Open Access
ARTICLE
Zihan Wang1, Boshan Zhang2, Hui Wang1,*, Qing Ai1, Xingchun Huang1
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048217
（This article belongs to the Special Issue: Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures)
Abstract The application of ultra-high performance concrete (UHPC) as a covering layer for steel bridge decks has gained widespread popularity. By employing a connection without a shear connector between the steel plate and UHPC, namely, the sandblasted interface and the epoxy adhesive with sprinkled basalt aggregate interface, the installation cannot only be simplified but also the stress concentration resulting from the welded shear connectors can be eliminated. This study develops constitutive models for these two interfaces without shear connectors, based on the interfacial pull-off and push-out tests. For validation, three-point bending tests on the steel-UHPC composite plates are conducted. The results… More >
Open Access
ARTICLE
Daisuke Ishihara*, Syunnosuke Nozaki, Tomoya Niho, Naoto Takayama
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.049694
Abstract The inverse and direct piezoelectric and circuit coupling are widely observed in advanced electro-mechanical systems such as piezoelectric energy harvesters. Existing strongly coupled analysis methods based on direct numerical modeling for this phenomenon can be classified into partitioned or monolithic formulations. Each formulation has its advantages and disadvantages, and the choice depends on the characteristics of each coupled problem. This study proposes a new option: a coupled analysis strategy that combines the best features of the existing formulations, namely, the hybrid partitioned-monolithic method. The analysis of inverse piezoelectricity and the monolithic analysis of direct piezoelectric and circuit interaction are strongly… More >
Open Access
ARTICLE
Ruijin Huo1,2,3, Qingxiang Pei1,2,3, Xiaohui Yuan1,*, Yanming Xu3
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.049185
（This article belongs to the Special Issue: Integration of Physical Simulation and Machine Learning in Digital Twin and Virtual Reality)
Abstract In this paper, a generalized th-order perturbation method based on the isogeometric boundary element method is proposed for the uncertainty analysis of broadband structural acoustic scattering problems. The Burton-Miller method is employed to solve the problem of non-unique solutions that may be encountered in the external acoustic field, and the th-order discretization formulation of the boundary integral equation is derived. In addition, the computation of loop subdivision surfaces and the subdivision rules are introduced. In order to confirm the effectiveness of the algorithm, the computed results are contrasted and analyzed with the results under Monte Carlo simulations (MCs) through several… More >
Open Access
REVIEW
Yifan Liu1, Shancang Li1,*, Xinheng Wang2, Li Xu3
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.046473
（This article belongs to the Special Issue: Machine Learning Empowered Distributed Computing: Advance in Architecture, Theory and Practice)
Abstract The Industrial Internet of Things (IIoT) has brought numerous benefits, such as improved efficiency, smart analytics, and increased automation. However, it also exposes connected devices, users, applications, and data generated to cyber security threats that need to be addressed. This work investigates hybrid cyber threats (HCTs), which are now working on an entirely new level with the increasingly adopted IIoT. This work focuses on emerging methods to model, detect, and defend against hybrid cyber attacks using machine learning (ML) techniques. Specifically, a novel ML-based HCT modelling and analysis framework was proposed, in which regularisation and Random Forest were used to… More >
Open Access
ARTICLE
Xiaojun Huang1, Liaojun Zhang2,*, Hanbo Cui1, Gaoxing Hu1
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.049124
（This article belongs to the Special Issue: Recent Advances in Computational Methods for Performance Assessment of Engineering Structures and Materials against Dynamic Loadings)
Abstract This study proposes an effective method to enhance the accuracy of the Differential Quadrature Method (DQM) for calculating the dynamic characteristics of functionally graded beams by improving the form of discrete node distribution. Firstly, based on the first-order shear deformation theory, the governing equation of free vibration of a functionally graded beam is transformed into the eigenvalue problem of ordinary differential equations with respect to beam axial displacement, transverse displacement, and cross-sectional rotation angle by considering the effects of shear deformation and rotational inertia of the beam cross-section. Then, ignoring the shear deformation of the beam section and only considering… More >
Open Access
REVIEW
Xiaoli You1,2,3,#, Ruiyu Bai1,2,3,4,#, Kai Xue1,2,3, Zimo Zhang1,2,3, Minghao Wang5, Xuanqi Wang1,2,3, Jiahao Wang1,2,3, Jinku Guo1,2, Qiang Shen3, Honglong Chang3, Xu Long6,*, Bowen Ji1,2,3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.049047
Abstract Implanted neural probes can detect weak discharges of neurons in the brain by piercing soft brain tissue, thus as important tools for brain science research, as well as diagnosis and treatment of brain diseases. However, the rigid neural probes, such as Utah arrays, Michigan probes, and metal microfilament electrodes, are mechanically unmatched with brain tissue and are prone to rejection and glial scarring after implantation, which leads to a significant degradation in the signal quality with the implantation time. In recent years, flexible neural electrodes are rapidly developed with less damage to biological tissues, excellent biocompatibility, and mechanical compliance to… More >
Open Access
ARTICLE
Mingjian Li, Ping Yang*, Pengyang Zhao
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048334
（This article belongs to the Special Issue: Computational Design and Modeling of Advanced Composites and Structures)
Abstract The experimental results in previous studies have indicated that during the ductile fracture of pure metals, vacancies aggregate and form voids at grain boundaries. However, the physical mechanism underlying this phenomenon remains not fully understood. This study derives the equilibrium distribution of vacancies analytically by following thermodynamics and the micromechanics of crystal defects. This derivation suggests that vacancies cluster in regions under hydrostatic compression to minimize the elastic strain energy. Subsequently, a finite element model is developed for examining more general scenarios of interaction between vacancies and grain boundaries. This model is first verified and validated through comparison with some… More >
Open Access
ARTICLE
Kun Yan1, Yunyu Wang2, Jun Yan3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048877
（This article belongs to the Special Issue: Structural Design and Optimization)
Abstract Topology optimization of thermal-fluid coupling problems has received widespread attention. This article proposes a novel topology optimization method for laminar two-fluid heat exchanger design. The proposed method utilizes an artificial density field to create two permeability interpolation functions that exhibit opposing trends, ensuring separation between the two fluid domains. Additionally, a Gaussian function is employed to construct an interpolation function for the thermal conductivity coefficient. Furthermore, a computational program has been developed on the OpenFOAM platform for the topology optimization of two-fluid heat exchangers. This program leverages parallel computing, significantly reducing the time required for the topology optimization process. To… More >
Open Access
ARTICLE
Jiaxiang Luo1,2, Weien Zhou2,3, Bingxiao Du1,*, Daokui Li1, Wen Yao2,3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048118
（This article belongs to the Special Issue: Structural Design and Optimization)
Abstract In recent years, there has been significant research on the application of deep learning (DL) in topology optimization (TO) to accelerate structural design. However, these methods have primarily focused on solving binary TO problems, and effective solutions for multi-material topology optimization (MMTO) which requires a lot of computing resources are still lacking. Therefore, this paper proposes the framework of multiphase topology optimization using deep learning to accelerate MMTO design. The framework employs convolutional neural network (CNN) to construct a surrogate model for solving MMTO, and the obtained surrogate model can rapidly generate multi-material structure topologies in negligible time without any… More >
Open Access
ARTICLE
Seyed Mohammad Reza Abtahi1, Saeid Ansari Sadrabadi2,*, Gholam Hosein Rahimi1, Gaurav Singh2, Hamid Abyar3, Daniele Amato4, Luigi Federico5
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.047575
Abstract Repairs of corroded high-pressure pipelines are essential for fluids transportation under high pressure. One of the methods used in their repairs is the use of layered composites. The composite used must have the necessary strength. Therefore, the experiments and analytical solutions presented in this paper are performed according to the relevant standards and codes, including ASME PCC-2, ASME B31.8S, ASME B31.4, ISO 24817 and ASME B31.G. In addition, the experimental tests are replicated numerically using the finite element method. Setting the strain gauges at different distances from the defect location, can reduce the nonlinear effects, deformation, and fluctuations due to… More >
Open Access
ARTICLE
Xu Xu1, Xiaoteng Wang1, Haitian Yang1, Zhenjun Yang2, Yiqian He1,3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048199
（This article belongs to the Special Issue: Advances on Mesh and Dimension Reduction Methods)
Abstract The multiscale method provides an effective approach for the numerical analysis of heterogeneous viscoelastic materials by reducing the degree of freedoms (DOFs). A basic framework of the Multiscale Scaled Boundary Finite Element Method (MsSBFEM) was presented in our previous works, but those works only addressed two-dimensional problems. In order to solve more realistic problems, a three-dimensional MsSBFEM is further developed in this article. In the proposed method, the octree SBFEM is used to deal with the three-dimensional calculation for numerical base functions to bridge small and large scales, the three-dimensional image-based analysis can be conveniently conducted in small-scale and coarse… More >
Open Access
ARTICLE
Deng Yang1, Chong Zhou1,*, Xuemeng Wei2, Zhikun Chen3, Zheng Zhang4
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048049
（This article belongs to the Special Issue: Bio-inspired Optimization in Engineering and Sciences)
Abstract In classification problems, datasets often contain a large amount of features, but not all of them are relevant for accurate classification. In fact, irrelevant features may even hinder classification accuracy. Feature selection aims to alleviate this issue by minimizing the number of features in the subset while simultaneously minimizing the classification error rate. Single-objective optimization approaches employ an evaluation function designed as an aggregate function with a parameter, but the results obtained depend on the value of the parameter. To eliminate this parameter’s influence, the problem can be reformulated as a multi-objective optimization problem. The Whale Optimization Algorithm (WOA) is… More >
Open Access
ARTICLE
Jing-Doo Wang1, Chayadi Oktomy Noto Susanto1,2,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048955
（This article belongs to the Special Issue: Artificial Intelligence Emerging Trends and Sustainable Applications in Image Processing and Computer Vision)
Abstract A significant obstacle in intelligent transportation systems (ITS) is the capacity to predict traffic flow. Recent
advancements in deep neural networks have enabled the development of models to represent traffic flow accurately.
However, accurately predicting traffic flow at the individual road level is extremely difficult due to the complex
interplay of spatial and temporal factors. This paper proposes a technique for predicting short-term traffic flow
data using an architecture that utilizes convolutional bidirectional long short-term memory (Conv-BiLSTM) with
attention mechanisms. Prior studies neglected to include data pertaining to factors such as holidays, weather
conditions, and vehicle types, which are interconnected… More >
Open Access
ARTICLE
Yunye Wan1, Peng Chen2, Yunni Xia1,*, Yong Ma3, Dongge Zhu4, Xu Wang5, Hui Liu6, Weiling Li7, Xianhua Niu2, Lei Xu8, Yumin Dong9
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048723
（This article belongs to the Special Issue: Machine Learning Empowered Distributed Computing: Advance in Architecture, Theory and Practice)
Abstract Mobile Edge Computing (MEC) is a promising technology that provides on-demand computing and efficient
storage services as close to end users as possible. In an MEC environment, servers are deployed closer to mobile
terminals to exploit storage infrastructure, improve content delivery efficiency, and enhance user experience.
However, due to the limited capacity of edge servers, it remains a significant challenge to meet the changing, timevarying, and customized needs for highly diversified content of users. Recently, techniques for caching content
at the edge are becoming popular for addressing the above challenges. It is capable of filling the communication
gap between the… More >
Open Access
ARTICLE
Hao Qi1, Mohamed Sharaf2, Andres Annuk3, Adrian Ilinca4, Mohamed A. Mohamed5,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048672
Abstract Hot dry rock (HDR) is rich in reserve, widely distributed, green, low-carbon, and has broad development potential
and prospects. In this paper, a distributionally robust optimization (DRO) scheduling model for a regionally
integrated energy system (RIES) considering HDR co-generation is proposed. First, the HDR-enhanced geothermal
system (HDR-EGS) is introduced into the RIES. HDR-EGS realizes the thermoelectric decoupling of combined
heat and power (CHP) through coordinated operation with the regional power grid and the regional heat grid,
which enhances the system wind power (WP) feed-in space. Secondly, peak-hour loads are shifted using price
demand response guidance in the context of time-of-day… More >
Open Access
ARTICLE
Ali S. Alghamdi1,*, Mohamed A. Zohdy2, Saad Aldoihi3,4
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048839
Abstract In the contemporary era, the global expansion of electrical grids is propelled by various renewable energy sources (RESs). Efficient integration of stochastic RESs and optimal power flow (OPF) management are critical for network optimization. This study introduces an innovative solution, the Gaussian Bare-Bones Levy Cheetah Optimizer (GBBLCO), addressing OPF challenges in power generation systems with stochastic RESs. The primary objective is to minimize the total operating costs of RESs, considering four functions: overall operating costs, voltage deviation management, emissions reduction, voltage stability index (VSI) and power loss mitigation. Additionally, a carbon tax is included in the objective function to reduce… More >
Open Access
ARTICLE
Nasser Sweilam1, Seham Al-Mekhlafi2,*, Aya Ahmed3, Ahoud Alsheri4, Emad Abo-Eldahab3
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.047896
（This article belongs to the Special Issue: Computer Modelling for Safer Built Environment and Smart Cities)
Abstract In this paper, two crossover hybrid variable-order derivatives of the cancer model are developed. Grünwald-Letnikov approximation is used to approximate the hybrid fractional and variable-order fractional operators. The existence, uniqueness, and stability of the proposed model are discussed. Adams Bashfourth’s fifth-step method with a hybrid variable-order fractional operator is developed to study the proposed models. Comparative studies with generalized fifth-order Runge-Kutta method are given. Numerical examples and comparative studies to verify the applicability of the used methods and to demonstrate the simplicity of these approximations are presented. We have showcased the efficiency of the proposed method and garnered robust empirical… More >
Open Access
ARTICLE
Haoyi Zhong, Yongjiang Zhao, Chang Gyoon Lim*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.049208
（This article belongs to the Special Issue: Emerging Artificial Intelligence Technologies and Applications)
Abstract This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery (LiB) time series data. As the energy sector increasingly focuses on integrating distributed energy resources, Virtual Power Plants (VPP) have become a vital new framework for energy management. LiBs are key in this context, owing to their high-efficiency energy storage capabilities essential for VPP operations. However, LiBs are prone to various abnormal states like overcharging, over-discharging, and internal short circuits, which impede power transmission efficiency. Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and irregular nature of LiB data.… More >
Open Access
ARTICLE
Ji Zhou1,2, Yijun Lu3, Qiong Tian1,2, Haichuan Liu3, Mahdi Hasanipanah4,5,*, Jiandong Huang3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048398
（This article belongs to the Special Issue: Meta-heuristic Algorithms in Materials Science and Engineering)
Abstract Blasting in surface mines aims to fragment rock masses to a proper size. However, flyrock is an undesirable
effect of blasting that can result in human injuries. In this study, support vector regression (SVR) is combined
with four algorithms: gravitational search algorithm (GSA), biogeography-based optimization (BBO), ant colony
optimization (ACO), and whale optimization algorithm (WOA) for predicting flyrock in two surface mines in Iran.
Additionally, three other methods, including artificial neural network (ANN), kernel extreme learning machine
(KELM), and general regression neural network (GRNN), are employed, and their performances are compared to
those of four hybrid SVR models. After modeling,… More >
Open Access
ARTICLE
So-Eun Jeon1, Ye-Sol Oh1, Yeon-Ji Lee1, Il-Gu Lee1,2,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.047239
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract With the advancement of wireless network technology, vast amounts of traffic have been generated, and malicious traffic attacks that threaten the network environment are becoming increasingly sophisticated. While signature-based detection methods, static analysis, and dynamic analysis techniques have been previously explored for malicious traffic detection, they have limitations in identifying diversified malware traffic patterns. Recent research has been focused on the application of machine learning to detect these patterns. However, applying machine learning to lightweight devices like IoT devices is challenging because of the high computational demands and complexity involved in the learning process. In this study, we examined methods… More >
Open Access
ARTICLE
Aadel M. Alatwi1,2, Abualkasim Bakeer3, Sherif A. Zaid1,*, Ibrahem E. Atawi1, Hani Albalawi1,4, Ahmed M. Kassem5
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.048521
（This article belongs to the Special Issue: Advanced Artificial Intelligence and Machine Learning Methods Applied to Energy Systems)
Abstract An autonomous microgrid that runs on renewable energy sources is presented in this article. It has a superconducting magnetic energy storage (SMES) device, wind energy-producing devices, and an energy storage battery. However, because such microgrids are nonlinear and the energy they create varies with time, controlling and managing the energy inside them is a difficult issue. Fractional-order proportional integral (FOPI) controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance. The suggested dedicated control for the SMES comprises two loops: the outer loop, which uses the FOPI to regulate the DC-link voltage, and the… More >
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