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1

Nielsen, Morten. Heavypuff: An interactive bulk model for dense gas dispersion with thermodynamical effects. Roskilde, Denmark: Riso National Laboratory, 1988.

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2

Kaganovich, B. M. Tekhnologii︠a︡ termodinamicheskogo modelirovanii︠a︡: Redukt︠s︡ii︠a︡ modeleĭ dvizhenii︠a︡ k modeli︠a︡m pokoi︠a︡ = Thermodynamic model engineering : Motion models reduction to rest models. Novosibirsk: Nauka, 2010.

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3

A, Crerar David, ed. Thermodynamics in geochemistry: The equilibrium model. New York: Oxford University Press, 1993.

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4

Wilmański, Krzysztof. Modele termodynamiczne ośrodków ciągłych. Poznań: Wydawn. Politechniki Poznańskiej, 1985.

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5

Thermodynamics of one-dimensional solvable models. Cambridge, U.K: Cambridge University Press, 1999.

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6

Nagnibeda, Ekaterina A. Transport properties of nonequilibrium gas flows: Models and applications. Noordwijk, The Netherlands: ESA Publications Division, 2005.

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7

Modeli gidrotermodinamiki dvusloĭno stratifit͡sirovannykh vodoemov. Moskva: Vychislitelʹnyĭ t͡sentr AN SSSR, 1987.

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8

Koliński, Andrzej. Lattice models of protein folding, dynamics, and thermodynamics. Austin, Tex: R.G. Landes, 1996.

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9

Discrete nonlinear models of the Boltzmann equation. Moscow: General Editorial Board for Foreign Language Publications, Nauka Publishers, 1987.

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10

Pál, Benedek. A modul elv: Akadémiai székfoglaló, 1988. február 16. Budapest: Akadémiai Kiadó, 1991.

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11

Mathematical models of convection. Berlin: De Gruyter, 2012.

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12

Grosse, Harald. Models in Statistical Physics and Quantum Field Theory. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988.

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13

McCarty, Robert D. The thermodynamic properties of nitrogen tetroxide. [Washington, D.C.]: U.S. Dept. of Commerce, National Bureau of Standards, 1986.

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14

McCarty, Robert D. The thermodynamic properties of nitrogen tetroxide. [Washington, D.C.]: U.S. Dept. of Commerce, National Bureau of Standards, 1986.

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15

Piquet, Jean. Turbulent Flows: Models and Physics. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999.

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16

Netsu tōkei rikigaku. Ōsaka-fu Sakai-shi: Ōsaka Kōritsu Daigaku Kyōdō Shuppankai, 2014.

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17

Filippov, S. P. (Sergeĭ Petrovich) and Kler A. M, eds. Ravnovesnai︠a︡ termodinamika i matematicheskoe programmirovanie. Novosibirsk: "Nauka", Sibirskai︠a︡ izdatelʹskai︠a︡ firma RAN, 1995.

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18

Dresar, Neil T. Van. Thermodynamic models for bounding pressurant mass requirements of cryogenic tanks. [Washington, DC: National Aeronautics and Space Administration, 1993.

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19

Srinivasan, Seshasai. Thermodiffusion in Multicomponent Mixtures: Thermodynamic, Algebraic, and Neuro-Computing Models. New York, NY: Springer New York, 2013.

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20

Fabrichnaya, Olga B., Surendra K. Saxena, Pascal Richet, and Edgar F. Westrum. Thermodynamic Data, Models, and Phase Diagrams in Multicomponent Oxide Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-10504-7.

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21

Catto, Isabelle. The mathematical theory of thermodynamic limits: Thomas-Fermi type models. Oxford: Clarendon Press, 1998.

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22

Francis, Olti, ed. Computer aided chemical thermodynamics of gases and liquids: Theory, models, and programs. New York: Wiley, 1985.

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23

Mauri, Roberto. Multiphase Microfluidics: The Diffuse Interface Model. Vienna: Springer Vienna, 2012.

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24

Netsurikigaku: Entoropī o rikaisuru tame ni = Thermodynamics for understanding entropy. Tōkyō-to Bunkyō-ku: Kyōritsu Shuppan, 2013.

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25

Geokhimicheskai︠a︡ migrat︠s︡ii︠a︡ i rudoobrazovanie. Kiev: Naukova Dumka, 2002.

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26

Netsu, tōkei rikigaku kōgi. Tōkyō-to Shibuya-ku: Saiensusha, 2012.

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27

Beris, Antony N. Thermodynamics of flowing systems: With internal microstructure. New York: Oxford University Press, 1994.

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28

Gorbanʹ, A. N. Termodinamicheskie ravnovesii︠a︡ i ėkstremumy: Analiz oblasteĭ dostizhimosti i chastichnykh ravnovesiĭ v fiziko-khimicheskikh i tekhnicheskikh sistemakh. Novosibirsk: Nauka, 2001.

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29

Vielberth, J. Fog dispersal by means of cold water spray: Thermodynamic model calculations and experimental test. Regensberg [Germany]: Roderer Verlag, 1997.

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30

Analytic Combustion: With Thermodynamics, Chemical Kinetics and Mass Transfer. Cambridge: Cambridge University Press, 2011.

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31

Benedek, P. Computer aided chemical thermodynamics of gases and liquids: Theory, models and programs. New York: Wiley, 1985.

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32

Wachspress, Eugene. The ADI Model Problem. New York, NY: Springer New York, 2013.

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33

Tickle, Graham A. Review of thermodynamic models for ethylene released from above its critical point. [Sudbury]: HSE Books, 1999.

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34

Dambiev, T︠S︡ T︠S︡. Termodinamicheskai︠a︡ modelʹ ustoĭchivogo razvitii︠a︡ regiona: Ėkologicheskiĭ i ėnergosberegai︠u︡shchiĭ aspekty. Ulan-Udė: Vostochno-Sibirskiĭ gos. tekhnologicheskiĭ universitet, 2001.

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35

Thomas, Schwager, ed. Computational granular dynamics: Models and algorithms. Berlin: Springer-Verlag, 2005.

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36

Roger, Prud'homme, ed. Mechanical and thermodynamical modeling of fluid interfaces. Singapore: World Scientific, 2001.

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37

Gaans-Godfroy, Pauline Francisca Maria van. The Pitzer model applied to aqueous GaCl₃ solutions with evaluation of regression methods. [Utrecht: Instituut voor Aardwetenschappen der Rijksuniversiteit Utrecht, 1990.

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38

K, Folas Georgios, ed. Thermodynamic models for industrial applications: From classical and advanced mixing rules to association theories. Chichester, U.K: Wiley, 2010.

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39

Maczek, Kazimierz. Optymalizacja urządzeń do realizowania obiegów lewobieżnych. Kraków: Politechnika Krakowska im. Tadeusza Kościuszki, 1990.

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40

Fedotov, Sergeĭ Aleksandrovich. Issledovanii︠a︡ po vulkanologii i seĭsmologii, ikh razvitie i znachenie na Kamchatke, istorii︠a︡ otechestvennoĭ nauki: Statʹi i ocherki 1973-2002 gg. Petropavlovsk-Kamchatskiĭ: Institut vulkanologii DO RAN, 2002.

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41

Re li xue li zi qun you hua suan fa yan jiu ji qi ying yong. Tianjin Shi: Tianjin da xue chu ban she, 2011.

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42

Krawietz, Arnold. Materialtheorie: Mathematische Beschreibung des phänomenologischen thermomechanischen Verhaltens. Berlin: Springer, 1986.

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43

Grigorʹev, I︠U︡ N. Chislennye metody "chastit︠s︡y-v-i︠a︡cheĭkakh". Novosibirsk: "Nauka," Sibirskai︠a︡ izd. firma RAN, 2000.

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44

Simonenko, Sergey V. Non-equilibrium statistical thermohydrodynamics of turbulence. Edited by Dolgikh G. I and Tikhookeanskiĭ okeanologicheskii institut im. V.I. Ilʹicheva. Moscow: Nauka, 2006.

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45

Thermodynamic equilibria and extrema: Analysis of attainability regions and partial equilibria. New York: Springer, 2006.

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46

Anderson, Greg M., and David A. Crerar. Thermodynamics in Geochemistry: The Equilibrium Model. Oxford University Press, USA, 1992.

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47

Swendsen, Robert H. An Introduction to Statistical Mechanics and Thermodynamics. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198853237.001.0001.

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This is a textbook on statistical mechanics and thermodynamics. It begins with the molecular nature of matter and the fact that we want to describe systems containing many (1020) particles. The first part of the book derives the entropy of the classical ideal gas using only classical statistical mechanics and Boltzmann’s analysis of multiple systems. The properties of this entropy are then expressed as postulates of thermodynamics in the second part of the book. From these postulates, the structure of thermodynamics is developed. Special features are systematic methods for deriving thermodynamic identities using Jacobians, the use of Legendre transforms as a basis for thermodynamic potentials, the introduction of Massieu functions to investigate negative temperatures, and an analysis of the consequences of the Nernst postulate. The third part of the book introduces the canonical and grand canonical ensembles, which are shown to facilitate calculations for many models. An explanation of irreversible phenomena that is consistent with time-reversal invariance in a closed system is presented. The fourth part of the book is devoted to quantum statistical mechanics, including black-body radiation, the harmonic solid, Bose–Einstein and Fermi–Dirac statistics, and an introduction to band theory, including metals, insulators, and semiconductors. The final chapter gives a brief introduction to the theory of phase transitions. Throughout the book, there is a strong emphasis on computational methods to make abstract concepts more concrete.
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48

Fournoil, Jacques M. Coupled acoustic and ocean thermodynamic model. 1987.

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49

Clarke, Andrew. Temperature and its measurement. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199551668.003.0003.

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Temperature is that property of a body which determines whether it gains or loses energy in a particular environment. In classical thermodynamics temperature is defined by the relationship between energy and entropy. Temperature can be defined only for a body that is in thermodynamic and thermal equilibrium; whilst organisms do not conform to these criteria, the errors in assuming that they do are generally small. The Celsius and Fahrenheit temperature scales are arbitrary because they require two fixed points, one to define the zero and the other to set the scale. The thermodynamic (absolute) scale of temperature has a natural zero (absolute zero) and is defined by the triple point of water. Its unit of temperature is the Kelvin. The Celsius scale is convenient for much ecological and physiological work, but where temperature is included in statistical or deterministic models, only thermodynamic temperature should be used. Past temperatures can only be reconstructed with the use of proxies, the most important of which are based on isotope fractionation.
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50

Boudreau, Joseph F., and Eric S. Swanson. Classical spin systems. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0020.

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The thermodynamic properties of spin systems are evaluated with Monte Carlo methods. A review of classical thermodynamics is followed by a discussion of critical exponents. The Monte Carlo method is then applied to the two-dimensional Ising model with the goal of determining the phase diagram for magnetization. Boundary conditions, the reweighting method, autocorrelation, and critical slowing down are all explored. Cluster algorithms for overcoming critical slowing down are developed next and shown to dramatically reduce autocorrelation. A variety of spin systems that illustrate first, second, and infinite order (topological) phase transitions are explored. Finally, applications to random systems called spin glasses and to neural networks are briefly reviewed.
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