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energy characteristics of urban buildings: Assessment by machine learning

Building Simulation 2021年第1期14卷 179-193页

作者： Wei Tian Chuanqi Zhu Yu Sun Zhanyong Li Baoquan Yin Tianjin Key Laboratory of Integrated Design and On-line Monitoring for Light Industry&Food Machinery and Equipment College of Mechanical EngineeringTianjin University of Science and TechnologyTianjin300222China Tianjin International Joint Research and Development Center of Low-Carbon Green Process Equipment Tianjin300222China School of Architecture Harbin Institute of TechnologyHarbin150090China Tianjin Architecture Design Institute Tianjin300074China

Machine learning techniques have attracted more attention as advanced data analytics in building energy ***,most of previous studies are only focused on the prediction capability of machine learning algorithms to provide reliable energy estimation in *** learning also has great potentials to identify energy patterns for urban buildings except for model ***,this paper explores energy characteristic of London domestic properties using ten machine learning algorithms from three aspects:tuning process of learning model;variable importance;spatial analysis of model *** results indicate that the combination of these three aspects can provide insights on energy patterns for urban *** tuning process of these models indicates that gas use models should have more terms in comparison with electricity in London and the interaction terms should be considered in both gas and electricity *** rankings of important variables are very different for gas and electricity prediction in London residential buildings,which suggests that gas and electricity use are affected by different physical and social ***,the importance levels for these key variables are markedly different for gas and electricity *** are much more important variables for electricity use in comparison with gas use for the importance levels over *** areas with larger model discrepancies can be determined using the local spatial analysis based on these machine learning *** identified areas have significantly different energy patterns for gas and electricity *** research is required to understand these unusual patterns of energy use in these areas.

关键词： urban buildings energy characteristics machine learning variable importance spatial analysis

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Infrared radiation signature of exhaust plume from solid propellants with different energy characteristics

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Chinese Journal of Aeronautics 2013年第3期26卷 594-600页

作者： Wang Weichen Li Shipeng Zhang Qiao Wang Ningfei China Academy of Space Technology School of Aerospace Engineering Beijing Institute of Technology

The infrared radiation signature of the plume from solid propellants with different energy characteristics is not the same. Three kinds of double-base propellants of different energy characteristics are chosen to measure the infrared spectral radiance from 1000 cm 1 to 4500 cm 1 of their plumes. The radiative spectrum is obtained in the tests. The experimental results indicate that the infrared radiation of the plume is determined by the energy characteristics of the propellant. The radiative transfer calculation models of the exhaust plume for the solid propellants are established. By including the chemical reaction source term and the radiation source term into the energy equation, the plume field and the radiative transfer are solved in a coupled way. The calculated results are consistent with the experimental data, so the reliability of the models is confirmed. The temperature distribution and the extent of the afterburning of the plume are distinct for the propellants of different energy characteristics, therefore the plume radiation varies for different propellants. The temperature of the fluid cell in the plume will increase or decrease to some extent by the influence of the radiation term.

关键词： Coupled solution energy characteristics Exhaust plume Infrared radiation signature Solid propellant

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Analysis of energy characteristics in the Process of Freak Wave Generation

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China Ocean Engineering 2014年第2期28卷 193-205页

作者：胡金鹏张运秋 School of Civil Engineering and Transportation South China University of Technology Naval Architecture and Ocean Engineering R & D Center of Guangdong Province South China University of Technology Guangzhou Institute of energy Conversion Chinese Academy of Sciences Key Laboratory of Renewable energy and Gas Hydrate Chinese Academy of Sciences

The energy characteristics in the evolution of the wave train are investigated to understand the inherent cause of the freak wave generation. The Morlet wavelet spectrum method is employed to analyze the numerical, laboratory and field evolution data of this generation process. Their energy distributions and variations are discussed with consideration of corresponding surface elevations. Through comparing the energy characteristics of three cases, it is shown that the freak wave generation depends not only on the continuous transfer of wave train energy to a certain region where finally the maximum energy occurs, but also on the distinct shift of the converged energy to high-frequency components in a very short time. And the typical energy characteristics of freak waves are also given.

关键词： freak wave generation process wavelet spectrum energy characteristics

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Inter-stage performance and energy characteristics analysis of electric submersible pump based on entropy production theory

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Petroleum Science 2024年第2期21卷 1354-1368页

作者： Hui Wang Yang Yang Bin Xi Wei-Dong Shi Chuan Wang Lei-Lei Ji Xiang-Yu Song Zhao-Ming He College of Hydraulic Science and Engineering Yangzhou UniversityYangzhou225009JiangsuChina College of Electrical and Mechanical Engineering Nanchang Institute of TechnologyNanchang330044JiangxiChina College of Mechanical Engineering Nantong UniversityNantong226019JiangsuChina National Research Center of Pumps Jiangsu UniversityZhenjiang212013JiangsuChina Zhejiang Zhenxing Petrochemical Machinery Co. Ltd.Ruian325204ZhejiangChina Department of Mechanical Engineering of Texas Tech University Lubbock79411TXUSA

The electric submersible pump(ESP) is a crucial apparatus utilized for lifting in the oil extraction *** lifting capacity is enhanced by the multi-stage tandem structure, but variations in energy characteristics and internal flow across stages are also introduced. In this study, the inter-stage variability of energy characteristics in ESP hydraulic systems is investigated through entropy production(EP) analysis,which incorporates numerical simulations and experimental validation. The EP theory facilitates the quantification of energy loss in each computational subdomain at all ESP stages, establishing a correlation between microscopic flow structure and energy dissipation within the system. Furthermore, the underlying causes of inter-stage variability in ESP hydraulic systems are examined, and the advantages and disadvantages of applying the EP theory in this context are evaluated. Consistent energy characteristics within the ESP, aligned with the distribution of internal flow structure, are provided by the EP theory, as demonstrated by our results. The EP theory also enables the quantitative analysis of internal flow losses and complements existing performance analysis methods to map the internal flow structure to hydraulic losses. Nonetheless, an inconsistency between the energy characterization based on EP theory and the traditional efficiency index when reflecting inter-stage differences is identified. This inconsistency arises from the exclusive focus of the EP theory on flow losses within the flow field, disregarding the quantification of external energy input to the flow field. This study provides a reference for the optimization of EP theory in rotating machinery while deeply investigating the energy dissipation characteristics of multistage hydraulic system, which has certain theoretical and practical significance.

关键词： Electric submersible pump(ESP) Entropy production theory energy characteristics Inter-stage differences

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A Novel Hybrid Clustering Based Transmission Protocol for Wireless Body Area Networks

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Computers, Materials & Continua 2021年第11期69卷 2459-2473页

作者： Neelam Sharma Harshita Chadha Karan Singh B.M.Singh Nitish Pathak Research Scholar Computer Science and EngineeringUttarakhand Technical University(UTU)DehradunIndia Computer Science and Engineering Maharaja Agrasen Institute of TechnologyNew DelhiIndia School of Computer&Systems Sciences Jawaharlal Nehru University(JNU)DelhiIndia College of Engineering Roorkee UTUDehradunIndia Department of Information Technology KIET Group of InstitutionsGhaziabadIndia

Wireless sensor networks are a collection of intelligent sensor devices that are connected to one another and have the capability to exchange information packets amongst *** recent years,this field of research has become increasingly popular due to the host of useful applications it can potentially serve.A deep analysis of the concepts associated with this domain reveals that the two main problems that are to be tackled here are throughput enhancement and network security *** present article takes on one of these two issues namely the throughput *** the purpose of improving network productivity,a hybrid clustering based packet propagation protocol has been *** protocol makes use of not only clustering mechanisms of machine learning but also utilizes the traditional forwarding function approach to arrive at an optimum *** result of the simulation is a novel transmission protocol which significantly enhances network productivity and increases throughput value.

关键词： Forwarding function wireless sensor networks WSNs WBANs energy characteristics clustering hybrid mechanism dissipated energy network stability

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