Contents:
A Wavelet Tour of Signal Processing. Particles, Sources, And Fields, Volume 3. Combinatorial Geometry in the Plane. Guide to Geometric Algebra in Practice. The Interesting Golden Ratio. Wave Propagation in Fluids. Multirate and Wavelet Signal Processing. Finite Element Analysis with Error Estimators. Introduction to Finite Element Analysis and Design. Polyhedral and Algebraic Methods in Computational Geometry.
Quantum Invariants of Knots and 3-Manifolds. Integrated Graphic and Computer Modelling. Electromagnetic Waves in Complex Systems.
An Algebraic Introduction to K-Theory. The Finite Element Method. Topics in Matroid Theory. Perspectives in Analysis, Geometry, and Topology. Finite Element Simulation of Heat Transfer. Geometry - Task Sheets Gr. How to write a great review. The review must be at least 50 characters long. The title should be at least 4 characters long. Your display name should be at least 2 characters long. At Kobo, we try to ensure that published reviews do not contain rude or profane language, spoilers, or any of our reviewer's personal information. You submitted the following rating and review.
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A practical, straightforward approach to this complex subject for engineers and students. A key technique for modelling physical systems. Ratings and Reviews 0 0 star ratings 0 reviews.
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Would you like us to take another look at this review? No, cancel Yes, report it Thanks! CFD in general is seen as a science, a tool to mathematically obtain fluid flow information. The envelope forms the foundation upon which the physics solver typically CFD solver must operate. Is there a need for a debate on the classification of grid-generation? Why worry on the details of grid generation? The simple reason being — all grids are not created equal. And all grids do not give you the same CFD results even for a simplistic geometry like an airfoil.
The definition of science tells us , a process can be termed as science if it can be replicated under similar conditions by different individuals who in the end should converge exactly to the same results. For instance, there is a reason for the first cell height placement inside the boundary layer, a reason for the growth rate used, a reason for the choice of the far-field distance, a reason for the orthogonality of cells inside a boundary layer, a reason for the choices of grid density, and, of course, a reason to stress high grid quality and so fourth. And, moreover, in addition to all of these rational choices, there is the underlying need to accurately represent the boundaries of the simulation region.
These choices and associated constraints upon the grid have their roots in the physics of fluid dynamics, the given regional geometric definitions, and the extent within which the numerical methods do function. In a way, this has helped to standardise the grid generation practices and has aided in automating parts of the grid-generation process.
Due to its importance, the committees running these workshops have come-up with formal guidelines for grid generation that address the classification of fluid flow problems. Imbedded in these classifications from the workshops, there are significant signals of what is good and what is not. Such decisions rely upon having enough CFD accuracy to answer our key questions with respect to the level of physics being modelled.
The following two chapters contain an introduction to the basic techniques ( mainly of unstructured grid generation, presenting the fundamentals of Delaunay. Purchase Basic Structured Grid Generation - 1st Edition. Print Book With an introduction to unstructured grid generation. Write a review.
All of this can make CFD a powerful and reliable design tool. Image source — Centaur Software. What is in grid-generation which makes one perceive it as more of as an art than a science? The answer lies in the way we go about filling the computational domain with the geometric elements.
Though, all we do is populating the fluid region by a grid of an element type or types, it is really how we go about doing it and which of the various options we use. It is this collective whole in the end which brings us to the differences among the grids.
Even, well within the standard grid generation framework that was laid out, there are various possibilities and it is up to the CFD engineer to decide which options to pick and use to create the grid. Even after adhering to the stringent guidelines prescribed by the committees, the grids, whether structured or unstructured are visibly different, which in turn are reflected in the simulated CFD results.
It is for this reason that the organizers would like the participants to use the workshop committee grids, as this will aid in reducing the wide scatter of CFD results due to variation in grids. What makes grid-generation seem artistic is the fuzzy value or nature of desired grid features, although many, of them, can be stated in a rather analytical way. This includes grid alignment to flows, grid point patterns, good element shapes, gentle transitions between the elements smoothness , local enrichment for anticipated physics, and relative cell orientations.
Although this list is not necessarily complete, it does indicate that various tradeoffs are required and that the person doing the grid generation must then make a number of choices along the way. Standard grid generation guidelines have laid out stringent rules for some specifics such as grid resolution, growth rate and cell count, but not for the fuzzy items like flow alignment or topology structure which bring in the differences in sometimes less than subtle ways.
Referring the same gridding guidelines, different organisations have generated different grids. The mysterious aspects of grid generation A common method to reduce uncertainty is to perform a grid convergence study, whereby a family of grids are generated and used at various levels of point count.
This is done in order to eliminate some of the uncertainties due to grid resolution. In doing so, one must navigate through items like the first cell off the wall and growth rate for the treatment of boundary layers.
However, albeit with the best of intentions, they do fail to quantify the role of the more fuzzy qualities. It is these aspects that seem to highlight the art of grid generation. In the case of multi-block grids, this process is easier to do and is also much more precise in the end. What one does in this context is to generate a fine grid that has a succession of embedded sub-grids of progressive lower density. For example, suppose that we simply want a fine, medium, and coarse grid. Then we generate a fine grid with a factor of 4 in its cell count from which we then combine neighboring cells to get the medium grid, and from the medium grid we do it again to get the coarse grid.
Aside from the ease with which this is executed, we do have grid points that do not change as we go up in resolution: However, we do have one concern, which is the required first spacing off of the wall for boundary layers.
What this means is that our fine grid first off the wall spacing must be 4 times finer than that in the coarse grid. For the various unstructured approaches, we do not generally have such a nice nested structure. Each grid level is generated separately with variations in the total number of points which then will give us say a fine, medium, and coarse mesh. Due to the separate mesh generation actions, it is easy to enforce the same first spacing off of the wall for the boundary layer.
However, the general transfer of data between the meshes needs interpolation.
Even the type of elements chosen to generate the grid plays a role in mystifying the differences brought to the CFD solution. Although improvements in CFD solver algorithms over time have diminished the influence of element types, there still remain such differences and those differences are hard to assess in an analytical way.
This is quite evident in the wider spread of CFD results from the various participants using unstructured grids when compared with the participants using structured grids. This phenomenon occurred in both the Drag Prediction and Highlift workshops. This is not by chance. Structured grids are more flow aligned, less dissipative, and better at capturing the physics than their unstructured counterparts. Though the type of elements are the same in Cartesian and multi-block structured grids, the lack of low alignment, the persistent presence of hanging-nodes, lack of smooth gradual transitioning across grid levels and the shift in the grid arrangement at the boundary layer padding interface, makes Cartesian grids less accurate compared to multi-block.
It is for this reason that, CFD engineers opt for structured multi-block when they want to quantify the change in fluid-flow due to minute changes in product design. Long term CFD engineers in certain specialised fields like Hypersonics assure structured multi-block is the only way for them to get accurate reliable numbers.
Apart from fixing the element size, growth rate, number of layers in the viscous padding, there is hardly anything much a user can do to influence the final grid. What the user gets is a pretty uniform carpeting of the flow region in an automated way. The mystery aspect of flow-alignment and the ways to control it is not understood in a clear way. This is something, which comes only with experience. The way the blocks are built and arranged and aligned around the body of interest is all dependent on the creative intelligence of the CFD Engineer.