The aviation industry is under increasing pressure towards de-carbonization and electrificationof commercial aircraft. However, their range limitations are heavily dependent ontheir expected battery energy storage capacity, and the direct operating costs of this propulsiontechnology are still not well understood. This paper provides a forecast of mission and directoperating costs of two fully electric commuter airplanes resembling the EL19 and the EviationAlice, as well as a hybrid-electric aircraft resembling the Do328HE, operating in Sweden inthe 2030 to 2070 time frame. NASA’s forecast for battery specific energy is used as inputfor aircraft models, allowing for the estimation of the maximum expected range under threescenarios: pessimistic, nominal, and optimistic, along with its respective direct operating costs.Results suggest that fully electric technology could become feasible for short domestic routesin Sweden in 2040, with the hybrid-electric model being able to cover longer routes earlier.Direct operating cost models project lower expenses for electric and hybrid-electric conceptscompared to smaller conventional aircraft, although they still remain more costly to operatethan the larger regional aircraft they plan on replacing. This research stresses the need forrealistic technological forecasting and financial awareness in developing sustainable aircraftconcepts, particularly regarding the commercial viability of electrified flight in Scandinavia.

Aerospace systems are connected with the operational environment and other systems in general. The focus in aerospace product development is consequently shifting from a singular system perspective to a System-of-Systems (SoS) perspective. This increasing complexity gives rise to new levels of uncertainty that must be understood and managed to produce aerospace solutions for an ever-changing future. This paper presents an approach to using architecture frameworks, and ontologies with description logic reasoning capabilities, to break down SoS needs into required capabilities and functions. The intention of this approach is to provide a consistent way of obtaining the functions to be realized in order to meet the overarching capabilities and needs of an SoS. The breakdown with an architecture framework results in an initial design space representation of functions to be performed. The captured knowledge is then represented in an ontology with description logic reasoning capabilities, which provides a more flexible way to expand and process the initial design space representation obtained from the architecture framework. The proposed approach is ultimately tested in a search and rescue case study, partly based on the operations of the Swedish Maritime Administration. The results show that it is possible to break down SoS needs in a consistent way and that ontology with description logic reasoning can be used to process the captured knowledge to both expand and reduce an available design space representation.

System of Systems (SoS) are everywhere, either created and directed by an organization or simply emerging to fulfill a need. SoS consist of many independent Constituent Systems (CS) with their own life cycles and behavior. One of the big challenges with studying SoS is building models to support the analysis of these large complex systems. For existent SoS, it may be tempting to use available models from subsequent levels and connect them in a common framework, rather than creating new models tailored for the SoS analysis. Typically, the already existing models often have a high level of fidelity and have been created from a certain point of view to best fit its purpose. This paper shows that a framework with higher fidelity models on Sub-Systems (SS) level will impact the performance on SoS level but also take longer time to converge and thus need more simulations in order for the results to be trusted. With an holistic approach to the development of SoS, we use hierarchical integration of CS and SS models to provide inputs to the simulation on SoS level. Using maritime Search and Rescue (SAR) as a case study, the mission performance of two aircraft searching for a lost life raft through Agent Based Simulation (ABS). Two cases are compared where one of them has a higher fidelity representation of the sensor model. Through the case study it is possible to investigate the impact of model fidelity on the SS level to the simulation results on SoS level. The two cases simulate the same scenario but still show a difference in mission performance. A convergence analysis show that with the the High Fidelity Models (HFM) the simulation takes slightly longer to converge. This paper is the beginning of a multi-fidelity model library that will be used to explore the impact of model fidelity on all the levels of SoS and from that find general methods for choosing model fidelity when analyzing SoS.

System-of-Systems Engineering (SoSE) has become a constantly growing field within product development for complex systems. Systems are becoming more and more connected with other systems and the operational environment in general. This takes the development process to new levels of complexity where high degrees of uncertainties are expected due to ever occurring changes in the operational environment, and other external factors such as politics, economy, and technology. This creates a need of being able to understand the influence of changes early in the development process and to facilitate the systems? perseverance. The focus of the development shifts from fulfilling specific requirements, to being able to meet needs and deliver capabilities over time. Additionally, modeling and simulation for complex systems and System-of-Systems (SoS) becomes a valued alternative to the economically prohibited and almost impossible prototype testing. In consideration of this problem, the presented work introduces a method for both modeling and simulation of a SoS. The method uses ontology with description logic reasoning to derive and narrow down a SoS design space which is further analyzed using Agent Based Simulation (ABS). A Search and Rescue (SAR) scenario is used as a case study to test the method. Measures of Effectiveness (MoE), based on the time it takes to find a rescue subject and the cost of doing so, are used to evaluate the SoS performances. The presented method is envisioned to be used early in the development of complex systems and SoS to increase the overall understanding of them.

This paper presents a multidisciplinary design optimization framework applied to the development of unmanned aerial vehicles with a focus on radar signature and sensor performance requirements while simultaneously considering the flight trajectory. The primary emphasis herein is on the integration and development of analysis models for the calculation of the radar cross section and sensor detection probability, whereas traditional aeronautical disciplines such as aerodynamics and mission simulation are also taken into account in order to ensure a flyable concept. Furthermore, this work explores the effect of implementing trajectory constraints as a supplementary input to the multidisciplinary design optimization process and presents a method that enables the optimization of the aircraft under a three-dimensional flight scenario. To cope with the additional computational cost of the high-fidelity radar cross section and sensor calculations, the use of metamodels is also investigated and an efficient development methodology that can provide high-accuracy approximations for this particular problem is proposed. Overall, the operation and performance of the framework are evaluated against five surveillance scenarios, and the obtained results show that the implementation of trajectory constraints in the optimization has the potential to yield better designs by 12–25% when compared to the more “traditional” problem formulations.

This paper explores the use of Multidisciplinary Design Optimization (MDO) in the development of Unmanned Aerial Vehicles (UAVs) when the requirements include a collaboration in a System of Systems (SoS) environment. In this work, the framework considers models that can capture the mission, stealth, and surveillance performance of each aircraft, while at the same time, a dedicated simulation module assesses the total cooperation effect on a given operational scenario. The resulting mixed continuous and integer variable problem is decomposed with a multi-level architecture, and in particular, it is treated as a fleet allocation problem that includes a nested optimization routine for sizing a “yet-to-be-designed” aircraft. Overall, the models and the framework are evaluated through a series of optimization runs, and the obtained Pareto front is compared with the results from a traditional aircraft mission planning method in order to illustrate the benefits of this SoS approach in the design of UAVs.

Contemporary aircraft design and development incurs high costs and consumes a lot of time for research and implementation. To minimize the development cost, an improvement of the conceptual design phase is desirable. A framework to support the initial design space exploration and conceptual design phase is presently being developed at Linköping University. In the aircraft design, the geometry carries a critical, discriminating role since it stores a significant part of the information and the data needed for most investigations. Methodology for design automation of a wing with a detailed description such that the geometry is effectively propagated for further analysis is presented in this paper. Initial weight estimation of the wing is performed by combining the weight penalty method with a sophisticated CAD model. This wing model is used for airfoil shape optimization and later for structural optimization. A methodology for automatic meshing of the geometry for CFD and FEM when the surfaces increase or decrease during the design automation is proposed. The framework combining automation capability with shape and structural optimization will enhance the early design phases of aircraft conceptual design.

Aircraft design is an inherently multidisciplinary activity that requires integrating different models and tools to reach a well-balanced and optimized product. At Linköping University a design framework is being developed to support the initial design space exploration and the conceptual design phase. Main characteristics of the framework are its flexible database in XML format, together with close integration of automated CAD and other tools, which allows the developed geometry to be directly used in the subsequent preliminary design phase. In particular, the aim of the proposed work is to test the framework by designing, optimizing and studying a transport aircraft wing with respect to aerodynamic, geometry, structural and accessability constraints. The project will provide an initial assessment of the capability of the framework, both in terms of processing speed and accuracy of the results.

This paper explores novel methodologies for enabling Multidisciplinary Design Optimization (MDO) of complex engineering products. To realize MDO, Knowledge Based Engineering (KBE) is adopted with the aim of achieving design reuse and automation. The aim of the on-going research at Linköping University is to shift from manual modelling of disposable geometries to Computer Aided Design (CAD) automation by introducing generic high-level geometry templates. Instead of repeatedly modelling similar instances of objects, engineers should be able to create more general models that can represent entire classes of objects. The proposed methodology enables utilization of commercial design tools, hence taking industrial feasibility into consideration. High Level CAD templates (HLCt) will be proposed and discussed as the building blocks of flexible and robust CAD models, which in turn enables high-fidelity geometry in the MDO loop. Quantification of the terms flexibility and robustness is also presented, providing a means to measure the quality of the geometry models. Finally, application examples are presented in which the outlined framework is evaluated. The applications have been chosen from three ongoing research projects aimed at automating the design of transport aircraft, industrial robots, and micro air vehicles.

Product development processes are continuously challenged by demands for increased efficiency. As engineering products become more and more complex, efficient tools and methods for integrated and automated design are needed throughout the development process. Multidisciplinary Design Optimization (MDO) is one promising technique that has the potential to drastically improve concurrent design. MDO frameworks combine several disciplinary models with the aim of gaining a holistic perspective of a system, while capturing the synergies between different subsystems. Among all disciplines, the geometric model is recognized as playing a key role, because it collects most of the data required to any other disciplinary analysis. In the present thesis, methodologies to enable multidisciplinary optimization in early aircraft design phases are studied. In particular, the research aims at putting the CAD geometric model in the loop. This requires the ability to automatically generate or update the geometric model, here referred to as geometry-based design automation.

The thesis proposes the use of Knowledge Based Engineering (KBE) techniques to achieve design reuse and automation. In particular, so called High Level CAD templates (HLCts) are suggested to automate geometry generation and updates. HLCts can be compared to parametric LEGO® blocks containing a set of design and analysis parameters. These are produced and stored in libraries, giving engineers or a computer agent the possibility to first topologically select the templates and then modify the shape of each template parametrically.

Since parameterization is central to modelling by means of HLCts, a thorough analysis of the subject is also performed. In most of the literature on MDO and KBE two recurring requirements concerning the geometrical model are expressed: the model should be flexible and robust. However, these requirements have never been properly formulated or defined. Hence, in the thesis a mathematical formulation for geometry model robustness and flexibility are proposed. These formulations ultimately allow the performance of geometric models to be precisely measured and compared.

Finally, a prototyping and validation process is presented. The aim is to quickly and cost-effectively validate analytical results from an MDO process. The proposed process adopts different manufacturing techniques depending on the size and purpose of the intended prototype. In the last part of the thesis, three application examples are presented. The examples are chosen from research projects that have been carried out at Linköping University and show how the proposed theoretical results have been successfully employed in practice.

Kraven på ökad effektivitet utmanar ständigt  produktutvecklingsprocessen. I och med att ingenjörsprodukter blir allt mer komplexa, växer genom hela utvecklingsprocessen behovet av verktyg och metoder för integrerad och automatiserad design. Multidisciplinär Design Optimering (MDO) är en lovande teknik som kan drastiskt förbättra parallell design. I ett MDO ramverk är flera disciplinära modeller sammankopplade för att uppnå ett holistiskt systemperspektiv, men där synergierna mellan olika delsystem också kan fångas upp. Bland alla möjliga discipliner spelar geometrimodellen en central roll, eftersom den innefattar en stor del av all information som är nödvändig för andra disciplinära analyser.

I avhandlingen studeras ett flertal metoder för att möjliggöra multidisciplinär optimering i de tidigaste faserna av flygplansdesign. I synnerlighet är forskningen riktad mot att införa geometriska CAD modeller i designloopen. Det blir därmed nödvändigt att kunna automatiskt generera eller uppdatera geometriska modeller, vilket i avhandlingen kallas för ”geometribaserad design automation”.

Avhandlingen förordar att Knowledge Based Engineering (KBE) tekniker används för att konstruktioner skall kunna automatiseras och återanvändas. Så kallade Hög Nivå CAD mallar (på engelska High Level CAD templates – HLCts) föreslås för att automatiskt generera och uppdatera geometrimodeller. HLCts kan jämföras med parametriska LEGO® klossar som innehåller variabler för design och analys. Mallarna kan samlas i bibliotek; därefter har konstruktörer eller dator agenter möjligheten att först topologiskt välja en mall och sedan ändra på dess utförande genom utvalda parametrar.

Eftersom parameterisering är ett centralt begrepp för HLCt principen, föreslås även en fördjupad analys av ämnet. I stor del av MDO och KBE litteraturen ställs det två återkommande krav på geometrimodellen: modellen bör vara flexibel och robust. Eftersom dessa krav aldrig har getts en formell formulering, förordas i avhandlingen en matematisk beskrivning av modellrobusthet och - flexibilitet. Tack vore formuleringen är det möjligt att noggrant mäta och jämföra till vilken grad geometriska modeller fungerar.

Slutligen presenteras en valideringsprocess baserad på kostnadseffektiva prototyper som används för att snabbt bekräfta analytiska resultat från MDO ramverket. Den föreslagna processen nyttjar olika tillverkningsmetoder, beroende på prototypens tänkta storlek och användning. I sista delen av avhandlingen presenteras även tre applikationsexempel, valda från forskningsprojekt som har bedrivits på Linköpings universitet och som visar hur de teoretiska resultaten har kommit till användning i praktiken.