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Daniel Guggenheim School of Aerospace Engineering

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Assessing An Aerospace Application Of Digital Twins For Multi-Agent Dynamic Decision Making

2023-05-02 , Marks, Ian

The concept of Dynamic Decision Making (DDM) is essential for achieving an overall goal by adapting to the results of previous decisions and unexpected environmental changes. Example applications of DDM in aerospace vary from individual predictive maintenance to multi agent tasking . When making dynamic decisions in a multi-agent scenario, the goal is to minimize uncertainty for future actions by predicting consequences for both the individual asset and the group. In a squadron with vehicles of the same type, it is expected that performance (e.g., fatigue rate and structural health ) vary form one vehicle to the next. Infusing individual performance capabilities and their uncertainties can overwhelm the decision maker. One approach to improve the decision-making process for multiple agents is by using Digital Twins, an authoritative virtual representation of a connected physical system. The digital twin’s aspects of computational, physical, and communications limits impact their overall utility. Furthermore, the aspects of fidelity, runtime, latency, and proximity (due to the physical requirements) need to be assessed to determine the value within multi-agent DDM. A vision for Digital Twins is to enable real time operational decision making by predictive and proactive measures while mitigating potential anomalies. This thesis seeks to evaluate the infusion of Digital Twins in a multi agent DDM architecture, the challenges with the infusion, and a comparison to historically deterministic decision-making processes for a relevant aerospace scenario to trade overall mission effectiveness. To that end, three steps are required: a method of evaluating different decision-making architectures, digital twin selection, and scenario definition. A structured decision-making process was developed such that both twinned and twinless multi agent DDM methods could be interchanged. The digital twin selected for evaluation was the airframe prognostic health of a remote-control aircraft. The digital twin determined how tightly a turn can be performed ( or ) as a function of health status mid-mission. A field surveillance/survey mission scenario was implemented with area surveilled as a metric. During the mission, each aircraft (twinned or twinless) defines their turn load, while a multi-agent coordinator modifies waypoints for agents. To ensure multi-agent interactions with DDM, a perturbance (treated as a gust event) occurs leading to one aircraft leaving the mission early and requiring the remaining aircraft to adapt their missions to mitigate the unexplored areas. Each aircraft leaves the mission area upon mission completion, digital twin health assessments or crashing. The assessment for permitting aircraft to leave the mission area is traded between the multi agent commander and by agents; both traded as a function of latency. Each agent has unique variations in both airframe life and digital twin architectures (instance vs aggregate) and are traded. The design of experiments enables trades across the agents factors of the digital twin fidelity (fit error with sensor to loads), initial health, and overall system latency. From the data generated, surrogate models were fit and analyzed to determine variable significance via ANOVA as well as a comparison between a turn only (treated as a twinless/human baseline) and various digital twin fidelities. Sensitivity analysis revealed that airframe life had the greatest impact on overall mission effectiveness among both digital twin-infused dynamic decision-making methods. Following closely was the influence of overall system latency, with digital twin fidelity being least important of the three. Additionally, the digital twin comparisons to human baseline show that digital twins significantly increase mission performance by longevity in the field as the entire fleet significantly ages. A simplified axiom for the digital twin’s infusion into multi agent dynamic decision making is as follows: 1) Having information is good (digital twin usage) 2) Having accurate information is better (digital twin fidelity) 3) Having information on time to make decisions is critical (data communication)

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A METHODOLOGY FOR CONDUCTING DESIGN TRADES FOR A SMALL SATELLITE LAUNCH VEHICLE WITH HYBRID ROCKET PROPULSION

2021-07-28 , Caglar, Havva Irem

The commercial space industry has recently seen a paradigm shift related to the launch of a small satellite into Low Earth Orbit. In the past, a small satellite was launched as a secondary payload with a medium or heavy launch vehicle where the primary payload placed a constraint on the orbit and schedule. Today, a dedicated launch of a small launch vehicle is the main operational concept to launch a small payload. Many Smallsat Launch Vehicles (SLV) have been under development by the commercial space industry to improve these launch services in recent years. Despite these efforts, the specific prices per launch are still high, and reducing these prices further remains a challenge. One promising technology candidate to reduce costs for SLV is hybrid rocket propulsion which has matured recently with some cost and safety advantages. Although hybrid rocket propulsion faces a number of challenges, including a low regression rate and combustion instabilities, academia and commercial companies have invested significant resources in developing this technology. With this motivation, this thesis has focused on the conceptual design of SLV with hybrid rocket propulsion. Moreover, a cost reduction strategy currently used by the commercial space industry was observed to be the development of a unique engine and using multiple of them in a launch vehicle. Following this trend, the vehicle concept investigated in this thesis was an expendable ground-launched vehicle with some architectural variables such as the number of stages and the number of hybrid motors in each stage. The design trade-off studies of such a small multistage launch vehicle with multiple hybrid motors in each stage require very long times especially when traditional point design approaches are used. As the number of design variables increase, the design space exploration becomes even more challenging. To provide a solution to this problem, a methodology for rapid conceptual design of such a vehicle was presented in this thesis. A physics-based conceptual design approach was followed in this study since SLV are relatively new concepts without much historical performance data. To conduct a multidisciplinary analysis, a physics-based, integrated modeling and simulation environment was constructed with four core disciplines: trajectory analysis, aerodynamics, propulsion, and weight. Aerodynamics and propulsion analysis were conducted using a first-principles approach, which was based on fundamental theories. A 3 Degree of Freedom (DOF) industrial, transparent, physics-based trajectory analysis software was used in this study based on availability. However, any other trajectory analysis software that a system designer is familiar with can be used in its place. In other words, the methodology developed in this thesis would remain unchanged if another trajectory analysis software were used. The weight discipline was represented at a high level by using Propellant Mass Fraction (PMF) design variable. A multidisciplinary modeling and simulation environment for launch vehicles may be computationally expensive depending on the fidelity levels of each discipline. Moreover, trajectory optimization is included in a launch vehicle design process conventionally which may be also computationally expensive depending on the optimization method. This expense poses a difficulty in performing a trade-off study for hundreds of vehicle design alternatives within the constraints of the schedule in the conceptual design phase. Because of this, trajectory optimization was removed from the design process to speed up the process by selecting a constant controller design. The methodology developed in this thesis consisted of two sequential steps. In the first step, a surrogate modeling approach was followed to replace the Modeling and Simulation (M&S) environment. A DOE method and a surrogate modeling method suitable to this problem were searched in this part. To cover the design space, a hybrid DOE consisting of a Fast Flexible Filling DOE and a three-level Full Factorial DOE was chosen. Artificial Neural Networks method was selected to fit approximation models because of the type of design variables (both continuous and discrete variables) and nonlinearity of the problem. The first experiment was conducted to test this hypothesis. As a result, it was demonstrated that this approach can provide accurate surrogate models for any desired response. In the second step, the specific mechanical energy-based design trade-off method was developed using some statistical methods. This method estimates the lower bound of the vehicles’ actual specific mechanical energy where the vehicles can be rapidly designed by using surrogate models. This lower bound was predicted with the help of the prediction interval of the specific mechanical energy’s model fit error. To fit the surrogate models, the necessary data were gathered by running the DOE in the integrated M&S environment while imposing some terminal conditions on the altitude of the vehicles analyzed in this environment. Specifically, the surrogate models of specific mechanical energy and flight path angle were used to design the vehicles rapidly. The second experiment was conducted to test this hypothesis. As a result, the actual specific mechanical energies computed via trajectory optimization were found to be consistent with the predictions. Overall, it was demonstrated that the proposed method enables a system designer to rapidly design some feasible vehicles, which can then proceed to the next design phase for further comparison, analysis, and design.

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An acoustical based approach to conceptual design of non-traditional rotorcraft configurations

2020-07-31 , Huelsman, Sara

As interstate and highway traffic increases, commute times become drastically large. Such large commute times create fatigue and take away from productive hours at work, or joyful hours at home. The idea of urban air mobility becomes increasingly more attractive and viable as technology improves. These more advanced rotor concepts have opened up the design space in order to satisfy a very different mission profile. Nontraditional rotor concepts can provide performance benefits within a new use of the design. Noise becomes an increasing concern since the mission profile allows these vehicles flying much closer to communities. This research investigates three configurations of rotorcraft: coaxial rotors, ducted rotors, and ducted coaxial rotors, to provide insight on how design configuration changes the acoustics of these vehicles. The methodology developed is a parametric environment to provide detail on influential parameters for a model to be created for use within the conceptual design stage. This provides designers a process for capturing acoustic changes early on in the design process, while these new vehicles are still being developed.

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Development of a methodology for technology requirement assessment for space habitats

2020-04-28 , Deguignet, Marie

There recently has been a renewed focus on space exploration and space habitats all over the world. Future lunar developments should focus on reusability, sustainability and affordability. To comply with these objectives, deep space exploration will be faced with technical and human limitations. New technologies must be developed to overcome these challenges. Because technology development is a long and onerous process, it is important to be able to identify the requirements early in the design process to reduce the risk of new developments. A clear methodology to evaluate the requirements of a technology to meet future goals must be provided to innovative companies. This work aims at establishing a clear and consistent methodology to evaluate future space technologies and compare their impact on several factors of a campaign to define the conceptual requirements. To prove that the developed methodology answers all the targeted requirements of the research objective, it will be tested on a technology: cryocoolers, and the space logistics framework FOLLOW. The proposed methodology uses Technology Impact Forecasting and applies and modifies it to take into consideration the specificity of the problem at hand: a smaller data set, long computation times and the goal of the thesis. The methodology can be used by companies to prove the worth of new innovative ideas and encourage investment. It is a rather safe process to help technology advancement.

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Conceptual Effectiveness-Based Hypersonic Evaluation (CEBREN)

2022-05-03 , Van Der Linden, James C. A.

For decades, the United States has largely been uncontested in its quest to advance its national interests in every domain – to protect the American people, promote prosperity, preserve peace, and advance American influence. To maintain technological superiority, the National Security Strategy calls upon the military to field new capabilities that clearly overmatch US adversaries in lethality. Furthermore, the US military has identified hypersonics as an area of interest to stay competitive on the global stage. Hypersonics have been around for over 70 years ranging from the X-20 to the Space Shuttle; however, these projects were products of the traditional design-build-test methodology which often never saw flight. This design-build-test methodology is unable to meet the demands of technological growth and complexity and often drives up costs and overruns. Thus, there is a need to develop a new methodology for assessing hypersonic weapon capability rapidly to support interactive decision making for conceptual development. Hypersonic conceptual design distinguishes itself from traditional aircraft design because the disciplines that must be considered are highly coupled and tightly integrated which drastically increases design risk due to sources of uncertainty. Additionally, it is difficult for engineers to evaluate revolutionary designs because the historical data necessary to perform initial analysis likely is unavailable. Due to this uncertainty, conceptual design is critical because the decisions made have profound ramifications throughout the entire process. To address this uncertainty, physical experiments are required to provide the highest quality of data; however, they are extremely limited in scope and expensive. Hence, there is a need to make well informed decisions at the conceptual design level when designing novel hypersonic vehicles. Due to the coupling of disciplines within hypersonic conceptual design, a Multidisciplinary Design Analysis and Optimization (MDAO) environment was used to design novel hypersonic vehicles. To aid in evaluating these alternatives, agent-based modelling was used to study the effectiveness of the vehicles through operational analysis (OA). By integrating an MDAO environment with an OA framework, novel hypersonic vehicles were constructed, and their capabilities assessed through a process known as effectiveness-based design (EDB). Within EBD, the design objective is shifted from performance metrics (e.g., weight, range, etc.) to effectiveness metrics (e.g. targets killed, survival, etc.) which allows decision makers to consider and understand the implications of design-space-limiting decisions earlier in the process. This shifts away from over-defining requirements before exploring potential best solutions to the problem. Thus, the purpose of this thesis presents a new methodology to address the need of designing and rapidly assessing hypersonic capability to better inform the decision maker through the integration of OA within an MDAO environment thereby closing the loop by coupling the effectiveness to vehicle design parameters.

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A Methodology for Demand Assessment and Integrated Schedule Design and Fleet Assignment Applied to Thin-Haul Scheduled Operations

2021-07-07 , Da Silva Oliveira, Thayna

The thin-haul market is characterized by short-range routes with low demand, occasionally served by commuter airlines. Historically, commuter operators have not been able to maintain profitable operations in this market, migrating to longer and more profitable routes throughout the years. As a result, many small cities have lost their air service and airports have become underutilized. Aiming to change this scenario, many studies have focused on the development of vehicle technologies to promote thin-haul scheduled operations and the assessment of potential demand. This thesis investigates thin-haul operations from the airline's point of view, aiming to understand how flight operations optimization can aid commuter operators to improve profitability and, ultimately, to restore the air service to small communities. Despite the low individual demand of each thin-haul route, an opportunity for profitability may exist if the origin-destination pairs are effectively served. This can be achieved if the airline makes the right schedule decisions, i.e., strategically defines when and where to fly, as well as the assignment of the aircraft with the right capacity to the right flight leg. These problems are part of the schedule planning process and are known in the literature as schedule design and fleet assignment (SD&FA). However, the lack of historical data and baseline schedule for thin-haul operations imposes challenges for demand estimation and SD&FA applications. Therefore, the contribution of this thesis is in the development of a methodology for demand assessment and integrated SD&FA applied to thin-haul operations that can overcome the aforementioned challenges. This is achieved by investigating thin-haul demand based on the competition with alternative modes of transport and by coupling the current SD&FA techniques with the concept of hourly demand distribution. The proposed methodology is implemented in a framework that allows different operational scenarios to be evaluated based on the operations metrics of effectiveness, which includes the airline profit, the potential thin-haul demand served, and the passenger time savings. Such framework enables stakeholders to understand the key elements that lead to profitable thin-haul operations, the extent to which the air service can be expanded, and the potential benefits for passengers and cities. The experiments conducted in this thesis demonstrated that the methodology can successfully perform SD&FA applied to thin-haul operations and determine the true market share, i.e., the potential demand that can be profitably served by an air carrier. Additional case studies highlighted that more efficient operations can be achieved if airlines adopt a mix of point-to-point and connecting flights, and that hub location and aircraft attributes can significantly impact the effectiveness of the operations.

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A systems of systems methodology for conceptual studies of in-situ resource utilization for near earth object applications

2020-07-28 , Kitson, Christopher Curtice

Near Earth Objects (NEO) have historically been neglected as an object of study relative to other celestial bodies. Interest has been increasing as more recognize the potential value of NEO resources represented by ‘asteroid mining’, especially as a supporting role in a Systems of Systems (SoS) context. After all, reusable rockets require refueling before reuse. That propellant needs to come from somewhere. Still, a feasible means to harness NEO resources has proven elusive. In-Situ Resource Utilization (ISRU) is a broad field with literature siloed by both disciplines and use cases. This is especially apparent for existing NEO ISRU concepts, with wildly varying levels of detail between systems in the same concept, including omission of key functions. Pet projects given context imply ‘technology push’ instead of ‘mission pull’. This thesis aims to show NEO ISRU is more feasible than previously believed, by providing a more comprehensive treatment of the required functionality and the means to deliver it. This boils down to permitting better comparisons via enabling trade studies at the conceptual level (NASA pre-phase A). A sample return mission using propellant produced from NEO resources for the return trip is formulated to contextualize the analysis. A program to develop a design that accomplishes this mission could be named “Sample return from Near earth object with In-situ Propellant production Technology demonstrator” (SNIPT). Both qualitative and quantitative design aspects are considered herein. Qualitative aspects are considered first. By reconciling commonalities between concepts, standardized terminology is proposed through a functional decomposition along with a morphological matrix of alternatives. A streamlined technology readiness assessment is performed to rank these morphological options. This information is used to select four concepts, one for each propellant type considered. Both impulsive (methalox and hydrolox) and continuous (hydrogen and steam) propulsion are considered as possible customers of an In-Situ Propellant Production (ISPP) SoS. Another significant part of this effort is quantifying alternatives sufficiently to permit comparisons beyond subject matter expert opinions. A modular sizing code is developed from scratch in line with the selected morphological options for each propellant, and verified at the module level using analog test data. By establishing baseline design(s), perturbations can be compared with directionally correct results. Input parameters for NEO orbital characteristics and then NEO composition are varied to ascertain effects upon sizing results. These results inform a trade study between the four propellant types considered. It was found that previous modeling efforts for NEO ISRU concepts have grossly underestimated the overall plant mass, likely due to neglecting indirect ISRU functionality and energy use. This includes sized values for mass payback ratio (MPR ≈ 5) and mass-specific regolith throughput (f_REG ≈ 0.3 day^(-1) ) which were previously overestimated by orders of magnitude. Methalox works better above 5 C: 1 H atoms by mass, a restrictive niche. Steam had the highest MPR but also heaviest plant mass. Hydrolox was found to be lightest on average for low Δv, with hydrogen lighter for high values, though hydrogen had MPR < 1 due to low volatile utilization. Increasing the proportion of volatiles used to make the propellant was found to reduce specific energy intensity, which in turn increases MPR.

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A Methodology to Capture the Acoustic Properties of Small Unmanned Aerial System Noise Using a Novel Frequency Weighting

2021-08-03 , Gabrielian, Ana Bella

As the advent of Urban Air Mobility (UAM) draws near, the obstacles to such vehicles and operations grow larger. One of these obstacles is the noise created through the operation of these air vehicles. Noise is a public concern as excessive exposure has been shown to contribute to lack of sleep, lack of cognitive abilities in children, and decline in overall cardiac health. There is extensive noise policy for traditional aircraft; however, no noise policy exists for vehicles in the category of UAM. In this thesis, the understanding of small Unmanned Aerial System (sUAS) noise is detailed by investigating the competence of current metrics to describe the annoyance that is created by such vehicles. With regulatory entities such as the Federal Aviation Administration (FAA) forecasting the viability of last mile delivery by sUASs by 2030, it is imperative that acoustical understanding is developed in parallel with this emerging technology. As a part of a NASA research effort, the Design Environment for Novel Vertical Lift Vehicles (DELIVER), a psychoacoustic test on sUASs was conducted to measure human annoyance toward these vehicles in comparison to current delivery vehicles. The study had two main findings: at the same decibel level, test subjects found sUASs more annoying than they did delivery vehicles and the correlation between annoyance and decibel level using four different noise metrics was relatively low. In a preliminary comparison of spectral content between a helicopter and one of the sUASs in this study, it is shown that the sUAS’s spectral content has more tones in the region of frequencies in which humans are especially sensitive. To account for human sensitivity to these tones, the hypothesis is posed: A new frequency weighting, which allows Sound Exposure Level to better correlate with human annoyance caused by an sUAS noise event, will create a larger SEL contour area that is more indicative of sUAS noise. In the first phase of the approach, this hypothesis was tested by creating a design of experiments of different frequency weightings to find a new weighting with a higher correlation coefficient. The resulting frequency weighting (the X-weighting) increased the R2 value from 0.784 to 0.853. In the second phase, Sound Exposure Level contours were created using the new frequency weighting and current frequency weightings in ANOPP2. The SEL 65 dB contour experienced a 79%, 18%, and 78% increase in width, length and area respectively between then X- and the A-weighting for one of the sUASs investigated. This methodology grants stakeholders such as regulators and original equipment manufacturers a process to assess frequency weightings and their efficacy in capturing human annoyance; in doing so, this could enable all sUAS stakeholders to create a common “language” with which to discuss the noise created by these vehicles effectively.

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A METHODOLOGY FOR THE PREDICTION AND ANALYSIS OF PRECURSORS TO FLIGHT ADVERSE EVENTS

2021-05-04 , Bleu-Laine, Marc-Henri

Air transportation is known to be the safest mean of transportation nowadays. The drastic improvements in aviation safety since its gain in popularity are undeniably a factor in the industry's growth over the last several decades. This growth brought social and economic benefits throughout the world and was expected to keep its momentum pre-COVID-19. Stakeholders such as the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), the National Transportation Safety Board (NTSB), aircraft manufactures, and airlines have developed systems, techniques, and technologies that are to thank for today's overall safety improvements and the reduction of accidents. The industry's maintained growth is welcomed, but current safety performances have been observed to stagnate instead of declining. With safety initiatives such as the Flight Operational Quality Assurance (FOQA) program and the growing number of aviation data, many of the previous techniques used to understand the causes of accidents are not scalable. These reasons led to the development of novel methods leveraging advanced analytical tools such as machine learning and deep learning. However, current use cases have focused mainly on anomaly detection and system health monitoring, which does not bring enough reaction time to deal with an imminent event. This research proposes the improvement of aviation safety through precursor mining. Precursors are defined as events that are highly correlated to the adverse event that they precede. Therefore, they provide predictive capabilities and can be used to explain pre-defined events. This thesis uses publicly available flight data to 1) develop a novel deep learning method to identify and rank precursors of multiple adverse events, 2) use unsupervised learning algorithms to group flights based on their precursors to identify potential causes for these events at a fleet-level, and finally 3) detect novelty to ensure that the developed precursor models operate within their limits and that new non pre-defined adverse events could be detected.

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A methodology to reduce dimensionality of a commercial supersonic transport design space using active subspaces

2020-04-28 , Crane, Nathan Thomas

As the commercial aviation industry continues to grow, the next technological leap is speed, and commercial supersonic transports are reappearing from multiple companies. Although this problem has been solved before, supersonic design is still difficult as it is highly interdisciplinary, lacks historical data, and requires additional design considerations earlier in the design cycle. Without historical data, higher fidelity analysis is needed early in the design process. The large number of design variables and the need for high fidelity analysis creates large computational costs, limiting design space exploration. To address this, the dimensionality of the design space needs to be reduced without removing the effects from the design variables. A recent technique called Active Subspaces has accomplished this goal by rotating a design space into the most active direction and taking surrogates in this active direction. Through rotation, the effects of each design variable are still present, but less impactful directions can be removed from the surrogate model, reducing dimensionality. This research applies this method to a commercial supersonic design space and asks additional questions about active subspace implementation into a design methodology. These questions address the gradient oversampling needed for good active subspace surrogate fits, if a better active subspace could be found in a partition of the full design space, and how the goodness of an initial surrogate, used to calculate gradients, affects the active subspace surrogate. Finally, the research compares computational cost between a traditional surrogate and an active subspace surrogate. These questions were addressed using aerodynamic data of various aircraft configurations at supersonic cruise conditions. Beginning with a design of experiments of 20 planform variables, the configurations were input into Engineering Sketch Pad to generate the geometry. The geometry was taken into an inviscid computational fluid dynamics (CFD) tool to calculate coefficients of lift and drag at the cruise condition, and these were tabulated. The results were post processed, and a traditional surrogate was created. From this surrogate, gradients were taken to develop active subspace variables. These variables were used to generate a sweep of active subspace surrogates starting from a single variable to a surrogate made from all 20 variables. From these surrogates, it was concluded that oversampling gradients beyond the published range does not decrease error while undersampling increases error at a lower significance than expected. An active subspace in a local partition of a design space initially reduced error, but error reduction decreased as more variables were included in the active subspace surrogate. The number of cases per design variable of an initial surrogate used to calculate gradients was significant. The error of the active subspace surrogate created from these gradients decreased until 50 cases per design variable, when the decrease in error plateaued. Finally, active subspaces saw a large potential to reduce computational time. A small reduction in dimensionality could greatly reduce computational time, especially if gradients are found within a tool. Using these results, a design methodology was presented incorporating active subspaces into the design loop.

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