# Computational Fluid Dynamics in Automotive Applications

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1 Computational Fluid Dynamics in Automotive Applications Hrvoje Jasak Wikki Ltd, United Kingdom FSB, University of Zagreb, Croatia 1/15

2 Outline Objective Review the adoption of Computational Fluid Dynamics (CFD) in automotive industry from mid 1980-s to today Outline lessons of automotive CFD relevant to other areas of numerical simulation Topics Computational Fluid Dynamics (CFD): methodology and areas of application CFD in modern automotive industry CFD capabilities in 1980s Early adopters and validation efforts Years of expansion Lessons learned: broken process and a killer application 2/15

3 Computational Fluid Dynamics Definition of CFD, from Versteeg and Malalasekera: An Introduction to Computational Fluid Dynamics Computational Fluid Dynamics or CFD is the analysis of systems involving fluid flow, heat transfer and associated phenomena such as chemical reactions by means of computer-based simulation. CFD is also a subset of Computational Continuum Mechanics: fundamentally identical numerical simulation technology is used for many sets of simular partial differential equations Numerical stress analysis Electromagnetics, including low- and high-frequency phenomena Weather prediction and global oceanic/atmosphere circulation models Large scale systems: galactic dynamics and star formation Complex heat and mass transfer systems Fluid-structure interaction and similar coupled systems In all cases, equations are very similar: capturing conservation of mass, momentum, energy and associated transport phenomena 3/15

4 Computational Fluid Dynamics CFD Methodology Numerous automotive components involve fluid flow and require optimisation. This opens a wide area of potential of CFD use in automotive industry CFD approaches the problem of fluid flow from fundamental equations: no problem-specific or industry-specific simplification A critical step involves complex geometry handling: it is essential to capture real geometrical features of the engineering component under consideration Traditional applications involve incompressible turbulent flow of Newtonian fluids While most people think of automotive CFD in terms of external aerodynamics simulations, reality of industrial CFD use is significantly different 4/15

5 Automotive CFD Today Use of CFD in Automotive Applications In numbers of users in automotive companies, CFD today is second only to CAD packages In some areas, CFD replaces experiments Engine coolant jackets Under-hood thermal management Passenger compartment comfort In comparison with CFD, experimental studies are expensive, carry limited information and it is difficult to achieve sufficient turn-over The biggest obstacle is validation: can CFD results be trusted? 5/15

6 Automotive CFD Today Use of CFD in Automotive Applications (cont d) In other areas, CFD is insufficiently accurate for complete design studies Required accuracy is beyond the current state of physical modelling (especially turbulence modelling) Simulation cost is prohibitive or turn-around is too slow Flow physics is too complex: incomplete modelling or insufficient understanding of detailed physical processes In some cases, combined 1-D/3-D studies capture the physics without resorting to complete 3-D study Examples: Prediction of the lift and drag coefficient on a car body In-cylinder simulations in an internal combustion engine Complete internal combustion engine system: air intake, turbo-charger, engine ports and valves, in-cylinder flow, exhaust and gas after-treatment CFD can still contribute: parametric study (trends), reduced experimental work etc. Numerical modelling is particularly useful in understanding the flow or looking for qualitative improvements: e.g. optimisation of vehicle soiling pattern on windows 6/15

7 External Aerodynamics Simulations 7/15

8 External Aerodynamics Simulations 8/15

9 Automotive CFD Today Use of CFD in Automotive Applications (cont d) CFD is used across the industry, at various levels of sophistication Impact of simulations and reliance on numerical methods is greatest in areas that were not studied in detail beforehand Considerable use in cases where it is difficult to quantify the results in simple terms like the lift and drag coefficient Flow organisation, stability and optimisation Detailed look at the flow field, especially in complex geometry Optimisation of secondary effects: fuel-air mixture preparation 9/15

10 CFD Capabilities in 1980s Early Adoption of CFD: Aerospace Industry Historically, early efforts in CFD involve simplified equations and simulations relevant for aerospace industry Experience in achieving best results with limited computational resources: attention given to solution acceleration techniques Application-specific physical models Linearised potential equations, Hess and Smith, Douglas Aircraft D panel codes developed by Boeing, Lockheed, Douglas and others in 1968 Specific turbulence models for aerospace flows, e.g. Baldwin-Lomax Coupled boundary layer-potential flow solver, Euler flow solver Capabilities beyond steady-state compressible flow were very limited 10/15

11 Early Adopters and Validation Efforts Early Automotive CFD Simulations First efforts aimed at simplified external aerodynamics ( )... but airfoil assumptions are not necessarily applicable Joint numerical and experimental studies: validation of numerical techniques and simulation tools, qualitative results, analysis of flow patterns and similar 11/15

12 Early Adopters and Validation Efforts Early Automotive CFD Simulations It is quickly recognised that the needs of automotive industry and (potential) capabilities of CFD solvers are well beyond contemporary experimental work Focus of early numerical work is on performance-critical components: internal combustion engines and external aerodynamics Geometry and flow conditions are simplified to help with simulation set-up Example: Intake Valve and Manifold 2-D steady-state incompressible turbulent fluid flow Axi-symmetric geometry with a straight intake manifold and fixed valve lift Simulation by Peric, Imperial College London /15

13 Automotive of CFD in 1990s Expanding Computer Power and Validated Models Numerical modelling is moving towards product design Improvements in computer performance: reduced hardware cost, Moore s law Improved physical modelling and numerics: fundamental problems are with flow, turbulence and discretisation are resolved Sufficient validation and experience accumulated over 10 years Notable improvement in geometrical handling: realistic 3-D geometry Graphical post-processing tools and animations: easier solution analysis Mesh generation for complex geometry is a bottle-neck: need better tools 13/15

14 Expansion of Automotive CFD Computational Resources Increase in computer performance drives the expansion of CFD into new areas by reducing simulation turn-over time Massively parallel computers provide the equivalent largest supercomputers at prices affordable in industrial environment (1000s of CPUs) Physical Modelling New physical models quickly find their use, e.g. free surface flows Looking at more complex systems in transient mode and in 3-D: simulation of a multi-cylinder engine, with dynamic effects in the intake and exhaust system Computing power brings in new areas of simulation and physical modelling paradigms. Example: Large Eddy Simulation (LES) of turbulent flows Integration into a CAE Environment Computer-Aided Design software is the basis of automotive industry Historically, mesh generation and CFD software are developed separately and outside of CAD environment, but the work flow is CAD based! Current trend looks to seamlessly include CFD capabilities in CAD 14/15

15 Summary Summary: Automotive CFD Today CFD is successfully used across automotive product development Initial landing target of external aerodynamics and in-cylinder engine simulation still not reached (!) sufficient accuracy difficult to achieve Lessons Learned The success of CFD in automotive simulation is based on providing industry needs rather than choosing problems we may simulate: find a critical broken process and offer a solution Numerical simulation tools will be adopted only when they fit the product development process: robust, accurate and validated solver, rapid turn-over Experimental and numerical work complement each other even if sufficient accuracy for predictive simulations cannot be achieved Validation of simulation results understanding experimental set-up Parametric studies: speeding up experimental turn-over True impact of simulation tools is beyond the obvious uses: industry will drive the research effort to answer its needs Images and animations courtesy Ansys/Fluent Inc. and my colleagues - thank you 15/15

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