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Computational Design Optimisation of a Centrifugal Pump

Computational Design Optimisation of a Centrifugal Pump
离心泵的计算设计优化
批准号:
1946827
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

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中文摘要
翻译
本项目的目的是在离心泵的设计过程中引入自动化,因此本项目属于工程设计研究领域。这是通过在设计过程中引入自动集成设计优化来实现的。为了实现这一目标,必须回答一些问题。首先,必须使用CFD模拟准确地模拟通过泵的流动。必须确定合适的求解器,以给出准确的流场,但不具有令人望而却步的巨大计算成本。另一方面,设计优化最容易在较少的参数上实现,因为在较大的参数集上进行优化通常是不可行的。因此,需要确定由一组足够小的参数组成的设计向量。如果使用CFD模拟评估潜在的泵设计非常耗时,则需要确定替代模型。通过评估设计空间中的多个设计,可以确定这一小部分设计的目标响应。然后可以在这个设计空间上创建一个代理模型来“填补空白”。一旦在设计空间上创建了目标函数的响应,则可以在该空间上进行优化。可以使用许多优化方法;其中包括局部优化器和全局优化器。这两种优化方法各有优缺点,需要对这两种方法的有效性进行测试。这些过程必须自动执行,这又增加了问题的复杂性。这一综合设计过程必须稳健,并能够处理实施过程中可能出现的一些潜在问题。此外,这可能是一个耗时的过程,因此必须考虑上述任何过程的计算成本。
英文摘要
The aim of this project is to introduce automation in the design process of a centrifugal pump, and therefore this project falls under the engineering design research area. This is achieved by introducing automatic integrated design optimization into the design process. In order to achieve this aim, there are a number of questions that must be answered. To begin with, flow through the pump must be accurately simulated using CFD simulations. Suitable solvers must be determined that give accurate flow fields, but do not have prohibitively large computational costs. On the other hand, design optimization is most easily implemented over a reduced number of parameters, as optimization over a large set of parameters is usually not feasible. Therefore, a design vector consisting of a sufficiently small set of parameters will need to be determined.If evaluating potential pump design using CFD simulations is significantly time-consuming, then a surrogate model will need to be determined. By evaluating a number of designs over the design space, the response of the objectives can be determined for this small number of designs. A surrogate model may then be created over this design space to 'fill in the blanks'. Once the response of the objective functions over the design space has been created, optimization over this space can then proceed. There are a number of optimization methods that may be used; these include local and global optimizers. Both of these methods of optimization have their advantages and disadvantages, and efficacy of both methods will need to be tested for this application.These processes must be automatically performed, which adds another level of complexity to the problem. This integrated design process must be robust and able to handle a number of potential issues that may arise during implementation. Furthermore, this may be a time-consuming process and therefore considerations must be made for the computational cost of any of the above processes.
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