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Littérature scientifique sur le sujet « Computational fluid dynamics »

Auteur : Grafiati

Publié le 4 juin 2021

Mis à jour le 1 mars 2025

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Articles de revues sur le sujet "Computational fluid dynamics"

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Thabet, Senan, et Thabit H. Thabit. « Computational Fluid Dynamics : Science of the Future ». International Journal of Research and Engineering 5, n^o 6 (2018) : 430–33. http://dx.doi.org/10.21276/ijre.2018.5.6.2.

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KAWAMURA, Tetuya, et Hideo TAKAMI. « Computational Fluid Dynamics ». Tetsu-to-Hagane 75, n^o 11 (1989) : 1981–90. http://dx.doi.org/10.2355/tetsutohagane1955.75.11_1981.

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Birchall, D. « Computational fluid dynamics ». British Journal of Radiology 82, special_issue_1 (janvier 2009) : S1—S2. http://dx.doi.org/10.1259/bjr/26554028.

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Lin, Ching-long, Merryn H. Tawhai, Geoffrey Mclennan et Eric A. Hoffman. « Computational fluid dynamics ». IEEE Engineering in Medicine and Biology Magazine 28, n^o 3 (mai 2009) : 25–33. http://dx.doi.org/10.1109/memb.2009.932480.

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Wrobel, L. C. « Computational fluid dynamics ». Engineering Analysis with Boundary Elements 9, n^o 2 (janvier 1992) : 192. http://dx.doi.org/10.1016/0955-7997(92)90070-n.

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Pericleous, K. A. « Computational fluid dynamics ». International Journal of Heat and Mass Transfer 32, n^o 1 (janvier 1989) : 197–98. http://dx.doi.org/10.1016/0017-9310(89)90105-1.

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Von Wendt, J. « Computational fluid dynamics ». Journal of Wind Engineering and Industrial Aerodynamics 40, n^o 2 (juin 1992) : 223. http://dx.doi.org/10.1016/0167-6105(92)90368-k.

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Lax, Peter D. « Computational Fluid Dynamics ». Journal of Scientific Computing 31, n^o 1-2 (25 octobre 2006) : 185–93. http://dx.doi.org/10.1007/s10915-006-9104-x.

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Pitarma, R. A., J. E. Ramos, M. E. Ferreira et M. G. Carvalho. « Computational fluid dynamics ». Management of Environmental Quality : An International Journal 15, n^o 2 (avril 2004) : 102–10. http://dx.doi.org/10.1108/14777830410523053.

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Leschziner, M. A. « Computational fluid dynamics ». International Journal of Heat and Fluid Flow 11, n^o 1 (mars 1990) : 82–83. http://dx.doi.org/10.1016/0142-727x(90)90031-6.

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Thèses sur le sujet "Computational fluid dynamics"

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Hussain, Muhammad Imtiaz. « Computational fluid dynamics ». Thesis, Aberystwyth University, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.257607.

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Ellam, Darren John. « Modelling smart fluid devices using computational fluid dynamics ». Thesis, University of Sheffield, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398597.

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Katz, Aaron Jon. « Meshless methods for computational fluid dynamics / ». May be available electronically:, 2009. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Molale, Dimpho Millicent. « A computational evaluation of flow through porous media ». Thesis, Link to the online version, 2007. http://hdl.handle.net/10019/686.

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Pagliuca, Giampaolo. « Model reduction for flight dynamics using computational fluid dynamics ». Thesis, University of Liverpool, 2018. http://livrepository.liverpool.ac.uk/3029018/.

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The coupling of computational fluid dynamics and rigid body dynamics promises enhanced multidisciplinary simulation capability for aircraft design and certification. Industrial application of such coupled simulations is limited however by computational cost. In this context, model reduction can retain the fidelity of the underlying model while decreasing the overall computational effort. Thus, investigation of such coupled model reduction is presented in this thesis. The technique described herein relies on an expansion of the full order non-linear residual function in a truncated Taylor series and subsequent projection onto a small modal basis. Two procedures are outlined to obtain modes for the projection. First, flight dynamics eigenmodes are obtained with an operator-based identification procedure which is capable of calculating the global modes of the coupled Jacobian matrix related to flight dynamics without computing all the modes of the system. Secondly, proper orthogonal decomposition is used as a data-based method to obtain modes representing the coupled system subject to external disturbances such as gusts. Benefits and limitations of the two methods are investigated by analysing results for both initial and external disturbance simulations. Three test cases of increasing complexity are presented. First, an aerofoil, free to translate vertically and rotate, is investigated with aerodynamics based on the Euler equations. Secondly, a two-dimensional wing-tail configuration is studied for longitudinal dynamics. Aerodynamics is modelled with Reynolds-averaged Navier-Stokes equations and Spalart-Allmaras turbulence model. Thirdly, a three-dimensional industrial use case, which concerns a large civil aircraft, is investigated and longitudinal as well as lateral dynamics are both taken into account. Overall, reduced order models relying on both operator-based and data-based identifications are able to retain the accuracy of the high-fidelity tools to predict accurately flight dynamics responses and loads while reducing the computational cost by up to two orders of magnitude. If adopted, these techniques are expected to speed-up aircraft design and lowering certification costs with the final aim of reduced expense for airlines and, as a consequence, for flying passengers.

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Da, Ronch Andrea. « On the calculation of dynamic derivatives using computational fluid dynamics ». Thesis, University of Liverpool, 2012. http://livrepository.liverpool.ac.uk/5513/.

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In this thesis, the exploitation of computational fluid dynamics (CFD) methods for the flight dynamics of manoeuvring aircraft is investigated. It is demonstrated that CFD can now be used in a reasonably routine fashion to generate stability and control databases. Different strategies to create CFD-derived simulation models across the flight envelope are explored, ranging from combined low-fidelity/high-fidelity methods to reduced-order modelling. For the representation of the unsteady aerodynamic loads, a model based on aerodynamic derivatives is considered. Static contributions are obtained from steady-state CFD calculations in a routine manner. To more fully account for the aircraft motion, dynamic derivatives are used to update the steady-state predictions with additional contributions. These terms are extracted from small-amplitude oscillatory tests. The numerical simulation of the flow around a moving airframe for the prediction of dynamic derivatives is a computationally expensive task. Results presented are in good agreement with available experimental data for complex geometries. A generic fighter configuration and a transonic cruiser wind tunnel model are the test cases. In the presence of aerodynamic non-linearities, dynamic derivatives exhibit significant dependency on flow and motion parameters, which cannot be reconciled with the model formulation. An approach to evaluate the sensitivity of the non-linear flight simulation model to variations in dynamic derivatives is described. The use of reduced models, based on the manipulation of the full-order model to reduce the cost of calculations, is discussed for the fast prediction of dynamic derivatives. A linearized solution of the unsteady problem, with an attendant loss of generality, is inadequate for studies of flight dynamics because the aircraft may experience large excursions from the reference point. The harmonic balance technique, which approximates the flow solution in a Fourier series sense, retains a more general validity. The model truncation, resolving only a small subset of frequencies typically restricted to include one Fourier mode at the frequency at which dynamic derivatives are desired, provides accurate predictions over a range of two- and three-dimensional test cases. While retaining the high fidelity of the full-order model, the cost of calculations is a fraction of the cost for solving the original unsteady problem. An important consideration is the limitation of the conventional model based on aerodynamic derivatives when applied to conditions of practical interest (transonic speeds and high angles of attack). There is a definite need for models with more realism to be used in flight dynamics. To address this demand, various reduced models based on system-identification methods are investigated for a model case. A non-linear model based on aerodynamic derivatives, a multi-input discrete-time Volterra model, a surrogate-based recurrence-framework model, linear indicial functions and radial basis functions trained with neural networks are evaluated. For the flow conditions considered, predictions based on the conventional model are the least accurate. While requiring similar computational resources, improved predictions are achieved using the alternative models investigated. Furthermore, an approach for the automatic generation of aerodynamic tables using CFD is described. To efficiently reduce the number of high-fidelity (physics-based) analyses required, a kriging-based surrogate model is used. The framework is applied to a variety of test cases, and it is illustrated that the approach proposed can handle changes in aircraft geometry. The aerodynamic tables can also be used in real-time to fly the aircraft through the database. This is representative of the role played by CFD simulations and the potential impact that high-fidelity analyses might have to reduce overall costs and design cycle time.

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Paton, Jonathan. « Computational fluid dynamics and fluid structure interaction of yacht sails ». Thesis, University of Nottingham, 2011. http://eprints.nottingham.ac.uk/14036/.

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This thesis focuses on the numerical simulation of yacht sails using both computational fluid dynamics (CFD) and fluid structure interaction (FSI) modelling. The modelling of yacht sails using RANS based CFD and the SST turbulence model is justified with validation against wind tunnel studies (Collie, 2005; Wilkinson, 1983). The CFD method is found to perform well, with the ability to predict flow separation, velocity and pressure profiles satisfactorily. This work is extended to look into multiple sail interaction and the impact of the mast upon performance. A FSI solution is proposed next, coupling viscous RANS based CFD and a structural code capable of modelling anistropic laminate sails (RELAX, 2009). The aim of this FSI solution is to offer the ability to investigate sails' performance and flying shapes more accurately than with current methods. The FSI solution is validated with the comparison to flying shapes of offwind sails from a bespoke wind tunnel experiment carried out at the University of Nottingham. The method predicted offwind flying shapes to a greater level of accuracy than previous methods. Finally the CFD and FSI solution described here above is showcased and used to model a full scale Volvo Open 70 racing yacht, including multiple offwind laminate sails, mast, hull, deck and twisted wind profile. The model is used to demonstrate the potential of viscous CFD and FSI to predict performance and aid in the design of high performance sails and yachts. The method predicted flying shapes and performance through a range of realistic sail trims providing valuable data for crews, naval architects and sail designers.

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Parolini, Nicola. « Computational fluid dynamics for naval engineering problems / ». [S.l.] : [s.n.], 2004. http://library.epfl.ch/theses/?nr=3138.

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Rüther, Nils. « Computational Fluid Dynamics in Fluvial Sedimentation Engineering ». Doctoral thesis, Norwegian University of Science and Technology, Department of Hydraulic and Environmental Engineering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1917.

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The present dissertation describes the improvement of a numerical model when predicting sedimentation and erosion processes in fluvial geomorphology. Various algorithms and parameters were implemented in a computational fluid dynamic model for simulation of three-dimensional water flow and coupled sediment transport to gain an insight into the capabilities of the numerical model. Within the scope of the test cases the model simulated suspended load concentrations at a water intake, transient bed deformation in a 90º channel bend, grain sorting processes as well as an unsteady flow regime in a 180º channel bend, transient bed deformation in a sine-shaped meandering channel with occurring bed forms and the free-forming meander evolution of an initially straight channel. All results matched well with the measurements. The results also showed that using computational fluid dynamics for modeling water flow and sediment transport is one step closer of having a universal predictor for processes in fluvial geomorphology. However, there are limitations and some uncertainties in computing the water surface location and alluvial roughness as well as in turbulence modeling. These should be clarified in future investigations.

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Demir, H. Ozgur. « Computational Fluid Dynamics Analysis Of Store Separation ». Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605294/index.pdf.

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In this thesis, store separation from two different configurations are solved using computational methods. Two different commercially available CFD codes
CFD-FASTRAN, an implicit Euler solver, and an unsteady panel method solver USAERO, coupled with integral boundary layer solution procedure are used for the present computations. The computational trajectory results are validated against the available experimental data of a generic wing-pylon-store configuration at Mach 0.95. Major trends of the separation are captured. Same configuration is used for the comparison of unsteady panel method with Euler solution at Mach 0.3 and 0.6. Major trends are similar to each other while some differences in lateral and longitudinal displacements are observed. Trajectories of a fueltank separated from an F-16 fighter aircraft wing and full aircraft configurations are found at Mach 0.3 using only the unsteady panel code. The results indicate that the effect of fuselage is to decrease the drag and to increase the side forces acting on the separating fueltank from the aircraft. It is also observed that the yawing and rolling directions of the separating fueltank are reversed when it is separated from the full aircraft configuration when compared to the separation from the wing alone configuration.

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Livres sur le sujet "Computational fluid dynamics"

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Chung, T. J. Computational fluid dynamics. 2^e éd. Cambridge : Cambridge University Press, 2010.

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2

Wendt, John F., dir. Computational Fluid Dynamics. Berlin, Heidelberg : Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-662-11350-9.

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Kajishima, Takeo, et Kunihiko Taira. Computational Fluid Dynamics. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-45304-0.

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Bates, Paul D., Stuart N. Lane et Robert I. Ferguson, dir. Computational Fluid Dynamics. Chichester, UK : John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470015195.

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Wendt, John F., dir. Computational Fluid Dynamics. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-85056-4.

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Leutloff, Dieter, et Ramesh C. Srivastava, dir. Computational Fluid Dynamics. Berlin, Heidelberg : Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79440-7.

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Center, Langley Research. Computational fluid dynamics. Hampton, Va : Langley Research Center, 1988.

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Lecheler, Stefan. Computational Fluid Dynamics. Wiesbaden : Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-38453-1.

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Wendt, John F. Computational Fluid Dynamics. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.

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K, Bose T. Computational fluid dynamics. New York : Wiley, 1988.

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Chapitres de livres sur le sujet "Computational fluid dynamics"

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Alobaid, Falah. « Computational Fluid Dynamics ». Dans Springer Tracts in Mechanical Engineering, 87–204. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76234-0_3.

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Wagner, S. « Computational Fluid Dynamics ». Dans High Performance Computing in Science and Engineering ’98, 197–98. Berlin, Heidelberg : Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-58600-2_21.

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Schwarze, Rüdiger. « Computational Fluid Dynamics ». Dans CFD-Modellierung, 3–22. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24378-3_1.

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Wagner, S. « Computational Fluid Dynamics ». Dans High Performance Computing in Science and Engineering ’01, 269–71. Berlin, Heidelberg : Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-56034-7_26.

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Hagler, Gina. « Computational Fluid Dynamics ». Dans Modeling Ships and Space Craft, 223–27. New York, NY : Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4596-8_11.

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Hoffmann, Alex C., et Louis E. Stein. « Computational Fluid Dynamics ». Dans Gas Cyclones and Swirl Tubes, 123–35. Berlin, Heidelberg : Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-07377-3_7.

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Thrane, Lars, Ana Bras, Paul Bakker, Wolfgang Brameshuber, Bogdan Cazacliu, Liberato Ferrara, Dimitri Feys et al. « Computational Fluid Dynamics ». Dans RILEM State-of-the-Art Reports, 25–63. Dordrecht : Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-8884-7_2.

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Monthei, Dean L. « Computational Fluid Dynamics ». Dans Electronic Packaging and Interconnects Series, 151–53. Boston, MA : Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5111-9_9.

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Beysens, Daniel. « Computational Fluid Dynamics ». Dans Dew Water, 161–84. New York : River Publishers, 2022. http://dx.doi.org/10.1201/9781003337898-8.

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Yan, Yihuan, et Jiyuan Tu. « Computational Fluid Dynamics ». Dans Bioaerosol Characterisation, Transportation and Transmission, 65–83. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2256-7_4.

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Actes de conférences sur le sujet "Computational fluid dynamics"

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Yamamoto, Yukimitsu, Yasuhiro Wada et Minako Yoshioka. « HYFLEX computational fluid dynamics analysis. II ». Dans Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-2274.

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Milholen, am E, I, William, et Ndaona IChokani. « Computational analysis of semi-span test techniques ». Dans Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-2290.

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Oberkampf, William, Frederick Blottner et Daniel Aeschliman. « Methodology for computational fluid dynamics code verification /validation ». Dans Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-2226.

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Chrisochoides, N., G. Fox et T. Haupt. « A computational toolkit for colliding black holes and CFD ». Dans Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-2249.

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Verhoff, A. « Global far-field computational boundary conditions for C-grid topologies ». Dans Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-2184.

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Hefazi, H., K. Kaups et Roger Murry. « A computational study of flow in a supersonic impulse turbine ». Dans Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-2287.

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Lekoudis, Spiro. « Computational Fluid Dynamics - Navy perspective ». Dans 11th Computational Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1993. http://dx.doi.org/10.2514/6.1993-3294.

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VIVIAND, H., C. LECOMTE et PH MORICE. « Computational fluid dynamics in France ». Dans 8th Computational Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1987. http://dx.doi.org/10.2514/6.1987-1131.

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ZHUANG, F., et H. ZHANG. « Computational fluid dynamics in China ». Dans 8th Computational Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1987. http://dx.doi.org/10.2514/6.1987-1134.

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Weed, R., et L. Sankar. « Computational strategies for three-dimensional flow simulations on distributed computer systems ». Dans Fluid Dynamics Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-2261.

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Rapports d'organisations sur le sujet "Computational fluid dynamics"

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Hall, Charles A. Computational Fluid Dynamics. Fort Belvoir, VA : Defense Technical Information Center, juin 1986. http://dx.doi.org/10.21236/ada177171.

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Hall, Charles A., et Thomas A. Porsching. Computational Fluid Dynamics. Fort Belvoir, VA : Defense Technical Information Center, janvier 1990. http://dx.doi.org/10.21236/ada219557.

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Haworth, D. C., P. J. O'Rourke et R. Ranganathan. Three-Dimensional Computational Fluid Dynamics. Office of Scientific and Technical Information (OSTI), septembre 1998. http://dx.doi.org/10.2172/1186.

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Calahan, D. A. Massively-Parallel Computational Fluid Dynamics. Fort Belvoir, VA : Defense Technical Information Center, octobre 1989. http://dx.doi.org/10.21236/ada217732.

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Garabedian, Paul R. Computational Fluid Dynamics and Transonic Flow. Fort Belvoir, VA : Defense Technical Information Center, octobre 1994. http://dx.doi.org/10.21236/ada288962.

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Garabedian, Paul R. Computational Fluid Dynamics and Transonic Flow. Fort Belvoir, VA : Defense Technical Information Center, octobre 1994. http://dx.doi.org/10.21236/ada292797.

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Wagner, Matthew, et Marianne M. Francois. Computational Fluid Dynamics of rising droplets. Office of Scientific and Technical Information (OSTI), septembre 2012. http://dx.doi.org/10.2172/1050489.

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OBERKAMPF, WILLIAM L., et TIMOTHY G. TRUCANO. Verification and Validation in Computational Fluid Dynamics. Office of Scientific and Technical Information (OSTI), mars 2002. http://dx.doi.org/10.2172/793406.

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Chou, So-Hsiang. Computational Methods for Problems in Fluid Dynamics. Fort Belvoir, VA : Defense Technical Information Center, février 1989. http://dx.doi.org/10.21236/ada221946.

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Gibson, J. S. Joint Research on Computational Fluid Dynamics and Fluid Flow Control. Fort Belvoir, VA : Defense Technical Information Center, novembre 1995. http://dx.doi.org/10.21236/ada308103.

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