计算流体动力学

By modifying the fan components such as the blade design, pitch angle or housing design, a fan of better performance based on higher efficiency and lower sound emission can be designed. However the fan component to modify and the degree of adjustment are often not known and trial and error testing waste too much time in the design process.

Using CFD, a computational model that represents a system or device that is subjected to study was built. Then fluid flow physics is applied to this virtual prototype, and the software outputs a prediction of the fluid dynamics. CFD gives a means of visualizing and enhanced understanding of designs. In a short time, one can predict how a design will perform, and test many variations until an optimal result in obtained. All of this is done before physical prototyping and testing. The foresight gained from CFD helps to design better and faster. Better and faster design or analysis leads to shorter design cycles. Time and money are saved. Products get to market faster. Equipment improvements are built and installed with minimal downtime. Thus, CFD is a tool for compressing the design and development cycle.

Computational Design Optimization techniques start with a specification of a fan design objective function and a statement of design constraints. An initial guess of a fan blade shape or configuration is then made to start the optimal design process to achieve the target design configuration which will optimizes the design objective function as well as satisfy all the design constraints. Then the design optimization techniques (stochastic/deterministic or hybrid methods) are used for the iterative design process until the target design which satisfies all the imposed design constraints is reached. During each design iteration, CFD is used to compute the flow field in the vicinity of the fan blade and to estimate the design objective function.

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