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  • Open Access

    ARTICLE

    Optimization of Chiller Loading Problem Using Improved Golden Jackal Optimization Algorithm Leads to Reduction in Energy Consumption

    Na Dong1,*, Xiao Yang2, Nasser Yousefi3,4,*

    Energy Engineering, Vol.120, No.11, pp. 2565-2583, 2023, DOI:10.32604/ee.2023.029862

    Abstract This paper proposes a modified golden jackal optimization (IGJO) algorithm to solve the OCL (which stands for optimal cooling load) problem to minimize energy consumption. In this algorithm, many tools have been developed, such as numerical visualization, local field method, competitive selection method, and iterative strategy. The IGJO algorithm is used to improve the research capabilities of the algorithm in terms of global tuning and rotation speed. In order to fully utilize the effectiveness of the proposed algorithm, three famous examples of OCL problems in basic ventilation systems were studied and compared with some previously published works. The results show… More >

  • Open Access

    ARTICLE

    A Calculation Method of Double Strength Reduction for Layered Slope Based on the Reduction of Water Content Intensity

    Feng Shen1,*, Yang Zhao1, Bingyi Li1, Kai Wu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 221-243, 2024, DOI:10.32604/cmes.2023.029159

    Abstract The calculation of the factor of safety (FOS) is an important means of slope evaluation. This paper proposed an improved double strength reduction method (DRM) to analyze the safety of layered slopes. The physical properties of different soil layers of the slopes are different, so the single coefficient strength reduction method (SRM) is not enough to reflect the actual critical state of the slopes. Considering that the water content of the soil in the natural state is the main factor for the strength of the soil, the attenuation law of shear strength of clayey soil changing with water content is… More >

  • Open Access

    ARTICLE

    Assessment of Nanoparticle-Enriched Solvents for Oil Recovery Enhancement

    Muayad M. Hasan1,*, Firas K. Al-Zuhairi2, Anfal H. Sadeq1, Rana A. Azeez1

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.11, pp. 2827-2835, 2023, DOI:10.32604/fdmp.2023.027746

    Abstract Solvents are generally used to reduce the viscosity of heavy crude oil and ultimately enhance oil recovery. Recently, a new method has been introduced where nanoparticles (NPs) are exploited to induce enhanced oil recovery owing to their ability to improve the mobility ratio, dampen the interfacial tension, and alter rock wettability. This study investigated the integration of nano-alumina (Al2O3) NPs with an n-hexane solvent. In particular, a Brookfield viscometer has been used to measure the crude oil viscosity and it has been found that NPs can effectively lead to a significant decrease in the overall oil viscosity (70 cp using… More >

  • Open Access

    ARTICLE

    Restructuring Tilth Layers Can Change the Microbial Community Structure and Affect the Occurrence of Verticillium Wilt in Cotton Field

    Ming Dong#, Yan Wang#, Shulin Wang, Guoyi Feng, Qian Zhang, Yongzeng Lin, Qinglong Liang, Yongqiang Wang*, Hong Qi*

    Phyton-International Journal of Experimental Botany, Vol.92, No.10, pp. 2841-2860, 2023, DOI:10.32604/phyton.2023.030465

    Abstract Restructuring tilth layers (RTL) is a tillage method that exchanges the 0–20 and 20–40 cm soil layers that can be applied during cotton cultivation to increase cotton yield, eliminate weeds and alleviate severe disease, including Verticillium wilt. However, the mechanism by which RTL inhibits Verticillium wilt is unclear. Therefore, we investigated the distribution of microbial communities after rotary tillage (CK) and RTL treatments to identify the reasons for the reduction of Verticillium wilt in cotton fields subjected to RTL. Illumina high-throughput sequencing was used to sequence the bacterial and fungal genes. The disease incidence and severity of Verticillium wilt decreased… More >

  • Open Access

    PROCEEDINGS

    Broadband Electromagnetic Scattering Analysis with Isogeometric Boundary Element Method Accelerated by Frequency-Decoupling and Model Order Reduction Techniques

    Yujing Ma1, Zhongwang Wang2, Xiaohui Yuan1, Leilei Chen2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-2, 2023, DOI:10.32604/icces.2023.09662

    Abstract The paper presents a novel fast calculation method for broadband Electromagnetic Scattering analysis. In this work, the isogeometric boundary element method is used to solve Helmholtz equations for the electromagnetic scattering problems. The non-uniform rational B-splines are employed to construct structural geometries and discretize electric and magnetic field integral equations [1,2]. To avoid timeconsuming multi-frequency calculations, the series expansion method is used to decouple the frequencydependent terms from the integrand in the boundary element method [3,4]. The second-order Arnoldi (SOAR) method is applied to construct a reduced-order model that retains the essential structures and key properties of the original model… More >

  • Open Access

    ARTICLE

    A Noise Reduction Method for Multiple Signals Combining Computed Order Tracking Based on Chirplet Path Pursuit and Distributed Compressed Sensing

    Guangfei Jia*, Fengwei Guo, Zhe Wu, Suxiao Cui, Jiajun Yang

    Structural Durability & Health Monitoring, Vol.17, No.5, pp. 383-405, 2023, DOI:10.32604/sdhm.2023.026885

    Abstract With the development of multi-signal monitoring technology, the research on multiple signal analysis and processing has become a hot subject. Mechanical equipment often works under variable working conditions, and the acquired vibration signals are often non-stationary and nonlinear, which are difficult to be processed by traditional analysis methods. In order to solve the noise reduction problem of multiple signals under variable speed, a COT-DCS method combining the Computed Order Tracking (COT) based on Chirplet Path Pursuit (CPP) and Distributed Compressed Sensing (DCS) is proposed. Firstly, the instantaneous frequency (IF) is extracted by CPP, and the speed is obtained by fitting.… More > Graphic Abstract

    A Noise Reduction Method for Multiple Signals Combining Computed Order Tracking Based on Chirplet Path Pursuit and Distributed Compressed Sensing

  • Open Access

    ARTICLE

    A Method of Evaluating the Effectiveness of a Hydraulic Oscillator in Horizontal Wells

    Zhen Zhong*, Yadong Li, Yuxuan Zhao, Pengfei Ju

    Sound & Vibration, Vol.57, pp. 15-27, 2023, DOI:10.32604/sv.2023.041954

    Abstract Bent-housing motor is the most widely used directional drilling tool, but it often encounters the problem of high friction when sliding drilling in horizontal wells. In this paper, a mathematical model is proposed to simulate slide drilling with a friction reduction tool of axial vibration. A term called dynamic effective tractoring force (DETF) is defined and used to evaluate friction reduction effectiveness. The factors influencing the DETF are studied, and the tool placement optimization problem is investigated. The study finds that the drilling rate of penetration (ROP) can lower the DETF but does not change the trend of the DETF… More >

  • Open Access

    ARTICLE

    Preliminary Study on the Treatment Efficiency of Pasteurized Lime Thermal Alkaline Hydrolysis for Excess Activated Sludge and Reduction of Tetracycline Resistance Genes

    Maoxia Chen1,2,*, Qixuan Zhou1, Jiayue Zhang1, Jiaoyang Li1, Wei Zhang1, Huan Liu1

    Journal of Renewable Materials, Vol.11, No.10, pp. 3711-3723, 2023, DOI:10.32604/jrm.2023.027826

    Abstract Thermal alkaline hydrolysis is a common pretreatment method for the utilization of excess activated sludge (EAS). Owing to strict environment laws and need for better energy utilization, new methods were developed in this study to improve the efficiency of pretreatment method. Direct thermal hydrolysis (TH), pasteurized thermal hydrolysis (PTH), and alkaline pasteurized thermal hydrolysis (PTH + CaO and PTH + NaOH) methods were used to treat EAS. Each method was compared and analyzed in terms of dissolution in ammonium nitrogen (NH4 + -N) and soluble COD (SCOD) in EAS. Furthermore, the removal of tetracycline resistance genes (TRGs) and class 1… More >

  • Open Access

    ARTICLE

    Dimensionality Reduction Using Optimized Self-Organized Map Technique for Hyperspectral Image Classification

    S. Srinivasan, K. Rajakumar*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2481-2496, 2023, DOI:10.32604/csse.2023.040817

    Abstract

    The high dimensionalhyperspectral image classification is a challenging task due to the spectral feature vectors. The high correlation between these features and the noises greatly affects the classification performances. To overcome this, dimensionality reduction techniques are widely used. Traditional image processing applications recently propose numerous deep learning models. However, in hyperspectral image classification, the features of deep learning models are less explored. Thus, for efficient hyperspectral image classification, a depth-wise convolutional neural network is presented in this research work. To handle the dimensionality issue in the classification process, an optimized self-organized map model is employed using a water strider optimization… More >

  • Open Access

    REVIEW

    Deep Learning Applied to Computational Mechanics: A Comprehensive Review, State of the Art, and the Classics

    Loc Vu-Quoc1,*, Alexander Humer2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1069-1343, 2023, DOI:10.32604/cmes.2023.028130

    Abstract Three recent breakthroughs due to AI in arts and science serve as motivation: An award winning digital image, protein folding, fast matrix multiplication. Many recent developments in artificial neural networks, particularly deep learning (DL), applied and relevant to computational mechanics (solid, fluids, finite-element technology) are reviewed in detail. Both hybrid and pure machine learning (ML) methods are discussed. Hybrid methods combine traditional PDE discretizations with ML methods either (1) to help model complex nonlinear constitutive relations, (2) to nonlinearly reduce the model order for efficient simulation (turbulence), or (3) to accelerate the simulation by predicting certain components in the traditional… More >

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