Open Access
EDITORIAL
Jian Xiong1,*, Jinshui Yang2, Hui Li3, Wu Xu4
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 357-359, 2022, DOI:10.32604/cmes.2022.023418
（This article belongs to this Special Issue: Mechanics of Composite Materials and Structures)
Abstract This article has no abstract. More >
Open Access
REVIEW
Quan Wen1, Fulei Jing1,*, Changxian Zhang1, Shibai Tang1, Junjie Yang2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 361-391, 2022, DOI:10.32604/cmes.2022.019528
（This article belongs to this Special Issue: Recent Trends in Thermal Barrier Coatings for Turbine Blades: Theory, Simulation, and Experiment)
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 >
Open Access
ARTICLE
Evren Hincal, Amna Hashim Alzadjali
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 393-411, 2022, DOI:10.32604/cmes.2022.019781
Abstract Excellent student’s academic performance is the uppermost priority and goal of educators and facilitators. The dubious marginal rate between admission and graduation rates unveils the rates of dropout and withdrawal from school. To improve the academic performance of students, we optimize the performance indices to the dynamics describing the academic performance in the form of nonlinear system ODE. We established the uniform boundedness of the model and the existence and uniqueness result. The independence and interdependence equilibria were found to be locally and globally asymptotically stable. The optimal control analysis was carried out, and lastly, numerical simulation was run to… More >
Open Access
ARTICLE
Chengya Hua1, Leihua Yao1,*, 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 >
Open Access
ARTICLE
Adel Hamdan Mohammad1,* , 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 >
Open Access
ARTICLE
Jun Zou*, Haolei Mou
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 451-469, 2022, DOI:10.32604/cmes.2022.020111
（This article belongs to this Special Issue: New Trends in Structural Optimization)
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 >
Open Access
ARTICLE
Yongsong Li1, Xiaomeng Yin2, Yanming Xu1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 471-488, 2022, DOI:10.32604/cmes.2022.020201
（This article belongs to this Special Issue: Recent Advance of the Isogeometric Boundary Element Method and its Applications)
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 >
Open Access
ARTICLE
Asad Ejaz1, Yasir Nawaz1, Muhammad Shoaib Arif1,3,*, Daoud S. Mashat2, Kamaleldin Abodayeh3
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 489-506, 2022, DOI:10.32604/cmes.2022.019440
（This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
Abstract The present study is concerned with formulating a predator-prey eco-epidemiological mathematical model
assuming that an infection exists in the predator species. The two classes of predator species (susceptible and
infected) compete for the same sources available in the environment with the predation option. It is assumed
that the disease does not spread vertically. The proposed model is analyzed for the stability of the coexistence
of the predators and prey. The fixed points are carried out, and the coexisting fixed point is studied in detail by
constructing the Lyapunov function. The movement of species in search of food or protection in… More >
Open Access
ARTICLE
Xiaowei Gu1,#, Shuwen Chen1,2,#,*, Huisheng Zhu1, Mackenzie Brown3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 507-530, 2022, DOI:10.32604/cmes.2022.018948
（This article belongs to this Special Issue: Computer-Assisted Imaging Processing and Machine Learning Applications on Diagnosis of Chest Radiograph)
Abstract Coronavirus disease 2019 brings a huge burden on the medical industry all over the world. In the background
of artificial intelligence (AI) and Internet of Things (IoT) technologies, chest computed tomography (CT) and
chest X-ray (CXR) scans are becoming more intelligent, and playing an increasingly vital role in the diagnosis
and treatment of diseases. This paper will introduce the segmentation of methods and applications. CXR and CT
diagnosis of COVID-19 based on deep learning, which can be widely used to fight against COVID-19. More >
Open Access
ARTICLE
Jinfu Wang1, Shunyi Zhao1,*, Fei Liu1, Zhenyi Ma2
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 531-552, 2022, DOI:10.32604/cmes.2022.019521
（This article belongs to this Special Issue: Advances on Modeling and State Estimation for Industrial Processes)
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 >
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