A KBE Application for Automatic Aircraft Wire Harness Routing

Wire harness design is an increasingly complex task. Knowledge Based Engineering (KBE) and optimization techniques can be used to support designers in handling this complexity. The wire harness design process can be divided in three main parts, namely electrical design, configuration design and geometrical routing. This paper describes the latest progress in the development of a KBE application aiming at the automation of the routing phase. Discrete optimization techniques are used to design shortest path harnesses, while complying with different type of constraints. Some preliminary results have been presented in a previous paper, where only geometrical constraints were addressed. However, wire harness design is affected also by other types of rules and constraints, which need to be accounted to obtain more realistic design results from the optimization process. This paper describes some new developments in the routing application to account for the presence of critical zones inside the aircraft. As study case, the presence of heat sources inside the airframe is considered, which either force the harness to be routed elsewhere, or require the use of wire protections, with obvious consequences on weight and manufacturing. First, some mathematic transformation techniques are used to model the presence of heat sources inside the routing environment. Then the A* algorithm is used for compute the 3D routing, aiming at minimum wire harness weight. The main architecture of the routing application is presented and its functionality is demonstrated with samples of wire harness routing inside a wing. The results show that the proposed KBE application can automate the routing of wire harness while taking into account different rules and constraints. The modeling approach for a heat source can be generalized and extended to address other criticality such as abrasion, electromagnetic interference, corrosion, etc. The achieved level of automation relieves designers from the repetitive work associated with the frequent changes affecting the design environment

Adjoint-based aerodynamic shape optimization on unstructured meshes

In this paper, the exact discrete adjoint of an unstructured finite-volume formulation of the Euler equations in two dimensions is derived and implemented. The adjoint equations are solved with the same implicit scheme as used for the flow equations. The scheme is modified to efficiently account for multiple functionals simultaneously. An optimization framework, which couples an analytical shape parameterization to the flow/adjoint solver and to algorithms for constrained optimization, is tested on airfoil design cases involving transonic as well as supersonic flows. The effect of some approximations in the discrete adjoint, which aim at reducing the complexity of the implementation, is shown in terms of optimization results rather than only in terms of gradient accuracy. The shape-optimization method appears to be very efficient and robust

Development of the Discrete Adjoint for a Three-Dimensional Unstructured Euler Solver

The discrete adjoint of a reconstruction-based unstructured finite volume formulation for the Euler equations is derived and implemented. The matrix-vector products required to solve the adjoint equations are computed on-the-fly by means of an efficient two-pass assembly. The adjoint equations are solved with the same solution scheme adopted for the flow equations. The scheme is modified to efficiently account for the simultaneous solution of several adjoint equations. The implementation is demonstrated on wing and wing–body configurations

Aerodynamic shape optimization by means of sequential linear programming techniques

A Sequential Linear Programming technique, known as the method of centers, is the driver of an aerodynamic shape optimization framework on unstructured meshes. The first order information required by this technique, functional values and their gradients, are computed by a median-dual flow/adjoint solver which is coupled to an analytical shape parameterization. Functional and geometric constraints are easily handled by the algorithm which appears to be very effective in obtaining efficiently near-optimal designs. Shape optimization results are presented for transonic as well as supersonic flows involving appreciable shape deformations

Sandwich fuselage design

Aerospace Engineerin

Method for bonding a thermoplastic polymer to a thermosetting polymer component

The invention relates to a method for bonding a thermoplastic polymer to a thermosetting polymer component, the thermoplastic polymer having a melting temperature that exceeds the curing temperature of the thermosetting polymer. The method comprises the steps of providing a cured thermosetting polymer component comprising an implant of a thermoplastic polymer at least at the part of the thermosetting polymer component to be bonded, locating a thermoplastic polymer in contact with at least the part to be bonded, heating the assembly to the melting temperature of the thermoplastic polymer, whereby the thermoplastic polymer of the implant melts and fuses with the thermoplastic polymer, and cooling the assembly. The thermoplastic polymer has a melting temperature that exceeds the curing temperature of the thermosetting polymer, and the implant is designed such that heating above the maximum operating temperature of the thermosetting polymer at the interface of the implant with the thermosetting polymer component is avoided during the bonding step.Aerodynamics, Wind Energy & PropulsionAerospace Engineerin

Discrete adjoint aerodynamic shape optimization using symbolic analysis with OpenFEMflow

The combination of gradient-based optimization with the adjoint method for sensitivity analysis is a very powerful and popular approach for aerodynamic shape optimization. However, differentiating CFD codes is a time consuming and sometimes a challenging task. Although there are a few open-source adjoint CFD codes available, due to the complexity of the code, they might not be very suitable to be used for educational purposes. An adjoint CFD code is developed to support students for learning adjoint aerodynamic shape optimization as well as developing differentiated CFD codes. To achieve this goal, we used symbolic analysis to develop a discrete adjoint CFD code. The least-squares finite element method is used to solve the compressible Euler equations around airfoils in the transonic regime. The symbolic analysis method is used for exact integration to generate the element stiffness and force matrices. 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). Besides, the symbolic analysis allows us to compute the exact Jacobian of the governing equations in a computationally efficient way, which is used for Newton iteration. The code includes a build-in gradient-based optimization algorithm and is released as open-source to be available freely for educational purposes

Winglet design using multidisciplinary design optimization techniques

A quasi-three-dimensional aerodynamic solver is integrated with a semi-analytical structural weight estimation method inside a multidisciplinary design optimization framework to design and optimize a winglet for a passenger aircraft. The winglet is optimized for minimum drag and minimum structural weight. The Pareto front between those two objective functions is found applying a genetic algorithm. The aircraft minimum take-off weight and the aircraft minimum direct operating cost are used to select the best winglets among those on the Pareto front