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Letteratura scientifica selezionata sul tema "Flow modeling"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 9 giugno 2025

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Articoli di riviste sul tema "Flow modeling"

1

Sindeev, S. V., S. V. Frolov, D. Liepsch, and A. Balasso. "MODELING OF FLOW ALTERATIONS INDUCED BY FLOW-DIVERTER USING MULTISCALE MODEL OF HEMODYNAMICS." Vestnik Tambovskogo gosudarstvennogo tehnicheskogo universiteta 23, no. 1 (2017): 025–32. http://dx.doi.org/10.17277/vestnik.2017.01.pp.025-032.

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2

Elizabeth Philip, Babitha, and Jaseela K H. "Traffic Flow Modeling and Study of Traffic Congestion." International Journal of Scientific Engineering and Research 4, no. 1 (January 27, 2016): 67–68. https://doi.org/10.70729/ijser15667.

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3

Giovangigli, Vincent. "Multicomponent flow modeling." Science China Mathematics 55, no. 2 (December 20, 2011): 285–308. http://dx.doi.org/10.1007/s11425-011-4346-y.

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4

Carr, John, and Mark Howells. "Modeling pig flow." Livestock 21, no. 3 (May 2, 2016): 180–86. http://dx.doi.org/10.12968/live.2016.21.3.180.

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5

Melikyan, V. Sh, V. D. Hovhannisyan, M. T. Grigoryan, A. A. Avetisyan, and H. T. Grigoryan. "Real Number Modeling Flow of Digital to Analog Converter." Proceedings of Universities. Electronics 26, no. 2 (April 2021): 144–53. http://dx.doi.org/10.24151/1561-5405-2021-26-2-144-153.

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This work introduces a flow of digital to analog (DAC) implementation in digital environment of SystemVerilog. Unlike the classical Verilog models, this digital to analog converter behavioral model is analog. Such type of model creation in general is called real number modeling. The DAC model is verified by the HSPICE and SystemVerilog Co-simulations which show its applicability in different register transfer level verification environments. The digital environment with real number modeled DAC runs around 8 times faster than the same environment with SPICE model. At the same time, the output signal’s voltage difference between RNM and SPICE models is less than 2 mV.

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6

Xiong, Jinbiao, Seiichi Koshizuka, and Mikio Sakai. "ICONE19-43282 TURBULENCE MODELING FOR MASS TRANSFER IN SEPARATED AND REATTACHING FLOWS FOR FLOW-ACCELERATED CORROSION." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2011.19 (2011): _ICONE1943. http://dx.doi.org/10.1299/jsmeicone.2011.19._icone1943_119.

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Pohll, G. M., and J. C. Guitjens. "Modeling Regional Flow and Flow to Drains." Journal of Irrigation and Drainage Engineering 120, no. 5 (September 1994): 925–39. http://dx.doi.org/10.1061/(asce)0733-9437(1994)120:5(925).

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8

Khan, Sarosh I., and Pawan Maini. "Modeling Heterogeneous Traffic Flow." Transportation Research Record: Journal of the Transportation Research Board 1678, no. 1 (January 1999): 234–41. http://dx.doi.org/10.3141/1678-28.

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Alley, R. B., and I. Joughin. "Modeling Ice-Sheet Flow." Science 336, no. 6081 (May 3, 2012): 551–52. http://dx.doi.org/10.1126/science.1220530.

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Ninković, Vladimir. "Dynamic migration flow modeling." Security Dialogues /Безбедносни дијалози 1-2 (2017): 149–67. http://dx.doi.org/10.47054/sd171-20149n.

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Tesi sul tema "Flow modeling"

1

Cappiello, Alessandra 1972. "Modeling traffic flow emissions." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/84328.

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2

Boulay, Fabienne. "Suspension-flow modeling : curvilinear flows and normal stress differences." Thesis, Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/11689.

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Rycroft, Christopher Harley. "Multiscale modeling in granular flow." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41557.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2007.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (p. 245-254).<br>Granular materials are common in everyday experience, but have long-resisted a complete theoretical description. Here, we consider the regime of slow, dense granular flow, for which there is no general model, representing a considerable hurdle to industry, where grains and powders must frequently be manipulated. Much of the complexity of modeling granular materials stems from the discreteness of the constituent particles, and a key theme of this work has been the connection of the microscopic particle motion to a bulk continuum description. This led to development of the "spot model", which provides a microscopic mechanism for particle rearrangement in dense granular flow, by breaking down the motion into correlated group displacements on a mesoscopic length scale. The spot model can be used as the basis of a multiscale simulation technique which can accurately reproduce the flow in a large-scale discrete element simulation of granular drainage, at a fraction of the computational cost. In addition, the simulation can also successfully track microscopic packing signatures, making it one of the first models of a flowing random packing. To extend to situations other than drainage ultimately requires a treatment of material properties, such as stress and strain-rate, but these quantities are difficult to define in a granular packing, due to strong heterogeneities at the level of a single particle. However, they can be successfully interpreted at the mesoscopic spot scale, and this information can be used to directly test some commonly-used hypotheses in modeling granular materials, providing insight into formulating a general theory.<br>by Christopher Harley Rycroft.<br>Ph.D.

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4

El, Kheiashy Karim. "Flow-Transport Modeling and Quantification." ScholarWorks@UNO, 2007. http://scholarworks.uno.edu/td/548.

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Several research investigations have been conducted on the flow and sediment transport over bed forms in alluvial rivers (e.g. mean flow field, turbulence, shear partitioning, bed load transport and bed form geometry). Much of this work was either laboratory studies or small scale field investigations. Recently, advance in technology have improved the way data are collected and analyzed, e.g. flow data, velocity data and detailed bathymetric information that provide greater knowledge about the bed form geometry. Recent advances in computing power have also reduced the computational restrictions on using three dimensional numerical models in modeling flow applications to predict the temporal and spatial changes of flow and sediment environments. The work performed in this research quantified the periodic nature of bed forms types and geometries along the Lower Mississippi river. Correlations were performed relating the hydrodynamics of the river to the bed form types and geometries. The research work showed the inability of hydrostatic numerical modeling systems to accurately predict flow separation at the bed form crest but indicated that these models could reasonably predict the out of phase relationship between the bed form and the water surface profile. Furthermore the hydrostatic models predicted the total bed resistance as adequately as the non-hydrostatic models. It was found that non-hydrostatic models are required to properly simulate flow separation at bed form crests. Models such as MIKE 3 with constant z-level vertical discretization failed to capture the observed boundary layers unless very fine grids are used. A new procedure was developed as a part of this research, in which relations and dependencies between the hydrodynamic resistance and the bed form dimensions relative to the numerical model spatial scale were derived. This procedure can be used to aid in numerical riverine model calibration and to provide a better representation of flow resistance in hydrodynamic modeling codes.

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Daniel, Michael M. "Multiresolution statistical modeling with application to modeling groundwater flow." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/10749.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.<br>Includes bibliographical references (p. 205-211).<br>by Michael M. Daniel.<br>Ph.D.

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6

Sharma, Yugdutt. "Modeling transient two-phase slug flow /." Access abstract and link to full text, 1985. http://0-wwwlib.umi.com.library.utulsa.edu/dissertations/fullcit/8605319.

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Kouba, Gene E. "Horizontal slug flow modeling and metering /." Access abstract and link to full text, 1986. http://0-wwwlib.umi.com.library.utulsa.edu/dissertations/fullcit/8700712.

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8

Tao, Ye. "Optimal power flow via quadratic modeling." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/45766.

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Optimal power flow (OPF) is the choice tool for determining the optimal operating status of the power system by managing controllable devices. The importance of the OPF approach has increased due to increasing energy prices and availability of more control devices. Existing OPF approaches exhibit shortcomings. Current OPF algorithms can be classified into (a) nonlinear programming, (b) intelligent search methods, and (c) sequential algorithms. Nonlinear programming algorithms focus on the solution of the Kuhn-Tucker conditions; they require a starting feasible solution and the model includes all constraints; these characteristics limit the robustness and efficiency of these methods. Intelligent search methods are first-order methods and are totally inefficient for large-scale systems. Traditional sequential algorithms require a starting feasible solution, a requirement that limits their robustness. Present implementations of sequential algorithms use traditional modeling that result in inefficient algorithms. The research described in this thesis has overcome the shortcomings by developing a robust and highly efficient algorithm. Robustness is defined as the ability to provide a solution for any system; the proposed approach achieves robustness by operating on suboptimal points and moving toward feasible, it stops at a suboptimal solution if an optimum does not exist. Efficiency is achieved by (a) converting the nonlinear OPF problem to a quadratic problem (b) and limiting the size of the model; the quadratic model enables fast convergence and the algorithm that identifies the active constraints, limits the size of the model by only including the active constraints. A concise description of the method is as follows: The proposed method starts from an arbitrary state which may be infeasible; model equations and system constraints are satisfied by introducing artificial mismatch variables at each bus. Mathematically this is an optimal but infeasible point. At each iteration, the artificial mismatches are reduced while the solution point maintains optimality. When mismatches reach zero, the solution becomes feasible and the optimum has been found; otherwise, the mismatch residuals are converted to load shedding and the algorithm provides a suboptimal but feasible solution. Therefore, the algorithm operates on infeasible but optimal points and moves towards feasibility. The proposed algorithm maximizes efficiency with two innovations: (a) quadratization that converts the nonlinear model to quadratic with excellent convergence properties and (b) minimization of model size by identifying active constraints, which are the only constraints included in the model. Finally sparsity technique is utilized that provide the best computational efficiency for large systems. This dissertation work demonstrates the proposed OPF algorithm using various systems up to three hundred buses and compares it with several well-known OPF software packages. The results show that the proposed algorithm converges fast and its runtime is competitive. Furthermore, the proposed method is extended to a three-phase OPF (TOPF) algorithm for unbalanced networks using the quadratized three-phase power system model. An example application of the TOPF is presented. Specifically, TOPF is utilized to address the problem of fault induced delayed voltage recovery (FIDVR) phenomena, which lead to unwanted relay operations, stalling of motors and load disruptions. This thesis presents a methodology that will optimally enhance the distribution system to mitigate/eliminate the onset of FIDVR. The time domain simulation method has been integrated with a TOPF model and a dynamic programming optimization algorithm to provide the optimal reinforcing strategy for the circuits.

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Yu, Tungsheng. "Traffic flow modeling in highway networks." Master's thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-12232009-020154/.

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Ocampo, Roel Maglente. "Understanding, modeling and using flow context." Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1445746/.

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This thesis presents a concept called flow context, defined as any information that can be used to characterize the situation of a sequence of protocol data units, called a flow, within a network. Flow context is designed to enable the realization of context-aware networks: networks that can sense, process, disseminate and use context information in order to enable or trigger services, or modify and optimize their operation. The thesis discusses a conceptualization for flow context, and describes its characteristics. A semantic model for flows and flow context in the form of an OWL-DL ontology is developed. The various components of the flow context life cycle, consisting of the stages of sensing, processing, dissemination and use, arc described. To account for its multi-faceted nature, a multi-dimensional approach to sensing flow con text is adopted. Novel implementations for three exemplar sensors, including sensors for intrinsic flow context, node and device characteristics, and for device location, are pre sented. Mechanisms for locating flow context sensors and propagating context event notifications using a distributed hash table (DHT) are described and evaluated. Simulation results suggest that DHTs can provide decentralized and scalable solutions for flow context location and dissemination. In addition, a novel mode of context distribution called path-coupled flow context dissemination is described. An evaluation of semantic flow context processing using the RacerPro reasoner is presented. Various platform-specific reasoning modes are tested, including the use of queries, ABox modification, and incomplete reasoning. Finally, several application scenarios illustrating the potential uses of flow context in areas such as mobility and moving networks, quality of service, intelligent flow classification, network management, and other applications, are presented. Many of these scenarios are demonstrated through proof-of-concept implementations, which may be further evaluated and developed into full, working, and useful applications.

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Libri sul tema "Flow modeling"

1

Chin, Wilson C. Borehole flow modeling. Houston: Gulf Pub. Co., 1992.

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2

Giovangigli, Vincent. Multicomponent Flow Modeling. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1580-6.

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3

Papadimitriou, Dimitri B., and Gennaro Zezza, eds. Contributions in Stock-flow Modeling. London: Palgrave Macmillan UK, 2012. http://dx.doi.org/10.1057/9780230367357.

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4

Sheng, Chunhua. Advances in Transitional Flow Modeling. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-32576-7.

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Bear, Jacob, and Arnold Verruijt. Modeling Groundwater Flow and Pollution. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3379-8.

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Morel-Seytoux, H. J., ed. Unsaturated Flow in Hydrologic Modeling. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2352-2.

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Institute for Computer Applications in Science and Engineering., ed. Modeling jets in cross flow. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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8

Zai-chao, Liang, Chen Ching Jen 1936-, and Cai Shutang, eds. Flow modeling and turbulence measurements. Washington: Hemisphere Pub., 1992.

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9

1936-, Chen Ching Jen, Chen L-D, Holly F. M. 1946-, International Symposium on Refined Flow Modelling and Turbulence Measurements (1985 : University of Iowa), International Symposium on Refined Modelling of Flows (2nd : 1985 : University of Iowa), and Symposium on Measurement Techniques and Prediction Methods in Turbulent Flow (2nd : 1985 : University of Iowa), eds. Turbulence measurements and flow modeling. Washington: Hemisphere Pub. Corp., 1987.

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10

Rajan, M. T. Regional groundwater modeling. New Delhi: Capital Pub. Co., 2004.

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Capitoli di libri sul tema "Flow modeling"

1

Holzbecher, Ekkehard. "Flow Modeling." In Environmental Modeling, 217–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22042-5_11.

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2

Greenspan, Donald. "Cavity Flow." In Particle Modeling, 71–82. Boston, MA: Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-1992-7_7.

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3

Paquier, André, Patrick Chassé, Nicole Goutal, and Amélie Besnard. "1D Flow Models." In Modeling Software, 177–200. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118557891.ch15.

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Jakobsen, Hugo A. "Multiphase Flow." In Chemical Reactor Modeling, 369–536. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05092-8_3.

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5

Chaudhry, M. Hanif. "LEVEE BREACH MODELING." In Open-Channel Flow, 461–88. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96447-4_16.

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6

Giovangigli, Vincent. "Introduction." In Multicomponent Flow Modeling, 1–4. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1580-6_1.

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7

Giovangigli, Vincent. "Chemical Equilibrium Flows." In Multicomponent Flow Modeling, 245–64. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1580-6_10.

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Giovangigli, Vincent. "Anchored Waves." In Multicomponent Flow Modeling, 265–300. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1580-6_11.

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9

Giovangigli, Vincent. "Numerical Simulations." In Multicomponent Flow Modeling, 301–15. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1580-6_12.

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10

Giovangigli, Vincent. "Fundamental Equations." In Multicomponent Flow Modeling, 5–36. Boston, MA: Birkhäuser Boston, 1999. http://dx.doi.org/10.1007/978-1-4612-1580-6_2.

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Atti di convegni sul tema "Flow modeling"

1

Myers, T. M., A. W. Marshall, and H. R. Baum. "Simplified modeling of sprinkler head fluid mechanics." In MULTIPHASE FLOW 2013. Southampton, UK: WIT Press, 2013. http://dx.doi.org/10.2495/mpf130211.

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2

Ramakrishnan, Srinivas, and Samuel Collis. "Variational Multiscale Modeling for Turbulence Control." In 1st Flow Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-3280.

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3

Vorobieff, P., M. Anderson, J. Conroy, C. Randall Truman, and S. Kumar. "Morphology of shock-accelerated multiphase flow: experiment and modeling." In MULTIPHASE FLOW 2013. Southampton, UK: WIT Press, 2013. http://dx.doi.org/10.2495/mpf130021.

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Truman, C. Randall, M. Anderson, P. Vorobieff, P. Wayne, C. Corbin, T. Bernard, and G. Kuehner. "Morphology of shock-accelerated multiphase flow: experiment and modeling." In MULTIPHASE FLOW 2013. Southampton, UK: WIT Press, 2013. http://dx.doi.org/10.2495/mpf130111.

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5

Ali, T. Ait, S. Khelladi, L. Ramirez, and X. Nogueira. "Cavitation modeling using compressible Navier–Stokes and Korteweg equations." In MULTIPHASE FLOW 2015. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/mpf150361.

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Seifert, A., R. Joslin, and Vassilis Theofilis. "Flow Control Experiments, Simulation and Modeling Approaches (Invited)." In 1st Flow Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-3277.

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Bisantino, T., P. Fischer, F. Gentile, and G. Trisorio Liuzzi. "Rheological properties and debris-flow modeling in a southern Italy watershed." In DEBRIS FLOW 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/deb100201.

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Kayakol, N. "CFD modeling of cavitation in solenoid valves for diesel fuel injection." In MULTIPHASE FLOW 2015. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/mpf150351.

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Tran, A. T. T., and M. M. Hyland. "Modeling of micrometre-sized molten metallic droplet impact on a solid wall." In MULTIPHASE FLOW 2015. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/mpf150321.

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Campos, L. D. O., P. Gardin, S. Vincent, and J. P. Caltagirone. "Physical modeling of turbulent multiphase flow in a continuous casting steel mold." In MULTIPHASE FLOW 2015. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/mpf150371.

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Rapporti di organizzazioni sul tema "Flow modeling"

1

White, Annie, and Jacob Riglin. Taylor-Couette Flow Modeling. Office of Scientific and Technical Information (OSTI), September 2024. http://dx.doi.org/10.2172/2448298.

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Allen, John S. Modeling of Coastal Ocean Flow Fields. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada398915.

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3

Le MaÒitre, Olivier P., Matthew T. Reagan, Omar M. Knio, Roger Georges Ghanem, and Habib N. Najm. Uncertainty quantification in reacting flow modeling. Office of Scientific and Technical Information (OSTI), October 2003. http://dx.doi.org/10.2172/918251.

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Allen, John S. Modeling of Coastal Ocean Flow Fields. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada609936.

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5

Patnaik, Soumya S., Eugeniya Iskrenova-Ekiert, and Hui Wan. Multiscale Modeling of Multiphase Fluid Flow. Fort Belvoir, VA: Defense Technical Information Center, August 2016. http://dx.doi.org/10.21236/ad1016834.

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Allen, John S. Modeling of Coastal Ocean Flow Fields. Fort Belvoir, VA: Defense Technical Information Center, March 1995. http://dx.doi.org/10.21236/ada300401.

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Allen, John S. Modeling of Coastal Ocean Flow Fields. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada627902.

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Winters, Kraig B. Modeling Non-Hydrostatic Flow Over Topography. Fort Belvoir, VA: Defense Technical Information Center, August 2002. http://dx.doi.org/10.21236/ada629083.

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Allen, John S. Modeling of Coastal Ocean Flow Fields. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada629791.

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10

Allen, John S. Modeling of Coastal Ocean Flow Fields. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada630171.

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