Survey on the status of Computational Design research and practice

This report presents the results from a survey of current practice in the use of design optimization conducted amongst UK companies. The survey was completed by the Design Optimization Group in the Department of Engineering at Cambridge University. The general aims of this research were to understand the current status of design optimization research and practice and to identify ways in which the use of design optimization methods and tools could be improved.

Multi-objective design and optimisation of bypass outlet-guide vanes

This paper describes the development of an automated design optimization system that makes use of a high fidelity Reynolds-Averaged CFD analysis procedure to minimize the fan forcing and fan BOGV (bypass outlet guide vane) losses simultaneously taking into the account the down-stream pylon and RDF (radial drive fairing) distortions. The design space consists of the OGV's stagger angle, trailing-edge recambering, axial and circumferential positions leading to a variable pitch optimum design. An advanced optimization system called SOFT (Smart Optimisation for Turbomachinery) was used to integrate a number of pre-processor, simulation and in-house grid generation codes and postprocessor programs. A number of multi-objective, multi-point optimiztion were carried out by SOFT on a cluster of workstations and are reported herein.

Towards topology-free optimization - An application to turbine internal cooling geometries

The application of automated design optimization to real-world, complex geometry problems is a significant challenge - especially if the topology is not known a priori like in turbine internal cooling. The long term goal of our work is to focus on an end-to-end integration of the whole CFD Process, from solid model through meshing, solving and post-processing to enable this type of design optimization to become viable & practical. In recent papers we have reported the integration of a Level Set based geometry kernel with an octree-based cut- Cartesian mesh generator, RANS flow solver, post-processing & geometry editing all within a single piece of software - and all implemented in parallel with commodity PC clusters as the target. The cut-cells which characterize the approach are eliminated by exporting a body-conformal mesh guided by the underpinning Level Set. This paper extends this work still further with a simple scoping study showing how the basic functionality can be scripted & automated and then used as the basis for automated optimization of a generic gas turbine cooling geometry. Copyright © 2008 by W.N.Dawes.

Structural optimization of lattice materials

Lattice materials are characterized at the microscopic level by a regular pattern of voids confined by walls. Recent rapid prototyping techniques allow their manufacturing from a wide range of solid materials, ensuring high degrees of accuracy and limited costs. The microstructure of lattice material permits to obtain macroscopic properties and structural performance, such as very high stiffness to weight ratios, highly anisotropy, high specific energy dissipation capability and an extended elastic range, which cannot be attained by uniform materials. Among several applications, lattice materials are of special interest for the design of morphing structures, energy absorbing components and hard tissue scaffold for biomedical prostheses. Their macroscopic mechanical properties can be finely tuned by properly selecting the lattice topology and the material of the walls. Nevertheless, since the number of the design parameters involved is very high, and their correlation to the final macroscopic properties of the material is quite complex, reliable and robust multiscale mechanics analysis and design optimization tools are a necessary aid for their practical application. In this paper, the optimization of lattice materials parameters is illustrated with reference to the design of a bracket subjected to a point load. Given the geometric shape and the boundary conditions of the component, the parameters of four selected topologies have been optimized to concurrently maximize the component stiffness and minimize its mass. Copyright © 2011 by ASME.

Neutronic optimization in high conversion Th-233U fuel assembly with simulated annealing

This paper reports on fuel design optimization of a PWR operating in a self sustainable Th-233U fuel cycle. Monte Carlo simulated annealing method was used in order to identify the fuel assembly configuration with the most attractive breeding performance. In previous studies, it was shown that breeding may be achieved by employing heterogeneous Seed-Blanket fuel geometry. The arrangement of seed and blanket pins within the assemblies may be determined by varying the designed parameters based on basic reactor physics phenomena which affect breeding. However, the amount of free parameters may still prove to be prohibitively large in order to systematically explore the design space for optimal solution. Therefore, the Monte Carlo annealing algorithm for neutronic optimization is applied in order to identify the most favorable design. The objective of simulated annealing optimization is to find a set of design parameters, which maximizes some given performance function (such as relative period of net breeding) under specified constraints (such as fuel cycle length). The first objective of the study was to demonstrate that the simulated annealing optimization algorithm will lead to the same fuel pins arrangement as was obtained in the previous studies which used only basic physics phenomena as guidance for optimization. In the second part of this work, the simulated annealing method was used to optimize fuel pins arrangement in much larger fuel assembly, where the basic physics intuition does not yield clearly optimal configuration. The simulated annealing method was found to be very efficient in selecting the optimal design in both cases. In the future, this method will be used for optimization of fuel assembly design with larger number of free parameters in order to determine the most favorable trade-off between the breeding performance and core average power density.

Differential geometry and design coupling in MDO

The notion of coupling within a design, particularly within the context of Multidisciplinary Design Optimization (MDO), is much used but ill-defined. There are many different ways of measuring design coupling, but these measures vary in both their conceptions of what design coupling is and how such coupling may be calculated. Within the differential geometry framework which we have previously developed for MDO systems, we put forth our own design coupling metric for consideration. Our metric is not commensurate with similar types of coupling metrics, but we show that it both provides a helpful geo- metric interpretation of coupling (and uncoupledness in particular) and exhibits greater generality and potential for analysis than those similar metrics. Furthermore, we discuss how the metric might be profitably extended to time-varying problems and show how the metric's measure of coupling can be applied to multi-objective optimization problems (in unconstrained optimization and in MDO). © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Optimization algorithms and ODE's in MDO

There is a need for a stronger theoretical understanding of Multidisciplinary Design Optimization (MDO) within the field. Having developed a differential geometry framework in response to this need, we consider how standard optimization algorithms can be modeled using systems of ordinary differential equations (ODEs) while also reviewing optimization algorithms which have been derived from ODE solution methods. We then use some of the framework's tools to show how our resultant systems of ODEs can be analyzed and their behaviour quantitatively evaluated. In doing so, we demonstrate the power and scope of our differential geometry framework, we provide new tools for analyzing MDO systems and their behaviour, and we suggest hitherto neglected optimization methods which may prove particularly useful within the MDO context. Copyright © 2013 by ASME.

Modelling and optimization of a pneumatic microfeeder system

This paper presents modelling and design optimization of a microfeeder which, as part of a microassembly system, is used for contactless object delivery. The microfeeder consists of an array of microactuators which are controlled by electrostatic actuation and used for maneuvering outcoming air jet for object hovering and delibery. The airflow behaviour in the microactuator is analysed by means of fluid mechanics and Computational Fluid Dynamics (CFD) simulation from three aspects, theoretical analysis, initial design assessment, and design modifications. The focus is put on the basic types of the microfeeder structure and the effects of structural details to the systematic performance. The structural pattern of the microactuator for forming airflow nozzle is identified and two design plans are proposed as basic structure patterns of pneumatic microactuators. The optimized design numerically shows the ability of delivering objects. This paper analyses the flow distribution pattern in microactuators and points out a way for effective design of pneumatic microfeeder systems. The optimization strategy provided by the present paper has close relevance to the design and manufacture of pneumatic microfeeder systems.

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.

Design of a deployment rotation mechanism for microsatellite

Solar array rotation mechanism provides a hinged joint between the solar panel and satellite body, smooth rota-tion of the solar array into deployed position and its fixation in this position. After unlocking of solar panel (while in orbit), rotation bracket turns towards ready-to-work position under the action of driving spring. During deployment, once reached the required operating angle (defined by power subsystem engineer), the rotation bracket collides with the fixed bracket that is mounted on body of the satellite, to stop rotation. Due to the effect of collision force that may alter the rotation mechanism function, design of centrifugal brake is essential. At stoppage moment micro-switches activate final position sensor and a stopper locks the rotation bracket. Design of spring and centrifugal brake components, static finite element stress analysis of primary structure body of rotation mechanism at stoppage moment have been obtained. Last, reliability analysis of rotation mechanism is evaluated. The benefit of this study is to aid in the design of rotation mechanism that can be used in micro-satellite applications.