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Daniel Guggenheim School of Aerospace Engineering

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College of Engineering

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Aerospace Design Group

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Aerospace Systems Design Laboratory (ASDL)

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Air Transportation Laboratory

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Cognitive Engineering Center

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Space Systems Design Laboratory (SSDL)

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Publication Search Results

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Multi-Fidelity Reduced-Order Modeling Applied to Fields with Inconsistent Representations

(Georgia Institute of Technology, 2020-12-06) Perron, Christian

Our ever-increasing capacity for high-performance computing has progressively elevated the role of physics-based simulations in the conceptual and preliminary phases of aircraft design. This virtualization of the early design process has allowed for additional design freedom and shorter development time while engineers continuously strive for cleaner and quieter aircraft. While modern high-fidelity simulations can provide results with great accuracy, their application is often hindered by their steep computational cost and the limited availability of computing resources. This is especially prohibitive for design problems requiring the analysis of many aircraft configurations and at several flight conditions. To overcome the overwhelming cost of high-fidelity simulations, these are often replaced in practice by cheaper surrogate models generated using a handful of previously obtained solutions. When applied to physics-based results, surrogate models are typically associated with the prediction of integrated quantities. Recently, a new form of surrogate modeling, referred to as Reduced-Order Modeling (ROM), was developed for the prediction of high-dimensional field quantities. In addition to providing physically richer results than conventional surrogate models, this form of approximation is especially relevant for multi-disciplinary applications where the physical quantities exchanged between the disciplines are typically fields. As with most empirical models, the accuracy of a ROM is contingent on the amount of data used for their construction. While these models offer fast predictions, collecting a sufficiently large dataset to achieve the desired accuracy can be impractical when applied to high-fidelity simulations, especially when considering many design parameters. Hence, the main objective of this dissertation is to improve current ROM methods by requiring less high-fidelity data while maintaining adequate accuracy. Specifically, we consider a multi-fidelity approach that enhances a few high-fidelity solutions with results from an inexpensive low-fidelity simulation. While various multi-fidelity solutions exist for conventional surrogate models, few are available for reduced-order modeling. A major factor behind the scarcity of multi-fidelity ROMs is that simulations of different fidelity generally produce fields with disparate representations. As a result, this work focuses on this issue and investigate methods to allow the fusion of inconsistent fields. This dissertation contributes to the field of reduced-order modeling by proposing a multi-fidelity method that employs manifold alignment to find a common low-dimensional representation of two datasets with heterogeneous fields. Once aligned, a single prediction model combines the multi-fidelity datasets with an approach inspired by existing fusion-based multi-fidelity techniques. Therefore, the developed method can combine fields from various models irrespective of their representations. The produced ROM then potentially has better performance than a single-fidelity model trained with the same computational budget. The viability of the proposed method is validated using two practical problems, i.e., the aerodynamic analysis of a transonic airfoil and a transonic wing. Multiple multi-fidelity scenarios are considered with different fidelity combinations, various model configurations, and inconsistent fields. In many cases, the developed method can effectively provide improved predictions compared to an equivalent single-fidelity approach despite fusing results with inconsistent representations. At worst, when the proposed method is applied to datasets with a large fidelity difference, the accuracy of the resulting ROM tends to that of a single-fidelity model. Also, the results show that the developed method behaves similarly to existing multi-fidelity ROM methods when joining high- and low-fidelity fields with a consistent representation.
A Framework for Fan Stage Conceptual Design Under Distortion Induced by Boundary Layer Ingestion

(Georgia Institute of Technology, 2020-12-04) Pokhrel, Manish

Various tightly integrated aircraft concepts have emerged as a result of aggressive performance goals set forth by various organizations. Most integrated aircraft system configurations exploit the concept of Boundary Layer Ingestion (BLI). While the potential benefits of BLI are huge, several significant challenges - both on the modeling and design fronts - appear due to BLI. This dissertation focuses on addressing the impacts of BLI induced circumferential flow distortion on the conceptual design of a fan stage. Distortion introduces extra losses in both rotors and stators in addition to increased unsteady rotor response. In presence of incidence swings, conventional conceptual design tools are inadequate to design optimal rotor blades and generate non-axisymmetric stators, a concept that has shown promise in alleviating stage losses due to distortion. Besides, concerns of structural integrity also arise for rotor blades due to the unsteady loading they experience when rotating in a distorted flow field. Parametric effects of these phenomena with varying levels of distortion are quantified, and a significant portion of the fan stage losses are shown to be recoverable using the aero-structural design framework introduced and developed in this dissertation. The aerodynamic design framework is developed through several extensions to the conventionally used multi-meanline method. The inclusion of additional features accounts for flow asymmetry, parametric blade angle optimization, rotor unsteady performance, and non-axisymmetric stator design. The model is verified, and experiments are performed to evaluate the effectiveness of each modeling element. Similarly, the Variational Asymptotic Method (VAM) is proposed as a computationally efficient technique to perform transient structural analysis of rotor blades. VAM is validated for a variety of loading scenarios and is leveraged to demonstrate the nature of vibratory stresses and highlight the concerns of resonance on a test case. The framework encapsulating both aerodynamic design and structural analysis is finally utilized to explore the design space to minimize vibratory stresses on the blades with a small trade-off in the stage efficiency. The fan stage design resulting from the framework proposed and formulated in this dissertation aims to serve as a starting point for the preliminary design of a distortion-tolerant fan.
Shear layer dynamics of a reacting jet in a vitiated crossflow

(Georgia Institute of Technology, 2020-12-01) Nair, Vedanth

The jet in crossflow (JICF) is a canonical shear flow that is present in a number of practical configurations including industrial gas turbines. Its complex flow topology, heavily influenced by underlying hydrodynamic instabilities, makes it an attractive configuration to implement when the mixing performance is critical. Past studies analyzing the behavior of non-reacting jets have noted that the overall performance of JICF configurations can be tied to the behavior of the shear layer, which influences both near-field and far-field jet dynamics. As a result, techniques used to manipulate jet mixing and penetration, such as active jet modulation, require an understanding of the dominant instability characteristics of the shear layer. Although this configuration finds extensive use in reacting applications, the hydrodynamics of reacting flows are often fundamentally different from non-reacting flows, and few studies have analyzed the influence of heat release and reactions on JICF dynamics. In addition to varying the momentum flux ratio (J) and the density ratio (S) this study presents a novel method of systematically moving the flame position with respect to the shear layer to gauge its impact on shear layer stability. High speed optical diagnostics including Stereoscopic PIV, OH-PLIF and OH* chemiluminescence were used to quantify the flowfield and infer the behavior of the reaction zone. Moving the flame inside the shear layer was observed to significantly change the jet topology as the shear layer vortices (SLV) were completely suppressed. This was further quantified through a growth rate defined based on tracking the swirling strength of SLV structures. Other structural characteristics including the location of mixing transition were shown to be highly correlated with this extracted growth rate. Time-resolved velocity data was further used to quantify the shear layer spectrum by extracting the dominant instability frequencies and classify the instability behavior as convectively and globally unstable. In order to explain the observed instability behavior, the counter current shear layer (CCSL) model was used to extract an analogous stratification parameter (S’), which along with the counter current velocity (Λ) ratio was shown to capture the stability behavior of both non-reacting as well as reacting configurations.
Development of a Framework for the Analysis and Assessment of Daily Airport Operations

(Georgia Institute of Technology, 2020-12-01) Mangortey, Eugene

Tremendous progress has been made over the last two decades towards modernizing the National Airspace System (NAS) by way of technological advancements, and the introduction of procedures and policies that have maintained the safety of the United States airspace. However, as with any other system, there is a need to continuously address evolving challenges pertaining to the sustainment and resiliency of the NAS. One of these challenges involves efficiently analyzing and assessing daily airport operations for the identification of trends and patterns to inform better decision making so as to improve the efficiency and safety of airport operations. Efforts have been undertaken by stakeholders in the aviation industry to categorize airports as a means to facilitate the analysis of their operations. However, a comprehensive, repeatable, and robust approach for this very purpose is lacking. In addition, these efforts have not provided a means for stakeholders to assess the impacts and effectiveness of traffic management decisions and procedures on daily airport operations. Furthermore, an efficient and secure framework for extracting, processing, and storing the data needed for the analysis and assessment of daily airport operations is needed, as the current process employed by FAA analysts is manual, time-consuming, and prone to human error. Consequently, this dissertation addresses these gaps through a set of methodologies that 1) leverage unsupervised Machine Learning algorithms to categorize daily airport operations, 2) leverage a supervised Machine Learning algorithm to determine the category that subsequent daily airport operations belong to, 3) facilitate the comparison of similar and different daily airport operations for the identification of trends and patterns, 4) enable stakeholders to analyze and assess the impacts and effectiveness of traffic management decisions and procedures on daily airport operations, and 5) develop a framework to facilitate the efficient and secure extraction, processing and storage of data needed for the analysis and assessment of daily airport operations. The developed framework automates the flow of data from extraction through storage, and enables users to track the flow of data in real time. It also facilitates data provenance by logging the history of all processes and is equipped with the capability to log errors and their causes, and to notify analysts via email whenever they occur. In addition, it has the capacity to automatically extract, process, and store the data needed for the analysis and assessment of the daily operations of all airports in the NAS. Indeed, this framework will be one of the first of its kind to be deployed into the FAA's Enterprise Information Management platform and will serve as a template for leveraging cloud-based services and technologies to improve operations in the NAS. Finally, this framework will enable FAA analysts to analyze and assess daily airport operations in an efficient manner to facilitate the identification of trends and patterns for better decision making, which will lead to improved airport operational performance.
A Refined Potential Theory for the Incompressible Unsteady Subcritical-Reynolds number Flows on Canonical Bluff Bodies

(Georgia Institute of Technology, 2020-11-19) Amoloye, Taofiq Omoniyi

The three main approaches to exploring fluid dynamics are actual experiments, numerical simulations, and theoretical solutions. In classical potential theory, the steady inviscid incompressible flow over a body can be obtained by the superposition of elementary flows with known analytical solutions. Analytical solutions can offer huge advantages over numerical and experimental solutions in the understanding of fluid flows and design. These advantages are in terms of cost and time consumption. However, the classical potential theory falls short of reconciling the actions of viscosity in an experimentally observed flow with the theoretical analysis of such a flow. As such, it is unable to resolve the boundary layer and predict the especially important flow separation phenomenon that results in the pressure drag experienced by a body in the flow. This has relegated potential theory to idealized flows of little practical importance. Therefore, an attempt is made in this thesis to refine the classical potential theory of the flow over a circular cylinder to bridge the gap between the theory and experimentally observed flows. This is to enhance the ability to predict and/or control the flows' aerodynamic quantities and the evolution of the wake for design purposes. The refinement is achieved by introducing a viscous sink-source-vortex sheet on the surface of the cylinder to model the boundary layer. These vortices, sources and sinks introduced at the cylinder surface are modeled as concentric at every location. The vortices are modeled as Burgers' vortices, and analytic expressions for their strengths and those of the sinks/sources are obtained from the classical theory. These are employed to obtain a viscous and time-dependent stream function that captures critical qualitative features of the flow including flow separation, reattachment, wake formation, and vortex shedding. After that, a viscous potential function, the Kwasu function, with which the pressure field is obtained from the Navier-Stokes equation, is derived from the stream function. It is obtained by defining the viscous stream function on a principal axis of the flow about which the vorticity vector is identically zero. Strategies have also been developed to account for the finite extent of the cylinder and dynamic unsteadiness of the flow, and to predict the points of separation/reattachment/transition and the boundary layer thickness. Additionally, the strategies are used to obtain forces and apply the solution to arbitrary geometries focusing on spheres and spheroids. These strategies include the gravity analogy that considers a fluid element-cylinder scenario to be like a two-body problem in orbital mechanics. This analogy introduces the perifocal frame of fluid motion and exploits it to resolve the d'Alembert's Paradox. The perifocal frame is also used to predict flow separation/reattachment/transition and explain the observation of sign changes in the shear stress distribution at the rear of a circular cylinder in a crossflow. The refined potential theory is verified against experimental and numerical data on the cylinder in an incompressible crossflow at freestream Re∞=3,900. Its drag prediction is within the error bound of measured data and tHRLES (transitional Hybrid Reynolds-averaged Navier-Stokes Large Eddy Simulation) prediction. The predictions of the pressure distribution, separation point and Strouhal number are also within acceptable ranges. Its prediction of the force coefficients over the range 25≤Re∞<300,000 is validated against experimental and theoretical data on the cylinder in crossflow. There is a good agreement in the magnitude and trend for Re∞>100. For Re∞<100, there is a disparity in magnitude that is unsafe for design purposes. Similarly, it under-predicts the coefficient of drag in some of the explored axial flow configurations. However, at Re∞=96,000 and an aspect ratio of 2, the RPT drag prediction falls within 1.2% of validated computational result. The energy spectra of the wake velocity display the Kolmogorov's Five-Thirds law of homogeneous isotropic turbulence. This verifies and validates the unsteadiness in refined potential theory as turbulent in nature. The drag coefficient of a sphere for 25≤Re∞< 300,000 is explored to demonstrate the application of refined potential theory. Additionally, the flow over a sphere at Re∞=100,000 is explored in detail. A generally good agreement is observed in the prediction of the experimental trend for Re∞≥2,000. The transitional incompressible flows over a 6:1 prolate spheroid at an angle of attack β=45° for Re∞=3,000$ and Re∞=4,000 are also explored. The present theoretical pressure distribution has a close agreement with the DNS (direct numerical simulation) result in the starboard rear of the spheroid. However, the magnitude of the predicted force coefficients are generally less than five times the corresponding DNS results. The asymmetry of the DNS pressure distribution in the meridian plane is not captured. Therefore, further analyses of the spheroid flow including the separation locations are recommended for further studies. It is concluded that the refined potential theory can be used to resolve, explore and/or control the aerodynamic quantities of the flows around canonical bluff bodies as well as the evolution of their wakes.
Methods for Construction of Surrogates For Computationally Expensive High-Dimensional Problems

(Georgia Institute of Technology, 2020-11-19) Rajaram, Dushhyanth

Maturation of computational models has increased reliance on numerical simulations for the analysis, and more importantly, design of complex engineered systems. The high accuracy and realism offered by simulation-based analysis often comes at a high computational cost especially in the many-query context, as such limiting its applicability in exploratory design studies. In the absence of inexpensive models that exploit physics-based simplifying assumptions, practitioners often resort to computationally cheap surrogate-based methods. However, several challenges arise when constructing surrogates for high-dimensional field outputs. Identifying and tackling these issues is the primary goal of this dissertation. The challenges posed by the following three key issues are investigated: 1) the need to handle large datasets under constrained computational resources, 2) the presence of a large number of inputs, 3) the need for accurate models under scarcity of data from expensive simulations with many inputs. Pursuit of the first issue investigates the viability of randomization as a means to perform computationally efficient data compression while retaining sufficient accuracy to construct surrogate models for large field responses. Accommodation of a large number of inputs is tackled through the formulation of a manifold optimization-based Gaussian Process (MO-GP) regression model that simultaneously finds a low-dimensional input subspace and trains a model in it using input-output pairs exclusively. To emulate field outputs using the Proper Orthogonal Decomposition (POD) and interpolation for analyses with a large number of inputs, the MO-GP model is leveraged to learn a map from the inputs to each POD coordinate. Finally, the use of a multifidelity extension to the MO-GP model in conjunction with a recently proposed manifold alignment-based model is proposed as a solution to improve predictive accuracy with insufficient high-fidelity data. Findings show that: 1) randomization enables efficient construction of competitive predictive models under constrained computational resources, 2) the MO-GP model is effective in finding a low-dimensional input subspace for each POD coordinate and results in a good predictive model, and 3) an initial feasibility assessment of the multifidelity model on an airfoil flow emulation problem shows promise but warrants further investigation.
Development and Evaluation of Terahertz Time-Domain Spectroscopy for Electric Propulsion Plasma Diagnostics

(Georgia Institute of Technology, 2020-11-19) Brown, Nathan P.

Terahertz time-domain spectroscopy (THz-TDS) is a novel plasma diagnostic that has the potential to fill present gaps in electric propulsion (EP) plasma diagnostic capabilities. However, there remain unanswered questions and challenges regarding THz-TDS capability and data interpretation that must be addressed before the diagnostic is readily applied to EP devices. The purpose of this dissertation is to develop and evaluate THz-TDS for EP plasma diagnostics. To that end, this dissertation provides three major contributions: 1) Analysis of the THz-TDS domain of applicability; 2) Development of a novel Bayesian THz-TDS plasma diagnostic analysis framework and subsequent evaluation of THz-TDS uncertainty; and 3) Development and application of THz-TDS to noninvasively probe plasma bounded and optically shielded by Hall thruster wall material.
A Methodology for Capturing the Aero-Propulsive Coupling Characteristics of Boundary Layer Ingesting Aircraft in Conceptual Design

(Georgia Institute of Technology, 2020-11-11) Ahuja, Jai

Economic and environmental benefits of fuel efficient aircraft have driven research towards unconventional configurations and technologies. Boundary Layer Ingesting (BLI) concepts appear to be a promising solution, relying on a synergistic interaction between the airframe and propulsor for improved fuel efficiency. Maximizing benefits of BLI while minimizing the risks not only involves careful design of the propulsor, but also the airframe given that the embedded propulsor performance is dependent on the ingested boundary layer flow, which in turn is affected by the airframe. The highly coupled nature of the propulsion system with the airframe for BLI concepts requires a Multidisciplinary Design Analysis and Optimization (MDAO) approach. Majority of the modeling approaches in literature, however, have treated the BLI problem in a decoupled fashion, especially at the vehicle sizing stage. On the other hand, coupled aero-propulsive methodologies proposed are better suited for point design refinement at the preliminary design stage. Decoupled methods fail to capture aero-propulsive interactions. The impacts of BLI may be overestimated or underestimated, and thus, there is a risk that the sized vehicle will not be satisfactory or even feasible. Quantifying the consequences of ignoring BLI aero-propulsive coupling at the aircraft sizing stage is the primary motivation of this research effort. To address this aspect, a parametric and coupled aero-propulsive design and analysis methodology that is appropriate for conceptual design BLI vehicle sizing and corresponding trade studies is necessary. A MDAO methodology for BLI aircraft in conceptual design is proposed, allowing for design space exploration and simultaneous optimization of the airframe and propulsor cycle. BLI effects on vehicle performance are identified using the Power Balance formulation. Studies are devised to identify the critical airframe and propulsor design space influencing these BLI effects. Through physics based reasoning, these studies provide rule of thumb guidelines for concept designers to focus on certain design parameters over others. High fidelity aerodynamic analysis, through CFD, is used strategically for constructing parametric semi-empirical models of the BLI effects, which are then integrated with a cycle analysis code, an aircraft sizing and mission analysis tool, and other analysis modules in a MDAO environment. A fine balance is thus achieved between high fidelity requirements for modeling complex physics and the need for expedited MDAO in conceptual design. The proposed method is applied to the design and analysis of two tube and wing BLI configurations with different engine locations, similar to the D8 and NOVA-BLI concepts. These vehicles are also designed using a decoupled approach that is reflective of similar methods in literature. A design space exploration involving engine cycle and airframe design parameters is conducted, using the decoupled and coupled approaches, followed by optimization to find the best designs within the specified constraints. The studies show noteworthy differences in performance and design trends between the two BLI modeling approaches. Additionally, the wing influence on the ingested airflow is observed to affect the BLI aero-propulsive coupling strength. The top-mounted engine configuration like the D8 exhibits stronger coupling compared to the side-mounted engine variant like the NOVA-BLI. In general, the results support use of coupled and parametric methodologies for BLI concept design.
Evaluating the Effects of Model Simplifications on the Transference of Policies Learned in Simulation

(Georgia Institute of Technology, 2020-10-08) Meyer, Patrick S.

Both the military and civil worlds are being transformed by the development and deployment of unmanned systems to a wider range of scenarios. As the field of unmanned systems has grown and matured, it has continuously advanced towards increasing levels of autonomy. As an example, the cars of today have gone from "maintain this speed" to "drive on this highway." As this push towards greater levels of autonomy continues, new methods for developing policies for control of these systems are required. Recent breakthroughs in reinforcement learning hope to address this problem. The primary advantage of reinforcement learning based systems is their focus on goal driven behavior. In developing reinforcement learning based policies, there is a need for significant exploration of a system’s possible state-action space. As such, modeling and simulation has been an indispensable tool. However, transferring policies from a simulated world to the real world presents its own challenges. This work develops a method for evaluating the relative importance of different possible simplifications that can be taken during the modeling process. This relies on a sampling-based method to explore the possible simplification space of a given referent model. Experiments show that this method compares favorably to a number of baseline model development strategies and can lead to significantly simplified system models that maintain similar transference properties. Additional experiments are presented that evaluate different choices within this sampling-based strategy and the effects of imperfect referent models on the resulting evaluations.
Entrainment, Mixing, and Ignition in Single and Multiple Jets in a Supersonic Crossflow

(Georgia Institute of Technology, 2020-08-19) Fries, Dan

Jets in crossflow are a canonical example for three-dimensional turbulent mixing. Here, non-reacting and reacting sonic jets in a supersonic crossflow are studied. The influence of injectant properties on turbulent mixing is investigated. Using pure gases, the molecular weight and specific heat ratio is varied between 4-44 g/mol and 1.24-1.66, respectively. The jets are injected into a Mach 1.71 crossflow with a stagnation temperature ~600 K. Two single jet injectors and two staged jet injectors are designed to characterize potential enhancements in turbulent mixing and combustion processes. Mixture fraction and velocity fields are determined via Mie-scattering off solid particles. Velocity vectors are obtained by processing Mie-scattering image pairs with a correlation technique (particle image velocimetry). To ignite the flow field and enable systematic variation of the ignition location a traversable laser spark system is employed. The reacting flow is probed via CH* chemiluminescence and OH planar laser induced fluorescence visualizing regions containing hot combustion products. A new trajectory scaling improves correlation between all data sets considered, suggesting that the bow shock, boundary layer and momentum flux ratio are the dominant controlling factors. Turbulent mixing rates are highest for injectants with higher molecular weight and lower specific heat ratio. The larger of two jet spacings tested yields the greater enhancement of turbulent mixing rates. Ignition locations on the symmetry plane of the flow field are evaluated for their ability to sustain chemical reactions/heat release. Most favorable ignition locations lie in the windward jet shear layer away from the regions of highest flow strain. The smallest diameter single jet with presumably more boundary layer interaction and moderate strain rates provides the best results with regard to thermal energy release after spark deposition. Trends suggest that moderate compressible strain rates and no flow expansion are advantageous to sustain thermal energy release. Implications for future research directions and opportunities are discussed.