Entransy—A physical quantity describing heat transfer ability

By Zengyuan Guo, Hongye Zhu, Xin-gang Liang. 2007

819 citations recorded by the source corpus.

Subfields: Building and Construction, Mechanical Engineering, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/9d53a555bf31233ae9f1e516a728296e03fec4ca

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Qun Chen

In Mechanical Engineering

1. Qun Chen
2. Wen-Quan Tao
3. Zhichun Liu
4. Zengyuan Guo
5. Wei David Liu
6. Xiaoyu Zhang
7. Xiaobin Liu
8. Kai Wang

In Statistical and Nonlinear Physics

1. Qun Chen
2. Xiaobing Luo
3. Sheng Liu
4. Kai Wang
5. Run Hu
6. Zengyuan Guo
7. Xiaobin Liu
8. Wen-Quan Tao

Citations in the corpus

• Optimization principles for convective heat transfer (2009, background): “[34] proposed the entransy dissipation extremum principle for heattransfer optimization: the extremum entransy dissipation corresponds to the minimum transfer resistant for a given heat-transfer problem.”
• Effectiveness–thermal resistance method for heat exchanger design and analysis (2010, background): “In view of this fact, an appropriate quantity, Gvh has been defined [17] as :”
• Numerical studies on heat transfer and flow characteristics for laminar flow in a tube with multiple regularly spaced twisted tapes (2012, background): “[32,33] also introduced a new quantity that corresponds to electrical potential energy in a capacitor based on the analogy between electrical and thermal systems.”
• Entransy dissipation-based thermal resistance method for heat exchanger performance design and optimization (2013, background): “[17] introduced the physical quantity of entransy to describe the heat transfer ability of an object, and then use the entransy dissipation to measure the loss of such ability due to the irreversibility of heat transfer.”
• Heat and fluid flow in high-power LED packaging and applications (2016, methodology): “Changing fin parameters is the most effective way to optimize fin performance, and many methods have been developed, such as the least energy method [213], the least entropy generation method [214-219], the minimum entransy dissipation-based thermal resistance principle [220-224], etc.”