a TO method is proposed to design self-supporting structures with an explicit continuous self-supporting constraint, which can be adaptively activated and tightened during the optimization procedure. The TO procedure is suitable for various critical overhang angles (COA), which is integrated with build direction assignment to reduce performance loss. Besides, a triangular directional self-supporting constraint sensitivity filter is devised to promote the downward evolution… More >

Quan Wen¹, Fulei Jing^1,*, Changxian Zhang¹, Shibai Tang¹, Junjie Yang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 361-391, 2022, DOI:10.32604/cmes.2022.019528

Abstract Thermally grown oxide (TGO) is a critical factor for the service life of thermal barrier coatings (TBC). Numerical simulations of the growth process of TGO have become an effective means of comprehensively understanding the progressive damage of the TBC system. At present, technologies of numerical simulation to TGO growth include two categories: coupled chemical-mechanical methods and mechanical equivalent methods. The former is based on the diffusion analysis of oxidizing elements, which can describe the influence of bond coat (BC) consumption and phase transformation in the growth process of TGO on the mechanical behavior of each layer of TBC, and has… More >