N
Na Deng
Researcher at Tianjin University
Publications - 61
Citations - 836
Na Deng is an academic researcher from Tianjin University. The author has contributed to research in topics: Heat pump & Waste heat. The author has an hindex of 14, co-authored 60 publications receiving 603 citations.
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Analysis of typical public building energy consumption in northern China
TL;DR: Wang et al. as mentioned in this paper investigated the characteristics of public building energy consumption, energy consumption of 119 public buildings in North China have been counted and discussed, and main factors influencing the energy consumption were analyzed by using eQUEST software.
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Experimental study on heat pipe assisted heat exchanger used for industrial waste heat recovery
TL;DR: In this article, the performance characteristics of a water-water heat pipe heat exchanger (HPHE) for a slag cooling process in steel industry were investigated experimentally by analyzing heat transfer rate, heat transfer coefficient, effectiveness, exergy efficiency and number of heat transfer units (NTU).
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Energy, exergy, economic, and environmental analysis of an integrated system of high-temperature heat pump and gas separation unit
Xiaoqiong Li,Yufeng Zhang,Lei Fang,Jin Zhendong,Zhang Yan,Yu Xiaohui,Xuelian Ma,Na Deng,Zhangxiang Wu +8 more
TL;DR: In this paper, a novel integrated system consisting of a high-temperature heat pump providing 120-130°C heat and a gas separation unit was developed to recover the industrial waste heat and replace the low-pressure steam used in traditional refinery process.
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Experimental analysis on performance of high temperature heat pump and desiccant wheel system
TL;DR: In this article, the problem of high energy consumption for regeneration of desiccant wheel in the rotary desiccants system, HTHP and DW system and corresponding air conditioning unit is built and tested in the extensive thermal hygrometric environment.
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Investigation of Support Vector Machine and Back Propagation Artificial Neural Network for performance prediction of the organic Rankine cycle system
TL;DR: SVM-LF and BP-ANN demonstrated better stability and higher accuracy for both two division methods and for different testing sets while SVM-RBF showed good results for random division method and disappointing results for blocked division method.