Optimization of a Centrifugal Compressor Impeller for Robustness to Manufacturing Uncertainties
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The current context leads energy system design to very demanding objectives, due to their variety. Indeed, despite an increasing energy demand, environment indicators are becoming always more important. So that for a given service, emission (and then assoc ...
This paper introduces a general framework that evaluates a numerical Bayesian multiresponse calibration approach based on a Gibbs within Metropolis searching algorithm and a statistical likelihood function. The methodology has been applied with two version ...
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The COST-731 action is focused on uncertainty propagation in hydrometeorological forecasting chains. Goals and activities of the action Working Group 2 are presented. Five foci for discussion and research have been identified: (1) understand uncertainties, ...
This thesis is about the numerical simulation and optimization of the alumina repartition in the bath of an aluminium electrolysis pot. A mathematical model is set up which contains the feeding of alumina particles to the bath, the dissolution of the parti ...
Many applications that require distributed optimization also include uncertainty about the problem and the optimization criteria themselves. However, current approaches to distributed optimization assume that the problem is entirely known before optimizati ...
Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the conte ...
In this work we present the concept of Uncertainty Feature Optimization (UFO), an optimization framework to handle problems due to noisy data. We show that UFO is an extension of standard methods as robust optimization and stochastic optimization and we sh ...
Challenges in real-time process optimization mainly arise from the inability to build and adapt accurate models for complex physico-chemical processes. This paper surveys different ways of using measurements to compensate for model uncertainty in the conte ...
In this work we present the concept of Uncertainty Feature Optimization (UFO), an optimization framework to handle problems due to noisy data. We show that UFO is an extension of standard methods as robust optimization and stochastic optimization and we sh ...