Chapter 7 Summary and conclusions

CHAPTER 7 SUMMARY AND CONCLUSIONSdependency on the Smagorinsky constant was large. But the need for special wall treatment in order toaccount for the reduction of subgrid scale lengths near the solid walls making this methods unfavourable,although it is simple to implement and very fast to compute. The dynamic model on the other hand gaveresults in good agreement with measurements. But the original dynamic model also needed a specialtreatment depending on whether the flow has one or more homogeneous direction(s) in which theequations could be averaged. For fully inhomogeneous flows only an averaging procedure in time isapplicable. To overcome the need for special treatment, the mixed scale model and a dynamic oneequationsubgrid model were also tested. The mixed scale model which was only tested by implementingit in the CFX software gave better results that the Smagorinsky model, but was not compatible with thedynamic subgrid models. The overall performance of the dynamic one-equation subgrid model did givebetter results than the other subgrid models, but were relatively expensive in terms of the computationalcosts, due to the fact that one more equation for the kinetic energy had to be solved, although the originaldynamic model requires some spatial averaging to obtain numerical stability.As for the two-equation turbulence model, like the standard k-I model which has been knownfor more than twenty years, it was found adequate for the full turbulent ventilation problems in thisproject. These kind of models will properly remain the most used models for the next decades.Nevertheless, its limitations are also well-known, particularly in flows where anisotropy is significant orin transitional flows. Several researchers have proposed modifications to this model, like anisotropicgeneralizations, or special treatment for low-Reynolds flows. An example is the k-I model arising fromthe renormalization group (RNG) theory. A high-strain correction, which is not strictly a result of theRNG analysis, to the I-equation is made so as to increase the dissipation rate and thus diminishingturbulent length scales. In separated flows, this leads to a relatively large recirculation zone as comparedto the standard k-I model. Unlike the k-I variants, the Wilcox k-q model can indeed be used across theviscous sublayer without low-Reynolds-number dependence. A qualified guess would be that due to thedevelopment and use of LES and DNS, the two-equations models will become more realisable forcomplex flows. But for transition problems and/or time dependent situations, LES will probably be thebest choice. But since LES is a relatively new tool compared to the two-equations models, some lessonshave to be learned, like better treatment of boundary conditions, and how advanced the subgrid scalemodels should be to capture important flow features.Finally, the need for a fast numerical solver and better implementation in order to improve thecomputational performance and efficiency when applying Large Eddy Simulation to a problem isemphasize. The explicit and implicit implementation was at last compared in terms of computationalefficiency (Elapsed Wall Clock Time). The implicit method did shown superior over the explicit method,due to the possibility of using larger time steps. It was however not investigated if the implicit methodwould retain superiority in the simulation of transitional flows. The demand for a very fast method forthe solution of the Pressure Poisson equation were shown while comparing different preconditioningmethods for the Conjugate Gradient iterative solver and a multigrid implementation. The ConjugateGradient with Matrix-Renumbering Incomplete LU preconditioning and the multigrid implementationdid show almost grid-independent convergence rate.186

CHAPTER 7 SUMMARY AND CONCLUSIONSIn general, the numerical simulation of turbulence is an extremely intensive computational taskand quickly saturates even the impressive gains in computer speed that marks every new development incomputer technology. This fact, coupled with the extraordinary theoretical difficulties involves indeveloping any statistical closure theory of turbulence propels Large Eddy Simulation as one of the mostversatile tools for the calculations of complex flows . Or the combination of traditional ReynoldsAveraging Simulation with Large Eddy Simulation, known as Detached Eddy Simulation.The use of high performance computer systems will make the Large Eddy Simulation methodmore attractive. Especially, the use of latest processor technology and the use of parallel computers. Mostof the simulation within this project was done of a PC-workstation, which is currently one year behindthe latest processor technology. Upgrading would reduce the computational time by almost a factor oftwo using PC technology and almost a factor of four when using UNIX workstation with the Alphaprocessor.The potential for Large Eddy Simulation for visualization of essential flow structures in the flowas well as for reliable quantitative predictions has been demonstrated, at least for relatively simplegeometries. One of the challenges ahead would be to demonstrate unambiguously that Large EddySimulation is able to predict quantitatively statistical measures of interest in the domain of truly complexengineering flows.7.2 Directions of future work.Beside the general cleanup and a small part of recoding, there are different paths to follow. Onewould be the extention of the code to be able to simulate the effect of dispersions of particles and gaseouspollutants in similar ventilated enclosures, since in general the building geometries that we are interestedin are rectangular. Another path would be the more advanced models for the simulation of non-isothermalconditions that would also be an important issue of the code. Last but not least the code needs to beextented with multi-block facilities. Which will enable more complex geometries to be simulated. Sincethe Large Eddy Simulation methods are very computing intensive, this subject was postponed to later.An extension to use parallel computer systems to further reduce the massive cpu-time consumption willbe need.One final word about parallel computing should be said: since the demands especially when usingLES are so high, the field of high performance computing should be studied further and in particular thatof parallel computing. The field of high performance computing is very relevant to turbulence flowsimulation in general. Even with the vector super computer available at present much remains to be done.Programming to achieve high performance on vector supercomputer and serial computer (RISC CPU) isquite different as illustrated in this project. The different architectures of these computer systems, requirethe adaptation of different implementations of existing algorithms, even such basic methods as the BLAS.Moreover, there is a great need for efficient algorithms based on parallel computing to realize the highcomputing speeds needed in the future. The aspects of communication between several processors in aparallel computer and the minimation of the associated overhead are worth further research. This is very187

CHAPTER 7 SUMMARY AND CONCLUSIONSevident with the development of the Beowolf 1 like computer systems. The Beowulf parallel workstationproject is driven by a set of requirements for high performance scientific workstations in the Earth andspace science communities and the opportunity of low cost computing made available through the PCrelated mass market of commodity subsystems. This opportunity is also facilitated by the availability ofthe Linux operating system, a robust Unix-like system environment with source codes that are targetedfor the Intel x86 family of microprocessors including the Intel Pentium.An important key component to forward compatibility is the system software used on Beowulf. With thematurity and robustness of Linux, GNU software and the "standardization" of message passing via PVMand MPI, programmers now have a guarantee that the programs they write will run on future Beowulfclusters, regardless of who makes the processors or the networks. A natural consequence of coupling thesystem software with vendor hardware is that the system software must be developed and refined onlyslightly ahead of the application software. The criticism that system software for high performancecomputers is always inadequate is actually unfair to those developing it. In most cases coupling vendorsoftware and hardware forces the system software to be perpetually immature. The model used forBeowulf system software can break that rule.Beyond the seasoned parallel programs, Beowulf clusters have been built and used by programmers withlittle or no parallel programming experience. In fact, Beowulf clusters provide universities, often withlimited resources, an excellent platform to teach parallel programming courses and provide cost effectivecomputing to their computational scientists as well. The startup cost in a university situation is minimalfor the usual reasons: most students interested in such a project are likely to be running Linux on theirown computers, setting up a lab and learning to write parallel programs is part of the learning experience.1 ) More information about the Beowolf system at the Internet homepage:http://www.beowulf.org/188

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