A Linear Transformation for the Reconstruction of the Responses of Systems in Similitude

Fiorella Tavasso, Alessandro Casaburo, Giuseppe Petrone, Francesco Franco, Sergio De Rosa
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Abstract

Recent years have seen an increasing interest towards similitude methods. In fact, the possibility of testing a scaled model, instead of a full-scale prototype, leads to many advantages: financial and time savings, easier experimental setups, etc. However, similitudes have drawbacks, too, mainly due to non-scalable effects and partial similitude, which prevent from an accurate reconstruction of the prototype response. For these reasons, an alternative method which can bypass these limitations is needed. A new method, called VOODOO (Versatile Offset Operator for the Discrete Observation of Objects), is herein proposed: it is based on the definition of a transformation matrix which links the outputs of a given linear systems to those belonging to another system, which may be a scaled model. The responses are acquired on a discrete number of points for both the systems. This work aims at investigating the method’s strengths and limitations of the method. The results show that, although VOODOO exhibits some lack of accuracy in off-design conditions due to the loss of spatial correlation, it is able to overcome some major restrictions that affect all similitude methods.

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一类近似系统响应重构的线性变换
近年来,人们对相似方法的兴趣日益浓厚。事实上,测试一个比例模型的可能性,而不是一个全尺寸的原型,会带来很多好处:节省资金和时间,更容易的实验设置,等等。然而,相似也有缺点,主要是由于不可扩展的效应和部分相似,这阻碍了原型响应的准确重建。由于这些原因,需要一种可以绕过这些限制的替代方法。本文提出了一种新的方法,称为VOODOO(用于对象离散观测的通用偏移算子):它是基于转换矩阵的定义,该变换矩阵将给定线性系统的输出与属于另一个系统的输出联系起来,该系统可能是一个缩放模型。在两个系统的离散点上获取响应。这项工作旨在调查该方法的优势和局限性。结果表明,尽管由于空间相关性的丧失,VOODOO在非设计条件下表现出一定的准确性不足,但它能够克服影响所有相似方法的一些主要限制。
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