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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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CASE STUDY

Beyond the barrier of perfection

Optimization Case study of a multi-stage steam turbine designed by Franco Tosi Meccanica

This case study details the design optimization of an axial steam turbine of 160 MW, focusing on maximizing the total-to-total isentropic efficiency of the last three low-pressure stages of the turbine.

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