The purpose of this study is to examine the multidisciplinary design optimization (MDO) of a distributed propulsion blended-wing-body (BWB) aircraft. The BWB is a hybrid shape resembling a flying wing, placing the payload in the inboard sections of the wing. The distributed propulsion concept involves replacing a small number of large engines with many smaller engines. The distributed propulsion concept considered here ducts part of the engine exhaust to exit out along the trailing edge of the wing. The distributed propulsion concept affects almost every aspect of the BWB design. Methods to model these effects and integrate them into an MDO framework were developed. The most important effect modeled is the impact on the propulsive efficiency. There has been conjecture that there will be an increase in propulsive efficiency when there is blowing out of the trailing edge of a wing. A mathematical formulation was derived to explain this. The formulation showed that the jet "fills in" the wake behind the body, improving the overall aerodynamic/propulsion system, resulting in an increased propulsive efficiency. The distributed propulsion concept also replaces the conventional elevons with a vectored thrust system for longitudinal control. An extension of Spence's Jet Flap theory was developed to estimate the effects of this vectored thrust system on the aircraft longitudinal control. It was found to provide a reasonable estimate of the control capability of the aircraft. An MDO framework was developed, integrating all the distributed propulsion effects modeled. Using a gradient based optimization algorithm, the distributed propulsion BWB aircraft was optimized and compared with a similarly optimized conventional BWB design. Both designs are for an 800 passenger, 0.85 cruise Mach number and 7000 nmi mission. The MDO results found that the distributed propulsion BWB aircraft has a 4% takeoff gross weight and a 2% fuel weight. Both designs have similar planform shapes, although the planform area of the distributed propulsion BWB design is 10% smaller. Through parametric studies, it was also found that the aircraft was most sensitive to the amount of savings in propulsive efficiency and the weight of the ducts used to divert the engine exhaust. / Ph. D.

A new noise metric has been developed that may be used for optimization problems involving aerodynamic noise from a clean wing. The modeling approach uses a classical trailing edge noise theory as the starting point. The final form of the noise metric includes characteristic velocity and length scales that are obtained from three-dimensional, steady, RANS simulations with a two- equation k-omega turbulence model. The noise metric is not the absolute value of the noise intensity, but an accurate relative noise measure as shown in the validation studies. One of the unique features of the new noise metric is the modeling of the length scale, which is directly related to the turbulent structure of the flow at the trailing edge. The proposed noise metric model has been formulated so that it can capture the effect of different design variables on the clean wing airframe noise such as the aircraft speed, lift coefficient, and wing geometry. It can also capture three-dimensional effects which become important at high lift coefficients, since the characteristic velocity and the length scales are allowed to vary along the span of the wing. Noise metric validation was performed with seven test cases that were selected from a two-dimensional NACA 0012 experimental database. The agreement between the experiment and the predictions obtained with the new noise metric was very good at various speeds, angles of attack, and Reynolds Number, which showed that the noise metric is capable of capturing the variations in the trailing edge noise as a relative noise measure when different flow conditions and parameters are changed. Parametric studies were performed to investigate the effect of different design variables on the noise metric. Two-dimensional parametric studies were done using two symmetric NACA four-digit airfoils (NACA 0012 and NACA 0009) and two supercritical (SC(2)-0710 and SC(2)-0714) airfoils. The three-dimensional studies were performed with two versions of a conventional transport wing at realistic approach conditions. The twist distribution of the baseline wing was changed to obtain a modified wing which was used to investigate the effect of the twist on the trailing edge noise. An example study with NACA 0012 and NACA 0009 airfoils demonstrated a reduction in the trailing edge noise by decreasing the thickness ratio and the lift coefficient, while increasing the chord length to keep the same lift at a constant speed. Both two- and three-dimensional studies demonstrated that the trailing edge noise remains almost constant at low lift coefficients and gets larger at higher lift values. The increase in the noise metric can be dramatic when there is separation on the wing. Three-dimensional effects observed in the wing cases indicate the importance of calculating the noise metric with a characteristic velocity and length scale that vary along the span. The twist change does not have a significant effect on the noise at low lift coefficients, however it may give significant noise reduction at higher lift values. The results obtained in this study show the importance of the lift coefficient on the airframe noise of a clean wing and favors having a larger wing area to reduce the lift coefficient for minimizing the noise. The results also point to the fact that the noise reduction studies should be performed in a multidisciplinary design and optimization framework, since many of the parameters that change the trailing edge noise also affect the other aircraft design requirements. It's hoped that the noise metric developed here can aid in such multidisciplinary design and optimization studies. / Ph. D.

The purpose of this study is to examine the multidisciplinary design optimization (MDO) of a strut-braced wing (SBW) aircraft compared to similarly designed cantilever wing aircraft. In this study, four different configurations are examined: cantilever wing aircraft, fuselage mounted engine SBW, wing mounted engine SBW, and wingtip mounted engine SBW. The cantilever wing design is used as a baseline for comparison. Two mission profiles were used. The first called for a 7380 nmi range with a 305 passenger load based on a typical Boeing 777 mission. The second profile was supplied by Lockheed Martin Aeronautical Systems (LMAS) and has a 7500 nmi range with a 325 passenger load. Both profiles have a 0.85 cruise Mach number and a 500 nmi reserve range. Several significant refinements and improvements have been made to the previously developed MDO code for this study. Improvements included using ADIFOR (Automatic Differentiation for FORTRAN) to explicitly compute gradients in the design code. Another major change to the MDO code is the improvement of the optimization architecture to allow for a more robust optimization process. During the Virginia Tech SBW study, Lockheed Martin Aeronautical Systems (LMAS) was tasked by NASA Langley to evaluate the results of previous SBW studies. During this time, the original weight equations which were obtained from NASA Langley's Flight Optimization System (FLOPS) was replaced by LMAS proprietary equations. A detailed study on the impact of the equations from LMAS on the four designs was done, comparing them to the designs that used the FLOPS equations. Results showed that there was little difference in the designs obtained using the new equations. An investigation of the effect of the design constraints on the different configurations was performed. It was found that in all the design configurations, the aircraft range proved to be the most crucial constraint in the design. However, results showed that all three SBW designs were less sensitive to constraints than the cantilever wing aircraft. Finally, a double-deck fuselage concept was considered. A double deck fuselage configuration would result in a greater wing/strut intersection angle which would, in turn, reduce interference drag at that section. Due to the lack of available data on double deck fuselage aircraft, a detailed study of passenger and cargo layout was done. Optimized design showed that there was a small improvement in takeoff gross weight and fuel weight over the single-deck fuselage SBW results when compared with a similarly designed cantilever wing aircraft. / Master of Science

The objective of this study is to use Multidisciplinary Design Optimization (MDO) to investigate the use of truss-braced wing concepts in concert with other advanced technologies to obtain a significant improvement in the performance of transonic transport aircraft. The truss topology introduces several opportunities. A higher aspect ratio and decreased wing thickness can be achieved without an increase in wing weight relative to a cantilever wing. The reduction in thickness allows the wing sweep to be reduced without incurring a transonic wave drag penalty. The reduced wing sweep allows a larger percentage of the wing area to achieve natural laminar flow. Additionally, tip-mounted engines can be used to reduce the induced drag. The MDO approach helps the designer achieve the best technology integration by making optimum trades between competing physical effects in the design space. To perform this study, a suite of approximate analysis tools was assembled into a complete, conceptual-level MDO code. A typical mission profile of the Boeing 777-200IGW was chosen as the design mission profile. This transport carries 305 passengers in mixed class seating at a cruise Mach number of 0.85 over a range of 7,380 nmi. Several single-strut configurations were optimized for minimum takeoff gross weight, using eighteen design variables and seven constraints. The best single-strut configuration shows a 15% savings in takeoff gross weight, 29% savings in fuel weight, 28% increase in L/D, and a 41% increase in seat-miles per gallon relative to a comparable cantilever wing configuration. In addition to the MDO work, we have proposed some innovative, unconventional arch-braced and ellipse-braced concepts. A plastic solid model of one of the novel configurations was created using the I-DEAS solid modeling software and rapid prototyping hardware. / Master of Science

With ever-increasing numbers of engine actuators to calibrate within increasingly stringent emissions legislation, the engine mapping and calibration task of identifying optimal actuator settings is much more difficult. The aim of this research is to evaluate the feasibility and effectiveness of the Multidisciplinary Design Optimisation (MDO) frameworks to optimise the multi-attribute steady state engine calibration optimisation problems. Accordingly, this research is concentrated on two aspects of the steady state engine calibration optimisation: 1) development of a sequential Design of Experiment (DoE) strategy to enhance the steady state engine mapping process, and 2) application of different MDO architectures to optimally calibrate the complex engine applications. The validation of this research is based on two case studies, the mapping and calibration optimisation of a JLR AJ133 Jaguar GDI engine; and calibration optimisation of an EU6 Jaguar passenger car diesel engine. These case studies illustrated that: -The proposed sequential DoE strategy offers a coherent framework for the engine mapping process including Screening, Model Building, and Model Validation sequences. Applying the DoE strategy for the GDI engine case study, the number of required engine test points was reduced by 30 – 50 %. - The MDO optimisation frameworks offer an effective approach for the steady state engine calibration, delivering a considerable fuel economy benefits. For instance, the MDO/ATC calibration solution reduced the fuel consumption over NEDC drive cycle for the GDI engine case study (i.e. with single injection strategy) by 7.11%, and for the diesel engine case study by 2.5%, compared to the benchmark solutions. / UK Technology Strategy Board (TSB)

The digital transformation of engineering design processes is essential for the aerospace industry to remain competitive in the global market. Multidisciplinary design optimization (MDO) frameworks play a crucial role in this transformation by integrating various engineering disciplines and enabling the optimization of complex spacecraft structures. Since the design team consists of multiple entities from different domains working together to build the final product, the design and analysis tools must be readily available and compatible. An integrated approach is required to handle the problem's complexity efficiently. Additionally, most aerospace structures are made from composite panels. It is challenging to optimize such panels as they require the satisfaction of constraints where the design ply thicknesses and orientations can only take discrete values prescribed by the manufacturers. Heuristics such as particle swarm or genetic algorithms are inefficient because they provide sub-optimal solutions when the number of design variables is large. They also are computationally expensive in handling the combinatorial nature of the problem. To overcome these challenges, this work proposes a two-fold solution that integrates multiple disciplines and efficiently optimizes composite spacecraft structures by building a rapid design framework. The proposed model-based design framework for spacecraft structures integrates commercially available software from Siemens packages such as NX and HEEDS and open-source Python libraries. The framework can handle multiple objectives, constraint non-linearities, and discrete design variables efficiently using a combination of black-box global optimization algorithms and Mixed Integer Programming (MIP)-based optimization techniques developed in this work. Lamination parameters and MIP are adopted to optimize composite panels efficiently. The framework integrates structural, thermal and acoustic analysis to optimize the spacecraft's overall performance while satisfying multiple design constraints. Its capabilities are demonstrated in optimizing a small spacecraft structure for required structural performance under various static and dynamic loading conditions when the spacecraft is inside the launch vehicle or operating in orbit. / Doctor of Philosophy / The design of new spacecraft takes several years and requires significant resources. The primary design objective is to minimize spacecraft mass/cost while satisfying the mission requirements. This is done by altering the structure's geometric and material properties. Most spacecraft panels are made from composite materials where the orientations of fiber paths and the thickness of the panel determine its strength and stiffness. Finding the best values for these parameters cannot be done efficiently using existing optimization algorithms, as several combinations of orientations can give a similar performance which can be subpar. In this dissertation, mathematical programming is adopted for fast evaluation of optimum panel properties, thereby saving a significant amount of resources compared to conventional techniques. Moreover, the requirements that govern the design process are handled one at a time in an organization. This leads to discrepancies in the various teams' designs that satisfy all requirements. A framework is built to integrate all requirements to account for their conflicting nature and quickly give the best possible spacecraft structural design configuration.

Automotive companies are exposed to tough competition and therefore strive to design better products in a cheaper and faster manner. This challenge requires continuous improvements of methods and tools, and simulation models are therefore used to evaluate every possible aspect of the product. Optimization has become increasingly popular, but its full potential is not yet utilized. The increased demand for accurate simulation results has led to detailed simulation models that often are computationally expensive to evaluate. Metamodel-based design optimization (MBDO) is an attractive approach to relieve the computational burden during optimization studies. Metamodels are approximations of the detailed simulation models that take little time to evaluate and they are therefore especially attractive when many evaluations are needed, as e.g. in multidisciplinary design optimization (MDO). In this thesis, state-of-the-art methods for metamodel-based design optimization are covered and different multidisciplinary design optimization methods are presented. An efficient MDO process for large-scale automotive structural applications is developed where aspects related to its implementation is considered. The process is described and demonstrated in a simple application example. It is found that the process is efficient, flexible, and suitable for common structural MDO applications within the automotive industry. Furthermore, it fits easily into an existing organization and product development process and improved designs can be obtained even when using metamodels with limited accuracy. It is therefore concluded that by incorporating the described metamodel-based MDO process into the product development, there is a potential for designing better products in a shorter time.

The rising complexity of CubeSat missions and the unique challenges faced by educational CubeSat programs lead to high rates of mission failure. Implementing project management and systems engineering practices can alleviate these challenges and improve mission success rates for educational CubeSat developers. However, existing project management and systems engineering resources are too cumbersome and often assume the student has a base-level understanding of project management and systems engineering fundamentals. A new universal project management and systems engineering framework was created and tailored specifically to the needs of an educational CubeSat mission. The framework was designed to accommodate first-time CubeSat developers, has no base-level assumptions, and uses software accessible by the majority of university CubeSat programs. The framework was implemented on an educational CubeSat mission being designed by a first-time CubeSat developer. The framework was iteratively updated based on the developer’s feedback and experience using the templates, tools, and trainings. The universal project management and systems engineering framework for educational CubeSat missions demonstrated that it was effectively tailored to the needs of educational CubeSat missions, taught students the value of project management and systems engineering, enhanced students’ professional development, and was accessible for first-year undergraduate students to utilize with minimal intervention.

Modeling and simulation tools are exceptionally useful for designing aerospace systems because they allow engineers to test and iterate designs before committing the massive resources required for system realization. The Horizon Simulation Framework (HSF) is a time-driven modeling and simulation tool which attempts to optimize how a modeled system could perform a mission profile. After 15 years of development, the HSF team aims to achieve a wider user and developer base by releasing the software open source. To ensure a successful release, the software required extensive testing, and the main scheduling algorithm required protections against new code breaking old functionality. The goal of the work presented in this thesis is to satisfy these requirements and officially release the software open source. The software was tested with > 80% coverage and a continuous integration pipeline which runs build and unit/integration tests on every new commit was set up. Finally, supporting documentation and user resources were created and organized to promote community adoption of the software, making Horizon ready for an open source release.

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