[BLANK_AUDIO] Welcome back to Sports & Building Aerodynamics in the week on Computational Fluid Dynamics. In the next two modules we're going to focus on Computational Wind Engineering. And we start again with the module question: Why is Computational Wind Engineering more complex than the routine application of CFD in aeronautics? Is it A) because of the lower Mach numbers in CWE? B) Because of the less streamlined bodies in CWE. C) The higher Reynolds numbers in CWE. Or D) The lower Reynolds numbers in CWE. Please hang on to your answer and we will come back to this question later in this module. At the end of this module you will understand what Computational Wind Engineering entails. You will understand why CWE is more complex than the routine application of CFD in aeronautics. You will understand some main concerns in CWE, such as verification, validation and specifying appropriate boundary conditions. And, this presentation is actually a short, slightly modified version of my keynote presentation at the 6th European-African Conference on Wind Engineering in Cambridge, UK. It has also been published in the Journal of Wind Engineering and Industrial Aerodynamics. So if you would like to read more about it you can find more information in this article. Let's start with the definition of CWE. In the broadest sense CWE is primarily defined as the use of Computation Fluid Dynamics for wind engineering applications, but can also include other approaches of computer modeling. It can even include field and wind tunnel measurements that support CWE model development and evaluation. However, in this MOOC we're going to use a narrower definition where we explicitly focus only on computer modeling as part of CWE. Let's have a brief look at the history of CWE. First some key dates and periods. It could be stated that CWE started about 50 years ago. Because then the first Symposium on Wind Effects on Buildings and Structures was held in Teddington. And it was also the time when the Smagorinsky-Lilly model was published. And this is a model that is still intensively used in many areas of fluid mechanics today. But the question is, was this the real starting point of CWE? Well, actually, what is the real starting point of CWE depends on the spatial scales that you want to consider. And in meteorology, a distinction can be made between the meteorological macroscale, so distances up to several hundreds of kilometers, then the meteorological mesoscale, between for example 10 kilometers and 1000 kilometers and then the meteorological microscale, with distances below about 1 to 10 kilometers. So let's have a look at early achievements at every of these spatial scales. So at the meteorological macroscale, already in 1922 there was actually the now very famous book of Lewis Fry Richardson, Weather Prediction by Numerical Process, in which he suggested, already at that early stage, to apply numerical integration to weather prediction. However, at that stage his approach was completely unfeasible because of the lack of computational power. And he actually stated in his book "Perhaps some day in the dim future it will be possible to advance the computations faster than the weather advances and at a cost less than the saving to mankind due to the information gained." And he concluded by stating "But that is a dream". A small note here, this Richardson is also the one that gave his name to the Richardson number and to Richardson extrapolation which we dealt with earlier in this MOOC. So, that was 1922. Fast forward towards the 1950s. That was when numerical weather prediction could actually be applied due to the emergence of the first electronic computers, and Jule Charney was quite active in this field. And, based on the successes, which he communicated then to Richardson, he also stated, during a conference, that: "To the extent that my work in weather prediction has been of value, it has been a vindication of the vision of my distinguished predecessor, Lewis Fry Richardson." So indeed, several decades after his now very famous book, Richardson's dream has come true. And after that, there were several other very valuable macroscale studies, early macroscale studies, and some of them are listed here. Focusing on meteorological mesoscale; in the 50s and 60s, there were some early mesoscale CWE studies. Including 2D numerical analysis, that means in a vertical section, of sea breezes with and without prevailing winds, convective motions over mountain ridges, and so on. And then later there were pioneering studies combining numerical simulations with dedicated wind-tunnel measurements for validation by Meroney and his co-workers in the U.S. Then, focusing on the meteorological microscale. Well, this is actually the scale where small-scale surface-mounted obstacles, such as buildings and trees and hills, are actually being modeled with their actual shape and dimensions. And these are a few examples of early microscale studies. Flow over, for example, square surface-mounted obstacles, over simplified hills, other types of idealized buildings, and so on. And then later, at the end of the 70s there were actually quite a lot of efforts focused on predicting mean velocity fields and mean pressure distributions on building surfaces in the lower part of the atmospheric boundary layer. Back to a few key dates and key periods. In 1991 there was the 8th International Conference on Wind Engineering in London, Ontario, chaired by Davenport. And for the first time this was a conference that had a full session dedicated to CFD. If was, of course, called Computational Fluid Dynamics and was shared by Stathopoulos and Kind. And only one year later there was the organization of the first symposium on Computational Wind Engineering in Tokyo, Japan. And this, for the first time, was a conference joining wind engineering delegates and classical aerodynamicists. And this conference actually very clearly outlined the many challenges to be encountered in CWE. And these have to do with the flow field around bluff bodies that have sharp edges and that yield problems that you cannot encounter in CFD computations of simple flows such as channel flow, simple shear flow and the like. And actually these challenges are very clearly outlined in this overview paper by Murakami, and they consist of the following: First, the high Reynolds numbers in wind engineering applications. Which means you have to apply high grid resolutions, especially in near-wall regions, and you need to work with accurate wall functions. Then there is the complex nature of the 3D flow field with impingement, massive separation and vortex shedding in the wake. And there's numerical difficulties associated with flow at sharp corners and the consequences that this has for discretization schemes. And finally, there's the inflow and also outflow boundary conditions which are particularly challenging for Large Eddy Simulation. And actually this complexity also indicates the necessity of solution verification and validation and of best practice guidelines in CWE. So I would like to offer you some quotes here on verification and validation, with a major disclaimer because this is only a very limited selection of quotes and there are many more very interesting and important quotes. So this selection is inherently incomplete but they tend to give quite a good flavor of the difficulties and the discussions at that time. This is the first one by Murakami saying that: "The results of numerical simulation cannot be free from various types of numerical errors. Therefore, it is indispensable that the accuracy of numerical simulation be examined by comparing numerical results with those from wind-tunnel tests or field experiments." He concluded: "Therefore, the two different methods of research should proceed in concert and in cooperation with each other." This quote by Ferziger, stating, "The frequently heard argument, any solution is better than none, can be dangerous in the extreme. The greatest disaster that one can encounter in computation is not instability or lack of convergence, but results that are simultaneously good enough to be believable, but bad enough to cause trouble." There's a quote by Roache stating that "The very important point, independent of the semantics, is that use of a verified code is not enough. Especially in the commercial CFD arena, user expectations are often that the purchase and use of a really good code will remove from the user the obligation of doing his homework. That is, the straightforward but tedious work of verification of calculations via systematic grid-convergence studies." A quote by Schatzmann stating "To simply compare model results with measured date is often inappropriate since data generated in field or laboratory experiments and those from model simulations exhibit systematic differences. In view of the remarks made above, it must be concluded that such a comparison often resembles the proverbial comparison of apples with oranges." Two quotes by Stathopoulos stating "Most practitioners are more concerned with obtaining results than with either the order of accuracy of their numerical schemes or the need to refine the grid until converged grid-independent solutions are obtained." And the second one "It appears that although CFD is definitely a good friend of wind engineering, it has not yet become a true ally." A quote by Murakami again, stating that "In this paper we have presented several applications of CFD analysis of outdoor climate ranging from human scale to urban scale. At this stage, the accuracy of CFD predictions is pretty good but not perfect. However, we do think that the comprehensive assessment based on the CFD method combining various factors seems to be the only approach for clarifying such complicated phenomena." A quote by Meroney stating that "Good mental health in a fluid or CFD modeler is always indicated by the presence of a suspicious nature, cynicism, and a show me attitude. These are not necessarily the best traits for a life mate or a best friend, but they are essential if the integrity of the modeling process is to be maintained." And I've been so bold to also include a statement by myself: "The judicial presumption of innocence does not hold in CFD. CFD results are wrong until proven otherwise." Given the importance of verification and validation, best practice guidelines have been established. And it is clear that in CFD a large number of choices need to be made by the user, and these can have a very large impact on the results. And this work on investigating the impact of computational parameters on the accuracy of the results already started in the late 70s, and 80s, where researchers have been testing all kinds of parameters and their influences. And a few of those studies are mentioned here. But in the beginning, these studies were actually fragmented over a large number of publications in journals and conference proceedings, and reports, and only later they have been compiled into what is now known as the best practice guideline documents. And I would like to give you an overview here, a list of several of those documents, including the ERCOFTAC Best Practice Guidelines, the COST Best Practice Guidelines and also the best practice guidelines from colleagues in the Architectural Institute of Japan, and also some others are mentioned here. And actually these best practice guidelines were supported by the underlying best practice guidelines on verification and validation and a list of those guidelines you can see on this slide. Briefly, something about appropriate boundary conditions in CWE, which is a very important topic. And imagine here a computational domain with a group of buildings in the middle, and then you apply boundary conditions, so an atmospheric boundary layer profile at the inlet. And as the profile flows towards the buildings, and it travels through the computational domain, it is often observed that this profile shows unintended streamwise changes, horizontal inhomogeneity. And Richards and Hoxey were actually of the first to point to this problem, and to also offer a solution. And they stated: "In 1958, Jensen showed that in wind-tunnel testing it is just as important to correctly model the wind as it is to correctly model the building. This lesson must surely carry over into the relatively new field of computational wind engineering." And it was a statement actually made by them at the occasion of the first symposium on Computational Wind Engineering and then published one year later in the Journal of Wind Engineering and Industrial Aerodynamics. So looking at their paper, well this is the title of the paper with the names of authors and affiliations. And if you look at the citation record of this paper something very remarkable can be seen. In the beginning it gathered very few citations so you could say this was an incubation period but at some point the number of citations really took off. And the current amount of citations is quite impressive for a paper in wind engineering. So it is clearly a success period and it shows several other things; that the citations have been obtained from a wide range of disciplines, meteorology, earth sciences, wind energy and so on, indicating that this was really an important achievement this paper. Also that, if you look at this graph, two years is not long enough to calculate an impact factor in wind engineering. But also, that this paper and many other wind engineering papers are almost timeless. So after that, indicating also that this was an important paper, several follow-up papers have been written, always addressing the same well, the similar problem with the different types of solutions. And you can see a list of some of those papers here. So let's turn to some quotes on appropriate boundary conditions. Well this is the one that we just presented. This is another one by Richards and Norris now, presented at a later stage at the 5th symposium of Computational Wind Engineering stating "Appropriate boundary conditions for Computational Wind Engineering was an issue addressed by Richards and Hoxey at the first Computational Wind Engineering Conference and is still a relevant issue today." This quote by Xie and Castro on LES inflow conditions mentioning that: "There's certainly scope for further development. Our feeling is that for general applicability it is important to model not only the turbulence stresses but also correlation scales in all three directions, as in the present method." And this is a quote by Mochida stating that: "In order to couple the LES with MMM, that stands for Mesoscale Meteorological Models, successfully, several problems should be solved. One of the most significant issues to be solved from the viewpoint of CWE applications is a treatment of the turbulent velocity fluctuations imposed at the inflow as the boundary conditions." So let's turn back to the module question. Why is Computational Wind Engineering more complex than the routine application of CFD in aeronautics? And the reason is actually twofold of the list suggested here. It's the less streamlined bodies in CWE and it's the higher Reynolds numbers in CWE. And they give rise to massive separation at edges, recirculation and vortex shedding that needs to be resolved, and would need to be resolved on a high-resolution grid. In this module, we have learned about what Computational Wind Engineering entails, why it is more complex than than the routine application of CFD in aeronautics. And we've looked at some main concerns in CWE such as verification, validation, and specifying appropriate boundary conditions. In the next module we continue our focus on Computational Wind Engineering by explaining some of its disadvantages, addressing the sense or nonsense of the numerical wind tunnel, looking at the history and progress in CWE as shown by symposia and overview papers. We'll address some concerns about RANS versus LES and we'll show some interesting findings from a literature study on CFD simulation of pedestrian-level wind conditions. Thank you for watching and we hope to see you again in the next module.
