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Processes
Special Issues
Thermophysical Properties of Working Mediums and Their Application in Thermodynamic...
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Thermophysical Properties of Working Mediums and Their Application in Thermodynamic Cycles

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 7638

Special Issue Editors

Dr. Yu Liu

E-Mail Website
Guest Editor
School of Energy and Power Engineering, Chongqing University, Chongqing 400030, China
Interests: machine learning; thermophysical property; refrigerants
Dr. Ian H. Bell

E-Mail Website
Guest Editor
Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, CO 80305, USA
Interests: computational routines and tools used for the development and application of thermodynamic mixture models
Prof. Dr. Giovanni Di Nicola

E-Mail Website
Guest Editor
Dipartimento di Energetica, Università Politecnicadelle Marche, Via BrecceBianche, 60100 Ancona, Italy
Interests: PVT (pressure–volume–temperature) properties; properties of the triple point; study and development of models for the calculation of thermophysical properties
Dr. Xiangyang Liu

E-Mail Website
Guest Editor
MOE Key Laboratory of Thermo-Fluid Science and Engineering, Xi’an Jiaotong University, Xi’an 710049, Shaanxi, China
Interests: process engineering; computer modeling; thermodynamics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Qibin Li

E-Mail Website
Guest Editor
Key Laboratory of Low-grade Energy Utilization Technologies and Systems, Ministry of Education, School of Energy and Power Engineering, Chongqing University, Chongqing 400030, China
Interests: thermodynamics; working fluid; energy storage
Special Issues, Collections and Topics in MDPI journals
Dr. Piotr Lampart

E-Mail Website
Guest Editor
Institute of Fluid Flow Machinery, Polish Academy of Sciences, 80-231 Gdansk, Poland
Interests: turbulence modeling; fluid mechanics; CFD simulation

Special Issue Information

Dear Colleagues,

This Special Issue of Processes concerns publications of research related to the application of studying thermophysical properties of various working mediums (including but are not limited to fuels, biodiesel, ionic liquids, lubricants, polymer solutions, melts, ferrofluids, molten metals and salts, water solutions, and refrigerants) and relevant applications in thermodynamic cycles. It includes research on the experimental measurement or computational simulation of thermophysical properties. In addition, works investigating the potential of novel working fluids for their use in thermodynamic cycles such as refrigeration cycles, organic Rankine cycle (ORC), etc. are of interest.

Topics include but are not limited to:

(1) Supplementing the thermophysical property data of fluids, especially for mixtures of working mediums. The approaches include both laboratory measurements and computer experiments (from quantum chemistry or from molecular simulations based on forced fields);

(2) Exploring a new highly efficient power cycle layout of low- and medium-temperature heat sources;

(3) Performance evaluation of key components and thermodynamic cycles.

Dr. Yu Liu
Dr. Ian H. Bell
Prof. Dr. Giovanni Di Nicola
Dr. Xiangyang Liu
Dr. Qibin Li
Dr. Piotr Lampart
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning
  • thermophysical property
  • fluids
  • nanofluids
  • artifical neural network
  • thermal conductivity
  • heat capacity
  • fuels
  • biodiesel
  • water solutions
  • refrigerants
  • surface tension
  • viscosity
  • solubility
  • density
  • PVT property
  • critical parameters
  • refrigeration cycle
  • power cycle

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

12 pages, 3291 KiB  
Article
Microscopic Mechanism on the Heat Conduction of Organic Liquids: A Molecular Dynamics Study
by Jing Fan, Hao Wang, Fenhong Song, Yandong Hou and Shuangshuo Liu
Processes 2022, 10(10), 1987; https://doi.org/10.3390/pr10101987 - 1 Oct 2022
Viewed by 1274
Abstract
The research on energy conversion and transportation of fuels at a microscopic level is of great significance to the development of industry. As a new alternative fuel, alcohols are widely used in industry and daily life, so it is necessary to investigate the [...] Read more.
The research on energy conversion and transportation of fuels at a microscopic level is of great significance to the development of industry. As a new alternative fuel, alcohols are widely used in industry and daily life, so it is necessary to investigate the thermophysical properties of them. In this work, seven species of pure liquid alcohols were performed to investigate the microscopic mechanisms of thermal energy transfer by non-equilibrium molecular dynamic (NEMD) method. Firstly, the thermal conductivity of alcohols was calculated and was found to be consistent with the experimental data. Then, the influence of temperature on energy transfer is investigated, the results show that the contribution of convection energy transfer increases and both the inter- and intramolecular terms decrease with the increase of temperature. Finally, the influence of molecular length on energy transfer was investigated at the same temperature, and it is concluded that the contribution of the convective term decreases and the interactive term increases to the total heat flux with increasing the length of the chain. It is worth mentioning that the contribution of intramolecular energy transfer gradually becomes a dominant part of the total energy transfer as the linear chain molecule increases to a certain length and the number of carbon atoms at the intersection point of inter- and intramolecular energy transfer is similar to the turning point of thermal conductivity. Full article
(This article belongs to the Special Issue Thermophysical Properties of Working Mediums and Their Application in Thermodynamic Cycles)
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11 pages, 2479 KiB  
Article
Adsorption and Self-Diffusion of R32/R1234yf in MOF-200 Nanoparticles by Molecular Dynamics Simulation
by Biyu Jing, Di Xia and Guoqiang Wang
Processes 2022, 10(9), 1714; https://doi.org/10.3390/pr10091714 - 28 Aug 2022
Cited by 2 | Viewed by 1951
Abstract
The thermophysical properties of a refrigerant can be modified via adding metal organic frameworks (MOF) to it. Understanding the adsorption–diffusion process of the mixture in MOFs at the molecular level is important to further improve the efficiency of the organic Rankine cycle. The [...] Read more.
The thermophysical properties of a refrigerant can be modified via adding metal organic frameworks (MOF) to it. Understanding the adsorption–diffusion process of the mixture in MOFs at the molecular level is important to further improve the efficiency of the organic Rankine cycle. The adsorption and diffusion of R32/R1234yf in MOF-200 was investigated by molecular dynamics simulation in the present work. The results show that the number of adsorbed molecules of R32 in MOF-200 per unit mass is higher than that of R1234yf in the pure fluid adsorption system. The adsorption capacity of the mixture is lower than that of a pure working medium due to competitive adsorption. For both pure and mixed refrigerants, the adsorption heat of R32 in MOF-200 is smaller than that of R1234yf. Compared with R1234yf, the self-diffusion coefficient of R32 in MOF-200 is larger because of the lower diffusion activation energy. Full article
(This article belongs to the Special Issue Thermophysical Properties of Working Mediums and Their Application in Thermodynamic Cycles)
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13 pages, 2602 KiB  
Article
Research on Load Optimal Dispatch for High-Temperature CHP Plants through Grey Wolf Optimization Algorithm with the Levy Flight
by Yang Wang, Xiaobing Yu, Li Yang, Jie Li, Jun Zhang, Yonglin Liu, Yongjun Sun and Fei Yan
Processes 2022, 10(8), 1546; https://doi.org/10.3390/pr10081546 - 7 Aug 2022
Cited by 2 | Viewed by 1324
Abstract
The combined heating and power (CHP) plants are considered one of the promising methods to support the goal of “Carbon Peak and Carbon Neutrality”. It is an important means to take heat and power load optimal dispatch (LOD) to further reduce the energy [...] Read more.
The combined heating and power (CHP) plants are considered one of the promising methods to support the goal of “Carbon Peak and Carbon Neutrality”. It is an important means to take heat and power load optimal dispatch (LOD) to further reduce the energy consumption of CHP plants. To achieve a better load dispatch scheme, this paper employs a potent algorithm by integrating the grey wolf optimization (GWO) algorithm and the Levy flight (i.e., Levy–GWO algorithm) to overcome premature convergence. Moreover, the constraint condition processing method is also proposed to handle the system constraints for ensuring the results within feasible zones. To confirm the effectiveness of this algorithm, it is tested on two widely used test systems (Test system I and Test system II). The accuracy of the used algorithm is proved by comparing the obtained results and reported data in other literature. Results show that the Levy–GWO algorithm can be used to obtain relatively lower power generation costs, with the values of 9231.41 $/h (Test system I) and 10,111.79 $/h (Test system II). The proposed constraint processing method effectively solves the problem that load optimal dispatch scheduling is difficult to solve due to the existence of multiple constraints. In addition, the comparison results indicate that the Levy–GWO algorithm owns a better robustness and convergence effect and has a promising application for solving LOD problems. Full article
(This article belongs to the Special Issue Thermophysical Properties of Working Mediums and Their Application in Thermodynamic Cycles)
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12 pages, 1938 KiB  
Article
Machine Learning Prediction of Critical Temperature of Organic Refrigerants by Molecular Topology
by Yi Que, Song Ren, Zhiming Hu and Jiahui Ren
Processes 2022, 10(3), 577; https://doi.org/10.3390/pr10030577 - 16 Mar 2022
Cited by 3 | Viewed by 2038
Abstract
In this work, molecular structures, combined with machine learning algorithms, were applied to predict the critical temperatures (Tc) of a group of organic refrigerants. Aiming at solving the problem that previous models cannot distinguish isomers, a topological index was introduced. [...] Read more.
In this work, molecular structures, combined with machine learning algorithms, were applied to predict the critical temperatures (Tc) of a group of organic refrigerants. Aiming at solving the problem that previous models cannot distinguish isomers, a topological index was introduced. The results indicate that the novel molecular descriptor ‘molecular fingerprint + topological index’ can effectively differentiate isomers. The average absolute average deviation between the predicted and experimental values is 3.99%, which proves a reasonable prediction ability of the present method. In addition, the performance of the proposed model was compared with that of other previously reported methods. The results show that the present model is superior to other approaches with respect to accuracy. Full article
(This article belongs to the Special Issue Thermophysical Properties of Working Mediums and Their Application in Thermodynamic Cycles)
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