Computational Fluid Dynamics Overview, Scope and Relevance P. R. Naren School of Chemical & Biotechnology SASTRA University Thanjavur 613401 E-mail: prnaren@scbt.sastra.edu at Faculty Development Program on Computational Fluid Dynamics School of Mechanical Engineering SASTRA University Thanjavur 613401 01 June 2015 Progress Through Quality Education
Objective of FDP on CFD Genesis Overall framework Outline Glimpse of applications Flow Modelling Why CFD? What CFD? When CFD? Typical Sequence of operation in CFD 2
Objective of FDP To provide basic understanding of fundamental concepts involved in CFD To comprehend numerical techniques involved in CFD Use CFD tool to complement learning process CFD tool (Ansys) used for illustration 3
Expected Outcome Should be able to describe the concepts involved in CFD simulation Should be able to develop CFD model for simple flow systems, simulate and better understand underlying physics Should be able to design and introduce a primer course of CFD for UG / PG level 4
Lectures (FN) Hands-on Session (AN) Framework of FDP Pipe flow Why simple test cases? Flow through flat plate Open Interaction on Day 3 and Day 5 Wikispace [https://www.wikispaces.com] Online web hosting repository classroom mgmt. system Share files Discussion forum https://sastra-fdp-cfd.wikispaces.com/ Join code: TNRMRPJ 5
Common Flow Structures http://www.flow.kth.se/?q=node/50 http://abyss.uoregon.edu/~js/glossary/boundary_layer.html http://www.open-ocean.org/pictures/53 6
Avenues for CFD http://www.aeroresearch-llc.com/ www.steamesteem.com/?boilers/combustion-engineering-v2m9 7
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Examples Cont. http://www.mentor.com/ 9
Modelling Modelling vs. Simulation Description of process / physics of a system mathematical expressions / entities Ability to comprehend the science Simulation Instance of model Output from model for particular input value 10
Characteristic Length and Time Scales http://www.tms.org/pubs/journals/jom/1111/krajewski-1111.html 11
Types of Models Phenomenological modeling Based on conversation laws Flow mostly compromised idealized Statistical modeling Experiment data fitting One or two dependent variables Known functional relationship Flow Modeling Detailed description of flow pattern in system Data driven modeling Cause effect relationship with/without exact functional relationship More state space 12
Why Flow Modelling 13
Why Flow Modelling Ideal Contactors In reality 14
Flow Modelling Experimental FD Theoretical FD Computational FD 15
Why CFD? Empirical procedures Scale up issues No generalization Investment Man hours and Currency Micro/Meso scale information 16
Computational fluid dynamics (CFD) is one of the branches of fluid mechanics that uses numerical methods and algorithms to solve and analyze problems that involve fluid flows. http://en.wikipedia.org/wiki/computational_fluid_dynamics 17
Advantage CFD Access to flow information Better understanding of physics Screen large reactor choices Efficient retrofitting solution Learning tool - The FEEL factor Save man hours per knowledge gained 18
Outcome from CFD Analysis Select the best design - aid design Performance Capacity Constraints Better understanding of flow behavior Local flow pattern Predict engineering parameters Drag coefficient Wall shear Pressure drop 19
Framework of CFD Observe Identify Physics Model development and discretion Conservation equation Model selection, Closures, BC Geometry Capture the real system into digital framework Solve Discretization PDE ODE Linear Eq. Analyze and re-observe Tune model parameters Transfer 20
Continuum Continuously fill the domain Knudsen number K n = λ L Knudsen 21
Governing Equations Conservation of mass Conservation of momentum Transport Equations Conservation of energy Concept of CV ρ = lim δ * δm δ 22
Closures Molecular transport mechanism Flow regimes Laminar/Turbulent, Shock waves Heat transfer Multiphase flow Interphase coupling Drag Lift 23
Boundary Conditions and Types Dirichlet Specific value Neumann Gradient specific Robin Weighted value and gradient Cauchy Both value and gradient Inlet Velocity/ mass/ pressure Outlet Velocity/ mass/ pressure Wall No slip/ Free slip Symmetric/ Periodic 24
All Set Go? Simulate Numerical parameters Choice of interpolation schemes Relaxation factors Errors and numerical convergence Grid Taylor Physical solution 25
Commercial Tools Grid Generation Geometry Modelling TGRID Gambit Ansys ICEM CFD Solvers Ansys CFX Fluent Star CD Comsol MFIX OpenFoam FeatFlow 26
Functionality of Commercial Tools Pre-processor Geometry creation Mesh Boundary and domain specification Solver Model selection Boundary conditions Operating conditions Solver controls Convergence criteria, residual intervals Post processing Contour Vector Data analysis 27
Summary CFD provides insight into flow Numerical solution of conservation equations Knowledge of Physics Numerical Techniques Computers Enables better understanding of physics of systems Learning tool Retrofit tool Design tool 28
Resources Chung T. J. (2002) Computational Fluid Dynamics. Cambridge University Press Date A. W. (2005). Introduction to Computational Fluid Dynamics. Cambridge University Press Fox, R. O. (2003) Computational Models for Turbulent Reacting Flows. Cambridge University Press Hoffmann K. A. and Chiang S. T. (2000). Computational Fluid Dynamics Vol1, 2 and 3. Engineering Education System, Kansas, USA. John F. W., Anderson, J.D. (1996) Computational Fluid Dynamics: An Introduction Springer Patankar, S. (1980) Numerical Heat Transfer and Fluid Flow. Taylor and Francis Ranade, V.V. (2002). Computational Flow Modeling for Chemical Reactor Engineering, Academic Press, New York. Versteeg, H.K. and Malalasekera, W. (1995) An Introduction to computational Fluid Dynamics - The Finite Volume Method. Longman Scientific and Technical 29
Web Resources http://www.cfd-online.com http://en.wikipedia.org/wiki/computational_fluid_dynamics http://www.cfdreview.com/ https://confluence.cornell.edu/display/simulation/fluent +Learning+Modules http://weblab.open.ac.uk/firstflight/forces/# NPTEL Balchandra Puranik and Atul Sharma Srinivaas Jayanthi 30
Gratitude Dr. Vivek V. Ranade My Mentor Guide and Teacher ifmg - Research group at NCL, Pune Audience For patient hearing and for their thirst in knowledge 31
THANK YOU A person who never made a mistake never tried anything new - Albert Einstein - 1879-1955 32