Harness 3D routing is one of the most challenging steps in the design of aircraft Electrical Wiring Interconnection System (EWIS). This is due not only to the intrinsic complexity of the EWIS, but also to the increasing number of applying design constraints and its dependency on any change in the design of the airframe and installed systems. The current routing process employed by EWISdesign is largely based on the manual work of expert engineers, partially supported by conventional CAD systems. As a result, the routing process is quite inefficient, error prone and unable to deliver optimal solutions. Although many harness components are selected from catalogues and the design process is largely repetitive and rule based, it has been found that none or very limited automation solutions, which can significantly decrease the workload of engineers and increase their efficiency, are currently available. In this paper, an innovative approach is proposed to solve the 3D routing automation as an optimization problem. Knowledge Based Engineering (KBE) and optimization methods are proposed to achieve minimum cost routing solutions that satisfy all relevant design rules and constraints. The proposed solution is scalable in terms of constraints, can be deployed on any type of routing environment, and, thanks to the achieved level of automation, able to reduce the process lead time drastically. The basic idea is to achieve optimal EWIS routing solutions by optimizing the position of the harnesses clamping points, which are used as way-points to route the harnesses inside the aircraft digital mock-up. The challenge to solve this optimization problem is that the number and initial value of design variables, namely the number and position of clamping points, are not known a priori. To handle this challenge, a two-step, hybrid optimization strategy has been devised. The first step, called Initialization, uses a road map based path finding method to generate a preliminary harness definition, including the required number and preliminary position of its clamping points. The second step, called Refinement, uses a conventional optimization method to move the position of the clamps and refine the preliminary harness definition aiming for the minimum cost and the satisfaction of all the design constraints. This approach has been implemented into a KBE application connected with a commercial optimization package and tested on several routing cases. The results demonstrate that the proposed method is capable of handling cases of representative geometric complexity and design constraints and delivering proper 3D harness models in full automation.

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Variable stiffness composites, where fibre angles are spatially varied by steering the tows in curvilinear paths to optimise the structural response, have been a subject of intensive study. In this paper, experimental validation of the variable stiffness composite technology is carried out for a panel representing a wing lower-skin with a large access hole designed against material failure. An idealised flat panel with a large cut-out under tension or combined tension and shear is modeled using finite elements. In addition to a quasi-isotropic laminate, constant stiffness and variable stiffness laminates are designed to maximise the failure load using a multi-step optimisation framework. Three panels, one for each type of laminate, are built from thermoset prepreg material using automated fibre placement. All three panels are tested in pure tension. The failure loads, failure modes and weights of the tested panels are compared. The results indicate that the variable stiffness laminate is capable of sustaining significantly larger loads, before failure, than the constant stiffness and quasi-isotropic laminates of equal weight.

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This paper discusses the development of a multidisciplinary design optimization tool intended for electronically power aircraft. The test subject of the optimizations is a hybrid blended wing body, delta wing UAV. First, the optimization problem is presented with the objective function, constraints, and design vector. Next, we describe the tool’s architecture and the analysis tools that are utilized. Finally, preliminary results for the test subject UAV are discussed for both the previous and current formulation of the MDO tool.@en

An alternative to the lamination parameters framework is proposed that uses the fiber angles as design variables: the manufacturing finite element mesh (MFEM) framework. The structure and implementation of the MFEM framework allows for both stiffness and strength constraints. In this manuscript the maximum failure index is minimized the case of a static analysis, while for buckling analysis the first buckling mode is maximized. For each case example are presented and discussed. To complete the manuscript the post- processing tool used to obtain feasible automated fiber placement machine tow paths is briey discussed. @en

The least-squares finite element method is used to solve the compressible Euler equations around airfoils in transonic regime. The symbolic analysis method is used to generate the element stiffness and force matrices. The equations of the element matrices are derived symbolically based on the flow primitive variables and the position of the element nodes. The symbolic analysis is also used to compute the exact derivatives of the residuals with respect to both design variables (e.g. the airfoil geometry) and the state variables (e.g. the flow velocity). The symbolic analysis allows to compute the exact Jacobian of the governing equations in a computationally efficient way, which is used for Newton iteration. Besides, using the symbolic analysis the sensitivities of the outputs, such as the airfoil drag, with respect to the design variables, such as the airfoil geometry, are computed using the discrete adjoint method without the need for automatic differentiation. This makes the analysis and optimization computationally more efficient. @en

The application and computational efficiency of wing aerostructural optimization us- ing simultaneous analysis and design (SAND) strategy is investigated. A coupled adjoint aerostructural analysis method based on quasi-three-dimensional aerodynamic analysis is used for this research. Two different optimization problems are tested. In the first case a wing aeroelastic optimization is performed using both nested analysis and design (NAND) and SAND strategies. In this optimization the wing box structure is optimized to achieve minimum wing weight. In the second optimization the wing structure as well as the outer aerodynamic shape are optimized to achieve minimum aircraft fuel weight. The results of both SAND and NAND optimizations have been compared based on accuracy and compu- tational cost @en

In this paper, a method is introduced that predicts the influence of gaps and overlaps introduced by fiber steering on the stiffness and strength of composite laminates. This method is based on the incorporation of a “density functional” which translates the effect of discrete gaps and laps into a continuous correction of the reduced stiffness matrix. It also includes a function to incorporate a fiber placement manufacturing strategy. Test configurations used to test the validity of the density functional approach show results consistent with the expected gap/overlap distributions, and also demonstrate the robustness of the manufacturing strategy function. The method is to be included in the TopSteer optimization code1 to study the influence of gaps and overlaps on optimization results. @en

This paper presents a method for wing aerostructural analysis and optimization, which needs much lower computational costs, while computes the wing drag and structural deformation with a level of accuracy comparable to the higher fidelity CFD and FEM tools. A quasi-threedimensional aerodynamic solver is developed and connected to a finite beam element model for wing aerostructural optimization. In a quasi-three-dimensional approach an inviscid incompressible vortex lattice method is coupled with a viscous compressible airfoil analysis code for drag prediction of a three dimensional wing. The accuracy of the proposed method for wing drag prediction is validated by comparing its results with the results of a higher fidelity CFD analysis. The wing structural deformation as well as the stress distribution in the wingbox structure is computed using a finite beam element model. The Newton method is used to solve the coupled system. The sensitivities of the outputs, for example the wing drag, with respect to the inputs, for example the wing geometry, is computed by a Ali Elham [email protected] Michel J. L. van Tooren [email protected] 1 Faculty of Aerospace Engineering, Delft University of Technology, Delft, Netherlands 2 McNair Center for Aerospace Research and Innovation, University of South Carolina, Columbia, South Carolina, USA combined use of the coupled adjoint method, automatic differentiation and the chain rule of differentiation. A gradient based optimization is performed using the proposed tool for minimizing the fuel weight of an A320 class aircraft. The optimization resulted in more than 10 % reduction in the aircraft fuel weight by optimizing the wing planform @en

A trust region filter-SQP method is used for wing multi-fidelity aerostructural optimization. Filter method eliminates the need for a penalty function, and subsequently a penalty parameter. Besides, it can easily be modified to be used for multi-fidelity optimization. A low fidelity aerostructural analysis tool is presented, that computes the drag, weight and structural deformation of lifting surfaces as well as their sensitivities with respect to the design variables using analytical methods. That tool is used for a mono-fidelity wing aerostructral optimization using a trust region filter-SQP method. In addition to that, a multi-fidelity aerostructural optimization has been performed, using a higher fidelity CFD code to calibrate the results of the lower fidelity model. In that case, the lower fidelity tool is used to compute the objective function, constraints and their derivatives to construct the quadratic programming subproblem. The high fidelity model is used to compute the objective function and the constraints used to generate the filter. The results of the high fidelity analysis are also used to calibrate the results of the lower fidelity tool during the optimization. This method is applied to optimize the wing of an A320 like aircraft for minimum fuel burn. The results showed about 9 % reduction in the aircraft mission fuel burn.@en