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Zhao X, Wang X, Zhao Y, Dong X, Wang Y, Gong M. Prediction of the Thermal Conductivity for Liquid Hydrocarbons and Halogenated Hydrocarbons. Ind Eng Chem Res 2023. [DOI: 10.1021/acs.iecr.2c03793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Xiufang Zhao
- Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences (CAS), Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Xian Wang
- Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences (CAS), Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Yanxing Zhao
- Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences (CAS), Beijing100190, China
| | - Xueqiang Dong
- Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences (CAS), Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Yunxiao Wang
- Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences (CAS), Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
| | - Maoqiong Gong
- Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences (CAS), Beijing100190, China
- University of Chinese Academy of Sciences, Beijing100049, China
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2
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Thermal conductivity prediction of pure refrigerants and mixtures based on entropy-scaling concept. J Mol Liq 2022. [DOI: 10.1016/j.molliq.2022.120568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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3
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Zeng F, Wan R, Xiao Y, Song F, Peng C, Liu H. Predicting the Self-Diffusion Coefficient of Liquids Based on Backpropagation Artificial Neural Network: A Quantitative Structure–Property Relationship Study. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c03342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Fazhan Zeng
- School of Chemistry & Molecular Engineering, East China University of Science and Technology, Shanghai200237, China
| | - Ren Wan
- School of Chemistry & Molecular Engineering, East China University of Science and Technology, Shanghai200237, China
| | - Yongjun Xiao
- School of Chemistry & Molecular Engineering, East China University of Science and Technology, Shanghai200237, China
| | - Fan Song
- School of Chemistry & Molecular Engineering, East China University of Science and Technology, Shanghai200237, China
| | - Changjun Peng
- School of Chemistry & Molecular Engineering, East China University of Science and Technology, Shanghai200237, China
| | - Honglai Liu
- School of Chemistry & Molecular Engineering, East China University of Science and Technology, Shanghai200237, China
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4
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Crossover Residual Entropy Scaling of the Viscosity and Thermal Conductivity of Carbon Dioxide. J Mol Liq 2022. [DOI: 10.1016/j.molliq.2022.120799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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5
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de Hemptinne JC, Kontogeorgis GM, Dohrn R, Economou IG, ten Kate A, Kuitunen S, Fele Žilnik L, De Angelis MG, Vesovic V. A View on the Future of Applied Thermodynamics. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c01906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Georgios M. Kontogeorgis
- Center for Energy Resources Engineering (CERE), Department of Chemical and Biochemical Engineering, Technical University of Denmark, Lyngby DK-2800, Denmark
| | - Ralf Dohrn
- Bayer AG, Process Technologies, Building E41, Leverkusen 51368, Germany
| | - Ioannis G. Economou
- Chemical Engineering Program, Texas A&M University at Qatar, Doha P.O. Box 23874, Qatar
| | | | - Susanna Kuitunen
- Neste Engineering Solutions Oy, P.O. Box 310, Porvoo FI-06101, Finland
| | - Ljudmila Fele Žilnik
- Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Hajdrihova 19, Ljubljana 1001, Slovenia
| | - Maria Grazia De Angelis
- Institute for Materials and Processes, School of Engineering, University of Edinburgh, Sanderson Building, Edinburgh EH9 3FB, UK
- Department of Civil, Chemical, Environmental and Materials Engineering University of Bologna, Bologna 40131 Italy
| | - Velisa Vesovic
- Department of Earth Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
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6
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Wan R, Li M, Song F, Xiao Y, Zeng F, Peng C, Liu H. Predicting the Thermal Conductivity of Ionic Liquids Using a Quantitative Structure–Property Relationship. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c01964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ren Wan
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Mingyan Li
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Fan Song
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Yongjun Xiao
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Fazhan Zeng
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Changjun Peng
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
| | - Honglai Liu
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, China
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7
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Malatesta WA, Yang B. Aviation Turbine Fuel Thermal Conductivity: A Predictive Approach Using Entropy Scaling-Guided Machine Learning with Experimental Validation. ACS OMEGA 2021; 6:28579-28586. [PMID: 34746553 PMCID: PMC8567267 DOI: 10.1021/acsomega.1c02934] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 10/06/2021] [Indexed: 05/17/2023]
Abstract
Although typical aircraft fuel thermal management analysis relies upon temperature-dependent thermodynamic and transport properties of aviation turbine fuel, the variation in properties associated with compositional variation in fuels and the subsequent impacts on system performance are not well established. With this in mind, the present work aimed to develop a predictive model of aviation turbine fuel thermal conductivity which utilized only compositional (hydrocarbon) and state (temperature and pressure) inputs and had errors within the bounds of typical uncertainty of the associated test data (3%). A novel modeling approach was developed to predict thermal conductivity using pseudo-component entropy scaling techniques with a machine learning-developed intermediate step in the overall model. Simple hyper-parameter optimization techniques were developed to promote model stability, computational efficiency, and long-term repeatability of the novel architecture. Validation data were gathered which included four fuel samples (3 JP-5 and 1 F-24), which underwent two-dimensional gas chromatography compositional testing and temperature-dependent density, viscosity, thermal conductivity, and specific heat testing. Model performance on the validation data set assembled from the literature data and present efforts showed an average deviation of 1% and an absolute average deviation of 2.5%. Model outputs outside the validation range are well-behaved and are expected to perform well on a large range of liquid hydrocarbon mixtures with the overall process expected to be well suited to prediction of other properties.
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Affiliation(s)
- William Anthony Malatesta
- Propulsion
and Power Department, Naval Air Systems
Command, 48298 Shaw Rd, Bldg 1461, Patuxent River, Maryland 20670, United States
| | - Bao Yang
- Center for
Environmental Energy Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20742, United States
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8
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Yang X, Kim D, May EF, Bell IH. Entropy Scaling of Thermal Conductivity: Application to Refrigerants and Their Mixtures. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c02154] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Xiaoxian Yang
- Fluid Science & Resources Division, Department of Chemical Engineering, University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Dongchan Kim
- Fluid Science & Resources Division, Department of Chemical Engineering, University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Eric F. May
- Fluid Science & Resources Division, Department of Chemical Engineering, University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Ian H. Bell
- Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, Colorado 80305, United States
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9
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Gonçalves CIS, Silva GM, Ndiaye PM, Tavares FW. Helmholtz Scaling: An Alternative Approach to Calculate Viscosity with the PCP-SAFT Equation of State. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c00837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Cliff I. S. Gonçalves
- Programa de Engenharia Química—COPPE, Universidade Federal do Rio de Janeiro, C.P. 68542 Rio de Janeiro, Brazil
| | - Gabriel M. Silva
- Escola de Química, Universidade Federal do Rio de Janeiro, C.P. 68542 Rio de Janeiro, Brazil
| | - Papa M. Ndiaye
- Programa de Engenharia Química—COPPE, Universidade Federal do Rio de Janeiro, C.P. 68542 Rio de Janeiro, Brazil
- Escola de Química, Universidade Federal do Rio de Janeiro, C.P. 68542 Rio de Janeiro, Brazil
| | - Frederico W. Tavares
- Programa de Engenharia Química—COPPE, Universidade Federal do Rio de Janeiro, C.P. 68542 Rio de Janeiro, Brazil
- Escola de Química, Universidade Federal do Rio de Janeiro, C.P. 68542 Rio de Janeiro, Brazil
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10
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Liu H, Yang F, Yang X, Yang Z, Duan Y. Modeling the thermal conductivity of hydrofluorocarbons, hydrofluoroolefins and their binary mixtures using residual entropy scaling and cubic-plus-association equation of state. J Mol Liq 2021. [DOI: 10.1016/j.molliq.2021.115612] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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11
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Bell IH. Entropy Scaling of Viscosity - II: Predictive Scheme for Normal Alkanes. JOURNAL OF CHEMICAL AND ENGINEERING DATA 2020; 65:10.1021/acs.jced.0c00749. [PMID: 34121765 PMCID: PMC8191377 DOI: 10.1021/acs.jced.0c00749] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
In this work, a residual entropy value 6/10 of the way between the critical point and a value of -2/3 of Boltzmann's constant is shown to collapse the scaled viscosity for the family of normal alkanes. Based on this approach, a nearly universal correlation is proposed that can reproduce 95% of the experimental data for normal alkanes within ±18% (without removal of clearly erroneous data). This universal correlation has no new fluid-specific empirical parameters and is based on experimentally accessible values. This collapse is shown to be valid to a residual entropy half way between the critical point and the triple point, beyond which the macroscopically-scaled viscosity has a super-exponential dependence on residual entropy, terminating at the triple point. A key outcome of this study is a better understanding of entropy scaling for fluids with intramolecular degrees of freedom. A study of the transport and thermodynamic properties at the triple point rounds out the analysis.
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Affiliation(s)
- Ian H Bell
- Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, CO 80305
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12
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Binti Mohd Taib M, Trusler JPM. Residual entropy model for predicting the viscosities of dense fluid mixtures. J Chem Phys 2020; 152:164104. [PMID: 32357798 DOI: 10.1063/5.0002242] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
In this work, we have investigated the mono-variant relationship between the reduced viscosity and residual entropy in pure fluids and in binary mixtures of hydrocarbons and hydrocarbons with dissolved carbon dioxide. The mixtures considered were octane + dodecane, decane + carbon dioxide, and 1,3-dimethylbenzene (m-xylene) + carbon dioxide. The reduced viscosity was calculated according to the definition of Bell, while the residual entropy was calculated from accurate multi-parameter Helmholtz-energy equations of state and, for mixtures, the multi-fluid Helmholtz energy approximation. The mono-variant dependence of reduced viscosity upon residual molar entropy was observed for the pure fluids investigated, and by incorporating two scaling factors (one for reduced viscosity and the other for residual molar entropy), the data were represented by a single universal curve. To apply this method to mixtures, the scaling factors were determined from a mole-fraction weighted sum of the pure-component values. This simple model was found to work well for the systems investigated. The average absolute relative deviation (AARD) was observed to be between 1% and 2% for pure components and a mixture of similar hydrocarbons. Larger deviations, with AARDs of up to 15%, were observed for the asymmetric mixtures, but this compares favorably with other methods for predicting the viscosity of such systems. We conclude that the residual-entropy concept can be used to estimate the viscosity of mixtures of similar molecules with high reliability and that it offers a useful engineering approximation even for asymmetric mixtures.
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Affiliation(s)
- Malyanah Binti Mohd Taib
- Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - J P Martin Trusler
- Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
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13
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Schilling J, Horend C, Bardow A. Integrating superstructure‐based design of molecules, processes, and flowsheets. AIChE J 2020. [DOI: 10.1002/aic.16903] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Johannes Schilling
- Institute of Technical ThermodynamicsRWTH Aachen University Aachen Germany
| | - Christian Horend
- Institute of Technical ThermodynamicsRWTH Aachen University Aachen Germany
| | - André Bardow
- Institute of Technical ThermodynamicsRWTH Aachen University Aachen Germany
- Institute of Energy and Climate Research – Energy Systems Engineering (IEK‐10)Forschungszentrum Jülich GmbH Jülich Germany
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