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Relevant bibliographies by topics / CRITICAL MACHINE ENERGY

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Journal articles

Academic literature on the topic 'CRITICAL MACHINE ENERGY'

Author: Grafiati

Published: 11 September 2023

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Journal articles on the topic "CRITICAL MACHINE ENERGY"

1

Chen, Chi, Yunxing Zuo, Weike Ye, Xiangguo Li, Zhi Deng, and Shyue Ping Ong. "A Critical Review of Machine Learning of Energy Materials." Advanced Energy Materials 10, no. 8 (2020): 1903242. http://dx.doi.org/10.1002/aenm.201903242.

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2

Ohtani, Hisashi. "Development of Energy-Saving Machine Tool." International Journal of Automation Technology 11, no. 4 (2017): 608–14. http://dx.doi.org/10.20965/ijat.2017.p0608.

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Environmental measures are urgently required to realize a society with a low environmental load. In response, various undertakings are being carried out in the field of machine tools, which is most critical in terms of requirement of energy-saving measures. The energy consumed when a machine tool is used to machine can be broadly divided into three categories: the “standby energy” to maintain the electrical devices operational when the machine is not operational; the “steady-state energy,” which is the fixed amount of energy required when the machine is in operation; and the “dynamic energy,”

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3

Fujishima, Makoto, Hiroshi Shimanoe, and Masahiko Mori. "Reducing the Energy Consumption of Machine Tools." International Journal of Automation Technology 11, no. 4 (2017): 601–7. http://dx.doi.org/10.20965/ijat.2017.p0601.

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Global warming is one of the most important environmental issues that the world faces today. Reducing energy consumption is critical in industrial environments. Machine tools have some of the highest energy consumption rates of all the equipment in factories. This makes it important to reduce machine tool energy consumption to protect the global environment. Some effective ways of reducing the energy consumption of machine tools are by reducing the required energy, shutting down the power to standby mode, and shortening cycle times. This paper introduces several approaches to the reduction of

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4

Yuan and Sun. "Server Consolidation Based on Culture Multiple-Ant-Colony Algorithm in Cloud Computing." Sensors 19, no. 12 (2019): 2724. http://dx.doi.org/10.3390/s19122724.

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High-energy consumption in data centers has become a critical issue. The dynamic server consolidation has significant effects on saving energy of a data center. An effective way to consolidate virtual machines is to migrate virtual machines in real time so that some light load physical machines can be turned off or switched to low-power mode. The present challenge is to reduce the energy consumption of cloud data centers. In this paper, for the first time, a server consolidation algorithm based on the culture multiple-ant-colony algorithm was proposed for dynamic execution of virtual machine m

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5

Alghamdi, Noof Awad, Israa Mohammed Budayr, Samar Mohammed Aljehani, and Majed Mohammed Aborokbah. "A Scheme for Predicting Energy Consumption in Smart Cities Using Machine Learning." Webology 19, no. 1 (2022): 3481–99. http://dx.doi.org/10.14704/web/v19i1/web19230.

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Fluctuating result on weather condition throughout several decades became a global concern due to the direct or indirect effect on energy consumption, and that was well-defined in several sector. Research investigates the use of technology and the speed of obtaining information ، which helps in decision-making. This paper Emphasize the role of data science and their application to monitoring energy consumption, also, explain the importance used and challenges of Internet of Things (IoT). Thus, there is a global concern on data transformation from IoT devices when taking into account deferent w

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6

Kandil, Abdelrahman, Samir Khaled, and Taher Elfakharany. "Prediction of the equivalent circulation density using machine learning algorithms based on real-time data." AIMS Energy 11, no. 3 (2023): 425–53. http://dx.doi.org/10.3934/energy.2023023.

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<abstract> <p>Equivalent circulation density (ECD) is one of the most important parameters that should be considered while designing drilling programs. With increasing the wells' deep, offshore hydrocarbon extraction, the costly daily rate of downhole measurements, operating restrictions, and the fluctuations in the global market prices, it is necessary to reduce the non-productive time and costs associated with hole problems resulting from ignoring and incorrect evaluation of ECD. Therefore, optimizing ECD and selecting the best drilling parameters are curial tasks in such operati

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7

RASTGOUFARD, P., and R. A. SCHLUETER. "APPLICATION OF CRITICAL MACHINE ENERGY FUNCTION IN POWER SYSTEM TRANSIENT STABILITY ANALYSIS." Electric Machines & Power Systems 16, no. 5 (1989): 343–61. http://dx.doi.org/10.1080/07313568908909392.

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8

Vijayapakavan, P., D. S. Robinson Smart, Kurinjimalar Ramu, and M. Ramachandran. "Superconducting Electromagnetic Launch Machine System for Aerospace Applications." Journal on Applied and Chemical Physics 2, no. 1 (2023): 40–47. http://dx.doi.org/10.46632/jacp/2/1/5.

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The aerospace industry is constantly experimenting with innovative technologies to improve efficiency, effectiveness and sustainability. The use of superconducting machines emerged as a promising solution to address the growing demands of Aerospace applications. Superconducting machines offer significant advantages such as higher power density, reduced weight and improved efficiency compared to conventional electrical machines. However, efficient cooling methods are critical to maintain superconducting materials at low-temperature operating conditions. This abstract provides a comprehensive ov

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9

Cristina Castejon, Cristina, Marıa Jesus Gomez, Juan Carlos Garcia-Prada, and Eduardo Corral. "Energy Distribution Analysis Regarding the Crack Size in a Rotating Shaft." Volume 24, No 3, September 2019 24, no. 3 (2019): 418–25. http://dx.doi.org/10.20855/ijav.2019.24.31190.

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Maintenance is critical to avoid catastrophic failures in rotating machinery, and the detection of cracks plays a critical role because they can originate failures with costly processes of reparation, especially in shafts. Vibration signals are widely used in machine monitoring and fault diagnostics. The most critical issue in machine monitoring is the suitable selection of the vibration parameters that represent the condition of the machine. Discrete Wavelet Transform, and one of its recursive forms, called Wavelet Packet Transform, provide a high potential for pattern extraction. Several fac

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10

Trontl, Krešimir, Dubravko Pevec, and Tomislav Šmuc. "Machine Learning of the Reactor Core Loading Pattern Critical Parameters." Science and Technology of Nuclear Installations 2008 (2008): 1–6. http://dx.doi.org/10.1155/2008/695153.

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The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear model

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