Composite materials with complex internal microstructures, such as the flax nonwoven bio-composite studied in this work, require advanced numerical models in order to predict their mechanical performance. Otherwise, the micro-structural interactions that take place between their components makes very difficult to obtain their mechanical properties and failure mechanisms. This paper presents a novel methodology that couples two homogenization formulations: a phenomenological one, the serial-parallel mixing theory; and a numerical multiscale procedure. The resulting methodology has a minimal computational cost, while it is capable to account for the different interactions that take place among the composite constituents. With the proposed approach, it is possible to characterize the mechanical response of nonwoven composites and to predict their structural failure. The methodology developed is applied to a flax nonwoven bio-composite manufactured and tested by the German Aerospace Center (DLR). The good results obtained from the simulation, when compared with the experimental values, allow considering the proposed procedure an excellent approach for the analysis of large structures made with complex microstructures, such as nonwoven biocomposites.

The use of Active Flow Control (AFC) technologies to modify the forces acting on streamlined bodies is one of the most active research fields in aerodynamics. For each particular application, finding the optimum set of AFC parameters which maximises lift, minimises drag or maximises lift-to-drag ratio (aerodynamic efficiency), has become a necessary design requirement. In the present paper, the AFC technology was applied to the Selig-Donovan 7003 (SD7003) airfoil at Reynolds number 6 x 10(4) . Synthetic jets were employed to modify the lift and drag forces acting on the airfoil. Four angles of attack (AoA) of 4 degrees, 6 degrees, 8 degrees and 14 degrees were considered, alongside five AFC parameters: jet position, jet width, momentum coefficient, forcing frequency and jet inclination angle. A multi objective optimisation based on genetic algorithms (GA) was performed for each angle of attack to find the optimum combination of AFC parameters. Each GA generation was simulated using Computational Fluid Dynamics (CFD). A home-made GA package was linked with a mesh generator and the CFD solver, and the results were automatically fed back to the GA code. Over 2200 CFD simulations were performed in two dimensions, using the Spalart-Allmaras turbulent model. The motivation behind the current study is to understand the dependence of the optimum set of AFC parameters on the AoA. Results show that, as AoA is increased, the potential benefits of AFC become more pronounced, which allows for considerable improvement in aerodynamic efficiency. The physics involved in the interaction between the main flow and synthetic jet are clearly presented and clarifies that the physical phenomenon to obtain maximum efficiency is completely different at pre-stall and post-stall AoA. In particular, the aerodynamic efficiency was increased by 251% from baseline (no actuation) by using a moderate/finite momentum coefficient at AoA=14 degrees, while a mere 39% increase was obtained at AoA=8 degrees. In addition, the interaction between the incoming flow and the synthetic jet pulsating flow at different injection angles has been thoroughly investigated. (C) 2021 Elsevier Inc. All rights reserved.

The potential benefits of active flow control are no more debated. Among many others applications, flow control provides an effective mean for manipulating turbulent separated flows. Here, a nonthermal surface plasma discharge (dielectric barrier discharge) is installed at the step corner of a backward-facing step ( U 0 = 15 m/s, Re h = 30,000, Re θ = 1650). Wall pressure sensors are used to estimate the reattaching location downstream of the step (objective function #1) and also to measure the wall pressure fluctuation coefficients (objective function #2). An autonomous multi-variable optimization by genetic algorithm is implemented in an experiment for optimizing simultaneously the voltage amplitude, the burst frequency and the duty cycle of the high-voltage signal producing the surface plasma discharge. The single-objective optimization problems concern alternatively the minimization of the objective function #1 and the maximization of the objective function #2. The present paper demonstrates that when coupled with the plasma actuator and the wall pressure sensors, the genetic algorithm can find the optimum forcing conditions in only a few generations. At the end of the iterative search process, 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 process. The objective function #2 is maximized for an actuation at half the shear layer mode. In this specific forcing mode, time-resolved PIV shows that the vortex pairing is reduced and that the strong fluctuations of the wall pressure coefficients result from the periodic passages of flow structures whose size corresponds to the height of the step model.

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 (CFDs) software. For MOEA, Robust Multi-Objective Optimisation Platform (RMOP) developed at 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. Numerical results show not only how the concept of Shock Control Bump (SCB) coupled to CFD can improve aerodynamic performance of classic transonic aerofoil at the variability of flight conditions but also how high performance (parallel/distributed) computation with applying Hybrid-Game increases the efficiency of optimisation in terms of computational cost and results accuracy.

This paper presents a research work on stacking sequence design optimisation for multilayered composite plate using a parallel/distributed evolutionary algorithm. The stacking sequence of fibres has a dramatic influence on the strength of multilayered composite plates. Multiple layers of fibre-reinforced material systems offer versatility in engineering material design due to the fact that the stacking sequence of each orthotropic layer can offer full advantage of superior mechanical properties. Numerical results show that the optimal composite structures have lower weight, higher stiffness and also affordable cost when compared to the extreme and intermediate composite structures. In addition, the benefits of using a parallel optimisation system are also presented.

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. (C) 2010 CIMNE (Universitat Politecnica de Catalunya). Published by Elsevier Espana, S.L. All rights reserved.

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 computational fluid dynamics (CFD) or fluid–structure interaction (FSI), can be extremely expensive. This study 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.

This work analyzes the influence of the discretization error associated with the finite element (FE) analyses of each design configuration proposed by the structural shape optimization algorithms over the behavior of the algorithm. The paper clearly shows that if FE analyses are not accurate enough, the final solution provided by the optimization algorithm will neither be optimal nor satisfy the constraints. The need for the use of adaptive FE analysis techniques in shape optimum design will be shown. The paper proposes the combination of two strategies to reduce the computational cost related to the use of mesh adaptivity in evolutionary optimization algorithms: (a) the use of an algorithm for the mesh generation by projection of the discretization error, which reduces the computational cost associated with the adaptive FE analysis of each geometrical configuration and (b) the successive increase of the required accuracy of the FE analyses in order to obtain a considerable reduction of the computational cost in the early stages of the optimization process. Copyright © 2011 John Wiley & Sons, Ltd.

This paper describes a joint research project carried out at the University of Wales Swansea in the ADOPT Research group and at Universitat Politecnica de Catalunya in CINME. The philosophy of the approach followed in this project ard the basic computational tools are introduced including topology optimization using the evolutionary and homogenization methods, post-processing of the topology images by automatic and manual shape fitting techniques and shape optimization using gradient based methods with adaptive finite element (FE) methods. bn example using a two dimensional plane stress finite element model is given to illustrate the fully integrated design optimization process.

In this paper, the aerodynamic shape optimization problems with uncertain operating conditions has been addressed. After a review of robust control theory and the possible approaches to take into account uncertainties, the use of Taguchi robust design methods in order to overcome single point design problems in Aerodynamics is proposed. Under the Taguchi concept, a design with uncertainties is converted into an optimization problem with two objectives which are the mean performance and its variance, so that the solutions are as less sensitive to the uncertainty of the input parameters as possible. Furthermore, the Multi-Criterion Evolutionary Algorithms (MCEAs) are used to capture a set of compromised solutions (Pareto front) between these two objectives. The flow field is analyzed by Navier-Stokes computation using an unstructured mesh. The proposed approach drives to the solution of a multi-objective optimization problem that is solved using a modification of a Non-dominated Sorting Genetic Algorithm (NSGA). In order to reduce the number of expensive evaluations of the fitness function a Response Surface Modeling (RSM) is employed to estimate the fitness value using the polynomial approximation model. During the solution of the optimization problem a Semi-torsional Spring Analogy is used for the adaption of the computational mesh to all the obtained geometrical configurations. The proposed approach is applied to the robust optimization of the 2D high lift devices of a business aircraft by maximizing the mean and minimizing the variance of the lift coefficients with uncertain free-stream angle of attack at landing and takeoff flight conditions, respectively.

This work proposes a new adaptive remeshing strategy based on the sensitivity of the point wise error in stresses with respect to the nodal coordinates, which is computed using the adjoint-state method. This sensitivity provides information about the influence of the discretization of each zone of the computational domain in the estimation of the error in stresses at a specific point. This information is also used for the development of an adaptive remeshing strategy that provides a strict and economical control of this error.

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. (c) 2005 Elsevier B.V. All rights reserved.

After two years of basic research on fractal electrodynamics, the FractalComs consortium presents the conclusions of the FractalComs Project (http://www.tsc.upc.es/fractalcoms/). They state the performance limits (fundamental and technological) of pre-fractal shaped miniature devices compared with conventional ones. Many miniature antennas and devices have been designed, analyzed and/or measured, the most outstanding being the two-arm square spiral antennas and the Hilbert superconductor resonators for miniature filters.

One of the major difficulties in meshing 3D complex geometries is to deal with non-proper geometrical definitions coming from CAD systems. Typically, CAD systems do not take care of the proper definition of the geometries for the analysis purposes. In addition, the use of standard CAD files (IGES, VDA, ...) for the transfer of geometries between different systems introduce some additional difficulties.In this work, a collection of algorithms to repair and/or to improve the geometry definitions are provided. The aim of these algorithms is to make as easy as possible the generation of a mesh over complex geometries given some minimum requirements of quality and correctness. The geometrical model will be considered as composed of a set of NURBS lines and trimmed surfaces.Some examples of application of the algorithms and of the meshes generated from the corrected geometry are also presented in this work. (C) 2002 Elsevier Science Ltd. All rights reserved.

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. Copyright (C) 2002 John Wiley Sons, Ltd.

The Finite Element Method (FEM) has become the most popular numerical method for solving a wide variety of complex engineering problems. However, from the programming point of view, when a FEM program has a lot of computational capabilities it is very difficult to maintain and enlarge the program codes. Recently the object-oriented programming paradigm has become a powerful method for overcoming such difficulties. This paper contains the description of an open environment for the FEM, written in C++, with explanations about how the sensitivity analysis and the non-linear material behaviour (damage models) have been taken into account.