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Master of Science in Aerospace Engineering

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https://hdl.handle.net/1853/73269
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search.filters.applied.f.advisor: Mavris, Dimitri N. × Start date: 2020 × End date: 2023 ×

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Now showing 1 - 4 of 4
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    Assessing An Aerospace Application Of Digital Twins For Multi-Agent Dynamic Decision Making
    (Georgia Institute of Technology, 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 systems of systems methodology for conceptual studies of in-situ resource utilization for near earth object applications
    (Georgia Institute of Technology, 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 reduce dimensionality of a commercial supersonic transport design space using active subspaces
    (Georgia Institute of Technology, 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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    Development of a methodology for technology requirement assessment for space habitats
    (Georgia Institute of Technology, 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.