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Search Results (22)
  • Open Access

    REVIEW

    CHARACTERISTICS OF MICROLAYER FORMATION AND HEAT TRANSFER IN MINI/MICROCHANNEL BOILING SYSTEMS: A REVIEW

    Yaohua Zhanga,*, Yoshio Utakab

    Frontiers in Heat and Mass Transfer, Vol.3, No.1, pp. 1-12, 2012, DOI:10.5098/hmt.v3.1.3003

    Abstract This paper reviews recent research on microlayer formed by confined vapor bubbles during boiling in mini/microchannels. Experimental measurements, simulations and theoretical studies are described and compared. As a reference to clarify the mechanism for the formation of a microlayer, Taylor flow (i.e. elongated bubble flow in mini/micro circular tubes under adiabatic conditions and at Re << 1) and elongated bubble flow at high velocity, with consideration of the influence of inertia, are also reviewed. Compared to the steady adiabatic conditions, one of the distinct points for the boiling condition is that the bubble grows exponentially due to rapid evaporation of… More >

  • Open Access

    PROCEEDINGS

    How Travelling Wavelength Affects Hydrodynamic Performance of Two Linear-Accelerating Mirror-Symmetric Fish-Like Swimmers

    Zhonglu Lin1,2, Dongfang Liang2, Yu Zhang1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-9, 2023, DOI:10.32604/icces.2023.010442

    Abstract Fish schools are capable of simultaneous linear acceleration. To reveal the underlying hydrodynamic mechanism, we numerically investigate how Reynolds number Re = 1000−2000, Strouhal number St = 0.2−0.7 and wavelength λ = 0.5−2 affects the mean net thrust of two side-by-side NACA0012 hydrofoils undulating in anti-phase. In total, 550 cases are simulated using immersed boundary method. The thrust is strengthened by wavelength and Strouhal number, yet only slightly by the Reynolds number. We apply the symbolic regression algorithm to formulate this relationship as a high-level summary. More >

  • Open Access

    ARTICLE

    Adaptive Multi-Updating Strategy Based Particle Swarm Optimization

    Dongping Tian1,*, Bingchun Li1, Jing Liu1, Chen Liu1, Ling Yuan1, Zhongzhi Shi2

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2783-2807, 2023, DOI:10.32604/iasc.2023.039531

    Abstract Particle swarm optimization (PSO) is a stochastic computation technique that has become an increasingly important branch of swarm intelligence optimization. However, like other evolutionary algorithms, PSO also suffers from premature convergence and entrapment into local optima in dealing with complex multimodal problems. Thus this paper puts forward an adaptive multi-updating strategy based particle swarm optimization (abbreviated as AMS-PSO). To start with, the chaotic sequence is employed to generate high-quality initial particles to accelerate the convergence rate of the AMS-PSO. Subsequently, according to the current iteration, different update schemes are used to regulate the particle search process at different evolution stages.… More >

  • Open Access

    ARTICLE

    Ensemble 1D DenseNet Damage Identification Method Based on Vibration Acceleration

    Chun Sha1,*, Chaohui Yue2, Wenchen Wang3

    Structural Durability & Health Monitoring, Vol.17, No.5, pp. 369-381, 2023, DOI:10.32604/sdhm.2023.027948

    Abstract Convolution neural networks in deep learning can solve the problem of damage identification based on vibration acceleration. By combining multiple 1D DenseNet submodels, a new ensemble learning method is proposed to improve identification accuracy. 1D DenseNet is built using standard 1D CNN and DenseNet basic blocks, and the acceleration data obtained from multiple sampling points is brought into the 1D DenseNet training to generate submodels after offset sampling. When using submodels for damage identification, the voting method ideas in ensemble learning are used to vote on the results of each submodel, and then vote centrally. Finally, the cantilever damage problem… More >

  • Open Access

    PROCEEDINGS

    Efficient Multigrid Method Based on Adaptive Weighted Jacobi in Isogeometric Analysis

    ShiJie Luo1, Feng Yang1, Yingjun Wang1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09474

    Abstract The isogeometric analysis Method (IGA) is an efficient and accurate engineering analysis method. However, in order to obtain accurate analysis results, the grid must be refined, and the increase of the number of refinements will lead to large-scale equations, which will increase the computational cost. Compared with the traditional equation solvers such as preconditioned conjugate gradient method (PCG), generalized minimal residual (GMRES), the advantage of multigrid method is that the convergence rate is independent of grid scale when solving large-scale equations. This paper presents an adaptive weighted Jacobi method to improve the convergence of geometric multigrid method to efficiently solve… More >

  • Open Access

    PROCEEDINGS

    An Acceleration Scheme for the Phase Field Fatigue Fracture Simulation with a Concurrent Temporal Homogenization Method

    Shuo Yang1, Yongxing Shen1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09207

    Abstract Fatigue refers to repeated cyclic loading well below the ultimate failure stress of the structure. It accounts for most mechanical failures, and thus deserves serious consideration in engineering practice. Phase field approach is a powerful tool for fracture simulation, which tracks arbitrary and complicated crack paths without extra criterion. This approach has been widely applied to various cracking problems, such as shell fracture, beam fracture , etc. The phase field approach for fracture has been adapted for fatigue fracture in recent years. Due to the mesh requirement of the phase field approach and the large amount of load steps of… More >

  • Open Access

    ARTICLE

    Wireless Self-Powered Vibration Sensor System for Intelligent Spindle Monitoring

    Lei Yu1, Hongjun Wang1,*, Yubin Yue1, Shucong Liu1, Xiangxiang Mao2, Fengshou Gu3

    Structural Durability & Health Monitoring, Vol.17, No.4, pp. 315-336, 2023, DOI:10.32604/sdhm.2022.024899

    Abstract In recent years, high-end equipment is widely used in industry and the accuracy requirements of the equipment have been risen year by year. During the machining process, the high-end equipment failure may have a great impact on the product quality. It is necessary to monitor the status of equipment and to predict fault diagnosis. At present, most of the condition monitoring devices for mechanical equipment have problems of large size, low precision and low energy utilization. A wireless self-powered intelligent spindle vibration acceleration sensor system based on piezoelectric energy harvesting is proposed. Based on rotor sensing technology, a sensor is… More >

  • Open Access

    ARTICLE

    Designing Adaptive Multiple Dependent State Sampling Plan for Accelerated Life Tests

    Pramote Charongrattanasakul1, Wimonmas Bamrungsetthapong2,*, Poom Kumam3

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1631-1651, 2023, DOI:10.32604/csse.2023.036179

    Abstract A novel adaptive multiple dependent state sampling plan (AMDSSP) was designed to inspect products from a continuous manufacturing process under the accelerated life test (ALT) using both double sampling plan (DSP) and multiple dependent state sampling plan (MDSSP) concepts. Under accelerated conditions, the lifetime of a product follows the Weibull distribution with a known shape parameter, while the scale parameter can be determined using the acceleration factor (AF). The Arrhenius model is used to estimate AF when the damaging process is temperature-sensitive. An economic design of the proposed sampling plan was also considered for the ALT. A genetic algorithm with… More >

  • Open Access

    REVIEW

    Edge Intelligence with Distributed Processing of DNNs: A Survey

    Sizhe Tang1, Mengmeng Cui1,*, Lianyong Qi2, Xiaolong Xu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 5-42, 2023, DOI:10.32604/cmes.2023.023684

    Abstract With the rapid development of deep learning, the size of data sets and deep neural networks (DNNs) models are also booming. As a result, the intolerable long time for models’ training or inference with conventional strategies can not meet the satisfaction of modern tasks gradually. Moreover, devices stay idle in the scenario of edge computing (EC), which presents a waste of resources since they can share the pressure of the busy devices but they do not. To address the problem, the strategy leveraging distributed processing has been applied to load computation tasks from a single processor to a group of… More >

  • Open Access

    ARTICLE

    Hybrid Global Optimization Algorithm for Feature Selection

    Ahmad Taher Azar1,2,*, Zafar Iqbal Khan2, Syed Umar Amin2, Khaled M. Fouad1,3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2021-2037, 2023, DOI:10.32604/cmc.2023.032183

    Abstract This paper proposes Parallelized Linear Time-Variant Acceleration Coefficients and Inertial Weight of Particle Swarm Optimization algorithm (PLTVACIW-PSO). Its designed has introduced the benefits of Parallel computing into the combined power of TVAC (Time-Variant Acceleration Coefficients) and IW (Inertial Weight). Proposed algorithm has been tested against linear, non-linear, traditional, and multiswarm based optimization algorithms. An experimental study is performed in two stages to assess the proposed PLTVACIW-PSO. Phase I uses 12 recognized Standard Benchmarks methods to evaluate the comparative performance of the proposed PLTVACIW-PSO vs. IW based Particle Swarm Optimization (PSO) algorithms, TVAC based PSO algorithms, traditional PSO, Genetic algorithms (GA),… More >

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