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Autumn 2022 | Product peek

Analyse design space data easily with Multivariate Clustering techniques for efficient decision making

by Mauro Munerato, Alessandro Viola | ESTECO
Futurities Year 19 n°3, Autumn 2022

When dealing with enormous amounts of data, analysing them is a challenging task. Clustering techniques come in handy for such data analyses.

Multivariate Analysis (MVA) refers to statistical techniques used to analyse datasets with a lot of variables to consequently identify patterns. It allows you to better understand the design space and the relationships between the variables before formulating the optimization study, making the process more efficient.

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The innovative integration platform for multi-objective and multi-disciplinary optimization

modeFRONTIER provides a seamless coupling with third party engineering tools, enables the automation of the design simulation process, and facilitates analytic decision making.

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CASE STUDY

The design optimization of a small axial turbine with millions of configurations

The case for computerized optimization over manual design interventions

In this article, we show that the main turbine characteristics, such as efficiency and exit flow angle, can be sufficiently improved using parametric optimization.

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