Multidiscipinary Optimization For Gas Turbines Design

02/03/2014
by   Francesco Bertini, et al.
0

State-of-the-art aeronautic Low Pressure gas Turbines (LPTs) are already characterized by high quality standards, thus they offer very narrow margins of improvement. Typical design process starts with a Concept Design (CD) phase, defined using mean-line 1D and other low-order tools, and evolves through a Preliminary Design (PD) phase, which allows the geometric definition in details. In this framework, multidisciplinary optimization is the only way to properly handle the complicated peculiarities of the design. The authors present different strategies and algorithms that have been implemented exploiting the PD phase as a real-like design benchmark to illustrate results. The purpose of this work is to describe the optimization techniques, their settings and how to implement them effectively in a multidisciplinary environment. Starting from a basic gradient method and a semi-random second order method, the authors have introduced an Artificial Bee Colony-like optimizer, a multi-objective Genetic Diversity Evolutionary Algorithm [1] and a multi-objective response surface approach based on Artificial Neural Network, parallelizing and customizing them for the gas turbine study. Moreover, speedup and improvement arrangements are embedded in different hybrid strategies with the aim at finding the best solutions for different kind of problems that arise in this field.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/26/2023

Multi objective Fitness Dependent Optimizer Algorithm

This paper proposes the multi objective variant of the recently introduc...
research
03/29/2022

A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization

This paper proposes a two-phase framework with a Bézier simplex-based in...
research
03/01/2021

Multi-Objective Evolutionary Design of Composite Data-Driven Models

In this paper, a multi-objective approach for the design of composite da...
research
04/10/2020

Uncrowded Hypervolume-based Multi-objective Optimization with Gene-pool Optimal Mixing

Domination-based multi-objective (MO) evolutionary algorithms (EAs) are ...
research
04/08/2022

Reproducibility and Baseline Reporting for Dynamic Multi-objective Benchmark Problems

Dynamic multi-objective optimization problems (DMOPs) are widely accepte...
research
06/22/2023

Multi-Objective Hull Form Optimization with CAD Engine-based Deep Learning Physics for 3D Flow Prediction

In this work, we propose a built-in Deep Learning Physics Optimization (...
research
12/20/2021

Evolutionary Hierarchical Harvest Schedule Optimization for Food Waste Prevention

In order to avoid disadvantages of monocropping for soil and environment...

Please sign up or login with your details

Forgot password? Click here to reset