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International audience; The paper provides an overview of the maturity achieved on multidisciplinary aeroelastic and aero-structural adjoint solvers developed during the European project MADELEINE. The main focus is on relevant industrial test cases specified by Airbus based on the XRF-1 research model, representative of a large passenger aircraft. First a crossvalidation of the computed sensitivities among project partners is presented for both rigid and flexible shape gradients, based on a shared wing shape parametrization prescribed by the aircraft manufacturer. Then studies are performed by considering an increased number of parameters representative of industrial design applications. The benefit of taking flexibility into account is demonstrated by comparing single and multi-point optimization results. Finally an outlook of ongoing aero-structural optimizations exploiting an integrated multidisciplinary feasible strategy is provided.

A high-fidelity adjoint-based aerodynamic shape optimization process has been set up that engages the Reynolds-averaged Navier-Stokes solver TAU and couples with the finite element solver Nastran and the thermodynamic engine cycle analysis tool GTlab-Performance. A so-called CAD-ROM, which is a reduced order model representation of a parametric computer-aided design model, is used as shape parameterization. The process enables a gradient-based aeroelastic optimization of full aircraft configurations with powered engines. Therein, a trimming module ensures that each optimization iteration is feasible by imposing an equilibrium of forces and moments. The process is embedded within FlowSimulator, an environment dedicated to efficient multi-physics simulations on high-performance computing clusters. The shape sensitivities are consistently derived by coupling the discrete flow, mesh and structural adjoints and by accounting for a trim-correction of the objective functional. The optimization process has been demonstrated for a cruise range optimization of a generic transport aircraft model. The range can be increased by approximately five percent within the first six optimization iterations by adapting the wing shape defined by a 126-dimensional wing section Bspline parameterization. &nbsp

The highly parameterized process cpacs-MONA for structural and aeroelastic design of aircraft configurations is presented. The parameterized design process is based on the Common Parametric Aircraft Configuration Schema (CPACS), developed by DLR, where almost all aircraft parameters like mission, geometry, structure, and material are defined. The process stands out for its independent use for structural and aeroelastic design on the one hand and its integration into high fidelity based multidisciplinary optimization tasks on the other hand. The process consists of preliminary mass and loads estimation based on conceptual design methods followed by a parameterized set-up of simulation models and an optimization model. They are used for a comprehensive loads analysis followed by a component wise structural optimization. The latter takes stress, strain, buckling and control surface efficiency as constraints into account. The structural simulation model consist of shell and beam elements for the wing-like component and the fuselage in order to represent the construction of the load carrying structure of the complete aircraft appropriately. Such depth of modelling allows also for the use of well-established structural optimization methods. MONA stands for ModGen, the in-house parametric model generation computer program, and MSC Nastran, used for loads and aeroelastic analysis as well as for structural optimization. cpacs-MONA is also integrated in MDO tasks, where other disciplines like aerodynamics and overall aircraft design are involved. Therein aerodynamic data from high fidelity CFD calculations are used to improve the vortex lattice based aerodynamic method that is applied of the aeroelastic loads analysis. The MDO tasks where cpcas-MONA is integrated can be gradient-free and gradient-based. For the gradient-based MDO task cpacs-MONA delivers to the system optimization level the structural variables, the structural responses the corresponding sensitivities. As structural optimization task alone can deal with a high number of variables and constraints, for the MDO task with other disciplines, like aerodynamics, methods were developed where the number of constraints is reduced that are taken into account on the system level. Two applications are presented for cpacs-MONA. In the first application cpacs-MONA is applied as independent and stand-alone structural and aeroelastic design process. For a long range wide body transport aircraft configuration the design loads case are estimated after a comprehensive loads analysis campaign. For the structural design especially the structural requirements and alternative strategies to achieve sufficient control surface effectiveness within the flight envelope are investigated. In the second application cpacs-MONA is part of a gradient-free optimization task with aerodynamics and the structure to be optimized simultaneously. The presented results show that the aerodynamic optimum lead on the one hand to a heavier wing mass, but investigating the structural optimization results more closely, also local benefits of the new aerodynamic design regarding the wing structure can be found.

This paper presents the cybermatrix protocol, a novel approach to multidisciplinary design optimization in the contex of multiple-fidelity disciplinary analyses, many involved disciplines and high use of high-performance computing resources. The approach is presented from its formal mathematical background to actual on-disk implementation of running processes. As the demonstration case, a twin-engine long-range transport aircraft is optimized. Four disciplines are employed: overall aircraft wing planform design, aerodynamic airfoil design using 3D RANS computations, structural wing design using global shell-element FEM model, and loads selection and evaluation process based on low fidelity aerodynamics.

This paper presents an approach to multi-disciplinary optimization (MDO) of transport aircraft developed within the DLR project VicToria that attempts to strike a balance between two broad classes of MDO approaches: those arising from the formal optimization background, and those coming from the aircraft design background. It starts from the observation that any kind of numerical design process can be viewed as an approximation of a formal optimization process, where Jacobians of cost functions may be inexact and are often not explicitly computed. Based on that, a specific MDO problem representation and a highly parallel process assembly and execution protocol (the ``cybermatrix'' protocol) is defined, as well as one possible realization on high-performance computing (HPC) resources. The approach is applied to an optimization of a long-range transport aircraft, employing disciplinary subprocesses for high-fidelity aerodynamic design of wing airfoil shapes, structural sizing of lifting surfaces, and determination and evaluation of design loads.

This report compares two approaches for achieving a trimmed state of an aircraft configuration during an aerodynamic optimization. In the optimizer-based approach, balance equations are posed as direct constraints to the optimizer. In the flow solver-based approach, balance equations are satisfied within the flow solver evaluation. These approaches are applied to a flying wing case, where blended trailing edge deflection is used to control the pitching moment. The wing is treated as rigid, and lift and pitching moment balance equations are taken into account for trimming. Tests are performed with varying numbers of shape design parameters and with varying numbers of flight points. It is concluded that the flow solver-based approach performs more robustly, and thus should be preferred in general, even though it may take more time than the optimizer-based approach.