Computational Fluid Dynamics: Science of the Future

  • Senan Thabet University of South Wales, Cardiff, UK
  • Thabit H. Thabit Ninevah University, Mosul, Iraq


This paper will answer a list of questions regarding the computational fluid dynamics (CFD). It will give a brief discussion regarding the significance of CFD and will recount the pros and cons of applying CFD. The following assignment will also give an overview of the terms that come under the ambit of CFD like discretization, numerical grid, initial conditions, boundary conditions, sweep, convergence, and turbulence modeling. The researchers such as Guang Xu et al. (2017), Raase and Nordström (2015), and Frigg et al. (2009) concluded that CFD is the science of the future as it cares in all aspects of life in the present and the future, CFD science treats the fluids mainly the air and the water as good and bad, bad when the CFD tries to find a way through the air and the water to get the minimum resistant for cost-effective and less fuel burning for greener, healthier and better world in many applications such submarines, air crafts, automobiles, ships, trains, motorbikes and too many other applications.


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[1] Guang Xu, Kray D. Luxbacher, SaadRagab, JialinXu, and Xuhan Ding, 2017, Computational fluid dynamics applied to mining engineering: a review, International Journal of Mining, Reclamation and Environment, Vol. 31, Iss. 4, pp. 251-275.
[2] Scott, Gordon, and Richardson, Philip, 1997, The application of computational fluid dynamics in the food industry, Trends in Food Science & Technology, Vol. 8, Iss. 4, pp. 119-124.
[3] Gandhi, Priya, Brager, Gail, and Dutton, Spencer, 2014, Mixed Mode Simulation Tools, Internal Report, University of California.
[4] Linfield, K. W., and Mudry, R. G., 2008, Pros and cons of CFD and physical flow modeling.
[5] Tu, J., Yeoh, G., and Liu, C., 2012, Computational Fluid Dynamics – A practical Approach, 2nd Edition, Elsevier, UK.
[6] El Hagrasy, A.S., Hennenkamp, J.R., Burke, M.D., Cartwright, J.J., and Litster, J.D., 2013, Twin screw wet granulation: Influence of formulation parameters on granule properties and growth behavior, Powder Technol .
[7] Draper, Norman R., and Box, George E.P., 1987, Empirical model-building and response surfaces‏, John Wiley and sons.
[8] Frigg, R., Hartmann S., and Imbert C., 2009, Special Issue Models and Simulation, Synthese, Springer Netherlands, Vol. 169, Iss. 3.
[9] Tsuboi, N., Daimon, Y., Hayashi, A., 2008, Three-dimensional numerical simulation of detonations in coaxial tubes, Shock Waves, 18: 379-392.
[10] Nomizu, Katsumi, 2001, Selected Papers on Classical Analysis, American Mathematical Society Translations: Series 2, USA.
[11] Ferziger, Joel H., and Peric, Milovan, 2002, Computational Methods for Fluid Dynamics, 3rd Edition, Springer, Germany.
[12] Raase, Sebastian, and Nordström, Tomas, 2015, On the Use of a Many-core Processor for Computational Fluid Dynamics Simulations, Procedia Computer Science, Vol. 51
[13] Thabit, Thabit H., and Younus, Saif Q., 2018, Risk Assessment and Management in Construction Industries, International Journal of Research and Engineering, Vol. 5, No. 2, pp. 315-320.
How to Cite
THABET, Senan; THABIT, Thabit H.. Computational Fluid Dynamics: Science of the Future. International Journal of Research and Engineering, [S.l.], v. 5, n. 6, p. 430-433, july 2018. ISSN 2348-7860. Available at: <>. Date accessed: 31 may 2020. doi: