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Journal articles on the topic 'Computational fluid dynamics'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 November 2024

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1

Thabet, Senan, and Thabit H. Thabit. "Computational Fluid Dynamics: Science of the Future." International Journal of Research and Engineering 5, no. 6 (2018): 430–33. http://dx.doi.org/10.21276/ijre.2018.5.6.2.

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2

Raza, Md Shamim, Nitesh Kumar, and Sourav Poddar. "Combustor Characteristics under Dynamic Condition during Fuel – Air Mixingusing Computational Fluid Dynamics." Journal of Advances in Mechanical Engineering and Science 1, no. 1 (August 8, 2015): 20–33. http://dx.doi.org/10.18831/james.in/2015011003.

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3

KAWAMURA, Tetuya, and Hideo TAKAMI. "Computational Fluid Dynamics." Tetsu-to-Hagane 75, no. 11 (1989): 1981–90. http://dx.doi.org/10.2355/tetsutohagane1955.75.11_1981.

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4

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

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5

Lin, Ching-long, Merryn H. Tawhai, Geoffrey Mclennan, and Eric A. Hoffman. "Computational fluid dynamics." IEEE Engineering in Medicine and Biology Magazine 28, no. 3 (May 2009): 25–33. http://dx.doi.org/10.1109/memb.2009.932480.

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6

Wrobel, L. C. "Computational fluid dynamics." Engineering Analysis with Boundary Elements 9, no. 2 (January 1992): 192. http://dx.doi.org/10.1016/0955-7997(92)90070-n.

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7

Pericleous, K. A. "Computational fluid dynamics." International Journal of Heat and Mass Transfer 32, no. 1 (January 1989): 197–98. http://dx.doi.org/10.1016/0017-9310(89)90105-1.

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8

Von Wendt, J. "Computational fluid dynamics." Journal of Wind Engineering and Industrial Aerodynamics 40, no. 2 (June 1992): 223. http://dx.doi.org/10.1016/0167-6105(92)90368-k.

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9

Lax, Peter D. "Computational Fluid Dynamics." Journal of Scientific Computing 31, no. 1-2 (October 25, 2006): 185–93. http://dx.doi.org/10.1007/s10915-006-9104-x.

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10

Pitarma, R. A., J. E. Ramos, M. E. Ferreira, and M. G. Carvalho. "Computational fluid dynamics." Management of Environmental Quality: An International Journal 15, no. 2 (April 2004): 102–10. http://dx.doi.org/10.1108/14777830410523053.

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11

Leschziner, M. A. "Computational fluid dynamics." International Journal of Heat and Fluid Flow 11, no. 1 (March 1990): 82–83. http://dx.doi.org/10.1016/0142-727x(90)90031-6.

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12

Bhardwaj, Shalini, and Yashwant Buke. "Computational Fluid Dynamics Analysis of A Turbocharger System." International Journal of Scientific Research 3, no. 5 (June 1, 2012): 161–64. http://dx.doi.org/10.15373/22778179/may2014/49.

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13

Lin, C. T., J. K. Kuo, and T. H. Yen. "Quantum Fluid Dynamics and Quantum Computational Fluid Dynamics." Journal of Computational and Theoretical Nanoscience 6, no. 5 (May 1, 2009): 1090–108. http://dx.doi.org/10.1166/jctn.2009.1149.

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14

C., Mohan Raj. "Analysis of Various Automotive Mufflers: Computational Fluid Dynamics Approach." Revista Gestão Inovação e Tecnologias 11, no. 4 (July 10, 2021): 1339–48. http://dx.doi.org/10.47059/revistageintec.v11i4.2191.

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15

Drikakis, Dimitris, Michael Frank, and Gavin Tabor. "Multiscale Computational Fluid Dynamics." Energies 12, no. 17 (August 25, 2019): 3272. http://dx.doi.org/10.3390/en12173272.

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Computational Fluid Dynamics (CFD) has numerous applications in the field of energy research, in modelling the basic physics of combustion, multiphase flow and heat transfer; and in the simulation of mechanical devices such as turbines, wind wave and tidal devices, and other devices for energy generation. With the constant increase in available computing power, the fidelity and accuracy of CFD simulations have constantly improved, and the technique is now an integral part of research and development. In the past few years, the development of multiscale methods has emerged as a topic of intensive research. The variable scales may be associated with scales of turbulence, or other physical processes which operate across a range of different scales, and often lead to spatial and temporal scales crossing the boundaries of continuum and molecular mechanics. In this paper, we present a short review of multiscale CFD frameworks with potential applications to energy problems.

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16

Norman, Michael L., David A. Clarke, and James M. Stone. "Computational Astrophysical Fluid Dynamics." Computers in Physics 5, no. 2 (1991): 138. http://dx.doi.org/10.1063/1.4822976.

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17

Bell, John B., Alejandro L. Garcia, and Sarah A. Williams. "Computational fluctuating fluid dynamics." ESAIM: Mathematical Modelling and Numerical Analysis 44, no. 5 (August 26, 2010): 1085–105. http://dx.doi.org/10.1051/m2an/2010053.

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18

Schierholz, W. F., and N. Gilbert. "Computational Fluid Dynamics (CFD)." Chemie Ingenieur Technik 75, no. 10 (October 15, 2003): 1412–14. http://dx.doi.org/10.1002/cite.200303306.

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19

Kim, Youngho, and Sangho Yun. "Fluid Dynamics in an Anatomically Correct Total Cavopulmonary Connection : Flow Visualizations and Computational Fluid Dynamics(Cardiovascular Mechanics)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2004.1 (2004): 57–58. http://dx.doi.org/10.1299/jsmeapbio.2004.1.57.

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20

Schneider, Kai, and Oleg V. Vasilyev. "Wavelet Methods in Computational Fluid Dynamics." Annual Review of Fluid Mechanics 42, no. 1 (January 2010): 473–503. http://dx.doi.org/10.1146/annurev-fluid-121108-145637.

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21

Teodosiu, Cătălin, Viorel Ilie, and Raluca Teodosiu. "Condensation Model for Application of Computational Fluid Dynamics in Buildings." International Journal of Materials, Mechanics and Manufacturing 3, no. 2 (2015): 129–33. http://dx.doi.org/10.7763/ijmmm.2015.v3.181.

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22

Subaschandar, N. "Flow Mixing Optimisation inside a Manifold using Computational Fluid Dynamics." Journal of Advanced Research in Applied Mechanics & Computational Fluid Dynamics 5, no. 3&4 (January 23, 2019): 7–14. http://dx.doi.org/10.24321/2349.7661.201802.

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23

Murti, Vishav, and Esar Ahmad. "Wind Effects on Bridge Deck: A Computational Fluid Dynamics Study." International Journal of Science and Research (IJSR) 12, no. 9 (September 5, 2023): 1056–59. http://dx.doi.org/10.21275/sr23905111754.

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24

Aksenov, Andrey A. "FlowVision: Industrial computational fluid dynamics." Computer Research and Modeling 9, no. 1 (February 2017): 5–20. http://dx.doi.org/10.20537/2076-7633-2017-9-5-20.

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25

Barman, Purna Chandra. "Introduction to Computational Fluid Dynamics." International Journal of Information Science and Computing 3, no. 2 (2016): 117. http://dx.doi.org/10.5958/2454-9533.2016.00014.4.

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26

Mehta, Unmeel B. "Credible Computational Fluid Dynamics Simulations." AIAA Journal 36, no. 5 (May 1998): 665–67. http://dx.doi.org/10.2514/2.431.

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27

SATOMURA, Takehiko. "Computational Fluid Dynamics in Meteorology." Wind Engineers, JAWE 1994, no. 60 (1994): 41–55. http://dx.doi.org/10.5359/jawe.1994.60_41.

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28

Chen, Goong, Qingang Xiong, Phillip J. Morris, Eric G. Paterson, Alexey Sergeev, and Yi-Ching Wang. "OpenFOAM for Computational Fluid Dynamics." Notices of the American Mathematical Society 61, no. 4 (April 1, 2014): 354. http://dx.doi.org/10.1090/noti1095.

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29

Wiwatanapataphee, Benchawan, Yonghong Wu, I. Ming Tang, and Shaoyong Lai. "Fluid Dynamics and Computational Engineering." Mathematical Problems in Engineering 2014 (2014): 1–3. http://dx.doi.org/10.1155/2014/649058.

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30

Wendt, John, Marc Bourzutschky, A. John Mallinckrodt, and Susan McKay. "Computational Fluid Dynamics: An Introduction." Computers in Physics 7, no. 5 (1993): 542. http://dx.doi.org/10.1063/1.4823215.

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31

Fisher, E. H., and N. Rhodes. "Uncertainty in Computational Fluid Dynamics." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 209, no. 2 (May 1995): 155–58. http://dx.doi.org/10.1243/pime_proc_1995_209_026_02.

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The Fifth Joint Engineering and Physical Sciences Research Council and Institution of Mechanical Engineers Expert Meeting was held in Bournemouth on 27-29 November 1994. The Fifth Joint Engineering and Physical Sciences Research Council and Institution of Mechanical Engineers Expert Meeting was held in Bournemouth on 27–29 November 1994.

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32

Fisher, E. H., and N. Rhodes. "Uncertainty in Computational Fluid Dynamics." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 210, no. 1 (January 1996): 91–94. http://dx.doi.org/10.1243/pime_proc_1996_210_173_02.

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The Annual EPSRC/IMechE Expert Meeting brought together some 44 experts to consider sources of uncertainty in computational fluid dynamics (CFD). Presentations and discussions covered modelling, numerical solution techniques, boundary conditions, evaluation protocols and QA (quality assurance) procedures. The principal conclusions to emerge were: (a) the need for additional collaborative validation studies; (b) the desirability of introducing appropriate QA procedures, possibly based on the CFD Community Club initiative; (c) the need for additional postgraduate training, possibly based on the IGDS principle; (d) the value of continuing work in modelling and error estimation techniques for numerical schemes.

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33

Lomax, H., TH Pulliam, DW Zingg, and TA Kowalewski. "Fundamentals of Computational Fluid Dynamics." Applied Mechanics Reviews 55, no. 4 (2002): B61. http://dx.doi.org/10.1115/1.1483340.

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34

Paul, P. "Computational Fluid Dynamics in Combustion." Defence Science Journal 60, no. 6 (November 20, 2010): 577–82. http://dx.doi.org/10.14429/dsj.60.600.

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35

Li, Sheng S. "Book review: Computational Fluid Dynamics." Canadian Journal of Civil Engineering 29, no. 6 (December 1, 2002): 919–20. http://dx.doi.org/10.1139/l02-090.

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36

Vassberg, John. "Expectations for computational fluid dynamics." International Journal of Computational Fluid Dynamics 19, no. 8 (November 2005): 549–58. http://dx.doi.org/10.1080/10618560500508375.

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37

Ueki, Heihachi, Toshiaki Yokoi, Hiroko Fujii, Atsushi Kunimatsu, Kazuhiro Hiwada, and Tsunemi Takahashi. "Computational Fluid Dynamics for Entertainment." Proceedings of The Computational Mechanics Conference 2002.15 (2002): 525–26. http://dx.doi.org/10.1299/jsmecmd.2002.15.525.

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38

Bhasker, C. "Computational techniques for fluid dynamics." Finite Elements in Analysis and Design 9, no. 1 (April 1991): 87–88. http://dx.doi.org/10.1016/0168-874x(91)90021-p.

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39

Bar-Yoseph, Pinhas Z. "Computational fluid dynamics review 1995." International Journal of Multiphase Flow 23, no. 5 (September 1997): 1003–4. http://dx.doi.org/10.1016/s0301-9322(97)80002-x.

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40

Mehta, Unmeel B. "Credible computational fluid dynamics simulations." AIAA Journal 36 (January 1998): 665–67. http://dx.doi.org/10.2514/3.13878.

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41

Dhotre, Mahesh T., Nandkishor Krishnarao Nere, Sreepriya Vedantam, and Mandar Tabib. "Advances in Computational Fluid Dynamics." International Journal of Chemical Engineering 2013 (2013): 1–2. http://dx.doi.org/10.1155/2013/917373.

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42

NAKAMURA, Tadao, and Hisaki DAIGUJI. "Computational Fluid Dynamics in Supercomputing." Journal of the Society of Mechanical Engineers 94, no. 866 (1991): 40–45. http://dx.doi.org/10.1299/jsmemag.94.866_40.

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43

Thornber, Ben. "Computational fluid dynamics for engineers." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 227, no. 12 (November 11, 2013): 2002. http://dx.doi.org/10.1177/0954410013478712.

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44

Ferziger, Joel H., Milovan Peric, and Anthony Leonard. "Computational Methods for Fluid Dynamics." Physics Today 50, no. 3 (March 1997): 80–84. http://dx.doi.org/10.1063/1.881751.

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45

Fletcher, D. F. "Computational techniques for fluid dynamics." Computer Physics Communications 70, no. 1 (May 1992): 221. http://dx.doi.org/10.1016/0010-4655(92)90103-6.

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46

Ranade, Vivek V., and Vishnu Pareek. "Guest editorial: computational fluid dynamics." Asia-Pacific Journal of Chemical Engineering 3, no. 2 (March 2008): 95–96. http://dx.doi.org/10.1002/apj.130.

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47

TAKAHIRA, Hiroyuki. "Computational Fluid Dynamics for Cavitaiton Bubble Dynamics." Proceedings of the Fluids engineering conference 2004 (2004): 4. http://dx.doi.org/10.1299/jsmefed.2004.4.

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48

ZHANG, Nan, Zhongning SUN, and Ming DING. "ICONE23-1895 COMPUTATIONAL FLUID DYNAMICS SIMULATIONS OF FLUID FLOW IN RANDOM PACKED BED WITH SPHERES." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2015.23 (2015): _ICONE23–1—_ICONE23–1. http://dx.doi.org/10.1299/jsmeicone.2015.23._icone23-1_425.

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49

Li, Lei, Carlos F. Lange, and Yongsheng Ma. "Association of design and computational fluid dynamics simulation intent in flow control product optimization." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 232, no. 13 (March 14, 2017): 2309–22. http://dx.doi.org/10.1177/0954405417697352.

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Computational fluid dynamics has been extensively used for fluid flow simulation and thus guiding the flow control device design. However, computational fluid dynamics simulation requires explicit geometry input and complicated solver setup, which is a barrier in case of the cyclic computer-aided design/computational fluid dynamics integrated design process. Tedious human interventions are inevitable to make up the gap. To fix this issue, this work proposed a theoretical framework where the computational fluid dynamics solver setup can be intelligently assisted by the simulation intent capture. Two feature concepts, the fluid physics feature and the dynamic physics feature, have been defined to support the simulation intent capture. A prototype has been developed for the computer-aided design/computational fluid dynamics integrated design implementation without the need of human intervention, where the design intent and computational fluid dynamics simulation intent are associated seamlessly. An outflow control device used in the steam-assisted gravity drainage process is studied using this prototype, and the target performance of the device is effectively optimized.

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50

Kochkov, Dmitrii, Jamie A. Smith, Ayya Alieva, Qing Wang, Michael P. Brenner, and Stephan Hoyer. "Machine learning–accelerated computational fluid dynamics." Proceedings of the National Academy of Sciences 118, no. 21 (May 18, 2021): e2101784118. http://dx.doi.org/10.1073/pnas.2101784118.

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Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics, and plasma physics. Fluids are well described by the Navier–Stokes equations, but solving these equations at scale remains daunting, limited by the computational cost of resolving the smallest spatiotemporal features. This leads to unfavorable trade-offs between accuracy and tractability. Here we use end-to-end deep learning to improve approximations inside computational fluid dynamics for modeling two-dimensional turbulent flows. For both direct numerical simulation of turbulence and large-eddy simulation, our results are as accurate as baseline solvers with 8 to 10× finer resolution in each spatial dimension, resulting in 40- to 80-fold computational speedups. Our method remains stable during long simulations and generalizes to forcing functions and Reynolds numbers outside of the flows where it is trained, in contrast to black-box machine-learning approaches. Our approach exemplifies how scientific computing can leverage machine learning and hardware accelerators to improve simulations without sacrificing accuracy or generalization.

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