Free Form Deformation Techniques Applied to 3D Shape Optimization Problems

The purpose of this work is to analyse and study an efficient parametrization technique for a 3D shape optimization problem. After a brief review of the techniques and approaches already available in literature, we recall the Free Form Deformation parametrization, a technique which proved to be efficient and at the same time versatile, allowing to manage complex shapes even with few parameters. We tested and studied the FFD technique by establishing a path, from the geometry definition, to the method implementation, and finally to the simulation and to the optimization of the shape. In particular, we have studied a bulb and a rudder of a race sailing boat as model applications, where we have tested a complete procedure from Computer-Aided-Design to build the geometrical model to discretization and mesh generation

Multiresolution analysis as an approach for tool path planning in NC machining

Wavelets permit multiresolution analysis of curves and surfaces. A complex curve can be decomposed using wavelet theory into lower resolution curves. The low-resolution (coarse) curves are similar to rough-cuts and high-resolution (fine) curves to finish-cuts in numerical controlled (NC) machining.;In this project, we investigate the applicability of multiresolution analysis using B-spline wavelets to NC machining of contoured 2D objects. High-resolution curves are used close to the object boundary similar to conventional offsetting, while lower resolution curves, straight lines and circular arcs are used farther away from the object boundary.;Experimental results indicate that wavelet-based multiresolution tool path planning improves machining efficiency. Tool path length is reduced, sharp corners are smoothed out thereby reducing uncut areas and larger tools can be selected for rough-cuts

Free Form Deformation Techniques for 3D Shape Optimization Problems

The purpose of this work is to analyse and study an efficient parametrization technique for a 3D shape optimization problem. After a brief review of the techniques and approaches already available in literature, we choose to use the Free Form Deformation parametrization, a recent technique which proved to be efficient and at the same time versatile, allowing to manage complex shapes even with few parameters. We tested and studied the technique by developing a link among different specialized softwares, in order to establish a path, from the geometry definition, to the method implementation, and finally to the simulation and to the optimization of the problem. In particular, we have studied a bulb and a rudder of a race sailing boat as model problems

Free form deformation techniques applied to 3D shape optimization problems

The purpose of this work is to analyse and study an efficient parametrization technique for a 3D shape optimization problem. After a brief review of the techniques and approaches already available in literature, we recall the Free Form Deformation parametrization, a technique which proved to be efficient and at the same time versatile, allowing to manage complex shapes even with few parameters. We tested and studied the FFD technique by establishing a path, from the geometry definition, to the method implementation, and finally to the simulation and to the optimization of the shape. In particular, we have studied a bulb and a rudder of a race sailing boat as model applications, where we have tested a complete procedure from Computer-Aided-Design to build the geometrical model to discretization and mesh generation

Tools for Analysing Military Tactics based on Bézier Surface Pattern Recognition

There are many factors which affect a military unit’s success in a battle exercise. Some of these factors could be regarded as tactical and others as human factors. Some of them can be measured with numerical values while others are difficult to quantify. Nevertheless, they all affect the success of the battle exercise. This paper describes how to develop and utilize a method based on Bézier surface pattern recognition, which could be used for the overall military tactical analysis of a company’s attack. This paper also explains how this method could be applied to an integrated analysis of the most important tactical factors affecting the success and task fulfilment of an attack together with the leader’s decision–making and his or her tactical solutions

Aerodynamic and cost modelling for aircraft in a multi-disciplinary design context.

A challenge for the scientific community is to adapt to and exploit the trend towards greater multidisciplinary focus in research and technology. This work is concerned with multi-disciplinary design for whole aircraft configuration, including aero performance and financial considerations jointly for an aircraft program. A Multi-Disciplinary (MD) approach is required to increase the robustness of the preliminary design data and to realise the overall aircraft performance objectives within the required timescales. A pre-requisite for such an approach is the existence of efficient and fully integrated processes. For this purpose an automatic aero high-speed analysis framework has been developed and integrated using a commercial integration/building environment. Starting from the geometry input, it automatically generates aero data for loads in a timescale consistent with level requirement, which can afterwards be integrated into the overall multi-disciplinary process. A 3D Aero-solution chain has been implemented as a high-speed aerodynamic evaluation capability, and although there is not yet a complementary fully automated Aerodynamic design process, two integrated systems to perform multi-objective optimisation have been developed using different optimisation approaches. In addition to achieving good aircraft performance, reducing cost may be essential for manufacturer survival in today's competitive market. There is thus a strong need to understand the cost associated with different competing concepts and this could be addressed by incorporating cost estimation in the design process along with other analyses to achieve economic and efficient aircraft. For this reason a pre-existing cost model has been examined, tested, improved, and new features added. Afterwards, the cost suite has been integrated using an integration framework and automatically linked with external domains, providing a capability to take input from other domain tool sets. In this way the cost model could be implemented in a multi-disciplinary process allowing a trade-off between weight, aero performance and cost. Additionally, studies have been performed that link aerodynamic characteristics with cost figures and reinforce the importance of considering aerodynamic, structural and cost disciplines simultaneously. The proposed work therefore offers a strong basis for further development. The modularity of the aero optimisation framework already allows the application of such techniques to real engineering test cases, and, in future, could be combined with the 3D aero solution chain developed. In order to further reduce design wall-clock time the present multi- level parallelisation could also be deployed within a more rapid multi-fidelity approach. Finally the 3D aero-solution chain could be improved by directly incorporating a module to generate aero data for performance, and linking this to the cost suite informed by the same geometrical variables.Engineering and Physical Sciences (EPSRC)PhD in Aerospac

FITTING A PARAMETRIC MODEL TO A CLOUD OF POINTS VIA OPTIMIZATION METHODS

Computer Aided Design (CAD) is a powerful tool for designing parametric geometry. However, many CAD models of current configurations are constructed in previous generations of CAD systems, which represent the configuration simply as a collection of surfaces instead of as a parametrized solid model. But since many modern analysis techniques take advantage of a parametrization, one often has to re-engineer the configuration into a parametric model. The objective here is to generate an efficient, robust, and accurate method for fitting parametric models to a cloud of points. The process uses a gradient-based optimization technique, which is applied to the whole cloud, without the need to segment or classify the points in the cloud a priori. First, for the points associated with any component, a variant of the Levenberg-Marquardt gradient-based optimization method (ILM) is used to find the set of model parameters that minimizes the least-square errors between the model and the points. The efficiency of the ILM algorithm is greatly improved through the use of analytic geometric sensitivities and sparse matrix techniques. Second, for cases in which one does not know a priori the correspondences between points in the cloud and the geometry model\u27s components, an efficient initialization and classification algorithm is introduced. While this technique works well once the configuration is close enough, it occasionally fails when the initial parametrized configuration is too far from the cloud of points. To circumvent this problem, the objective function is modified, which has yielded good results for all cases tested. This technique is applied to a series of increasingly complex configurations. The final configuration represents a full transport aircraft configuration, with a wing, fuselage, empennage, and engines. Although only applied to aerospace applications, the technique is general enough to be applicable in any domain for which basic parametrized models are available

Feasible Form Parameter Design of Complex Ship Hull Form Geometry

This thesis introduces a new methodology for robust form parameter design of complex hull form geometry via constraint programming, automatic differentiation, interval arithmetic, and truncated hierarchical B- splines. To date, there has been no clearly stated methodology for assuring consistency of general (equality and inequality) constraints across an entire geometric form parameter ship hull design space. In contrast, the method to be given here can be used to produce guaranteed narrowing of the design space, such that infeasible portions are eliminated. Furthermore, we can guarantee that any set of form parameters generated by our method will be self consistent. It is for this reason that we use the title feasible form parameter design. In form parameter design, a design space is represented by a tuple of design parameters which are extended in each design space dimension. In this representation, a single feasible design is a consistent set of real valued parameters, one for every component of the design space tuple. Using the methodology to be given here, we pick out designs which consist of consistent parameters, narrowed to any desired precision up to that of the machine, even for equality constraints. Furthermore, the method is developed to enable the generation of complex hull forms using an extension of the basic rules idea to allow for automated generation of rules networks, plus the use of the truncated hierarchical B-splines, a wavelet-adaptive extension of standard B-splines and hierarchical B-splines. The adaptive resolution methods are employed in order to allow an automated program the freedom to generate complex B-spline representations of the geometry in a robust manner across multiple levels of detail. Thus two complementary objectives are pursued: ensuring feasible starting sets of form parameters, and enabling the generation of complex hull form geometry

Optimisation de forme d’un avion pour sa performance sur une mission

Les avions rencontrent de nombreuses conditions d’opérations au cours de leurs vols, comme le nombre de Mach, l’altitude et l’angle d’attaque. Leur prise en compte durant la conception améliore la robustesse du système et finalement la consommation des flottes d’avions. L’optimisation de formes aérodynamiques contribue à la conception des avions, et repose sur l’automatisation de la génération de géométries ainsi que la simulation numérique de la physique du vol. La minimisation de la trainée des formes aérodynamiques doit prendre en compte de multiples conditions d’opération, étant donne que l’optimisation a une unique condition de vol mène a des formes dont la performance se dégrade fortement quand cette condition de vol est perturbée. De plus, la flexibilité structurelle déforme les ailes différemment selon la condition de vol, et doit donc être simulée lors de telles optimisations. Dans cette thèse, la minimisation de la consommation de carburant au cours d’une mission est formulée en problème d’optimisation. Une attention particulière est apportée au choix des conditions d’opérations à inclure dans le problème d’optimisation, étant donne que celles-ci ont un impact majeur sur la qualité des résultats obtenus, et que le cout de calcul est proportionnel à leur nombre. Un nouveau cadre théorique est proposé pour adresser cette question, offrant un point de vue original et surmontant des difficultés révélées par les méthodes a l’état-de-l’ art en matière de mise en place de problèmes d’optimisation multipoints. Un algorithme appelé Gradient Span Analysis (GSA), est proposé pour automatiser le choix des conditions d’opération. Il est base sur la réduction de dimension de l’espace vectoriel engendre par les gradients adjoints aux différentes conditions de vol. Des contributions de programmation a la chaine d’optimisation ont permis d’évaluer les méthodes aux optimisations du profil académique RAE2822 et de la configuration voilure-fuselage XRF-1, représentative des avions de transport modernes. Alors que les formes résultant d’optimisation mono-point présentent de fortes dégradations de performance hors du point de conception, les optimisations multipoints adéquatement formulées fournissent de bien meilleurs compromis. Il est finalement montre que les interactions fluide-structure ajoutent de nouveaux degrés de liberté, et ont un impact sur les optimisations en de multiples conditions de vol, ouvrant des perspectives en matière d’adaptation passive de forme. ABSTRACT : An aircraft encounters a wide range of operating conditions during its missions, i.e. flight altitude, Mach number and angle of attack, which consideration at the design phase enhances the system robustness and consequently the overall fleet consumption. Numerical optimization of aerodynamic shapes contributes to aircraft design, and relies on the automation of geometry generation and numerical simulations of the flight physics. Minimization of aerodynamic shapes drag must take into account multiple operating conditions, since optimization at a single operating condition leads to a strong degradation of performance when this operating condition varies. Besides, structural flexibility deforms the wings differently depending on the operating conditions, so has to be simulated during such optimizations. In the present thesis, the mission fuel consumption minimization is formulated as an optimization problem. The focus is made on the choice of operating conditions to be included in the optimization problem, since they have a major impact on the quality of the results, and the computational cost is proportional to their number. A new theoretical framework is proposed, overcoming and giving new insights on problematic situations revealed by state-of-the-art methods for multipoint optimization problem setup. An algorithm called Gradient Span Analysis is proposed to automate the choice of operating conditions. It is based on a reduction of dimension of the vector space spanned by adjoint gradients obtained at the different operating conditions. Programming contributions to the optimization chain enabled the evaluation of the new method on the optimizations of the academic RAE2822 airfoil, and the XRF-1 wing-body configuration, representative of a modern transport aircraft. While the shapes resulting of single-point optimizations present strong degradations of the performance in off-design conditions, adequately formulated multi-Machmulti- lift optimizations present much more interesting performance compromises. It is finally shown that fluid-structure interaction adds new degrees of freedom, and has consequences on multiple flight conditions optimizations, opening the perspective of passive shape adaptation