Research on Multidisciplinary Design Optimization of Aeroengine Turbine Flow Path in the Preliminary Design Phase

Author(s):  
Xiuli Shen ◽  
Dan Long

The design of an aero-engine is traditionally divided into three levels: conceptual design, preliminary design and detailed design. This three-step design process is inherently iterative, which can slow the design process and overall productivity. Additionally, as an integrated systems engineering analysis, aero-engine design involves multiple-disciplines. The complex coupled-relationship among multiple-disciplines and multiple-components gives rise to severe conflict with performance requirements when designing, especially when it comes to high-performance aero-engine. Traditionally, designers need to empirically balance all kinds of requirements, which lead to a longer design cycle. So it is necessary to apply Multidisciplinary Design Optimization (MDO) to organize and manage the process of design system which sufficiently utilizes the effect of interaction of multidisciplines for the optimal solution. The MDO of a turbine flow path is one of the key multidisciplinary optimization technologies in aeroengine overall design. The problem studied and presented in this paper consists in optimizing a turbine modeled by a multidisciplinary system of two coupled disciplines: turbine aerodynamics and structural strength, with temperature limited by the materials. In the present work, three modules are established to conduct the MDO research of turbine flow path: flow path design, turbine strength calculation and MDO. The aeroengine turbine flow path, including high and low pressure turbine flow path, is designed in the first module, with its efficiency estimated. In the second module, turbine rotors consisting of blades, discs and the low spool shaft are parametric modeled so as to analyze the structural aspects of turbine rotors, such as weight and stresses. MDO is conducted using multi-island genetic algorithm optimization (MIGA) optimization algorithm provided in iSIGHT software. Fully Integrated Optimization (FIO) strategy is studied to deal with the multidisciplinary analysis. The complex coupling relations between aerodynamic performance and turbine strength are analyzed to establish turbine multidisciplinary optimization system. The optimal values of loading coefficient, rotational speed, bore diameter of rotor discs defined by the shaft size, and other independent design variables are obtained in order to achieve minimum weight of turbine rotors while simultaneously meeting the strength and aerodynamics efficiency requirements. This method presented in this paper can greatly shorten turbine design cycle, improve aeroengine design ability, and is prospective to be widely applied to engineering field.

Author(s):  
Mehdi Mcharek ◽  
Toufik Azib ◽  
Moncef Hammadi ◽  
Cherif Larouci ◽  
Jean-Yves Choley

Purpose Within the current industrial context, companies aim to decrease the design process time and cost. The multidisciplinary design optimization (MDO) appears as a solution to accelerate the process and support designers in different stages of the design cycle. However, this relatively new concept needs to be integrated efficiently in the industrial environment and issues related to collaboration, data management, traceability and reuse need to be overcome. Design/methodology/approach The aim of this work is to efficiently integrate the MDO in the industrial design cycle by means of knowledge management (KM) techniques. To take into account the industrial environment, the methodology was applied in a collaborative software. Findings An example of collaborative design and optimization of an electronic throttle body (ETB) controller is presented with industrial requirements. The design problem was solved successfully and demonstrates the efficiency of the methodology in collaborative environments. Originality/value The contributions of this work lie in the structuration of the knowledge to support MDO and the definition of a general way to connect the existent MDO tools to the knowledge base. This methodology will enable to freely link different steps of the design process and reduce considerably the setting time of MDO in industries.


Author(s):  
Dongqin Li ◽  
Yifeng Guan ◽  
Qingfeng Wang ◽  
Zhitong Chen

The design of ship is related to several disciplines such as hydrostatic, resistance, propulsion and economic. The traditional design process of ship only involves independent design optimization within each discipline. With such an approach, there is no guarantee to achieve the optimum design. And at the same time improving the efficiency of ship optimization is also crucial for modem ship design. In this paper, an introduction of both the traditional ship design process and the fundamentals of Multidisciplinary Design Optimization (MDO) theory are presented and a comparison between the two methods is carried out. As one of the most frequently applied MDO methods, Collaborative Optimization (CO) promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, Design Of Experiment (DOE) and a new support vector regression algorithm are applied to CO to construct statistical approximation model in this paper. The support vector regression algorithm approximates the optimization model and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method. Then this new Collaborative Optimization (CO) method using approximate technology is discussed in detail and applied in ship design which considers hydrostatic, propulsion, weight and volume, performance and cost. It indicates that CO method combined with approximate technology can effectively solve complex engineering design optimization problem. Finally, some suggestions on the future improvements are proposed.


2021 ◽  
Author(s):  
Chris V. Pilcher

A multidisciplinary design optimization (MDO) strategy for the preliminary design of a sailplane has been developed. The proposed approach applies MDO techniques and multi-fidelity analysis methods which have seen successful use in many aerospace design applications. A customized genetic algorithm (GA) was developed to control the sailplane optimization that included aerodynamics/stability, structures/weights and balance and, performance/airworthiness disciplinary analysis modules. An adaptive meshing routine was developed to allow for accurate modeling of the aero structural couplinginvolved in wing design, which included a finite element method (FEM) structural solver along with a vortex lattice aerodynamics solver. Empirical equations were used to evaluate basic sailplane performance and airworthiness requirements. This research yielded an optimum design that correlated well with an existing high performance sailplane. The results of this thesis suggest that preliminary sailplane design is a well suited application for modern optimization techniques when coupled with, multi-fidelity analysis methods.


Author(s):  
Pascal Prado ◽  
Yulia Panchenko ◽  
Jean-Yves Tre´panier ◽  
Christophe Tribes

Preliminary Multidisciplinary Design Optimization (PMDO) project addresses the development and implementation of the Multidisciplinary Design Optimization (MDO) methodology in the Concept/Preliminary stages of the gas turbine design process. These initial phases encompass a wide range of coupled engineering disciplines. The PMDO System is a software tool intended to integrate existing design and analysis tools, decompose coupled multidisciplinary problems and, therefore, allow optimizers to speed-up preliminary engine design process. The current paper is a brief presentation of the specifications for the PMDO System as well as a description of the prototype being developed and evaluated. The current assumed e xible architecture is based on three software components that can be installed on different computers: a Java/XML MultiServer, a Java Graphical User Interface and a commercial optimization software.


2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Xiaojian Sun ◽  
Jianquan Ge ◽  
Tao Yang ◽  
Qiangqiang Xu ◽  
Bin Zhang

Integral solid propellant ramjet (ISPR) supersonic cruise vehicles share the characteristic that they are highly integrated configurations. The traditional design of vehicles cannot achieve a balance between computational expense and accuracy. A multifidelity multidisciplinary design optimization (MDO) platform has been developed in this study. The focus of the platform is on ISPR supersonic cruise vehicles. Firstly, codes of discipline with different levels of fidelity (LoF) were established, such as geometry, aerodynamics, radar cross-section calculations, propulsion, mass, and trajectory discipline codes. Secondly, two MDO frameworks were constructed through discipline codes. A low LoF MDO framework is suitable for conceptual design, and a medium LoF MDO framework is suitable for preliminary design. Finally, taking the optimization problem with the minimum overall detection probability of flight trajectory as an example, the low LoF framework first explores the entire design space to achieve the mission requirements, and then, the medium LoF MDO framework accepts the low LoF framework optimization parameters. Hence, the optimization target is reached with more detailed parameters and higher fidelity. Additionally, an example for a solid propellant missile with minimum total mass is tested by the platform. The study results show that the multifidelity MDO framework not only exploits interactions between the disciplines but also improves the accuracy of optimization results and reduces the iteration time.


2017 ◽  
Vol 26 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Loïc Brevault ◽  
Mathieu Balesdent ◽  
Sébastien Defoort

The design of complex systems such as launch vehicles involves different fields of expertise that are interconnected. To perform multidisciplinary studies, concurrent engineering aims at providing a collaborative environment which often relies on data set exchange. In order to efficiently achieve system-level analyses (uncertainty propagation, sensitivity analysis, optimization, etc.), it is necessary to go beyond data set exchange which limits the capabilities of performance assessments. Multidisciplinary design optimization methodologies is a collection of engineering methodologies to optimize systems modelled as a set of coupled disciplinary analyses and is a key enabler to extend concurrent engineering capabilities. This article is focused on several examples of recent developments of multidisciplinary design optimization methodologies (e.g. multidisciplinary design optimization with transversal decomposition of the design process, multidisciplinary design optimization under uncertainty) with applications to launch vehicle design to illustrate the benefices of taking into account the coupling effects between the different physics all along the design process. These methods enable to manage the complexity of the involved physical phenomena and their interactions in order to generate innovative concepts such as reusable launch vehicles beyond existing solutions.


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