Multilevel Monte-Carlo methods applied to the stochastic analysis of aerodynamic problems

This paper demonstrates the capabilities of the Multi-Level Monte Carlo Methods (MLMC) for the stochastic analysis of CFD aeronautical problems with uncertainties. These capabilities are compared with the classical Monte Carlo Methods in terms of accuracy and computational cost through a set of benchmark test cases. The real possibilities of solving CFD aeronautical analysis with uncertainties by using MLMC methods with a reasonable computational cost are demonstrated.Postprint (published version

A comparison between new adaptive remeshing strategies based on point wise stress error estimation and energy norm error estimation

Traditionally, the most commonly used mesh adaptive strategies for linear elastic problems are based on the use of an energy norm for the measurement of the error, and a mesh refinement strategy based on the equal distribution of the error between all the elements. However, little attention has been paid to the study of alternative error norms and alternative refinement strategies. This paper studies the feasibility of using alternative mesh refinement strategies based on — the use of the classical error energy norm and an optimality criterion based on the equal distribution of the density of error, — the use of alternative error norms based on measurements of the point wise error contained in the main magnitudes that control the equilibrium problem and/or the material constitutive equations such as the stresses (e.g. the Von Mises stress). The feasibility of using all the described strategies is demonstrated through the solution of a benchmark example. This example is also used for comparison between the described refinement criteria

A new adaptive remeshing scheme based on the sensitivity analysis of the SPR point wise error estimation

This paper presents a formulation for the obtainment of the sensitivity analysis of a point wise error estimator with respect to the nodal coordinates using the adjoint state method. The proposed point wise error estimator is based on the SPR method. The numerical accuracy of the presented sensitivity analysis has been tested by perturbing a mesh. The capability of the presented sensitivity analysis for the detection of pollution error has also been tested. A new adaptive remeshing strategy based on the sensitivity analysis of the point wise error estimation has been developed and tested. This strategy produces very cheap meshes for the accurate evaluation of stresses at specific points

Robust Design Optimization applied to aeronautics combining stochastic calculus with evolutionary algoritms

Las incertidumbres son un problema cotidiano en la ingeniería aeroespacial y en sus aplicaciones. Los métodos de optimización robusta utilizan, normalmente, y para asegurar la robustez de las soluciones, la generación aleatoria de los valores con incertidumbres así como criterios de selección multi-punto para la determinación del óptimo. Desde un punto de vista computacional, la aplicación a problemas de fluido-dinámica (CFD) o interacción fluido-estructura (FSI) puede ser extremadamente cara. Este trabajo presenta el acoplamiento entre el cálculo estocástico y los algoritmos evolutivos para la definición de un procedimiento de optimización robusta. Se propone, en primer lugar, una metodología para el cálculo estocástico, que a continuación se aplica a la solución de problemas de optimización. Estos métodos propuestos se han aplicado a dos tipos de problemas; un problema de CFD y otro de FSI orientados a la reducción de la resistencia aerodinámica y del fenómeno de estabilidad estructural conocido por «flutter», respectivamente.Uncertainties are a daily issue to deal with in aerospace engineering and applications. Robust optimization methods commonly use a random generation of the inputs and take advantage of multi-point criteria to look for robust solutions accounting with uncertainty definition. From the computational point of view, the application to coupled problems, like fluid-dynamics (CFD) or fluid-structure interaction (FSI), can be extremely expensive. This work presents a coupling between stochastic analysis techniques and evolutionary optimization algorithms for the definition of a stochastic robust optimization procedure. At first, a stochastic procedure is proposed to be applied into optimization problems. The proposed method has been applied to both CFD and FSI problems for the reduction of drag and flutter, respectively.Peer Reviewe

Global search methods for nonlinear optimisation: a new probabilistic-stochastic approach

In this work the problem of overcoming local minima in the solution of nonlinear optimisation problems is addressed. As a first step, the existing nonlinear local and global optimisation methods are reviewed so as to identify their advantages and disadvantages. Then, the major capabilities of a number of successful methods such as genetic, deterministic global optimisation methods and simmulated annealing, are combined to develop an alternative global optimisation approach based on a Stochastic-Probabilistic heuristic. The capabilities, in terms of robustness and efficiency, of this new approach are validated through the solution of a number of nonlinear optimisation problems. A well know evolutionary technique (Differential Evolution) is also considered for the solution of these case studies offering a better insight of the possibilities of the method proposed here.Postprint (published version

Robust active shock control bump design optimisation using parallel hybrid-MOGA

The paper investigates a robust optimisation for detail design of active shock control bump on a transonic Natural Laminar Flow (NLF) aerofoil using a Multi-Objective Evolutionary Algorithm (MOEA) coupled to Computational Fluid Dynamics (CFD) software. For MOEA, Robust Multi-objective Optimisation Platform (RMOP) developed in CIMNE is used. For the active shock control bump design, two different optimisation methods are considered; the first method is a Pareto- Game based Genetic Algorithm in RMOP (denoted as RMOGA). The second method uses a Hybridised RMOGA with Game-Strategies and a parallel computation for high performance computation. The paper not only shows how a shock control bump approach coupled to CFD improves aerodynamic performance of original transonic aerofoil but also it shows how high performance computation with applying Hybrid- Game and parallel computation increase the efficiency of optimisation in terms of computational cost and result accuracy.Postprint (published version

Multi-input genetic algorithm for experimental optimization of the reattachment downstream of a backward-facing step with surface plasma actuator

The practical interest of flow control approaches is no more debated as flow control provides an effective mean for considerably increasing the performances of ground or air transport systems, among many others applications. Here a fundamental configuration is investigated by using non-thermal surface plasma discharge. A dielectric barrier discharge is installed at the step corner of a backward-facing step (Reh=30000, Re¿=1650). Wall pressure sensors are used to estimate the reattaching location downstream of the step. The primary objective of this paper is the coupling of a numerical optimizer with an experiment. More specifically, optimization by genetic algorithm is implemented experimentally in order to minimize the reattachment point downstream of the step model. Validation through inverse problem is firstly demonstrated. When coupled with the plasma actuator and the wall pressure sensors, the genetic algorithm finds the optimum forcing conditions with a good convergence rate, the best control design variables being in agreement with the literature that uses other types of control devices than plasma. Indeed, the minimum reattaching position is achieved by forcing the flow at the shear layer mode where a large spreading rate is obtained by increasing the periodicity of the vortex street and by enhancing the vortex pairing phenomena. At the best forcing conditions, the mean flow reattachment is reduced by 20%. This article, with its experiment-based approach, demonstrates the robustness of a single-objective multi-design optimization method, and its feasibility for wind tunnel experiments.Postprint (published version

Experimental optimization by genetic algorithm for flow separation control with surface plasma actuator

Postprint (published version

Shape sensitivity analysis for structural problems with non‐linear material behaviour

This paper describes some considerations around the analytical structural shape sensitivity analysis when the structural behaviour is computed using the finite element method with a non‐linear constitutive material model. Depending on the type of non‐linear behaviour two different approaches are proposed. First, a new direct (non‐incremental) formulation is proposed for material models characterized by the fact that the stresses at any time t can be expressed in terms of the strains at the same time t and, in some cases, the strains at a specific past time tu (tu<t). This is the case of elasticity (linear as well as non‐linear), perfect plasticity and damage models. Second, a more classical incremental approach is proposed for general plasticity cases. A special strategy is also proposed for material models with strain softening. The quality and reliability of the proposed approaches are assessed through their application in different examples

Drag reduction via turbulent boundary layer flow control

The final publication is available at Springer via http://dx.doi.org/10.1007/s11431-016-9013-6Turbulent boundary layer control (TBLC) for skin-friction drag reduction is a relatively new technology made possible through the advances in computational-simulation capabilities, which have improved the understanding of the flow structures of turbulence. Advances in micro-electronic technology have enabled the fabrication of active device systems able to manipulating these structures. The combination of simulation, understanding and micro-actuation technologies offers new opportunities to significantly decrease drag, and by doing so, to increase fuel efficiency of future aircraft. The literature review that follows shows that the application of active control turbulent skin-friction drag reduction is considered of prime importance by industry, even though it is still at a low technology readiness level (TRL). This review presents the state of the art of different technologies oriented to the active and passive control for turbulent skin-friction drag reduction and contributes to the improvement of these technologies.Peer ReviewedPostprint (author's final draft