1,720,984 research outputs found
Shape optimization of turbine blade firtrees
No full textThe effective application of various optimisation techniques including classic gradient-based and modern evolutionary computation methods in engineering design practice can not only deliver better quality, but also shorten design cycle time. However, the success of using these techniques relies on a number of factors, such as efficient design parameterisation, complete automation, and expertise in deploying various search tools and managing the high computational cost associated with the use of high-fidelity simulation code. A CAD-based shape optimisation method is investigated in this work using knowledge-based ICAD* system with focus on the optimum shape design of turbine blade firtrees. The design of such a structure component involves a large number of constraints derived from industrial experience. The overall aim of this work is to employ some effective and efficient search techniques to explore various new shapes based on an automated design-to-analysis integration, which is achieved by incorporating a knowledge-based intelligent computer-aided design system (ICAD) into the process using sequential rule-based modelling methods. Analysis-related information as well as geometric data is integrated together to produce a general template for the firtree. A high-fidelity finite element analysis code is used as the assessment tool of structural strength, and different types of stress criteria are used in the formation of the optimisation problem. Both the existing shape features inherent to CAD systems and new features offered by the use of free-form shape modelling using Non-Uniform Rational B-Splines (NURBS) are investigated. This leads to a combined feature-based and free-form shape parameterisation method. A two-stage (Genetic Algorithms + Local Search) procedure is used in order to make use of the advantages offered by these two methods while overcoming some of their weaknesses. The problem of high computational cost problem is also tackled by the efficient use of a Gaussian Process based surrogate model coupled with Genetic Algorithms. Both the combined shape parameterisation methods and framework for incorporating surrogates with GA can be applied to general engineering design problems.</p
Parameter screening using impact factors and surrogate-based ANOVA techniques
No full textThis paper introduces the concept of parameter impact factors in order to screen important parameters in high dimensional design optimization problems which make use of computationally expensive high fidelity simulation models. Based on a snapshot dataset obtained by evaluating design points produced by Design of Experiments techniques, a simple concept of parameter impact factors is introduced and calculated to obtain preliminary estimates on the importance of parameters in the simulation results. Combined with parallel tuning of hyperparameters used in Gaussian process surrogate models and ANOVA techniques using the progressively built surrogate models, a more accurate estimation on the impact of different parameters can be achieved. Less important parameters can then be fixed in order to reduce the dimensionality of the problem to make the problem more tractable within given computational budget and time constraints
Surrogate-based aerodynamic shape optimization of a civil aircraft engine nacelle
No full textIn this paper, we present a study on the aerodynamic shape optimization of a three-dimensional subsonic engine
nacelle using computational fluid dynamics simulations. Gaussian process-based surrogate modeling (kriging) and
parameter screening techniques are combined to tackle the high cost associated with both computational fluid
dynamics simulations and the large number of design variables involved, with a multi-objective genetic algorithm
being used to obtain the Pareto fronts. The primary goal of the study was to identify the tradeoff between
aerodynamic performance and noise effects associated with various geometric features within practical
computational costs. The fan face total pressure recovery is used to measure the aerodynamic performance, and the
scarf angle is used as an indicator of the noise impact on the ground. The geometry is modeled using a feature-based
parametric computer-aided design package. An unstructured tetrahedral mesh is generated for the subsequent
solution using the Reynolds averaged Navier–Stokes flow equations. Analyses of variance techniques are used to
identify the dominant geometry parameters, thereby reducing the number of design variables and computational
cost in the trade study. Multiple Pareto fronts are constructed using progressively built kriging models based on
simulation data with the reduced parameter set. A full-scale search was also carried out for comparison with the
results produced using the reduced parameter set. The procedures outlined can be further applied to other
optimization problems with significant numbers of parameters and high-fidelity analysis codes
CFD-based shape optimisation with grid-enabled design search toolkits
No full textThis paper presents an application of applying Grid computing technologies in the field of engineering design optimisation using computational fluid dynamics (CFD). Three essential elements in CFD-based shape optimisation problems (CAD, mesh generation, and solution) are integrated and automated within the Matlab scripting environment augmented with Grid-enabled computation and database toolkits in the form of Matlab functions. The toolkits allow easy access to remote computational resources and data archive capabilities. A design search and optimisation package is exposed to Matlab users in various ways and applied to an engine nacelle shape optimisation problem. A response surface model is constructed and searches conducted on it reveal the effect of negative scarf angle on the aerodynamic performance of the nacelle
A study of shape parameterisation methods for airfoil optimisation
No full textThis paper presents a study on parameterisation methods for airfoil shape optimisation within a CAD-based design optimisation framework. The objective of the paper is to study the effect of different methods on airfoil shape optimisation when using computational fluid
dynamics (CFD). Parameterisation of geometry is one of the essential requirements in shape optimisation, and it presents further challenges when carrying out multidisciplinary design optimisation, as it is critically important to maintain shape consistency between analysis domains, while providing different analysis models from the same CAD definition. It is usually the case that there are numerous possibilities in defining the parametric model, and it will prescribe to a large extent the scope of the search space and landscape of the objective function. This paper adopts design of experiments and optimisation approaches to study several representative parameterisation methods in terms of flexibility and accuracy of the methods for aerodynamic shape optimiation
Turbine blade fir-tree root design optimisation using intelligent CAD and finite element analysis
No full textThis paper is concerned with automation and optimisation of the design of a turbine blade fir-tree root by incorporating a knowledge based intelligent computer-aided design system (ICAD) and finite element analysis. Various optimisation algorithms have been applied in an effort to optimise the shape against a large number of geometric and mechanical constraints drawn from industrial experience in the development of such a structure. Attention is devoted to examining the effects of critical geometric features on the stress distribution at the interface between the blade and disk using a feature-based geometry modelling tool and the optimisation techniques. Various aspects of this problem are presented: (1) geometry representation using ICAD and transfer of the geometry to a finite element analysis code, (2) application of boundary conditions/loads and retrieval of analysis results, (3) exploration of various optimisation methods and strategies including gradient-based and modern stochastic methods. A product model from Rolls-Royce is used as a base design in the optimisation
Numerical optimisation as grid services for engineering design
Full text linkIn this paper we discuss the use of Grid services, an emerging Internet-based technology, to enable the application of numerical optimisation algorithms in heterogeneous, distributed systems for engineering design optimisation tasks. By being presented as Grid services, numerical optimisation algorithms can be consumed with a number of message interactions. The services are built using a combination of standard Web services and newly developed Grid technologies, based on the concept of Reverse Communication. The proposed approach eases the burden of integration by encapsulating optimisation algorithms into generic interfaces, which can be integrated into different client environments.
The design of the optimisation Grid services is explained in detail, and is illustrated with concrete implementations. We also demonstrate the use of the optimisation services with real engineering design optimisation problems performed in scripting problem solving environment
Deployment and exploitation of Grid-enabled data management for engineers
No full textIn this paper we describe the Geodise Database Toolbox, which utilises Web services, XML, databases and Grid technologies to help manage data created by engineering applications running locally or on the Grid. It has been integrated into the Matlab and Jython scripting environments for ease of use, and into other applications via its Java API. The toolbox supports centralised vs. personal data repositories, the former accessed via secure Web services from platform independent client applications. Metadata can be easily defined on files, data structures, collections of related data, and workflows. A distinctive feature is the support for user-defined application specific metadata that can be queried to locate required data efficiently. We describe the toolbox, how it has been deployed and exploited, and indicate that our approach has proved sufficiently generic to be useful in a range of application areas
Two dimensional airfoil optimisation using CFD in a grid computing environment
No full textIn this paper, a two-dimensional airfoil shape optimisation problem is investigated using CFD within a grid computing environment (GCE) implemented in Matlab. The feature-based parametric CAD tool ProEngineer is used for geometry modelling. The industrial level mesh generation tool Gambit and flow solver Fluent are employed as remote services using the Globus Toolkit as the low level API. The objective of the optimisation problem is to minimize the drag-to-lift coefficient ratio for the given operating condition. A Matlab interface to the design exploration system (OPTIONS) is used to obtain solutions for the problem. The adoption of grid technologies not only simplifies the integration of proprietary software, but also makes it possible to harness distributed computational power in a consistent and flexible manner
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