Nwagoum, Idriss Chatrian
(2020)

*aerodynamic performance improvement of a twin scroll
turbocharger turbine using the design of experiments method.*
[Laurea magistrale], Università di Bologna, Corso di Studio in

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## Abstract

This dissertation aims to improve the aerodynamic performance of a turbocharger turbine using the design of experiments method (DoE) and optimisation algorithms; the design of experiments aims at predicting the outcome by introducing a change of the preconditions, which are represented by one or more independent variables, also referred to as "input variables" or "predictor variables"; the change in one or more independent variables is
generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables".
The dissertation is structured in the following main points: a first chapter resuming a literature background on turbomachinery, a second chapter containing the design of experiments and the optimisation methods, then the DoE, which is performed by first setting properly the upper and lower bounds for each turbine geometrical parameter, followed by a Latin hypercube sampling (LHS) of the design space; a third chapter which presents the
turbine geometries building process using Daimler in-house tools; this step is then followed by the CFD simulations and a final chapter where the metamodels for the turbine performance prediction are build through the software OptiSlang and finally the optimisation process using an adaptative response to surface (ARSM) algorithm, an evolutionary algorithm (EA) and the non-linear programming by quadratic lagrangian (NLPQL) algorithm.
This paper present the results obtained from three different optimization algorithms, namely the improved designs predicted by the metamodels and the validation results from the CFD simulations; it is found that in case of a single objective optimization with few constraints which is our specific case, the NLPQL algorithm finds the best improved design with an increment in efficiency of 1:3% with respect to the base turbine, this result is further validated with CFD simulations.

Abstract

This dissertation aims to improve the aerodynamic performance of a turbocharger turbine using the design of experiments method (DoE) and optimisation algorithms; the design of experiments aims at predicting the outcome by introducing a change of the preconditions, which are represented by one or more independent variables, also referred to as "input variables" or "predictor variables"; the change in one or more independent variables is
generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables".
The dissertation is structured in the following main points: a first chapter resuming a literature background on turbomachinery, a second chapter containing the design of experiments and the optimisation methods, then the DoE, which is performed by first setting properly the upper and lower bounds for each turbine geometrical parameter, followed by a Latin hypercube sampling (LHS) of the design space; a third chapter which presents the
turbine geometries building process using Daimler in-house tools; this step is then followed by the CFD simulations and a final chapter where the metamodels for the turbine performance prediction are build through the software OptiSlang and finally the optimisation process using an adaptative response to surface (ARSM) algorithm, an evolutionary algorithm (EA) and the non-linear programming by quadratic lagrangian (NLPQL) algorithm.
This paper present the results obtained from three different optimization algorithms, namely the improved designs predicted by the metamodels and the validation results from the CFD simulations; it is found that in case of a single objective optimization with few constraints which is our specific case, the NLPQL algorithm finds the best improved design with an increment in efficiency of 1:3% with respect to the base turbine, this result is further validated with CFD simulations.

Tipologia del documento

Tesi di laurea
(Laurea magistrale)

Autore della tesi

Nwagoum, Idriss Chatrian

Relatore della tesi

Scuola

Corso di studio

Ordinamento Cds

DM270

Parole chiave

Turbine optimization,turbocharger,DOF,design of experiments

Data di discussione della Tesi

9 Ottobre 2020

URI

## Altri metadati

Tipologia del documento

Tesi di laurea
(NON SPECIFICATO)

Autore della tesi

Nwagoum, Idriss Chatrian

Relatore della tesi

Scuola

Corso di studio

Ordinamento Cds

DM270

Parole chiave

Turbine optimization,turbocharger,DOF,design of experiments

Data di discussione della Tesi

9 Ottobre 2020

URI

Gestione del documento: