Benefit is claimed under 35 U.S.C 119(a)-(d) to Indian Application Serial No. 4230/CHE/2013 entitled “BOUNDARY LAYER COMPUTATIONS ON CFD GRIDS” filed on Sep. 20, 2013 by AIRBUS INDIA OPERATIONS PVT. LTD.
Embodiments of the present subject matter generally relate to computational fluid dynamics (CFD), and more particularly, to boundary layer computations on CFD grids.
Typically, CFD analysis requires accurate prediction of the properties of the boundary layer, i.e., the fluid surrounding the wall of a structure. For example, accurate aerodynamic analysis is particularly important when designing aircraft surfaces, such as the surface of a wing or control surface.
Generally, such boundary layer computations require creating a physical model or computer model, so that a simulation of the fluid flow over the boundary layer can be carried out and properties of the simulated fluid flow can be measured. Such measured fluid-flow properties over the boundary layer may be used to predict the characteristics of the wing including lift, drag, boundary-layer velocity and temperature profiles, pressure distribution and the like.
However, creating either a physical model or a computer model and carrying out the simulations may be very time consuming and expensive. Complex CFD simulation modules can be computationally expensive and may require hours or even days to execute using high-performance computer processing hardware.
System and method for boundary layer computations on CAD girds are disclosed. According to one aspect of the present subject matter, a first boundary layer cell that is substantially close to a wall is selected. A recursive function is then launched for each cell adjacent and around the selected first boundary layer cell to determine a cell having a highest dot product with the normal of the first boundary layer cell. The cell having the highest dot product with the first cell is declared as the second boundary layer cell. The declared cell is selected as the second boundary layer cell. The above steps of selecting, launching and declaring are repeated until a desired number of layers in the boundary layer are completed. The boundary layer properties associated with each selected boundary layer is computed using CFD analysis.
According to another aspect of the present subject matter, a system including a processor, and memory coupled to the processor and the memory includes a FEA tool having instructions that is configured to select a first boundary layer cell that is substantially close to a wall of a structure. Launch a recursive function for each cell adjacent and around the selected first boundary layer cell to determine a cell having a highest dot product with the normal of the first boundary layer cell. Declares the cell having the highest dot product with the first cell as the second boundary layer cell. Selects the declared cell as the second boundary layer cell. Repeats the above steps of selecting, launching and declaring until a desired number of layers in the boundary layer are completed. Computes the boundary layer properties associated with each selected boundary layer using CFD analysis.
The systems and methods disclosed herein may be implemented in any means for achieving various aspects. Other features will be apparent from the accompanying drawings and from the detailed description that follow.
Various embodiments are described herein with reference to the drawings, wherein:
The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way.
System and method of boundary layer computations on CFD grids are disclosed. In the following detailed description of the embodiments of the present subject matter, references are made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the present subject matter may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the present subject matter, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present subject matter. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present subject matter is defined by the appended claims.
Although certain terms are used primarily herein, other terms could be used interchangeably to yield equivalent embodiments and examples. For example, it is well known that equivalent terms in the field of CFD of related fields could be substituted for such terms as “cell”, “element”, “grid cell” or the like. The terms “mesh” and “grid” are used interchangeably throughout the document.
Example embodiments proposes an amalgamation of algorithms, techniques and rules to overcome the drawbacks associated with creating physical model on a computer model to predict boundary layer properties over the boundary layer. The proposed example algorithm/technique/rules/formulas proposed works for all cell shapes as it relies mostly on nodes and faces rather than the topology of the cells. This algorithm can be used to generate element-node-element connectivity data when element-face-element connectivity data is present.
Example Processes
In block 104, a recursive function is launched for each cell that is adjacent to and around the selected first boundary layer cell to determine a cell having a highest dot product with the normal of the first boundary layer cell. In our running example in
In some embodiments, a recursive function is launched for each cell that is adjacent to and around the selected first boundary layer cell includes selecting a cell that is adjacent to and having a common face with the first boundary layer cell, because a cell with a common face may have more stored cell connectivity information. In our running example in
In block 106 the cell having the highest dot product with the first cell as the is declared as the second boundary layer cell. In these embodiments, the steps of selecting, determining and computing are repeated for each cell that is adjacent and having a common face or edge with the first boundary layer cell as show in
In some embodiments, the inputs to the recursive function are current layer cell index, new cell index and direction to be traversed. In these embodiments, current layer cell index and direction are stored in global variables outside the recursive function. Within the function, following steps may be carried out:
In block 110 the above steps of selecting, launching and declaring is repeated until a desired number of layers in the boundary layer are completed. The desired number of layers in the boundary layer may be based on the distance or temperature at some distance from the wall or temperature gradient from wall to a distance away from wall.
In block 112, the boundary layer properties associated with each selected boundary layer is computed using CFD analysis. Example boundary layer properties are temperature, velocity, species and the like.
The computing system 402 includes a processor 404, memory 406, a removable storage 418, and a non-removable storage 420. The computing system 402 additionally includes a bus 414 and a network interface 416. As shown in
Exemplary user input devices 422 include a digitizer screen, a stylus, a trackball, a keyboard, a keypad, a mouse and the like. Exemplary output devices 424 include a display unit of the personal computer, a mobile device, and the like. Exemplary communication connections 426 include a local area network, a wide area network, and/or other network.
The memory 406 further includes volatile memory 408 and non-volatile memory 410. A variety of computer-readable storage media are stored in and accessed from the memory elements of the computing system 402, such as the volatile memory 408 and the non-volatile memory 410, the removable storage 418 and the non-removable storage 420. The memory elements include any suitable memory device(s) for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, hard drive, removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, Memory Sticks™, and the like.
The processor 404, as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a graphics processor, a digital signal processor, or any other type of processing circuit. The processor 404 also includes embedded controllers, such as generic or programmable logic devices or arrays, application specific integrated circuits, single-chip computers, smart cards, and the like.
Embodiments of the present subject matter may be implemented in conjunction with program modules, including functions, procedures, data structures, and application programs, for performing tasks, or defining abstract data types or low-level hardware contexts. Machine-readable instructions stored on any of the above-mentioned storage media may be executable by the processor 404 of the computing system 402. For example, a computer program 412 includes machine-readable instructions capable for implementing the boundary layer computations on the CFD grids, according to the teachings and herein described embodiments of the present subject matter. In one embodiment, the computer program 412 is included on a compact disk-read only memory (CD-ROM) and loaded from the CD-ROM to a hard drive in the non-volatile memory 410. The machine-readable instructions cause the computing system 402 to encode according to the various embodiments of the present subject matter.
As shown, the computer program 412 includes a boundary layer computation module 430 within a CFD tool 428. For example, the boundary layer computation module 430 can be in the form of instructions stored on a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium having the instructions that, when executed by the computing system 402, causes the computing system 402 to perform the methods described in
The above technique works for cells of all shapes as it relies on the nodes and faces of the cells rather than the topology of cell itself. In addition to carrying out the boundary layer calculations, the recursive function can also be used to generate node-element-node connectivity data from face-element-face data.
Although certain methods, systems, apparatus, and articles of manufacture have been described herein, the scope of coverage of this patent is not limited thereto. To the contrary, this patent covers all methods, apparatus, and articles of manufacture fairly falling within the scope of the appended claims either literally or under the doctrine of equivalents.
Number | Date | Country | Kind |
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4230/CHE/2013 | Sep 2013 | IN | national |