New strategies for the aerodynamic design optimization of aeronautical configurations through soft-computing techniques

Premio Extraordinario de Doctorado de la UAH en 2013Lozano Rodríguez, Carlos, codir.This thesis deals with the improvement of the optimization process in the aerodynamic design of aeronautical configurations. Nowadays, this topic is of great importance in order to allow the European aeronautical industry to reduce their development and operational costs, decrease the time-to-market for new aircraft, improve the quality of their products and therefore maintain their competitiveness. Within this thesis, a study of the state-of-the-art of the aerodynamic optimization tools has been performed, and several contributions have been proposed at different levels: -One of the main drawbacks for an industrial application of aerodynamic optimization tools is the huge requirement of computational resources, in particular, for complex optimization problems, current methodological approaches would need more than a year to obtain an optimized aircraft. For this reason, one proposed contribution of this work is focused on reducing the computational cost by the use of different techniques as surrogate modelling, control theory, as well as other more software-related techniques as code optimization and proper domain parallelization, all with the goal of decreasing the cost of the aerodynamic design process. -Other contribution is related to the consideration of the design process as a global optimization problem, and, more specifically, the use of evolutionary algorithms (EAs) to perform a preliminary broad exploration of the design space, due to their ability to obtain global optima. Regarding this, EAs have been hybridized with metamodels (or surrogate models), in order to substitute expensive CFD simulations. In this thesis, an innovative approach for the global aerodynamic optimization of aeronautical configurations is proposed, consisting of an Evolutionary Programming algorithm hybridized with a Support Vector regression algorithm (SVMr) as a metamodel. Specific issues as precision, dataset training size, geometry parameterization sensitivity and techniques for design of experiments are discussed and the potential of the proposed approach to achieve innovative shapes that would not be achieved with traditional methods is assessed. -Then, after a broad exploration of the design space, the optimization process is continued with local gradient-based optimization techniques for a finer improvement of the geometry. Here, an automated optimization framework is presented to address aerodynamic shape design problems. Key aspects of this framework include the use of the adjoint methodology to make the computational requirements independent of the number of design variables, and Computer Aided Design (CAD)-based shape parameterization, which uses the flexibility of Non-Uniform Rational B-Splines (NURBS) to handle complex configurations. The mentioned approach is applied to the optimization of several test cases and the improvements of the proposed strategy and its ability to achieve efficient shapes will complete this study

New strategies for the aerodynamic design optimization of aeronautical configurations through soft-computing techniques

Premio Extraordinario de Doctorado de la UAH en 2013Lozano Rodríguez, Carlos, codir.This thesis deals with the improvement of the optimization process in the aerodynamic design of aeronautical configurations. Nowadays, this topic is of great importance in order to allow the European aeronautical industry to reduce their development and operational costs, decrease the time-to-market for new aircraft, improve the quality of their products and therefore maintain their competitiveness. Within this thesis, a study of the state-of-the-art of the aerodynamic optimization tools has been performed, and several contributions have been proposed at different levels: -One of the main drawbacks for an industrial application of aerodynamic optimization tools is the huge requirement of computational resources, in particular, for complex optimization problems, current methodological approaches would need more than a year to obtain an optimized aircraft. For this reason, one proposed contribution of this work is focused on reducing the computational cost by the use of different techniques as surrogate modelling, control theory, as well as other more software-related techniques as code optimization and proper domain parallelization, all with the goal of decreasing the cost of the aerodynamic design process. -Other contribution is related to the consideration of the design process as a global optimization problem, and, more specifically, the use of evolutionary algorithms (EAs) to perform a preliminary broad exploration of the design space, due to their ability to obtain global optima. Regarding this, EAs have been hybridized with metamodels (or surrogate models), in order to substitute expensive CFD simulations. In this thesis, an innovative approach for the global aerodynamic optimization of aeronautical configurations is proposed, consisting of an Evolutionary Programming algorithm hybridized with a Support Vector regression algorithm (SVMr) as a metamodel. Specific issues as precision, dataset training size, geometry parameterization sensitivity and techniques for design of experiments are discussed and the potential of the proposed approach to achieve innovative shapes that would not be achieved with traditional methods is assessed. -Then, after a broad exploration of the design space, the optimization process is continued with local gradient-based optimization techniques for a finer improvement of the geometry. Here, an automated optimization framework is presented to address aerodynamic shape design problems. Key aspects of this framework include the use of the adjoint methodology to make the computational requirements independent of the number of design variables, and Computer Aided Design (CAD)-based shape parameterization, which uses the flexibility of Non-Uniform Rational B-Splines (NURBS) to handle complex configurations. The mentioned approach is applied to the optimization of several test cases and the improvements of the proposed strategy and its ability to achieve efficient shapes will complete this study

Aerodynamic improvement methods for a medium-altitude long-endurance UAV wing

Aerodynamic studies are critical in the development of aircraft and aircraft technology. To this end, a study of three means for improving the aerodynamic performance using range and endurance metrics is presented in this thesis to guide future design iterations of a mediumaltitude long-endurance tactical unmanned aerial vehicle, the Hydra Technologies S45 Bàalam. The results presented are obtained using computational fluid dynamics simulations and are therefore of high fidelity. Surrogate-based modeling using Gaussian processes is used to reduce the number of computationally-intensive simulations required in the optimizations performed. A Bayesian efficient global optimization algorithm using expected improvement is used in the two optimization series. The first set of results establishes the baseline performance of the wing and assesses the impact of an optionally-installed upswept blended winglet on the development of forces on the wing. Results show that the winglet consistently improves the wing aerodynamics. The spanwise distribution of forces shows that the presence of the winglet introduces a component of force in the direction of thrust owing to the curved shape and flow field, thus reducing drag at the wing tip. The second set of results presents an optimization study on global wing parameters. Three planform parameters, the aspect ratio, taper ratio, and sweep angle, as well as the out-of-plane geometric twist angle, are the design variables. Results show that possible improvements are modest at best unless the aspect ratio is increased because there are no significant design levers to increase the lift without causing a greater increase in the drag. Wing twist is identified to be a parameter useful in manipulating the angle of attack at which the maximum lift-to-drag ratio occurs. The third set of results focuses on the aerodynamic enhancements achievable through active morphing of the flexible upper surface of the wing in flight using actuated rods. Three amplitudes of displacement of the deformable surface are used to represent the morphing process simulated at a range of angles of attack and flow speeds over the full flight envelope of the vehicle. Up to 4 % improvement is obtained on the range and endurance metrics. Improvements are not obtained at all flight conditions tested. It is observed that the morphing process gains influence as the Reynolds number becomes higher because of the associated increase in turbulent flow on the wing which can be delayed to obtain improved aerodynamic coefficients

MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability

When learning simulations for modeling physical phenomena in industrial designs, geometrical variabilities are of prime interest. While classical regression techniques prove effective for parameterized geometries, practical scenarios often involve the absence of shape parametrization during the inference stage, leaving us with only mesh discretizations as available data. Learning simulations from such mesh-based representations poses significant challenges, with recent advances relying heavily on deep graph neural networks to overcome the limitations of conventional machine learning approaches. Despite their promising results, graph neural networks exhibit certain drawbacks, including their dependency on extensive datasets and limitations in providing built-in predictive uncertainties or handling large meshes. In this work, we propose a machine learning method that do not rely on graph neural networks. Complex geometrical shapes and variations with fixed topology are dealt with using well-known mesh morphing onto a common support, combined with classical dimensionality reduction techniques and Gaussian processes. The proposed methodology can easily deal with large meshes without the need for explicit shape parameterization and provides crucial predictive uncertainties, which are essential for informed decision-making. In the considered numerical experiments, the proposed method is competitive with respect to existing graph neural networks, regarding training efficiency and accuracy of the predictions

Development of a decision support system for the design and adjustment of sailboat rigging

The two main objective of this work are: - To develop a simulation program of the behaviour of upwind sails and rigging, to help the crew to optimize the performance of the sailing yacht in real time. For this purpose, it will be necessary to formulate a fluid-structure interaction algorithm to compute the performance of a particular sail/rigging configuration. Since the crew dynamically trims the rigging and sails, in order to evaluate the performance of the actual configuration, a tool to monitor the rigging and sails will be necessary, too. - To adjust a monitoring element to quantify in physic values the manoeuvre of the crew. This will be our monitoring tool. - To reproduce the crew manoeuvre in the simulation program with the data obtained with the monitoring tool. Once the sail/rigging configuration has been adapted ‘in real time’ to the actual one, the performance of this new configuration can be computed. For this purpose the simulation program and the monitoring tool must communicate among them

Advances in Modeling of Fluid Dynamics

This book contains twelve chapters detailing significant advances and applications in fluid dynamics modeling with focus on biomedical, bioengineering, chemical, civil and environmental engineering, aeronautics, astronautics, and automotive. We hope this book can be a useful resource to scientists and engineers who are interested in fundamentals and applications of fluid dynamics

Hypersonic Aeroelastic Stability Boundary Computations Using Radial Basis Functions for Mesh Deformation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97135/1/AIAA2012-5943.pd

Fluid-Structure-Jet Interaction Effects on High-Speed Vehicles

This dissertation is focused on two design considerations for supersonic intercept missiles: (i) increased structural slenderness and (ii) attitude control jets. The resulting new designs have the potential to increase vehicle performance, but will lead to a coupled fluid-structure-jet interaction that has yet to be studied. Numerical results of the vehicle response across the design space and flight envelope can be used as guidelines for assessment of improved control effectiveness, maneuverability and agility. First, vehicle models are developed that include slender structures and attitude control jets to conduct flight simulations. The numerical analysis of fluid-structure-jet interaction using these vehicle models deleted{helps to fill the gap in the literature and} provides insight into how this interaction can be leveraged during the design to improve performance. Next, approximate methods for including jet interaction effects are developed for slender high-speed vehicles. These methods allow for more complex geometry, a range of flight conditions, and varying control inputs. The jet interaction models are developed for flight simulation to maintain accuracy without significant computational cost. A detailed computational model of the maneuverable vehicle with fluid-structure-jet interaction is created to study the sensitivity to changes in flight conditions. These steady and dynamic results of the nonlinear system identify the conditions that may be difficult to model as well as those that can be exploited for improved performance. Next, modeling methods for the fluid-structure-jet interaction dynamics in flight are developed and evaluated using aggressive maneuvers throughout the flight envelope. Previous methods are evaluated to identify their effectiveness and a new method is developed specifically to model the nonlinear vehicle response to aggressive maneuvers. Finally, fluid-structure-jet interaction effects introduced by a slender missile body and attitude control jets are modeled during flight simulations. Multiple vehicle configurations are considered and the simulation results demonstrate the corresponding design modifications can impact vehicle maneuverability and agility. Overall, this dissertation explores a new topic in fluid-structure-jet interaction that arises due to new design trends that seek to improve intercept missile performance. New modeling methods were developed to analyze the problem and numerical simulation results identify regions where the fluid-structure-jet interaction significantly affects the vehicle response.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147571/1/kitson_1.pd