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Journal articles on the topic 'Simulation thermodynamique de phases'

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Published: 4 June 2021

Last updated: 7 February 2022

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1

Soustelle, M., B. Guilhot, A. A. Fournier, M. Murat, and A. Negro. "Stabilite thermodynamique des phases dans le systeme CaOAl2O3CO2H2O." Cement and Concrete Research 15, no. 3 (May 1985): 421–30. http://dx.doi.org/10.1016/0008-8846(85)90115-2.

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2

Sabbah, R., and E. N. L. E. Buluku. "Étude thermodynamique des trois isomères du dihydroxybenzène." Canadian Journal of Chemistry 69, no. 3 (March 1, 1991): 481–88. http://dx.doi.org/10.1139/v91-072.

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The present work is concerned with a thermodynamic study of the three isomers of dihydroxybenzene. By combustion calorimetry of small amounts of substance, sublimation calorimetry, differential thermal analysis, and heat capacity measurements, it was possible to determine the enthalpies of formation of 1,2-, 1,3-, and 1,4-dihydroxybenzene in the condensed and gaseous phases, their enthalpies of fusion and transition, and the temperature of their triple point and transition. The experimental results are used to discuss the relative stability and determine the conjugation energy of the three compounds. The values are in good agreement with the theoretical values obtained from a quantum chemical calculation. The enthalpies of atomization enabled us to determine an energy value for the intramolecular Cb—OH bond in dihydroxybenzenes and to correlate it with previous results obtained from a study of alkane-diols. The enthalpies of sublimation were discussed. An intramolecular hydrogen bond was displayed in the ortho isomer. Intermolecular hydrogen bonds associated with van der Waals interactions exist in dihydroxybenzenes. Their energy contributions were determined. Key words: thermodynamics, calorimetry, differential thermal analysis, 1,2-benzenediol or 1,2-dihydroxybenzene or catechol; 1,3-benzenediol or 1,3-dihydroxybenzeneorresorcinol; 1,4-benzenediol or 1,4-dihydroxybenzene or hydroquinone or quinol; enthalpies of combustion, of sublimation, of fusion, of transition, energy of conjugation, enthalpies of atomization, of inter- and intramolecular bonds; triple point and transition temperatures.

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3

Coulet, M. V., R. Bellissent, and C. Bichara. "Séparation de phases dans les liquides covalents : diffusion de neutrons et modélisation thermodynamique." Journal de Physique IV (Proceedings) 111 (September 2003): 147–66. http://dx.doi.org/10.1051/jp4:2002821.

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4

Larson, R. G. "Molecular simulation of ordered amphiphilic phases." Chemical Engineering Science 49, no. 17 (September 1994): 2833–50. http://dx.doi.org/10.1016/0009-2509(94)e0102-v.

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5

Jackson, Robert A., James E. Huntington, and Richard G. J. Ball. "Computer simulation of uranium oxide phases." Radiation Effects and Defects in Solids 134, no. 1-4 (December 1995): 161–64. http://dx.doi.org/10.1080/10420159508227205.

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6

Parlinski, Krzysztof. "Molecular-dynamics simulation of incommensurate phases." Computer Physics Reports 8, no. 4 (August 1988): 153–219. http://dx.doi.org/10.1016/0167-7977(88)90002-0.

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7

Landwehr, B., G. Wozny, and H. Hartmann. "Simulation of coupled columns with three phases." Computers & Chemical Engineering 16 (May 1992): S395—S402. http://dx.doi.org/10.1016/s0098-1354(09)80047-1.

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8

Wu, Benjun, Han Hank Xia, Tao Wang, and Xiaoqing Shi. "Simulation of Core Phases From Coda Interferometry." Journal of Geophysical Research: Solid Earth 123, no. 6 (June 2018): 4983–99. http://dx.doi.org/10.1029/2017jb015405.

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9

Horsch, Martin, and Hans Hasse. "Molecular simulation of nano-dispersed fluid phases." Chemical Engineering Science 107 (April 2014): 235–44. http://dx.doi.org/10.1016/j.ces.2013.12.026.

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10

Landwehr, B., G. Wozny, and H. Hartmann. "Simulation of coupled columns with three phases." Computers & Chemical Engineering 17, no. 5-6 (May 1993): 527–33. http://dx.doi.org/10.1016/0098-1354(93)80041-k.

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11

van der Eerden, J. P. J. M., M. M. E. Snel, J. Makkinje, A. D. J. van Dijk, and H. A. Rinia. "Striped phases in thin layers: simulation and observation." Journal of Crystal Growth 237-239 (April 2002): 111–15. http://dx.doi.org/10.1016/s0022-0248(01)01860-7.

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12

Trew, A. S., G. S. Pawley, and A. Cairns-Smith. "The simulation of condensed phases in cyclohexane clusters." Acta Crystallographica Section A Foundations of Crystallography 46, no. 12 (December 1, 1990): 979–88. http://dx.doi.org/10.1107/s0108767390008777.

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13

Wentzel, Nathaniel, and Scott T. Milner. "Simulation of multiple ordered phases in C23n-alkane." Journal of Chemical Physics 134, no. 22 (June 14, 2011): 224504. http://dx.doi.org/10.1063/1.3589417.

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14

TREW, A. S., WILDING, and G. S. PAWLEY. "The Phases of Cyclohexane Predicted by MD Simulation." International Journal of Modern Physics C 02, no. 01 (March 1991): 515–22. http://dx.doi.org/10.1142/s0129183191000809.

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Phase changes in cyclohexane have been studied by MD simulation on the AMT DAP computer, using a zero-pressure technique to simulate clusters of 512 molecules. This work builds upon a previous study [1] in which we performed MD calculations on a smaller sample and found a phase intermediate between the experimentally determined low temperature crystalline structure (C2/c) and the high temperature plastic one (Fm3m). This new phase had not been observed experimentally in the bulk at ambient pressure [2]. We determined the intermediate structure to be rhombohedral with a space group of [Formula: see text]. A subsequent neutron diffraction study of cyclohexane at high pressures (< 5) kbar has permitted the identification of two orthorhombic phases [3] which occur for deuterated cyclohexane. In addition, for very small sample sizes another, as yet unidentified, phase has been observed at ambient pressure [4]: clear evidence that there are differences between the crystal structure in the bulk and in small clusters. We therefore decided to extend our earlier work in order to investigate the behaviour of the phase as a function of sample size. Using a larger sample we find behaviour much closer to that seen in the bulk material. The rhombohedral structure is still observed but over a very much reduced temperature range and the transition temperatures are closer to those seen experimentally. Although -we cannot identify the structure observed by Bosio and Dumas [4] with that simulated it is clear that there is an obvious parallel with the behaviour of the model. A further study of this system is underway.

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15

Zhou, Xiaojun, Hao Wu, and Jingjing Ma. "Simulation of T-junctions two phases separation characteristics." Vibroengineering PROCEDIA 26 (September 26, 2019): 100–105. http://dx.doi.org/10.21595/vp.2019.20866.

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16

Sekkal, W., and A. Zaoui. "Molecular dynamics simulation of superhard phases in RuO2." Journal of Physics: Condensed Matter 13, no. 16 (April 5, 2001): 3699–708. http://dx.doi.org/10.1088/0953-8984/13/16/301.

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17

Kopal-Engeländer, Dagmar. "A simulation of stance-phases of symmetric movements." Journal of Biomechanics 27, no. 6 (January 1994): 673. http://dx.doi.org/10.1016/0021-9290(94)90999-7.

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18

Iuga, Maria, and Friedrich Raether. "Simulation of the Thermoelastic Properties of Sintered Ceramics." Advances in Science and Technology 45 (October 2006): 89–94. http://dx.doi.org/10.4028/www.scientific.net/ast.45.89.

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Many ceramic materials are composed of various phases, which can differ in their individual thermal, elastic or electrical properties by orders of magnitude. The microstructural arrangement of the phases controls important material properties of the composite. To simulate these macroscopic material properties from the material properties of the constituting phases, a 3-D FEM model is used. The key for an adequate description of real materials is the accurate threedimensional modeling of their microstructure. Basic morphological parameters of many ceramics are reflected by a modified Voronoi model, e.g.: the volume fractions, grain size ratios and contiguity of the phases. By automatically generating thousands of test structures and comparing them to quantitative data derived from image analysis of scanning electron micrographs, structures are selected which closely fit to the microstructure of experimental samples. The model considerations are illustrated on two types of bi-continuous ceramic materials, a porous alumina (Al2O3) and a dense zirconia toughened alumina (ZTA) ceramic. Using different volume fractions of the phases, Voronoi type microstructures and truncated sphere models are exemplified. For these two ceramic systems, elastic moduli and thermal conductivity are calculated and compared to experimental data of samples of the respective microstructure.

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19

Chabba, Hanae, and Driss Dafir. "Compression Behavior of Al-Mg Phases, Molecular Dynamics Simulation." International Journal of Engineering Research in Africa 46 (January 2020): 15–31. http://dx.doi.org/10.4028/www.scientific.net/jera.46.15.

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Aluminum alloys development always exit in the manufacturing process. Al/Mg alloys have been attracted significant attention because of their excellent mechanical properties. The microstructural evolution and deformation mechanisms are still challenging issues, and it is hard to observe directly by experimental methods. Accordingly, in this paper atomic simulations are performed to investigate the uniaxial compressive behavior of Al/Mg phases; with different ratio of Mg ranging from 31% to 56%. The compression is at the same strain rate (3.1010 s⁻¹), at the same temperature (300K) and pressure, using embedded atom method (EAM) potential to model the interactions and the deformation behavior between Al and Mg.From these simulations, we get the radial distribution function; the stress–strain responses to describe the elastic and plastic behaviors of β-Al3Mg2, ε-Al30Mg23, Al1Mg1 and γ-Al12Mg17 phases with 31, 41, 50 and 56% of Mg added to pure aluminum, respectively. The mechanical properties, such as Young’s modulus, elasticity limit and rupture pressure, are determined and presented. The engineering equation was used to plot the stress-strain curve for each phase.From the results obtained, the chemical composition has a significant effect on the properties of these phases. The stress-strain behavior comprised elastic, yield, strain softening and strain hardening regions that were qualitatively in agreement with previous simulations and experimental results. These stress-strain diagrams obtained show a rapid increase in stress up to a maximum followed by a gradual drop when the specimen fails by ductile fracture. Under compression, the deformation behavior of β-Al3Mg2 and γ-Al12Mg17 phases is slightly similar. From the results, it was found that ε-Al30Mg23 phase are brittle under uniaxial compressive loading and γ-Al12Mg17 phase is very ductile under the same compressive loading.The engineering stress-strain relationship suggests that β-Al3Mg2 and γ-Al12Mg17 phases have high elasticity limit, ability to resist deformation and also have the advantage of being highly malleable. From this simulation, we also find that the mechanical properties under compressive load of ε-Al30Mg23 phase are evidently less than other phases, which makes it the weakest phase. The obtained results were compared with the previous experimental studies, and generally, there is a good correlation.The Al-Mg system was built and simulated using molecular dynamics (MD) software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator).

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20

Phillips, Tim L., Zeyn A. Saigol, and Simon Hanna. "Computer Simulation of Rotator Phases in Liquid-Crystalline Polymers." Molecular Crystals and Liquid Crystals Science and Technology. Section A. Molecular Crystals and Liquid Crystals 303, no. 1 (September 1997): 9–14. http://dx.doi.org/10.1080/10587259708039398.

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21

Torrisi, Antonio, Charlotte K. Leech, Kenneth Shankland, William I. F. David, Richard M. Ibberson, Jordi Benet-Buchholz, Roland Boese, Maurice Leslie, C. Richard A. Catlow, and Sarah L. Price. "Solid Phases of Cyclopentane: Combined Experimental and Simulation Study." Journal of Physical Chemistry B 112, no. 12 (March 2008): 3746–58. http://dx.doi.org/10.1021/jp710017y.

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22

Parlinski, Krzysztof. "Molecular-dynamics simulation of a model with incommensurate phases." Physical Review B 35, no. 16 (June 1, 1987): 8680–95. http://dx.doi.org/10.1103/physrevb.35.8680.

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23

Baranyai, András, Albert Bartók, and Ariel A. Chialvo. "Computer simulation of the 13 crystalline phases of ice." Journal of Chemical Physics 123, no. 5 (August 2005): 054502. http://dx.doi.org/10.1063/1.1989313.

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24

Shukla, K. P., and M. Robert. "Computer simulation of interfaces between two-dimensional fluid phases." Fluid Phase Equilibria 79 (November 1992): 139–49. http://dx.doi.org/10.1016/0378-3812(92)85126-s.

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25

Kryukova, O. N., and A. L. Maslov. "Simulation of oxide phases formation under pulsed electron beam." IOP Conference Series: Materials Science and Engineering 124 (April 2016): 012034. http://dx.doi.org/10.1088/1757-899x/124/1/012034.

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26

Visscher, P. B., and D. M. Heyes. "Growth of hexagonal string phases in sheared colloid simulation." Journal of Chemical Physics 101, no. 7 (October 1994): 6096–100. http://dx.doi.org/10.1063/1.467324.

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27

Guissani, Yves, and Bertrand Guillot. "Coexisting phases and criticality in NaCl by computer simulation." Journal of Chemical Physics 101, no. 1 (July 1994): 490–509. http://dx.doi.org/10.1063/1.468160.

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28

Horsch, Martin, and Hans Hasse. "Reprint of: Molecular simulation of nano-dispersed fluid phases." Chemical Engineering Science 115 (August 2014): 195–204. http://dx.doi.org/10.1016/j.ces.2014.05.033.

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29

Allen, Michael P. "Simulation of condensed phases using the Distributed Array Processor." Theoretica Chimica Acta 84, no. 4-5 (January 1993): 399–411. http://dx.doi.org/10.1007/bf01113278.

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30

Baimova, J. А., L. Kh Rysaeva, and A. I. Rudskoy. "Deformation behavior of diamond-like phases: Molecular dynamics simulation." Diamond and Related Materials 81 (January 2018): 154–60. http://dx.doi.org/10.1016/j.diamond.2017.12.001.

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31

Bow, J. S., R. W. Carpenter, and M. J. Kim. "HREM image simulation of Ti5Si3TiC/6H-SiC interfaces." Proceedings, annual meeting, Electron Microscopy Society of America 52 (1994): 518–19. http://dx.doi.org/10.1017/s0424820100170323.

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Researches on interfacial structures by experimental HREM and computer simulation to the present have concentrated on solving one interface between two phases. Interfaces with a thin third phase interlayer between two major phases are of more recent interest. As the thickness of the interlayer phasedecreases, the strain fields of the bounding interfaces are no longer completely accommodated by the interlayer phase. The structures of both interfaces have to be considered simultaneously. This abstract describes some early work on establishment of a supercell including three phases and two interfaces for HREM simulation.The interface triad, Ti5Si3/TiC/6H-SiC, which was formed during annealing Ti/6H-SiC contacts, is an important example. The TiC thickness observed in the experimental HREM image, Fig. 1, is about 2.5 nm. The interlayer dimension normal to the interfaces is not large, and the size of the required supercell is small enough for computation on a moderately fast workstation.The simplest way to build a supercell including these three phases is to build each individual crystal constituent of the triad in the desired orientation and dimension and then assemble them with suitable translation vectors.

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32

Wojakowska, A., A. Górniak, and A. Wojakowski. "L'étude thermodynamique des mélanges liquides chlorure d'argent – chlorure de zinc et bromure d'argent – bromure de zinc à partir des diagrammes d'équilibres des phases." Journal de Physique IV (Proceedings) 113 (January 2004): 159–62. http://dx.doi.org/10.1051/jp4:20040034.

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33

Memmer, R. "Computer simulation of chiral liquid crystal phases VIII. Blue phases of the chiral Gay-Berne fluid." Liquid Crystals 27, no. 4 (April 2000): 533–46. http://dx.doi.org/10.1080/026782900202723.

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34

Ilnytskyi, Lintuvuori, and Wilson. "Simulation of bulk phases formed by polyphilic liquid crystal dendrimers." Condensed Matter Physics 13, no. 3 (2010): 33001. http://dx.doi.org/10.5488/cmp.13.33001.

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35

Birkett, G. R., and D. D. Do. "On the heat capacity of adsorbed phases using molecular simulation." Journal of Chemical Physics 126, no. 6 (February 14, 2007): 064702. http://dx.doi.org/10.1063/1.2434149.

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36

Schneider, Ludwig Y., and Marcus Müller. "Engineering Scale Simulation of Nonequilibrium Network Phases for Battery Electrolytes." Macromolecules 52, no. 5 (February 21, 2019): 2050–62. http://dx.doi.org/10.1021/acs.macromol.8b02703.

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37

Stillinger, Frank H., and Thomas A. Weber. "Computer simulation of local order in condensed phases of silicon." Physical Review B 31, no. 8 (April 15, 1985): 5262–71. http://dx.doi.org/10.1103/physrevb.31.5262.

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38

Pizzirusso, A., M. Savini, L. Muccioli, and C. Zannoni. "An atomistic simulation of the liquid-crystalline phases of sexithiophene." J. Mater. Chem. 21, no. 1 (2011): 125–33. http://dx.doi.org/10.1039/c0jm01284j.

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39

Bates, Martin A., and Martin Walker. "Computer simulation of the columnar phases of liquid crystalline bolaamphiphiles." Liquid Crystals 38, no. 11-12 (November 2011): 1749–57. http://dx.doi.org/10.1080/02678292.2011.631301.

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40

Eckert, E. "Dynamic simulation of a distillation column with multiple liquid phases." Computers & Chemical Engineering 19, no. 1 (June 11, 1995): S393—S398. http://dx.doi.org/10.1016/0098-1354(95)00047-6.

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41

Eckert, E., and M. Kubíček. "Dynamic simulation of a distillation column with multiple liquid phases." Computers & Chemical Engineering 19 (June 1995): 393–98. http://dx.doi.org/10.1016/0098-1354(95)87068-7.

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42

Yang, Shouhong, Xiuqing Zhang, and Shiling Yuan. "Mesoscopic simulation studies on micellar phases of Pluronic P103 solution." Journal of Molecular Modeling 14, no. 7 (May 14, 2008): 607–20. http://dx.doi.org/10.1007/s00894-008-0319-7.

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43

Massidda, Myosotis, Lucia Cugusi, Maurizio Ibba, Iosto Tradori, and Carla M. Calò. "Energy Expenditure during Competitive Latin American Dancing Simulation." Medical Problems of Performing Artists 26, no. 4 (December 1, 2011): 206–10. http://dx.doi.org/10.21091/mppa.2011.4033.

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The aims of this study were to estimate the energy expenditure (EE) and the intensity of physical activity (PA) during a competitive simulation of Latin American dancing and to evaluate the differences in PA and EE values between the sexes, between different dance types, and between the various phases of the competition. METHODS: Ten Italian dancers (five couples, 5 males and 5 females) competing in Latin American dancing at the international level were examined in this study. The EE (kcal) was measured during the semifinal and final phases of the competition using the SenseWear Pro Armband (SWA). Paired-sample t-tests were used to determine differences in the metabolic equivalent (MET) and EE values between the semifinal and final phases and between each dance. One-way analysis of variance was used to analyze the differences in the MET and EE values between the sexes. RESULTS: The intensity of PA during the dance sequence ranged from moderate (3 to 6 METs) to vigorous (6 to 9 METs). The male dancers had higher EE values than the female dancers during all phases of the simulation. Similar MET values were observed in both sexes. The PA intensity during the finals phase was vigorous for 56% of the time of dance. Of all the dance styles, the rumba had the lowest MET and EE values. CONCLUSION: Our results demonstrate that competitive Latin American dancing is a heavy exercise and suggest that monitoring variables during normal training can improve training protocols and the dancers’ fitness levels.

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44

Faizan, Niluefer Deniz, Alexander Löffler, Robert Heininger, Matthias Utesch, and Helmut Krcmar. "Classification of Evaluation Methods for the Effective Assessment of Simulation Games: Results from a Literature Review." International Journal of Engineering Pedagogy (iJEP) 9, no. 1 (February 22, 2019): 19. http://dx.doi.org/10.3991/ijep.v9i1.9948.

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As a current trend in teaching, simulation games play an active and important role in the area of technology-based education. Simulation games create an envi-ronment for scholars to solve real-world problems in a risk-free environment. Therefore, they aim to increase the knowledge base as well as learning experienc-es for students. However, assessing the effectiveness of a simulation game is necessary to optimize elements of the game and increase their learning effect. In order to achieve this aim, different evaluation methods exist, which do not always involve all phases when running a simulation game. In this study, we conduct a literature review to analyze evaluation methods for three phases of simulation games: pre-game, in-game, and post-game. Thirty-one peer-reviewed research papers met specified selection criteria and we classified them according to a di-dactic framework that illustrates four phases of running simulation games: Prepa-ration, Introduction, Interaction and Conclusion phase. Based on the results, we provide a concrete evaluation strategy that will be a guide to assess simulation games during all phases. This study contributes to theory by providing an over-view of evaluation methods for the assessment of simulation games within the different game phases. It contributes to practice by providing a concrete evalua-tion strategy that can be adapted and used to assess simulation games.

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45

Muramatsu, Mayu, Tatsuya Kawada, and K. Terada. "A Simulation of Ferroelastic Phase Formation by Using Phase Field Model." Key Engineering Materials 725 (December 2016): 208–13. http://dx.doi.org/10.4028/www.scientific.net/kem.725.208.

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In order to incorporate the mechanical behavior of ferroelastic phase into the stress analysis of solid oxide fuel cell in consideration of elastic, creep, thermal and reduction strains, we propose a mathematical model to predict the formation of ferroelastic phases in crystal grains of La0.6Sr0.4Co0.2Fe0.8O3-δ. The phase field model equipped with the elastic energy is introduced to realize the morphology formation of ferroelastic phases in a crystal grain. By the use of the developed mathematical model, some numerical examples are performed to reproduce the deformation-induced nucleation and growth of ferroelastic phases of La0.6Sr0.4Co0.2Fe0.8O3-δ.

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46

FLORES, FERNANDO GARCÍA, XAVIER MARTIN, and DENJOE O'CONNOR. "SIMULATION OF A SCALAR FIELD ON A FUZZY SPHERE." International Journal of Modern Physics A 24, no. 20n21 (August 20, 2009): 3917–44. http://dx.doi.org/10.1142/s0217751x09043195.

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The ϕ4 real scalar field theory on a fuzzy sphere is studied numerically. We refine the phase diagram for this model where three distinct phases are known to exist: a uniformly ordered phase, a disordered phase, and a nonuniformly ordered phase where the spatial SO(3) symmetry of the round sphere is spontaneously broken and which has no classical equivalent. The three coexistence lines between these phases, which meet at a triple point, are carefully located, with particular attention paid to the one between the two ordered phases and the triple point itself. In the neighborhood of the triple point all phase boundaries are well approximated by straight lines which, surprisingly, have the same scaling. We argue that unless an extra term is added to enhance the effect of the kinetic term the infinite matrix limit of this model will not correspond to a real scalar field on the commutative sphere or plane.

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47

Liang, Runhong, Xiaolin Fan, Xianbing Luo, Shuyu Sun, and Xingyu Zhu. "Improved IMPES Scheme for the Simulation of Incompressible Three-Phase Flows in Subsurface Porous Media." Energies 14, no. 10 (May 11, 2021): 2757. http://dx.doi.org/10.3390/en14102757.

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In this work, an improved IMplicit Pressure and Explicit Saturation (IMPES) scheme is proposed to solve the coupled partial differential equations to simulate the three-phase flows in subsurface porous media. This scheme is the first IMPES algorithm for the three-phase flow problem that is locally mass conservative for all phases. The key technique of this novel scheme relies on a new formulation of the discrete pressure equation. Different from the conventional scheme, the discrete pressure equation in this work is obtained by adding together the discrete conservation equations of all phases, thus ensuring the consistency of the pressure equation with the three saturation equations at the discrete level. This consistency is important, but unfortunately it is not satisfied in the conventional IMPES schemes. In this paper, we address and fix an undesired and well-known consequence of this inconsistency in the conventional IMPES in that the computed saturations are conservative only for two phases in three-phase flows, but not for all three phases. Compared with the standard IMPES scheme, the improved IMPES scheme has the following advantages: firstly, the mass conservation of all the phases is preserved both locally and globally; secondly, it is unbiased toward all phases, i.e., no reference phases need to be chosen; thirdly, the upwind scheme is applied to the saturation of all phases instead of only the referenced phases; fourthly, numerical stability is greatly improved because of phase-wise conservation and unbiased treatment. Numerical experiments are also carried out to demonstrate the strength of the improved IMPES scheme.

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48

Walker, H. A., and J. H. Davidson. "Analysis and Simulation of a Two-Phase Self-Pumping Water Heater." Journal of Solar Energy Engineering 112, no. 3 (August 1, 1990): 153–60. http://dx.doi.org/10.1115/1.2930474.

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The thermal performance of a two-accumulator self-pumping solar water heater is characterized in a daily simulation. The passive vapor transport system operates in cycles, alternating between run, pressurizing, and pump phases. Three isothermal closed-system thermodynamic models characterize the operational phases of the system. The applicable conservation of mass and energy equations of each model are combined in the numerical simulation. Instantaneous temperature and heat transfer rates, as well as integrated energy quantities and thermal efficiencies, are compared to experimental values. The qualitative behavior of the analytical model agrees with that of the physical system. Multiplying thermal loss coefficients by 2.5 and adjusting the theoretical solar model to correspond with measured insolation forces quantitative agreement of overall daily performance. The simulation reveals the impact of the duration of the pressurizing and pumping phases on overall performance. The volume and thermal capacitance of the components used during the pressurizing and pump phases should be minimized, while the insulation on those components should be maximized to optimize system performance. The validated model will be used in future work to optimize system design.

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Wang, Hao, and Xiao Mei Shi. "The Time Domain Simulation of Non-Stationary Road Roughness." Applied Mechanics and Materials 423-426 (September 2013): 1238–42. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.1238.

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Abstract:

The input of road roughness, which affects the ride comfort and the handling stability of vehicle, is the main excitation for the running vehicle. The time history of the road roughness was researched with the random phases, based on the stationary power spectrum density of the road roughness determined by the standards. Through the inverse Fourier transform, the random phases can be used to get the road roughness in time domain, together with the amplitude. Then, the time domain simulation of the non-stationary random excitation when the vehicle ran at the changing speed, would also be studied based on the random phases. It is proved that the random road excitation for the vehicle with the changing speed is stationary modulated evolution random excitation, and its power spectrum density is the stationary modulated evolutionary power spectrum density. And the numerical results for the time history of the non-stationary random inputs were also provided. The time history of the non-stationary random road can be used to evaluate the ride comfort of the vehicle which is running at the changing speed.

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DIAKONOVA, M., and R. S. MACKAY. "MATHEMATICAL EXAMPLES OF SPACE-TIME PHASES." International Journal of Bifurcation and Chaos 21, no. 08 (August 2011): 2297–304. http://dx.doi.org/10.1142/s0218127411029793.

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Abstract:

The space-time phases of a complex dynamic system are the probability distributions for state as a function of space and time which arise by evolving initial probability distributions from the distant past. Toom proved important results about space-time phases for a class of majority voter probabilistic cellular automata (PCA). Here, variants of the majority voter PCA are presented which are proved to exhibit a variety of types of space-time phase. These examples are expected to serve as useful steps on the way to a general theory of space-time phases.

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