To strengthen the transition from conceptual to preliminary rotorcraft design, this work develops an integrated methodology combining early mass and load predictions with structural optimization. Embedded within the DLR frameworks IRIS and PANDORA, the approach orchestrates mass estimation, flight load prediction, and structural assessment in a semi-automated process. Topology optimization techniques are employed to design internal reinforcements between the aerodynamic fuselage and the cabin, enhancing structural fidelity ahead of preliminary design. A primary rescue helicopter serves as a case study, using representative ground and flight load cases as a basis for optimization. Although a full certification load spectrum is not covered, the selected cases capture the main design-driving conditions, demonstrating the benefits of early structural optimization. The presented method enables more informed structural decisions immediately after conceptual design, laying a solid foundation for robust preliminary design.

Over the last years a process chain for the generation of ditching models based on numerical methods for transient dynamic calculations has been developed at the German Aerospace Center. With the integration of automated tool capabilities for mesh-refinement and to extrude cross-sections flexible detailed FE aircraft representations are generated using the structural modelling framework PANDORA. The detailed area of the aircraft model is relevant to sufficiently describe structural deformations. In combination with fluid domains discretized by a set of particles using the SPH formulation representative ditching models are generated and calculated. The SPH- FE approach for ditching models was previously investigated and validated in the scope of a European ditching project using flexible panels in experimental test campaigns. This work focuses on high-fidelity ditching simulations including aircraft models with different mesh densities and representative pools with adapted particle distributions. Ditching simulations are analyzed in terms of result quality, performance, model handling and data transfer. Results are intended to contribute to semi-analytical methods in an industrial driven environment.

As part of the design process, structural assessment represents an important aspect in the development of new airand rotorcraft. It plays a critical role in supporting the weight of the aircraft, transmitting loads from the rotors to the airframe, and ensuring the overall safety and integrity of the vehicle. The conceptual design phase is characterized by exploration and evaluation of broad design concepts, with minimal detail regarding structural design. In contrast, the preliminary design phase involves refining the chosen design concept and conducting more detailed structural analysis and optimization to prepare for the subsequent detailed design phase. In order to evaluate the airframe, the opensource based design environment PANDORA has been developed at DLR. This paper presents an overview of model generation, topology optimization, sizing, and crashworthiness aspects in PANDORA using validation examples and generic rotorcraft models.

Over the years, the German Aerospace Center (DLR) has developed a multidisciplinary process chain for aircraft design. This paper introduces a novel feature of this process chain, implemented in the Python tool called "Parametric Numerical Design and Optimization Routines for Aircraft" (PANDORA) developed at the Institute of Structures and Design (BT) featuring enhanced numerical tools for the fuselage structure analysis and sizing. The ongoing development focuses on achieving a high level of detail in the aircraft Finite Element (FE) modeling chain for crashworthiness evaluations, including a more detailed cabin description as well as advanced anthropomorphic test devices (ATDs). The aim is to study the dynamic behavior of novel cabin layouts and structures under crash conditions starting from their parametrical definition, and evaluate innovative design choices in terms of safety. Such a fully integrated process chain becomes necessary due to recent changes in aviation crashworthiness regulations, where the shift from prescriptive to performance-based requirements may significantly influence both the aircraft design and certification process.

Within the DLR project VicToria various high fidelity-based MDO processes were set-up as applicalble methods for aircraft design. Apart from aerodynamic optimization using high fidelity-based CFD analysis, the sub-processes overall aircraft design synthesis, loads analysis, and structural optimization were part of the MDO processes. The presented paper expounds such MDO sub-processes in order to exhibit their contributions and capabilities for the respected MDO process.

Cybermatrix is a novel approach to aircraft design through multidisciplinary optimization, developed within the DLR project VicToria. It combines three aspects: representing a design problem by an approximate Karush-Kuhn-Tucker system, distributing the rows of the system among disciplinary groups, and employing large computational resources and many humans experts in a parallel fashion. For demonstration an optimization of a long-range, twin-engine transport aircraft has been performed.

The DLR project VicToria brings together disciplinary methods and tools of different fidelity for collaborative multidisciplinary design optimization (MDO) of long-range passenger aircraft configurations, necessitating the use of high-performance computing. Three different approaches are being followed to master complex interactions of disciplines and software aspects: an integrated aero-structural wing optimization based on high-fidelity methods, a multi-fidelity gradient-based approach capable of efficiently dealing with many design parameters and many load cases, and a many-discipline highly-parallel approach, which is a novel approach towards computationally demanding and collaboration intensive MDO. The XRF-1, an Airbus provided research aircraft configuration representing a typical long-range wide-body aircraft, is used as a common test case to demonstrate the different MDO strategies. Additional results are presented for the NASA Common Research Model (CRM) to show their flexibility. Parametric disciplinary models are used in terms of overall aircraft design synthesis, loads analysis, flutter, structural analysis and optimization, engine design, and aircraft performance. The different MDO strategies are shown to be effective in dealing with complex, real-world MDO problems in a highly collaborative, cross-institutional design environment, involving many disciplinary groups and experts and a mix of commercial and in-house design and analysis software.

Aviation is undergoing a transformation, fueled by the Corona pandemic, and methods to evaluate new technologies for more economical and environment-friendly flight in a timelier manner and to enable new aircraft to be designed (almost) exclusively using computers are sought after. The DLR project Victoria brings together disciplinary methods and tools of different fidelity for collaborative multidisciplinary design optimization (MDO) of long-range passenger aircraft configurations, necessitating the use of high-performance computing. Three different approaches are being followed to master complex interactions of disciplines and software aspects: an integrated aero-structural wing optimization based on high-fidelity methods, a multi-fidelity gradient-based approach capable of efficiently dealing with many design parameters and many load cases, and a many-discipline highly-parallel approach, which is a novel approach towards computationally demanding and collaboration intensive MDO. The XRF-1, an Airbus provided research aircraft configuration representing a typical long-range wide-body aircraft, is used as a common test case to demonstrate the different MDO strategies. Parametric disciplinary models are used in terms of overall aircraft design synthesis, loads analysis, flutter, structural analysis and optimization, engine design, and aircraft performance. The different MDO strategies are shown to be effective in dealing with complex, real-world MDO problems in a highly collaborative, cross-institutional design environment, involving many disciplinary groups and experts and a mix of commercial and in-house design and analysis software. © 2021 32nd Congress of the International Council of the Aeronautical Sciences, ICAS 2021. All rights reserved.

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 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.

The DLR project VicToria deals also with high fidelity-based MDO with various approaches. Aside from aerodynamic optimization, further sub-processes are part of the developed MDO processes. They belong to overall aircraft design synthesis, loads analysis, and structural sizing and optimization. The Paper lays out the mentioned MDO sub-processes in order show their contribution and capabilities for the selected MDO process, but also their complexity when dealing with a high fidelity based MDO approach.

The DLR project VicToria brings together design methods that necessite use of high-performance computing, for the multi-disciplinary optimization of a long-range transport aircraft. Three different approaches are followed: the integrated aerostructural wing optimization, the multi-fidelity gradient-based approach, and the many-discipline highly-parallel approach. A common test case is used: XRF1, an Airbus provided research configuration representing a typical long-range wide-body aircraft.

Over the last years a multidisciplinary aircraft predesign process chain was established at the DLR, including different numerical tools for the modelling and structural sizing of fuselage structures. To improve the flexibility and performance of this structural analysis part in the MDO process a new tool development has been started in 2016 called “Parametric Numerical Design and Optimization Routines for Aircraft” (PANDORA). The PANDORA framework is using the interpreted high-level programming language Python and is focused on using dedicated open-source packages. Within PANDORA a lot of new packages have been implemented, like a new interface to access CPACS data, a python based FE pre- and postprocessor, a FE data converter to build an interface between PANDORA and different FE solver and a visualization interface using “The Visualization Toolkit” (VTK). Some further packages to generate a FE model based on a CPACS file using the geometry core “Open Cascade” (OCC) and a new FE sizing algorithm is also under development. To simplify the usage of PANDORA and to keep it comprehensible - a graphical user interface (GUI) has been added using the PYQT toolkit. In this paper the current state of the PANDORA development is presented and initial applications are shown.

Purpose The purpose of this paper is to present some of the key achievements. At DLR, a sophisticated interdisciplinary aircraft design process is being developed, using the CPACS data format (Nagel et al., 2012; Scherer and Kohlgrüber, 2016) as a means of exchanging results. Within this process, TRAFUMO (Scherer et al., 2013) (transport aircraft fuselage model), built on ANSYS and the Python programming language, is the current tool for automatic generation and subsequent sizing of global finite element fuselage models. Recently, much effort has gone into improving the tool performance and opening up the modeling chain to further finite element solvers. Design/methodology/approach Much functionality has been shifted from specific routines in ANSYS to Python, including the automatic creation of global finite element models based on geometric and structural data from CPACS and the conversion of models between different finite element codes. Furthermore, a new method for modeling and interrogating geometries from CPACS using B-spline surfaces has been introduced. Findings Several new modules have been implemented independently with a well-defined central data format in place for storing and exchanging information, resulting in a highly extensible framework for working with finite element data. The new geometry description proves to be highly efficient while also improving the geometric accuracy. Practical implications The newly implemented modules provide the groundwork for a new all-Python model generation chain, which is more flexible at significantly improved runtimes. With the analysis being part of a larger multidisciplinary design optimization process, this enables exploration of much larger design spaces within a given timeframe. Originality/value In the presented paper, key features of the newly developed model generation chain are introduced. They enable the quick generation of global finite element models from CPACS for arbitrary solvers for the first time.

DLR's work on developing a distributed collaborative MDO environment is presented. A multi-level Approach combining high-fidelity MDA for aerodynamics and structures with conceptual aircraft design methods is employed. Configuration-specific sizing loads are evaluated and used for sizing the structure. A gradient-free optimization algorithm is used to optimize the fuel burn of a generic long-range wide-body transport aircraft configuration with 9 shape parameters. The results show a truly multidisciplinary improvement of the modified design. The result of a gradient-free high-fidelity MDO with preselected load cases and five shape parameters is also presented, comparing a full mission analysis with results for the Breguet range equation.

Combining the expertise of many institutes, an increasingly sophisticated interdisciplinary aircraft design process is being developed at DLR, using the CPACS data format (Nagel et al., 2012; Scherer and Kohlgruber, 2014) as a means of exchanging results. Within this process, TRAFUMO (Scherer et al., 2013) (Transport Aircraft Fuselage Model), developed at the Institute of Structures and Design (DLR-BT), is currently the established tool for automatic generation and subsequent sizing of global finite element fuselage models using Ansys and the Python programming language. Recent efforts to increase tool performance and to open up the modelling chain for a wider range of finite element solvers have led to a lot of functionality being shifted from specific routines in Ansys to Python. This includes the automatic creation of global finite element models based on geometric and structural data from CPACS and the conversion of models between different codes. Taking advantage of the modular and object-oriented nature of Python, each new module has been implemented independently with a well-defined central data format in place for storing and exchanging information, thus laying the groundwork for a new all-Python model generation chain, which provides more flexibility at significantly improved runtimes. In the presented paper, the overall structure of the newly developed model generation chain will be introduced. Additionally, the development status of several key modules, such as geometry processor, finite element generator and converter will be discussed in detail, with special attention paid to the interfaces between modules.

Am Deutschen Zentrum fur Luft- und Raumfahrt (DLR) wird an automatisierten Prozessketten fur den Flugzeugvorentwurf geforscht. Ziel ist die Entwicklung und Bewertung von neuen Flugzeugkonzepten sowie die Verknupfung unterschiedlicher Disziplinen im Vorentwurf wie Aerodynamik und Strukturauslegung. Das am DLR entwickelte CPACS-Datensatzformat [1] (Common Parametric Aircraft Configuration Schema, https://github.com/DLR-LY/CPACS) dient dabei als Austauschformat. Fur die Auslegung der Rumpfstruktur zur Massenabschatzung hat das Institut fur Bauweisen und Strukturtechnologie (BT) des DLR bereits das Tool TRAFUMO [2] (Transport Aircraft Fuselage Model) entwickelt, welches masgeblich die skriptfahige Finite-Elemente-Software ANSYS nutzt. Um kunftig deutliche Laufzeitreduktionen, weitere Anwendungsmoglichkeiten sowie mehr Schnittstellen mit anderen Tools zu ermoglichen wird aktuell eine alternative Open Source basierte Prozesskette mit Python entwickelt. Ausgehend vom CPACS-Parametersatz wird die Flugzeugoberflache mittels Open Cascade erstellt und die Geometrie von Strukturkomponenten berechnet. Basierend auf eigens in Python entwickelten Tools wie einem FE-Praprozessor sowie einem FE-Konverter, wird ein FE-Modell der Flugzeugstruktur aufgebaut, welches in die Formate verschiedener FE-Solver exportiert werden kann. Zur Handhabung und Visualisierung dieser Datenmengen werden Module wie Numpy, Pandas und Mayavi verwendet. Die Dimensionierung der Struktur erfolgt zukunftig in Python auf Grundlage von Berechnungsergebnissen fur verschiedene Lastfalle. Dabei konnen neben proprietaren Solvern auch Open-Source-FE-Solver genutzt werden, wodurch die gesamte Prozesskette lizenzfrei lauft und der Datenaustausch vereinfacht sowie die Flexibilitat erhoht wird. Weiterhin ermoglicht die modulare, objektorientierte Programmierung in Python neben der rein statischen Auslegung der Rumpfstruktur auch die Vorbereitung von Crashberechnungen mit komplexeren Anforderungen an das FE-Modell in einer Toolumgebung zu vereinen. Damit bietet die Open Source Prozesskette deutliche Vorteile im Vergleich zur Variante auf Basis bisher verwendeter kommerzieller Tools. Wahrend der FrOSCon werden Einblicke in die Prozesskette gegeben, Schnittstellen zwischen den Modulen dargestellt sowie der Entwicklungsstand von einzelnen Kernmodulen wie dem FE-Praprozessor und dem FE-Konverter im Detail diskutiert sowie an Beispielanwendungen demonstriert. Literatur [1] B. Nagel, D. Bohnke, V. Gollnick, P. Schmollgruber, A. Rizzi, G. La Rocca, J.J. Alonso: „Communication in Aircraft Design: Can We Establish a Common Language?”, 28th Congress of the International Council of the Aeronautical Sciences (ICAS), Brisbane, Australia, 2012. [2] J. Scherer, D. Kohlgruber, F. Dorbath, M. Sorour, „Finite element based Tool Chain for Sizing of Transport Aircraft in the Preliminary Aircraft Design Phase”, 62. DLRK, Stuttgart, Germany, 2013

Rural depopulation resulting in altered hospital coverage, new challenges for medical evacuation during military operations, and increased off-shore activities of energy suppliers, lead to changed requirements of helicopter emergency medical services (HEMS). Recently, interest has significantly increased to overcome the traditional physical limitation of flight speed by providing helicopters with auxiliary propulsive devices, so-called compound rotorcraft. In order to assess these novel rotorcraft concepts, an integrated, multidisciplinary, and automated design procedure has been established at the German Aerospace Center (DLR) using the data model CPACS (Common Parametric Aircraft Configuration Schema). The design processes of rotary- and fixed-wing aircraft highly resemble each other: In the first stage of a typical aircraft design process, the conceptual stage, basic characteristics are established that typically consist of e.g. outer dimensions (i.e. its aerodynamic shape), flight performance, mass breakdown, etc. At this stage of the design process mostly fast, analytical, and statistical methods are applied featuring many simplifications. In the subsequent preliminary design phase the detail level increases. The continuously growing computational power has enabled design engineers to integrate higher fidelity methods at this design stage. At the DLR Institute of Structures and Design, tools have been developed in the last couple of years that use finite element (FE) methods to size aeronautical fuselage structures according to static load cases to allow a more precise prediction of the structural mass, and thus in turn to a different maximum take-off mass which is considered as a major design parameter. Although based on the same framework approach, these FE based tools developed for preliminary sizing of rotary- and fixed-wing fuselages diverged over the years due to different project requirements, such as specific modeling aspects, different syntax for the involved FE solvers, or different design emphases. These issues resulted in different tools to generate FE meshes and to conduct analyses with some inconsistencies between the individual tools. In order to unify the tools, the development of the software framework PANDORA (Parametric Numerical Design and Optimization Routines for Aircraft) has been started at DLR in 2016 from scratch using the Python programming language. The key idea behind PANDORA is to generate one common software framework to model, analyze, and size both fixed- and rotary-wing fuselage structures. Particular focus in the development of PANDORA lies in the use of dedicated open-source packages and the interchangeability of different commercial and open-source FE solvers. This paper first shows the approach of the PANDORA toolbox for fixed-wing aircraft. Then, the process of adapting respectively integrating specific modeling and analysis methods for rotorcraft fuselages into the new framework is shown. Concluding this article an outlook of new enhancements into PANDORA is given highlighting its benefits in the context of preliminary structural analysis of novel rotorcraft concepts.