Multidisciplinary Design Analysis And Optimization Research Articles

From Requirements to Product: an MBSE Approach for the Digitalization of the Aircraft Design Process

AbstractDuring the aircraft conceptual design phase, many different design options need to be explored and compared in a short time frame. To speed up this process, efforts have been made in the past decades to digitalize parts of the design process, with a focus on the automation of the repetitive and non‐creative tasks inherent to the iterative design process. Whilst many of the newly developed methodologies focus on specific parts of the design process, a holistic model‐based design framework, incorporating the latest design technology developments, is lacking. To fill this gap, this paper presents the latest version of the Design and Engineering Engine (DEE) framework, originally proposed in the early 2000s and progressively matured through the experience of several international research collaborations. The DEE enables the setup and execution of Multidisciplinary Design Analysis and Optimization (MDAO) problems for aircraft (sub)systems, leveraging the automated, rule‐based modeling capabilities offered by Knowledge‐Based Engineering (KBE) and recent developments in the automatic formulation and integration of MDAO workflows. While the traditional MDAO process focuses on a given product architecture, the DEE allows also architectural design studies and makes use of Model‐Based Systems Engineering (MBSE) principles to address the whole design process, from requirements modeling up to the automatic verification of the requirements. In practice, the DEE provides a single conceptual framework or template from which specific design framework instances can be formulated and executed, according to the user's needs. This paper describes the DEE architecture and its implementation concepts. Furthermore, it demonstrates the application of the DEE template to four different scenarios, ranging from a simple requirement verification study, up to the simultaneous synthesis and optimization of an aircraft system and its production process, including multiple system architecture options.

The AGILE 4.0 Project: MBSE to Support Cyber‐Physical Collaborative Aircraft Development

AbstractThis paper presents the main output of the EU‐funded H2020 AGILE 4.0 project: the AGILE 4.0 MBSE‐MDAO Development Framework. The framework aims at connecting upstream Model‐Based Systems Engineering (MBSE) activities to downstream Multidisciplinary Design Analysis and Optimization (MDAO) activities, applied to the development of complex aeronautical systems. Upstream activities include the definition of stakeholders, needs, semantic requirements, and modeling the system architecture design space. Downstream activities include defining, implementing, and executing cross‐organizational and collaborative MDAO workflows to support system synthesis. The development framework is implemented in an Operational Collaborative Environment (OCE), a web‐based platform for project data and modeling tool access. A business jet family design application case demonstrates the use of the development framework and OCE.

Development of a medium/long-haul reference aircraft

For the evaluation of future aircraft architectures or novel technologies, a well-understood and sound reference to compare to is essential to prove the impact of intended changes. A reference aircraft serves as a basis for calibration of the aircraft and is used as a starting point for subsequent investigations, sensitivity studies or optimizations. The prime need for such a reference arose from the European Clean-Sky-2 project HLFC-Win (Hybrid Laminar Flow Control—Wing), where no industrial reference data for a conventional aircraft were available. The project investigates a HLFC system integrated into the wing aiming to reduce the wing drag and consequently reducing the fuel consumption. Therefore, this paper presents the D300-XRF1 designed by DLR, which is based on the AIRBUS research aircraft XRF1 (eXternal Research Forum). It is intended to be used as a reference aircraft database representing aircraft for medium- and long-range missions. A variable fidelity multidisciplinary design analysis and optimization (MDAO) aircraft design environment is set up to provide a consistent estimate of the geometry, mass breakdown, propulsion system, aerodynamics and aircraft performance. A conceptual aircraft design tool is utilized in the aircraft design environment to initialize the process, and higher-fidelity modules are used to enhance the results. The presented results describe the overall aircraft characteristics of the D300-XRF1 based on 2010 entry into service technology level and is offered to be used as a reference within the aviation research community, hopefully reducing similar design efforts in other research projects.The aircraft operates at a design cruise Mach number of 0.83, has a design range of 5500 NM and transports a payload of 31.5 t (300 PAX at 105 kg/PAX). The D300-XRF1 serves as a consistent reference aircraft database and provides a holistic overview of the aircraft’s performance that has been presented to and approved by AIRBUS. Therefore, this reference aircraft design can be used for future studies and to assess new technologies on a sophisticated level.

Modeling and Design Optimization of an Electric Environmental Control System for Commercial Passenger Aircraft

The aircraft environmental control system (ECS) is the second-highest fuel consumer system, behind the propulsion system. To reduce fuel consumption, one research direction intends to replace conventional aircraft with more electric aircraft. Thus, new electric architectures have to be designed for each system, such as for the ECS. In this paper, an electric ECS is modeled and then sized and optimized for different sizing scenarios with the aim of minimizing fuel consumption at the aircraft level. For the system and for each component, such as air inlets and heat exchangers, parametric models are developed to allow the prediction of relevant characteristics. These models, developed in order to be adapted to aircraft design issues, are of different types, such as scaling laws and surrogate models. They are then assembled to build a preliminary sizing procedure for the ECS by using a multidisciplinary design analysis and optimization (MDAO) formulation. Results show that the ECS design is highly dependent on the sizing scenario considered. An approach to size the ECS globally with respect to all the sizing scenarios leads to an ECS that accounts for around 200 N of drag, 190 kW of electric power, and 1500 kg of mass for the CeRAS aircraft.

A Safety-Focused System Architecting Framework for the Conceptual Design of Aircraft Systems

To reduce the environmental impact of aviation, aircraft manufacturers develop novel aircraft configurations and investigate advanced systems technologies. These new technologies are complex and characterized by electrical or hybrid-electric propulsion systems. Ensuring that these complex architectures are safe is paramount to enabling the certification and entry into service of new aircraft concepts. Emerging techniques in systems architecting, such as using model-based systems engineering (MBSE), help deal with such complexity. However, MBSE techniques are currently not integrated with the overall aircraft conceptual design, using automated multidisciplinary design analysis and optimization (MDAO) techniques. Current MDAO frameworks do not incorporate the various aspects of system safety assessment. The industry is increasingly interested in Model-Based Safety Assessment (MBSA) to improve the safety assessment process and give the safety engineer detailed insight into the failure characteristics of system components. This paper presents a comprehensive framework to introduce various aspects of safety assessment in conceptual design and MDAO, also considering downstream compatibility of the system architecting and safety assessment process. The presented methodology includes specific elements of the SAE ARP4761 safety assessment process and adapts them to the systems architecting process in conceptual design. The proposed framework also introduces a novel safety-based filtering approach for large system architecture design spaces. The framework’s effectiveness is illustrated with examples from applications in recent collaborative research projects with industry and academia. The work presented in this paper contributes to increasing maturity in conceptual design studies and enables more innovation by opening the design space while considering safety upfront.

From System Architecting to System Design and Optimization: A Link Between MBSE and MDAO

AbstractOptimization of system architectures can help deal with finding better system architectures in a large design space plagued by combinatorial explosion of alternatives. To enable architecture optimization, the design space should therefore be formalized into a numerical optimization problem, and it should be possible to quantitatively evaluate architecture alternatives. This paper presents a methodology for generating and modeling architecture design spaces using the Architecture Design Space Graph (ADSG), and using collaborative Multidisciplinary Design Analysis and Optimization (MDAO) techniques to evaluate architectures. Collaborative MDAO leverages disciplinary expertise while ensuring that analysis tools exchange data consistently and correctly using a central data schema. The problem solved in this paper is the missing link between architecture optimization and collaborative MDAO: the reflection of generated architectures in the central data schema. It is solved by the authors by mapping architecture components and Quantities of Interest (QOIs) to the central data schema using Data Schema Operations (DSOs). Such a mapping also assists the user in identifying missing or unnecessary disciplinary analysis tools. Three web‐based software tools implementing the methodology are presented. Finally, the methodology and tools are demonstrated using the design of a supersonic business jet as an example.

Multidisciplinary Design Optimization of Twin-Fuselage Aircraft with Boundary-Layer-Ingesting Distributed Propulsion

The requirements of sustainable and fuel-efficient next-generation air transportation place greater demands on future aircraft design. Distributed electric propulsion (DEP) and twin-fuselage (TF) are promising concepts to improve aircraft aerodynamic efficiency and flight performance. This paper aims to develop a multidisciplinary design analysis and optimization (MDAO) framework for the TF DEP aircraft concept to investigate the potential of introducing these two technologies in improving aircraft energy efficiency. The most important effect modeled in this study is the influence of the boundary-layer-ingesting DEP system on the propulsive efficiency. Besides, analytical models are derived for the mass, aerodynamic, and performance analysis, separately. Design cases of a wing-segment-mounted DEP, and a TF DEP unmanned aerial vehicle are analyzed to investigate the design space of DEP parameters and to demonstrate the MDAO process. The results show that the best arrangement of the DEP is to distribute the propulsors evenly on the three wing segments of the wing divided by the two fuselages. The optimization leads to more than a 65% increment in the endurance and an 8% reduction in the takeoff mass of the exemplary aircraft.

A Review of Design, Analysis and Optimization Methodologies for Floating Offshore Wind Turbine Substructures

The development of novel energy technologies to meet net zero carbon emission is imperative in the provision of solutions to realize an increasing worldwide demand for renewable energy. Floating Offshore Wind Turbine (FOWT) is one of the emerging technologies to exploit the vast wind resources available in deep waters within the offshore wind sector. However, as a result of the complexity of a FOWT system, bringing FOWT technology up to speed requires a detailed understanding of the different disciplines within the system and the relationship between the FOWT system and the dynamics of the marine environment; hence, the need for Multidisciplinary Design Analysis and Optimization (MDAO) of a FOWT system.

Multidisciplinary aircraft integration within a collaborative and distributed design framework using the AGILE paradigm

The aircraft design is a collaborative and multidisciplinary process. It involves several experts with different disciplinary competences. These disciplinary experts often belong to different departments or organizations. The EU funded H2020 AGILE project aims at developing new generation of Multidisciplinary Design Analysis and Optimization (MDAO) frameworks. In particular, the AGILE project tackles the investigation and the development of technologies able to enhance the collaboration between the disciplinary experts. The present paper deals with a MDAO framework developed in the context of the AGILE research project. The integration of some disciplinary expertise is described by means of a case study of an innovative regional aircraft. Some disciplinary design variables are investigated to verify the correctness of disciplines integration and to quantify the mutual dependences among the design disciplines. In particular, the variation of the engine By Pass Ratio and the electrification level of the On-Board Systems are investigated through the MDAO workflow developed for aircraft preliminary design. Finally, the results show a plausible interaction among the disciplines and interesting trends regarding aircraft systems electrification.

Controllability Gramian as Control Design Objective in Aircraft Structural Design Optimization

Because of their higher aerodynamic efficiency and lighter structural weight, thin composite wings with large aspect ratios are increasingly being used for civil transport aircraft wing design. However, the increased flexibility can induce several performance issues, such as high deflections, reduced control authority, coupled flight dynamics, and, possibly, a reduction in the flutter speed. Therefore, including control surface and control law design at the conceptual design stage is becoming increasingly important. This paper presents a novel approach for integrating a control objective into an aircraft design optimization at the conceptual design stage by proposing the use of the eigenvalues of the controllability Gramian to enhance the controllability of an aircraft. The individual eigenvalues of the controllability Gramian quantify the energy required to move along the corresponding eigenvector, which is observed to be dominated by one state-space variable. A higher eigenvalue implies lower energy requirements for controlling that eigenvector, thus the corresponding state-space variable. This approach does not rely on a control law design but on modifying the open-loop system such that it is easier to control. The approach is applied to conduct multidisciplinary design analysis and optimization (MDAO) of a composite flying-wing test aircraft. A previously developed MDAO framework is used to design the internal structural layout, using curvilinear spars and ribs (SpaRibs) and straight spars and ribs. It is found that the optimal control designs have up to 8% higher flutter speed with a 3.7% weight penalty. Moreover, the frequencies of the vibration mode shapes are higher for the optimal control designs. The active flutter suppression controllers are designed after the MDAO process, and it is found that the optimal control designs have significantly higher gain and phase margins. As a result, the optimal control designs yield higher robust closed-loop flutter speed as compared with the weight-minimized design.

Automatic modeling of aircraft external geometries for preliminary design workflows

This article introduces a high-fidelity geometry definition methodology enabling Multidisciplinary Design, Analysis and Optimization (MDAO) of aircraft configurations. All definitions and functional features have been implemented within the JPAD software, a Java-based computing library for aircraft designers, which provides a dedicated geometric modeling module called JPADCAD. The geometric module, that comes as an application programming interface (API) built on top of the OpenCASCADE Technology solid modeling kernel, is conceived for the automatic production of parametric aircraft CAD geometries. The tool allows the definition of input geometries for low-fidelity as well as high-fidelity aerodynamic analyses, hence proves to be a key factor in the entire MDAO process, particularly in conceptual or preliminary design analysis workflows. The main goal of such a geometric library remains ease of use and support for automation to minimize unnecessary or repetitive human effort.The backbone of the presented methodology is the parametric definition of a generic commercial transport aircraft configuration that translates into software data structures and functionalities of CAD surface modelers. These aspects are discussed in the first part of the article. The second part presents a use case example of the geometric modeling API, where an automated aerodynamic analysis workflow is used to construct a prediction model for canard-wing configurations.

Applying a distributed collaborative MDAO environment to study the power matching of the propulsion system and the on-board electrified systems for advanced regional and short- to medium-range jetliners

ABSTRACTThis paper deals with the study of the power matching of the propulsion system and on-board systems changing the on-board systems’ electrification level. In particular, four system architectures have been studied, each one with a different level of electrification starting from the More Electric Aircraft (MEA) to the All Electric Aircraft (AEA) systems. The mass and the power requirement of each system architectures have been analysed together with the change in engine specific fuel consumption. Then, these results have been used to quantify the influences of engine and systems power matching to the entire aircraft. In particular, the beneficial effect of system electrification has been evaluated as an increment of aircraft range. Moreover, two reference aircraft – a regional jet and a short/medium range liner – have been selected to understand the variance of the power matching changing aircraft dimensions and mission range. The study is carried out using a distributed and collaborative Multi-Disciplinary Design Analysis and Optimization (MDAO) environment. The results show a beneficial effect of systems electrification on systems mass and engine specific fuel consumption. At aircraft level, the results point out an increment of aircraft range up to 7.7% with a different trend for the two studied cases.

Formulation and integration of MDAO systems for collaborative design: A graph-based methodological approach

This paper proposes a novel methodology and its software implementation, called KADMOS (Knowledge- and graph-based Agile Design for Multidisciplinary Optimization System), to increase the agility of design teams in collaborative Multidisciplinary Design Analysis and Optimization (MDAO). Agility here refers to the ease and flexibility to assemble, adjust and reconfigure MDAO computational systems. This is a necessary feature to comply with the complex and iterative nature of the (aircraft) design process. KADMOS has been developed on the notion that a formal specification of an MDAO system is required before proceeding with integration of the executable workflow. A thorough formulation of the system becomes essential when such system is built on the many contributions of large, heterogeneous design teams. KADMOS can automate the generation of such formulations through a graph-based methodological approach. The graph syntax and manipulation algorithms form the core content of this paper. First, a simple MDAO benchmark problem is used to illustrate KADMOS's working principles. Second, a wing aerostructural design case is discussed to demonstrate KADMOS's capabilities to enable collaborative MDAO on large problems of industry-representative complexity. Next to its graph-theoretic foundation, KADMOS makes use of two data schemas: one containing the parametric representation of the product being designed and a second to store the achieved formulation of the MDAO system. The latter enables the interchangeable use of different process integration and design optimization platforms to automatically integrate the generated MDAO system formulation as an executable workflow. The proposed approach has been estimated to be capable of halving the time typically required to set up and iteratively reconfigure a complex MDAO system, while allowing discipline experts and system architects to maintain constant oversight and control of the overall system and its components by means of human-readable dynamic visualizations.

A graph theoretic approach to problem formulation for multidisciplinary design analysis and optimization

The formulation of multidisciplinary design, analysis, and optimization (MDAO) problems has become increasingly complex as the number of analysis tools and design variables included in typical studies has grown. This growth in the scale and scope of MDAO problems has been motivated by the need to incorporate additional disciplines and to expand the parametric design space to enable the exploration of unconventional design concepts. In this context, given a large set of disciplinary analysis tools, the problem of determining a feasible data flow between tools to produce a specified set of system-level outputs is combinatorially challenging. The difficulty is compounded in multi-fidelity problems, which are of increasing interest to the MDAO community. In this paper, we propose an approach for addressing this problem based on the formalism of graph theory. The approach begins by constructing the maximal connectivity graph (MCG) describing all possible interconnections between a set of analysis tools. Graph operations are then conducted to reduce the MCG to a fundamental problem graph (FPG) that describes the connectivity of analysis tools needed to solve a specified system-level design problem. The FPG does not predispose a particular solution procedure; any relevant MDO solution architecture could be selected to implement the optimization. Finally, the solution architecture can be represented in a problem solution graph (PSG). The graph approach is applied to an example problem based on a commercial aircraft MDAO study.