Search Results - loading computing

Power selection of a static symmetrical device under dynamically changing load conditions by A. V. Petrov, V. E. Martusenko, R. A. Magayayev, V. E. Martusenko

“…Determination of the optimum value of the reactive elements power of the static symmetering device on the basis of the Steinmetz scheme at symmetrization of the variable load.Materials and methods. The research is based on a series of computational experiments allowing to form different load schedules with the possibility of selecting the optimal parameters of the symmetering device.Results and discussion. …”
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Dynamic Interaction Analysis of Long-Span Bridges Under Stochastic Traffic and Wind Loads by Ruien Wu, Yang Quan, Jia Wang, Le Li, Dingfu Ge, Siman Guo, Yaoyu Hu, Ping Xiang

“…An innovative method is proposed to analyze the coupled vibration between random traffic and large-span bridges under the combined action of wind loads. The dynamic behavior of bridges subjected to these multifactorial influences is investigated through a comprehensive bridge dynamics model. …”
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The Nonlinear Vibration Response of Umbrella-Shaped Membrane Structure Under Heavy Rainfall Loads by Zhongwei Luo, Zhoulian Zheng, Rui Yang, Peng Zhang

“…The equivalent uniform load of different rainfall intensity is determined by the theory of the stochastic process. …”
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Mitigating Load Imbalance and Enhancing Distribution Transformer Performance via Fuzzy Inference System by Althoff Hibban, Azriyenni Azhari Zakri, Dirman Hanafi, Boy Ihsan, Umair Ali

“…These findings confirm that fuzzy logic provides an effective, adaptable, and computationally efficient solution for balancing phase loads in distribution transformers, with strong potential for real-time intelligent grid applications.…”
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Dynamic Load Management in Modern Grid Systems Using an Intelligent SDN-Based Framework by Khawaja Tahir Mehmood, Muhammad Majid Hussain

“…For modern power plants to be dependable, safe, sustainable, and provide the highest operational efficiency (i.e., enhance dynamic load distribution with a faster response time at reduced reactive losses), there must be an intelligent dynamic load management system based on modern computational techniques to prevent overloading of power devices (i.e., alternators, transformers, etc.) in grid systems. …”
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Load identification method based on one class classification combined with fuzzy broad learning by Wang Yi, Wang Xiaoyang, Li Songnong, Chen Tao, Hou Xingzhe, Fu Xiuyuan

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Heterogeneous networking and simulation implementation for distributed “source-load-storage” resource collaborative interaction by Song Yanbin, Wang Wanqiao, Zhang Hui, Guan Luyao, Ding Huixia, Gao Kaiqiang, Yao Xianjiong, Xiang Jiani

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Entanglement of Microwave and Optical Fields Using Electrical Capacitor Loaded With Plasmonic Graphene Waveguide by Montasir Qasymeh, Hichem Eleuch

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Two-Stage Robust Optimization Considering the Uncertainty of Sources and Loads in Virtual Power Plants by Shixun Qi, Duo Li, Liyong Hou, Haili Wang, Li Xin, Yaojie Jin, Yuanji Cai, Mingfei Ban

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BASIC BIOMECHANICAL CHARACTERIZATION OF POLYURETHANE BASED ARTIFICIAL CANCELLOUS STRUCTURES by Jan Šleichrt, Daniel Kytýř, Kateřina Pithartová, Sascha Senck, David Fürst, Andreas Schrempf

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INFLUENCE OF PRINTING AND LOADING DIRECTION ON MECHANICAL RESPONSE IN 3D PRINTED MODELS OF HUMAN TRABECULAR BONE by Tomáš Doktor, Ivana Kumpová, Sebastian Wroński, Maciej Śniechowski, Jacek Tarasiuk, Giancarlo Forte, Daniel Kytýř

“…Sample of trabecular bone tissue was resected from human donor and 3D model was obtained by X-ray computed tomography. Then a series of cubical samples was prepared by additive manufacturing technique and tested by uniaxial compression loading mode. …”
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Development of an efficient system for predicting CRSS ratios of HCP polycrystalline metals using uniaxial loading conditions by Sotaro MIKAMI, Yoshiki KAWANO, Kenji IWADATE

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Parallel Agent-Based Framework for Analyzing Urban Agricultural Supply Chains by Manuel Ignacio Manríquez, Veronica Gil-Costa, Mauricio Marin

“…To efficiently handle the computational demands of large-scale scenarios, we adopt an optimistic approximate parallel execution strategy. …”
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Parallel Simulation Multi-Sample Task Scheduling Approach Based on Deep Reinforcement Learning in Cloud Computing Environment by Yuhao Xiao, Yping Yao, Feng Zhu

“…Therefore, herein, a parallel simulation multi-sample task scheduling method based on deep reinforcement learning in a cloud computing environment is proposed. The method collects cluster load information and simulation application information as state inputs in the cloud environment, designs a multi-objective reward function to balance the cost and execution efficiency, and uses deep Q-networks (DQNs) to train agents for intelligent scheduling of multi-sample parallel simulation tasks. …”
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An analysis of the effect between the heat index and Long Short-Term Memory model to electricity load forecasting by Nguyen Thi Ngoc Anh, Vu Viet Hoang, Do Thi Thanh Chau, Bui Duy Linh, Nguyen Duc Huy

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Experiments and Computational Research of Biomass Pyrolysis in a Cylindrical Reactor by A. V. Mitrofanov, V. E. Mizonov, S. V. Vasilevich, M. V. Malko

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DYNAMIC METHOD OF LOAD BALANCING OF DATA CENTERS TAKING INTO ACCOUNT THE FRACTAL PROPERTIES OF NETWORK TRAFFIC by G. I. Linets, N. Y. Bratchenko, V. P. Mochalov, I. S. Palkanov

“…The practical significance of the proposed research results lies in the substantiation and development of a method for dynamic distribution and load balancing in cloud computing, taking into account the fractal properties of network traffic. …”
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AI-Driven Framework for Secure and Efficient Load Management in Multi-Station EV Charging Networks by Md Sabbir Hossen, Md Tanjil Sarker, Marran Al Qwaid, Gobbi Ramasamy, Ngu Eng Eng

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Asymptotic analysis of multiserver retrial queueing system with \(\pi\)-defeat of negative arrivals under heavy load by Natalya P. Meloshnikova, Ekaterina A. Fedorova

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Application of the Fuzzy Computational Intelligence in Power Quality Data Management by Hoda Farag

“…This Paper addresses the perfect load management using the computational techniques by analyzing the data of the system taking into account the density of the  feeding nodes and its distribution  also the classification of major Power quality degradations such as power factor and harmonics in the System and The methodology will be illustrated, simulated and evaluated using the fuzzy technique clustering the data and on an Artificial Neural Network (ANN) to achieve the optimum utilization of the energy loads and perfect load management and optimization. …”
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