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Letteratura scientifica selezionata sul tema "Gas dynamics computer simulation"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 18 febbraio 2022

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Articoli di riviste sul tema "Gas dynamics computer simulation"

1

Borman, V. D., S. V. Bogovalov, V. D. Borisevich, I. V. Tronin e V. N. Tronin. "The computer simulation of 3d gas dynamics in a gas centrifuge". Journal of Physics: Conference Series 751 (settembre 2016): 012017. http://dx.doi.org/10.1088/1742-6596/751/1/012017.

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2

Rakkapao, Natthida. "Molecular Dynamics Simulation of Gas Transport in Polyisoprene Matrix". Advanced Materials Research 844 (novembre 2013): 209–13. http://dx.doi.org/10.4028/www.scientific.net/amr.844.209.

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Molecular Dynamics (MD) simulation was employed to study the diffusivity of biogas in a PI matrix with the aim to verify simulations as a useful tool to predict PI membrane properties for biogas treatment. The simulation model of PI numerical was reliable and accurate in predicting both the material properties and the diffusivity of gases in PI matrix. The diffusion coefficients (D) of the major components in biogas, namely CH4, CO2, H2O, O2, and N2, were computed by simulating trajectories of each gas in PI matrix at 300 K. The simulations gave DCO2 that was 6 times larger than DCH4, and this agrees well with permeabilities reported in the literature. This suggests that PI membranes could be used to treat biogas by separating CO2 and CH4. However, the diffusivities of N2, H2O, and CH4 are closely similar, so PI membranes are not capable of separating these. The potential application of PI membrane to CO2/CH4 separation seems worth further exploration.

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Zhu, Likuan, Boyan Song e Zhen Long Wang. "Computational Fluid Dynamics Analysis on Rupture of Gas Bubble". Applied Mechanics and Materials 339 (luglio 2013): 468–73. http://dx.doi.org/10.4028/www.scientific.net/amm.339.468.

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Hydrodynamic information of the flow occurring as a bubble ruptures at a gas liquid interface has being obtained from computer simulations. The simulation result is verified by conducting high-speed photography experiment. Process of bubble rupture is clearly captured with simulation and experiment. Shear force generated by bubble rupture increases along with decrease of bursting bubble diameter or increase of coefficient of surface tension. The maximum average shear force ranges from 0.97Pa to 1.91Pa, when bursting bubble diameter changes from 2mm to 10mm.

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4

Thompson, Bradley, e Hwan-Sik Yoon. "Internal Combustion Engine Modeling Framework in Simulink: Gas Dynamics Modeling". Modelling and Simulation in Engineering 2020 (3 settembre 2020): 1–16. http://dx.doi.org/10.1155/2020/6787408.

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With advancements in computer-aided design, simulation of internal combustion engines has become a vital tool for product development and design innovation. Among the simulation software packages currently available, MATLAB/Simulink is widely used for automotive system simulations, but does not contain a comprehensive engine modeling toolbox. To leverage MATLAB/Simulink’s capabilities, a Simulink-based 1D flow engine modeling framework has been developed. The framework allows engine component blocks to be connected in a physically representative manner in the Simulink environment, reducing model build time. Each component block, derived from physical laws, interacts with other blocks according to block connection. In this Part 1 of series papers, a comprehensive gas dynamics model is presented and integrated in the engine modeling framework based on MATLAB/Simulink. Then, the gas dynamics model is validated with commercial engine simulation software by conducting a simple 1D flow simulation.

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POHL, PHILLIP, GRANT HEFFELFINGER e DOUGLAS SMITH. "Molecular dynamics computer simulation of gas permeation in thin silicalite membranes". Molecular Physics 89, n. 6 (20 dicembre 1996): 1725–31. http://dx.doi.org/10.1080/00268979609482570.

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6

Wu, S. Z., D. N. Wormley, D. Rowell e H. M. Paynter. "Dynamic Modeling and Simulation of Gaseous Systems". Journal of Dynamic Systems, Measurement, and Control 107, n. 4 (1 dicembre 1985): 262–66. http://dx.doi.org/10.1115/1.3140733.

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A general computer-based mathematical modeling system for analyzing air/gas system dynamics has been developed. A set of generic lumped and distributed elements are interconnected by generalized junction structures to represent system configurations. The dynamic response of pressure, flow, temperature, and heat transfer rate at any point in a system, due to control actions, or fluid, thermal, or mechanical disturbances can be determined. The model has been used to analyze furnace implosion and disturbance propagation problems in fossil fuel power plants. To illustrate the modeling techniques, a model of a coal-fired plant has been constructed and pressure transients computed following a fuel trip. The model simulation predictions of the furnace pressure excursions are in close agreement with the data from field tests.

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Knoll, G., H. Peeken, R. Lechtape-Gru¨ter e J. Lang. "Computer-Aided Simulation of Piston and Piston Ring Dynamics". Journal of Engineering for Gas Turbines and Power 118, n. 4 (1 ottobre 1996): 880–86. http://dx.doi.org/10.1115/1.2817009.

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A numerical computer simulation program was developed, aiding in finding optimum design parameters in the multibody-system piston, piston-rings, and cylinder with respect to optimum sealing, minimal friction, and minimum noise stimulation (impact impulse). In the simulation of piston secondary movement and piston ring motion, forces arising from the combustion process, subsonic/supersonic gas flow between the combustion chamber and the crank case, inertial forces and forces resulting from the hydrodynamic lubrication between cylinder liner and piston shaft and piston rings and between piston ring flanks and piston grooves are considered. In addition it is possible to account for effects of global, three-dimensional ring deformation as well as local piston deformation, roughness effects in lubricated contacts, and variable viscosity and variable oil supply. The governing differential equations for the pressure as well as the deformation are solved via finite element techniques, while initial value problems are solved by efficient implicit time integration schemes. The application of the developed computer code is presented in examples.

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8

Ismagilov, Rinat R., Ildar R. Khamidullin, Kuo-Hui Yang e Alexander N. Obraztsov. "Computer Simulation Study of Gas Dynamics for Torches Operating at Atmosphere Pressure". Journal of Nanoelectronics and Optoelectronics 8, n. 1 (1 gennaio 2013): 119–23. http://dx.doi.org/10.1166/jno.2013.1440.

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9

Shi, H., e C. Kleinstreuer. "Simulation and Analysis of High-Speed Droplet Spray Dynamics". Journal of Fluids Engineering 129, n. 5 (19 ottobre 2006): 621–33. http://dx.doi.org/10.1115/1.2717621.

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An experimentally validated computer simulation model has been developed for the analysis of gas-phase and droplet characteristics of isothermal sprays generated by pressure jet atomizers. Employing a coupled Euler-Lagrange approach for the gas-droplet flow, secondary droplet breakup (based on the ETAB model), was assumed to be dominant and the k-ε model was selected for simulating the gas flow. Specifically, transient spray formation in terms of turbulent gas flow as well as droplet velocities and size distributions are provided for different back pressures. Clearly, two-way coupling of the phases is important because of the impact of significant gas entrainment, droplet momentum transfer, and turbulent dispersion. Several spray phenomena are discussed in light of low back-pressure (1atm) and high back-pressure (30atm) environments. At low back-pressure, sprays have long thin geometric features and penetrate faster and deeper than at high back-pressures because of the measurable change in air density and hence drag force. Away from the nozzle exit under relatively high back pressures, there is no distinct droplet size difference between peripheral and core regions because of the high droplet Weber numbers, leading to very small droplets which move randomly. In contrast to transient spray developments, under steady-state conditions droplets are subject to smaller drag forces due to the fully-developed gas entrainment velocities which reduce gas-liquid slip. Turbulent dispersion influences droplet trajectories significantly because of the impact of random gas-phase fluctuations.

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Turner, Dean E. "Dynamic Computer Simulation of the Motion of Gas Molecules". Journal of Chemical Education 71, n. 9 (settembre 1994): 784. http://dx.doi.org/10.1021/ed071p784.

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Tesi sul tema "Gas dynamics computer simulation"

1

Zhao, Yong. "Computer simulation of gas dynamics in engine manifolds". Thesis, University of Manchester, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318589.

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2

Foster, P. A. "The computer simulation of the gas dynamics in ring galaxy formation". Thesis, University of Manchester, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.375065.

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3

Lyons, Eric P. "Computer simulation of poly(ethylene terephthalate) and derivatives structure and their ramifications for gas transport". Thesis, Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/11039.

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4

JUNG, JANGWOOK PHILIP. "Computer Simulation of Transport of Small Molecules Through a Gas Channel Embedded in a Phospholipid Bilayer". University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1131054184.

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5

Shukla, Charu L. "Computationally Probing the Cybotactic Region in Gas-Expanded Liquids". Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14510.

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Gas-expanded liquids (GXLs) are novel and environmentally benign solvent systems with applications in reactions, separations, nanotechnology, drug delivery, and microelectronics. GXLs are liquid mixtures consisting of an organic solvent combined with a benign gas, such as CO2, in the nearcritical regime. In this work, molecular dynamics simulations have been combined with experimental techniques to elucidate the cybotactic region or local environment in gas-expanded liquids. Molecular dynamics simulations show clustering of methanol molecules in carbon dioxide-methanol mixtures. This clustering was not observed in carbon dioxide-acetone mixtures. Furthermore, addition of carbon dioxide enhances diffusivity of solutes in gas-expanded media as shown by both simulations and Taylor-Aris dispersion experiments. Finally, local structure and local compositions around pyrene in carbon dioxide-methanol and carbon-dioxide acetone were investigated using simulations and UV-vis spectroscopy.

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Gohres, John Linton III. "Spectroscopic and computational investigations of molecular interactions in gas-expanded liquids". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24692.

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Thesis (Ph.D.)--Chemical Engineering, Georgia Institute of Technology, 2008.
Committee Chair: Charles A. Eckert; Committee Co-Chair: Charles L. Liotta; Committee Member: J. Carson Meredith; Committee Member: Rigoberto Hernandez; Committee Member: William J. Koros

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Pinilla, Castellanos Carlos Celimo. "Computer simulation studies of the structure and dynamics of gas, liquid and solid phases of complex ionic liquids". Thesis, Queen's University Belfast, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.479393.

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8

Hendricks, Todd B. "An investigation into computer simulation of the dynamic response of a gas turbine engine". Springfield, Va. : Available from National Technical Information Service, 1997. http://handle.dtic.mil/100.2/ADA328006.

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9

Johnson, Perry L. "Toward increasing performance and efficiency in gas turbines for power generation and aero-propulsion unsteady simulation of angled discrete-injection coolant in a hot gas path crossflow". Honors in the Major Thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/444.

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This thesis describes the numerical predictions of turbine film cooling interactions using Large Eddy Simulations. In most engineering industrial applications, the Reynolds-Averaged Navier-Stokes equations, usually paired with two-equation models such as k-Greek lowercase letter epsilon] or k-Greek lowercase letter omega], are utilized as an inexpensive method for modeling complex turbulent flows. By resolving the larger, more influential scale of turbulent eddies, the Large Eddy Simulation has been shown to yield a significant increase in accuracy over traditional two-equation RANS models for many engineering flows. In addition, Large Eddy Simulations provide insight into the unsteady characteristics and coherent vortex structures of turbulent flows. Discrete hole film cooling is a jet-in-cross-flow phenomenon, which is known to produce complex turbulent interactions and vortex structures. For this reason, the present study investigates the influence of these jet-crossflow interactions in a time-resolved unsteady simulation. Because of the broad spectrum of length scales present in moderate and high Reynolds number flows, such as the present topic, the high computational cost of Direct Numerical Simulation was excluded from possibility.
B.S.M.E.
Bachelors
Engineering and Computer Science
Mechanical Engineering

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10

Ha, Oai The. "Modeling and Numerical Investigation of Hot Gas Defrost on a Finned Tube Evaporator Using Computational Fluid Dynamics". DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/400.

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Defrosting in the refrigeration industry is used to remove the frost layer accumulated on the evaporators after a period of running time. It is one way to improve the energy efficiency of refrigeration systems. There are many studies about the defrosting process but none of them use computational fluid dynamics (CFD) simulation. The purpose of this thesis is (1) to develop a defrost model using the commercial CFD solver FLUENT to simulate numerically the melting of frost coupled with the heat and mass transfer taking place during defrosting, and (2) to investigate the thermal response of the evaporator and the defrost time for different hot gas temperatures and frost densities. A 3D geometry of a finned tube evaporator is developed and meshed using Gambit 2.4.6, while numerical computations were conducted using FLUENT 12.1. The solidification and melting model is used to simulate the melting of frost and the Volume of Fluid (VOF) model is used to render the surface between the frost and melted frost during defrosting. A user-defined-function in C programming language was written to model the frost evaporation and sublimation taking place on the free surface between frost and air. The model was run under different hot gas temperatures and frost densities and the results were analyzed to show the effects of these parameters on defrosting time, input energy and stored energy in the metal mass of the evaporator. The analyses demonstrate that an optimal hot gas temperature can be identified so that the defrosting process takes place at the shortest possible melting time and with the lowest possible input energy.

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Libri sul tema "Gas dynamics computer simulation"

1

Computer simulation of dynamic phenomena. Berlin: Springer, 1999.

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2

Ferlet, X. F. Computer simulation of combustion and gas dynamics in racing engines. Manchester: UMIST, 1995.

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3

Xu, Kun. Rayleigh-Beńard simulation using gas-kinetic BGK scheme in the incompressible limit. Hampton, Va: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1998.

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4

Hendricks, Todd B. An investigation into computer simulation of the dynamic response of a gas turbine engine. Springfield, Va: Available from National Technical Information Service, 1997.

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5

Goldstein, David B. Creating a simple single computational approach to modeling rarefied and continuum flow about aerospace vehicles: Research summary for NASA Johnson Space Center's University Grant Program, grant number NAG 9-840. [Washington, DC: National Aeronautics and Space Administration, 1997.

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6

Molecular gas dynamics and the direct simulation of gas flows. Oxford: Clarendon Press, 1994.

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7

Bird, G. A. Molecular gas dynamics and the direct simulation of gas flows. Oxford: Clarendon Press, 1998.

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8

1937-, Amyot Joseph R., a cura di. Computer-aided simulation in railway dynamics. New York: M. Dekker, 1988.

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9

J, Tildesley D., a cura di. Computer simulation of liquids. Oxford [England]: Clarendon Press, 1996.

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10

J, Tildesley D., a cura di. Computer simulation of liquids. Oxford [England]: Clarendon Press, 1987.

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Capitoli di libri sul tema "Gas dynamics computer simulation"

1

Borisov, Sergey, Oleg Sazhin e Olesya Gerasimova. "The Monte Carlo and Molecular Dynamics Simulation of Gas-Surface Interaction". In Lecture Notes in Computer Science, 143–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11428862_21.

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2

de Graaf, L. A. "Analysis of Neutron Scattering and Computer Simulation Studies on Noble-Gas Fluids". In Static and Dynamic Properties of Liquids, 2–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74907-0_1.

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3

Berezovsky, Vladimir, Marsel Gubaydullin, Alexander Yur’ev e Ivan Belozerov. "Examination of Clastic Oil and Gas Reservoir Rock Permeability Modeling by Molecular Dynamics Simulation Using High-Performance Computing". In Communications in Computer and Information Science, 208–17. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05807-4_18.

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4

Becerra Fernández, Mauricio, Elsa Cristina González La Rotta, Federico Cosenz e Isaac Dyner Rezonzew. "Supporting the Natural Gas Supply Chain Public Policies Through Simulation Methods: A Dynamic Performance Management Approach". In Communications in Computer and Information Science, 363–76. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00350-0_31.

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Roberson, Robert E., e Richard Schwertassek. "Computer Simulation". In Dynamics of Multibody Systems, 365–411. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-86464-3_14.

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6

Sutugin, A. G., A. J. Simonov, V. N. Korpusov, S. K. Ayzatulin e V. Y. Kostromin. "Simulation of the Process of the Cosmic Body Formation". In Rarefied Gas Dynamics, 1413–20. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2467-6_73.

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7

Schwan, W., M. Fiebig, N. K. Mitra e A. U. Chatwani. "Investigation of Nonequilibrium Effects in Separation Nozzles by Monte-Carlo Simulation". In Rarefied Gas Dynamics, 1327–39. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4613-2467-6_65.

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8

Kersch, Alfred, e William J. Morokoff. "Numerical Methods for Rarefied Gas Dynamics". In Transport Simulation in Microelectronics, 77–99. Basel: Birkhäuser Basel, 1995. http://dx.doi.org/10.1007/978-3-0348-9080-9_3.

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Stauffer, Dietrich, Friedrich W. Hehl, Nobuyasu Ito, Volker Winkelmann e John G. Zabolitzky. "Dynamics of Strings". In Computer Simulation and Computer Algebra, 59–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78117-9_6.

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Seguchi, Y., Y. C. Fung e T. Ishida. "Respiratory Dynamics—Computer Simulation". In Frontiers in Biomechanics, 377–91. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4866-8_27.

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Atti di convegni sul tema "Gas dynamics computer simulation"

1

Liang, Guangchuan, e Bingqiang Zhang. "The Dynamic Simulation of Underground Gas Storage by Computer". In 2011 International Conference on Computational and Information Sciences (ICCIS). IEEE, 2011. http://dx.doi.org/10.1109/iccis.2011.289.

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2

Degtyarev, Vladimir M., e Michael N. Gusev. "Computer simulation of gas dynamic process for a jet engine". In Fourth International Workshop on Nondestructive Testing and Computer Simulations in Science and Engineering. SPIE, 2001. http://dx.doi.org/10.1117/12.417684.

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3

Palmer, Carl A., e Kenneth W. Ragland. "Dynamic Simulation of the Gravel Bed Combustor-Gas Turbine System". In ASME 1991 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/91-gt-285.

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A novel gravel bed, downdraft, woodchip combustor that directly-fires a gas turbine for use in a cogeneration system has been developed. In this combustor, the fuel burning rate is determined by pressure, temperature, air flow rate, and fuel moisture content, and not by the fuel feed rate. When the gravel bed combustor is connected to a gas turbine system, the operator loses the freedom to directly set the fuel flow rate, which is the primary control variable for conventional gas turbine systems. Other control problems introduced by the gravel bed include a large thermal lag and a sizable pressure drop. This paper presents a computer model that integrates the dynamic characteristics of an actual gas turbine with the characteristics of the gravel bed combustor. The program determines system behavior and helps evaluate possible control strategies. The system is controlled using the CO2 level leaving the gravel bed. The bypass valve setting determines the load level. Both the slow temperature dynamics and quick turbomachinery dynamics must be considered when operating the system.

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Xu, Yuna, Wu Liu, Muyang Ai, Yi Liu e Denghai Wang. "Research on Dynamic Simulation for Leakage of Natural Gas Pipeline". In 2010 Second International Conference on Computer Modeling and Simulation (ICCMS). IEEE, 2010. http://dx.doi.org/10.1109/iccms.2010.271.

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5

Schobeiri, T., M. Abouelkheir e C. Lippke. "GETRAN: A Generic, Modularly Structured Computer Code for Simulation of Dynamic Behavior of Aero- and Power Generation Gas Turbine Engines". In ASME 1993 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/93-gt-388.

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The design concept, the theoretical background essential for the development of the modularly structured simulation code GETRAN, and several critical simulation cases are presented in this paper. The code being developed under contract with NASA Lewis Research Center is capable of simulating the nonlinear dynamic behavior of single- and multi-spool core engines, turbofan engines, and power generation gas turbine engines under adverse dynamic operating conditions. The modules implemented into GETRAN correspond to components of existing and new generation aero- and stationary gas turbine engines with arbitrary configuration and arrangement. For precise simulation of turbine and compressor components, row-by-row diabatic and adiabatic calculation procedures are implemented that account for the specific turbine and compressor cascade, blade geometry, and characteristics. The nonlinear, dynamic behavior of the subject engine is calculated solving a number of systems of partial differential equations, which describe the unsteady behavior of each component individually. To unambiguously identify each differential equation system, special attention is paid to the addressing of each component. The code is capable of executing the simulation procedure at four levels which increase with the degree of complexity of the system and dynamic event. As representative simulations, four different transient cases with single- and multi-spool thrust and power generation engines were simulated. These transient cases vary from throttling the exit nozzle area, operation with fuel schedule, rotor speed control, to rotating stall and surge.

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Sun, Jin, Francine Battaglia e S. Subramaniam. "Hybrid Two-Fluid DEM Simulation of Gas-Solid Fluidized Beds". In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14831.

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Simulations of gas-solid fluidized beds have been carried out using a hybrid simulation method, which couples the discrete element method (DEM) for particle dynamics with the ensemble-averaged two-fluid (TF) equations for the fluid phase. The coupling between the two phases is modeled using an interphase momentum transfer term. The results of the hybrid TF-DEM simulations are compared to experimental data and two-fluid model simulations. It is found that the TF-DEM simulation is capable of predicting general fluidized bed dynamics, i.e., pressure drop across the bed and bed expansion, which are in agreement with experimental measurements and two-fluid model predictions. In addition, the TF-DEM model demonstrates the capability to capture more heterogeneous structural information of the fluidized beds than the two-fluid model alone. The microstructures in fluidized beds are analyzed and the implications to kinetic theory for granular flows are discussed. However, the TF-DEM simulations depend on the form of the interphase momentum transfer model, which can be computed in terms of averaged or instantaneous particle quantities. Various forms of the interphase momentum transfer model are examined, and their suitability to the hybrid TF-DEM simulation approach is evaluated.

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Akhmedzyanov, Albert, e Dmitry Kozhinov. "About approach to computer simulation of thermo-gas-dynamic processes in aircraft engines". In 35th Joint Propulsion Conference and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1999. http://dx.doi.org/10.2514/6.1999-2846.

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Avanessian, Tadeh, e Gisuk Hwang. "Adsorption-Controlled Thermal Switch Using Nonequilibrium Molecular Dynamics Simulation". In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-66707.

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A thermal switch is a system to control the heat transfer “on/off” for the desired functionalities, and this serves as a basic building block to design advanced thermal management systems in various applications including electronic packaging, waste heat recovery, cryogenic cooling, and new applications such as thermal computers. The existing thermal switches employ the macroscale mechanical-based, relatively slow transient “on/off” switch mechanisms, which may be challenging to provide solutions for micro/nanoscale applications. In this study, a fast and efficient thermal switch mechanism without having extra mechanical controlling system is demonstrated using gas-filled, heterogeneous nanogaps with asymmetric surface interactions in Knudsen regime. Argon gas atoms confined in metal-based solid surfaces are employed to predict the degree of thermal switch, S. Non-equilibrium molecular dynamics simulation is used to create the temperature gradient over the two nanogaps, and the maximum degree of thermal switch is Smax ∼ 13, which results from the difference in adsorption-controlled thermal accommodation coefficient (TAC) and pressure between the two sides of the gaps.

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Perez-Blanco, Horacio, e Todd B. Henricks. "A Gas Turbine Dynamic Model for Simulation and Control". In ASME 1998 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/98-gt-078.

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The useful life of gas turbines and the availability of power after start-up depend on their transient response. For this reason, several articles have been written on the dynamic simulation of gas turbine systems in electrical generation, cogeneration, and marine applications. The simulations typically rely on performance maps and time lags extracted from manufacturer’s specifications. This work was undertaken to increase the generality of turbine models over what can be obtained from performance maps. The paper describes a mathematical computer model developed to investigate the dynamic response of a simple single-shaft gas turbine system. The model uses design parameters normally incorporated in gas turbine design (e.g. load coefficient, flow coefficient, and deHaller Number) as well as compressor and turbine stage geometry and compressor and turbine material properties. A dynamic combustion chamber model is also incorporated. Other input parameters are included to enable the model to be adaptable to various system sizes and environments. The model was formulated in a graphical interface, and the results of several trials are displayed. The influence of important parameters (e.g. fuel-air ratio, IGVs, load, efficiencies) on turbine response from a “cold” start and from steady-state is studied. To gain further insights into the response, a start-up procedure similar to that reported in the literature for an industrial gas turbine system is simulated. Because of the approach used, the computer model is easily adaptable to further improvements and combined simulation of turbines and control systems.

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Mirnouri Langroudi, S. M., M. Ghasemi, A. Shahabi e H. Rezaei Nejad. "Investigation of Bubble Nucleation on Platinum Solid Surface Using Molecular Dynamics (MD) Simulation". In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-25114.

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The main purpose of this paper is to numerically investigate the contact angle of a bubble on a solid surface and the effect of bubble curvature on the surface tension. A computer code based on Molecular Dynamics method is developed. The code carries out a series of simulations to generate bubbles between two planar solid surfaces for different wettabilities. In our simulation, the surface wettability affects the bubble contact angle and curvature. The pair potential for the liquid–liquid and liquid-solid interaction is considered using Lennard-Jones model. Density profiles are locally calculated. Furthermore, surface tension is computed using Young-Laplace equation. It is observed that the gas pressure is independent of the bubble radius. However, the liquid pressure becomes more negative as the radius decreases. In addition, the amount of surface tension decreases by decrease of the radius.

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Rapporti di organizzazioni sul tema "Gas dynamics computer simulation"

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Wirth, B. D., M. J. Caturla e Diaz de la Rubia, T. Modeling and Computer Simulation: Molecular Dynamics and Kinetic Monte Carlo. Office of Scientific and Technical Information (OSTI), ottobre 2000. http://dx.doi.org/10.2172/792741.

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2

Chi, Joseph. Dynamics of Marine Cloud Layers: Computer Simulation and Experimental Verification. Fort Belvoir, VA: Defense Technical Information Center, dicembre 1998. http://dx.doi.org/10.21236/ada358174.

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Wolf, R. A. Computer Simulation of the Dynamics of the Near-Earth Part of the Geomagnetic Tail. Fort Belvoir, VA: Defense Technical Information Center, maggio 1986. http://dx.doi.org/10.21236/ada169449.

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Shahriar, Selim. (QC Themes) Type-Two Quantum Computing in PBG-Based Cavities for Efficient Simulation of Lattice Gas Dynamics. Fort Belvoir, VA: Defense Technical Information Center, aprile 2008. http://dx.doi.org/10.21236/ada481605.

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5

Bishir, John, James Roberds, Brian Strom e Xiaohai Wan. Documentation and user guides for SPBLOB: a computer simulation model of the join population dynamics for loblolly pine and the southern pine beetle. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 2009. http://dx.doi.org/10.2737/srs-gtr-114.

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Bishir, John, James Roberds, Brian Strom e Xiaohai Wan. Documentation and user guides for SPBLOB: a computer simulation model of the join population dynamics for loblolly pine and the southern pine beetle. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station, 2009. http://dx.doi.org/10.2737/srs-gtr-114.

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Bobashev, Georgiy, John Holloway, Eric Solano e Boris Gutkin. A Control Theory Model of Smoking. RTI Press, giugno 2017. http://dx.doi.org/10.3768/rtipress.2017.op.0040.1706.

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We present a heuristic control theory model that describes smoking under restricted and unrestricted access to cigarettes. The model is based on the allostasis theory and uses a formal representation of a multiscale opponent process. The model simulates smoking behavior of an individual and produces both short-term (“loading up” after not smoking for a while) and long-term smoking patterns (e.g., gradual transition from a few cigarettes to one pack a day). By introducing a formal representation of withdrawal- and craving-like processes, the model produces gradual increases over time in withdrawal- and craving-like signals associated with abstinence and shows that after 3 months of abstinence, craving disappears. The model was programmed as a computer application allowing users to select simulation scenarios. The application links images of brain regions that are activated during the binge/intoxication, withdrawal, or craving with corresponding simulated states. The model was calibrated to represent smoking patterns described in peer-reviewed literature; however, it is generic enough to be adapted to other drugs, including cocaine and opioids. Although the model does not mechanistically describe specific neurobiological processes, it can be useful in prevention and treatment practices as an illustration of drug-using behaviors and expected dynamics of withdrawal and craving during abstinence.

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