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Daniel Guggenheim School of Aerospace Engineering

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https://hdl.handle.net/1853/70742

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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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https://finding-aids.library.gatech.edu/agents/corporate_entities/106

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Publication Search Results

Now showing 1 - 10 of 333

Evaluation of Convolutional Neural Networks for Modeling Blast Propagation in Multi-room Bunkers

(Georgia Institute of Technology, 2023-12-15) Luo, Felix

The rapid evaluation of blasts in enclosed geometrically complex spaces has long eluded the design of safer blast-resistant structures. Traditional methods of determining blast responses in enclosed geometrically complex spaces oftentimes rely on the use of traditional computational fluid dynamics (CFD) solvers to compute the entire flow field of the structure. This method has an enormous computational burden, especially considering that blasts are highly transient in nature and require the transient pressure fluctuations to be determined to formulate an accurate blast response prediction. However, more efficient methods of blast evaluation are desired such that parametric sweeps or optimization processes can be performed at low cost to provide a tool for iterative design. To rectify this gap in capabilities, a convolutional neural network based (CNN) model was developed to provide rapid blast predictions for 2D structures to establish this capability to aid in the design of more blast resistant structures. This approach leverages the inherent spatial awareness of CNNs to provide predictions for peak pressures since blasts in enclosed spaces are highly dependent on the spatial relationships between blast locations and wall location. This approach provides a nearly 5,000 times speed up against CFD simulations used within this study with good convergence of errors, correlation coefficients, predicted and truth values and distributions in all situational evaluations. These computational advantages, in part, comes from using the CNN based model to directly predict peak pressures whereas traditional CFD solvers require iterations to propagate fluid flows over time. However, some limitations do exist with respect to higher errors, such as model training costs, and the capability to predict 3D structures. Nonetheless, the results provide a characterization of the capabilities CNN based models in predicting peak pressures from blasts in enclosed spaces. From these evaluations and studies, a model which can provide significant computational savings while maintaining a similar accuracy can be obtained, which enables the rapid iterative design of more blast resistant structures.
A Sliding-Window Matrix Pencil Method for Aeroelastic Design Optimization with Limit-Cycle Oscillation Constraints

(Georgia Institute of Technology, 2023-12-15) Golla, Tarun

This paper presents a new approach for constraining limit-cycle oscillations in aeroelastic design optimization. The approach builds on a gradient-oriented limit-cycle oscillation constraint that bounds the recovery rate to equilibrium, bypassing the need for bifurcation diagrams. Previous work demonstrated the constraint using recovery rates approximated via a conservative approach. This work introduces a new approach to accurately evaluate recovery rates from transient simulations. The approach uses the matrix pencil method within a time window that slides along the time history for the quantity of interest, allowing this damping identification method to resolve amplitude-variant nonlinear effects. The new sliding-window matrix pencil method is verified with reference recovery rates from envelope finite differencing of the dynamic responses induced with a large initial perturbation of a typical aeroelastic section. Sensitivity analyses identify optimal parameters to obtain accurate recovery rates while minimizing computational costs. The new developments are then demonstrated by optimizing the typical section subject to the proposed limit-cycle oscillation constraint along with flutter and side constraints. The results are compared with previous work that solved the same optimization problem by evaluating the limit-cycle oscillation constraint using approximate recovery rates. The limit-cycle oscillation constraint based on the new sliding-window matrix pencil method allows the optimizer to achieve a less conservative design solution while satisfying the constraints. This methodology was additionally extended through the optimization of a more complex 3-variable optimization. The implementation was further ported into a modular framework within which results were verified, allowing for future extensions to this methodology. This work is anticipated to pave the way for larger-scale aeroelastic design optimizations subject to limit-cycle oscillation constraints.
A Sliding-Window Matrix Pencil Method for Aeroelastic Design Optimization with Limit-Cycle Oscillation Constraints

(Georgia Institute of Technology, 2023-12-13) Golla, Tarun

This thesis presents a new approach to constraining limit-cycle oscillations (LCOs) in aeroelastic design optimization. LCOs are self-excited oscillations that can develop in nonlinear aeroelastic systems experiencing flutter, and they must be avoided during operation to keep safety and performance. One approach to addressing this problem is to design the system using an optimization process that includes an LCO constraint. Previous efforts have proposed various LCO constraints for aeroelastic design optimization but have not addressed realistic design applications. This gap persists because existing LCO constraints are not oriented toward scalable gradient-based optimization algorithms. The proposed approach builds on a recent LCO constraint that bounds the recovery rate to equilibrium and is suited to gradient-based optimization. The new contribution from this thesis consists of introducing a new matrix pencil method for accurately evaluating the recovery rate within the LCO constraint using output data from transient responses. The amplitude-varying behavior of the recovery rate in the presence of dynamic nonlinearities is captured using a sliding time window along the transient response for a chosen quantity of interest. This new approach differs from the conventional matrix pencil method, which considers an entire transient response at once under linearized assumptions. Sensitivity studies are conducted to identify the optimal singular-value decomposition tolerance, sliding window size, stride size, output data sampling step, and aggregation parameters for obtaining accurate results. The new sliding-window matrix pencil method is then used to optimize a typical aeroelastic section model with a subcritical LCO behavior, enforcing no flutter or LCOs at chosen operation conditions. Optimization results are compared with previous work that used the same LCO constraint formulation combined with an approximate, conservative method to evaluate the recovery rate. The LCO constraint evaluated using the new sliding-window matrix pencil method allows the optimizer to completely suppress subcritical LCOs within the specified operating conditions while minimizing design changes, achieving a less conservative optimized solution. This work is a step toward constraining LCOs in large-scale aeroelastic design optimization to enable higher-performance designs while avoiding undesirable dynamics, such as subcritical LCOs. Future work includes formulating adjoint derivatives of the LCO constraint and demonstrating the methodology for aeroelastic models of increasing physical and computational complexity.
Development of empirical models for the analysis of multirotor aerodynamic interactions

(Georgia Institute of Technology, 2023-12-10) Marangoni, Gioele

In the 21st century, the concept of Advanced Air Mobility (AAM) has emerged as a highly promising transportation solution for urban and regional areas, attracting considerable interest from both private companies and government agencies. In this dynamic and innovative environment, a multitude of new aerial vehicle designs is emerging. During the initial conceptual phase of designing a new vehicle, empirical methods based on institutional knowledge are typically employed, while Computational Fluid Dynamics (CFD) methods are reserved for later stages of the design process. This is because CFD tools require more detailed design information that is not available during the conceptual phase such as accurate Computer-Aided Design (CAD) models and properties of materials, which are typically obtained as the design progresses and becomes more refined. However, the novelty of these multirotor configurations poses unprecedented challenges due to the limited research, experimentation, and available data on the aerodynamic interactions among the rotors and the impact of various design choices on performance. In this context, traditional empirical methods do not prove effective as they fail to account for design choices unique to these new multirotor configurations and the aerodynamic interactions between the rotors. This can lead to costly redesigns and schedule delays. This effort proposed to conduct a parametric study of various eVTOL configurations, observe general trends and derive empirical-based models that can guide engineers in making informed configuration choices during the conceptual phase of a new vehicle design. To traverse a vast configuration design space quickly, the mid-fidelity analysis tool Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM) has been adopted. CHARM, which is based on lifting line and distorting wake methods, has demonstrated its capability in accurately predicting vehicle performance while maintaining cost-effectiveness in terms of setup and execution time. This approach is correlated with theory and experiment to build confidence in the analysis and conclusions.
Effects of Aero-Propulsive Interactions for Various Wing Integration Techniques on Electric Ducted Fan Performance

(Georgia Institute of Technology, 2023-12-10) Safieh Matheu, Derek Anthony

This study explores the aero-propulsive coupling effects of wing blended electric ducted fans (EDF) lifting systems over the EDF unit. Wing blended EDFs and isolated EDF are on the rise as a solution to increase efficiency on regional mobility platforms. Electrification of platforms has permitted the introduction of novel integration concepts that use phenomena like BLI to enhance their performance. The lack of complex mechanical links permits designers to place propulsive devices practically anywhere on the aircraft, opening opportunities for research and development. As noted in the literature review section, little attention has been given to understanding the effects of novel integrations on the EDF. This experimental study aims to examine two edge cases: the leading edge integration and the trailing edge integration. The leading edge integration studied in this work is characterized by having the leading edge of the inlet of the EDF and the leading edge of the wing flushed. The trailing edge features the EDF mounted with the exhaust of the duct flushed with the wing’s trailing edge; the angle between the freestream and the EDF is parallel. The duct is translated vertically so that the inlet of the trailing edge EDF is tangent with the wing’s surface. Note that this is not an optimization study; simplified integrations that represent the generalized qualities of each integration were adopted. What is novel about the research is that the EDF forces are decoupled from the system loads, providing unprecedented insight into each integration’s effects on the EDF itself. The study was formed by three major test rigs described in the methodology section. The first rig was designed to test EDFs in isolation at various angles of attack. In this test, various sizes of EDFs were tested with a common duct geometry; the sizes ranged from 51 cm2 fan-swept area to 215 cm2 fan-swept area. The EDFs were tested between the cruise condition, edgewise flight, and descent stages; performance data and 6 forces and moments are explored in the results section. The second rig focused on studying the integration of the EDF in both cases, but by introducing a symmetric airfoil design, the upper surface and lower surface integration was studied. This rig permitted to study such configuration in the low-turbulence tunnel at lower airspeeds and mostly the cruise condition. For these tests, a Clark-Y duct shape coupled with Schuebeler Technologies DS51-HST formed the EDF system. These tests provided insight into all 4 possible integration edge cases and presented interesting findings on pitching moment, thrust output, and performance effects that the integration had on the EDF. The last test rig focused on studying the EDF integration in a more realistic platform (slimmer airfoil) and studying the transition cases, cruise flight, wing stall scenario, and high angles of attack. This test rig was placed in the Low Turbulence Wind Tunnel and the Harper Wind Tunnel. The tests in the low turbulence tunnel focused on edgewise flight, early transition, and the descent cases, studying airspeeds between 2 m/s and 10 m/s. The tests on the Harper Wind Tunnel study the integration in cruise and wing stall conditions at airspeeds between 10 m/s and 20 m/s. In that test, the performance, thrust output, and normal force generated by the duct are investigated.
An Inertial and Aerodynamic Approach to Active Flutter Suppression Control Law Design and Wind Tunnel Evaluation

(Georgia Institute of Technology, 2023-12-07) Szymanski, Jacob

This thesis examines multiple continuous time adaptive control methodologies for use in Active Flutter Suppression (AFS). Typical AFS control methodologies rely on feedback in the form of inertial and elastic data such as acceleration and strain. This approach has been shown to be effective, however potential improvements may be made with the inclusion of additional information in the form of surface pressure data. Aeroelasticity involves the interaction of aerodynamic, inertial, and elastic forces, thus the inclusion of surface pressure data completes this triangle of forces. There are two main parts of this thesis. The simulation portion examines the effectiveness of three adaptive control methodologies at mitigating flutter of a nonlinear aeroelastic simulation model. Due to the difficulty of simulating surface pressure fluctuations, the simulation models relied on the inertial data in the form of the pitch and plunge motions of the model for feedback. Analysis in both the time and frequency domains provided a complete spectral analysis of the closed loop behavior of the model which provided insights into the underlying mechanisms acting within the adaptive controllers. Key pieces of information were the energy transfer between modes of motion, frequency trends over time, and relative phase between deflections and control inputs. The most effective controller from the simulations was selected for implementation on an experimental aeroelastic test rig in the experimental portion of this thesis. The test rig was used to examine the effects of including the surface pressure data within a feedback control loop. Experimental testing was conducted on a cantilever wing model which was instrumented with an angular rate sensor, an accelerometer, and upper and lower surface pressure transducers. Trailing edge flaps on the wing were used as the control effectors. The open loop behavior was characterized, then control with angular rate feedback into an adaptive controller was evaluated. Multiple configurations of inertial and surface pressure feedback control were evaluated, with the final configuration achieving a 25% increase in flow velocity over the open loop case. Each control configuration was evaluated using spectral analysis to determine the modifications necessary to improve the control. Overall, it was shown that the inclusion of surface pressure data provided information which was not present in the inertial data which enabled more stable control of the test rig. Controller tuning via examining the spectral information within the signals was found to be a valid approach which did not rely on precise modelling of the entire test rig.
Internal Flow Dynamics in Liquid Swirl Injectors with Coaxial Gas Flow

(Georgia Institute of Technology, 2023-12-06) Trucchi, Matteo

Injectors are essential components in aerospace propulsion systems, serving a crucial role in achieving high-quality propellant atomization and mixing, as well as engine stability. They are integral components within a complex dynamic system and are responsible for coupling the feed system to the combustion chamber. Thus, a profound understanding of injector dynamics is imperative to attain a robust engine design. Since the early studies, the typical configurations of interest have involved closed-head injectors, where the liquid propellant swirls around a stationary gas core. Gas-liquid interactions were introduced with recessed coaxial swirl injectors and air-blast injectors with major emphasis on the atomization process. The classical theory on injector dynamics lacks the consideration for the effect of the shear stress at the liquid-wall and gas-liquid interfaces in the governing equations. Therefore, the damping effect on propagating waves is modelled exclusively through an artificial viscosity factor. This work conducts a theoretical and numerical investigation for an alternative configuration of open-end swirl injectors. The distinctive feature of this configuration is an open head and a high speed gas that flows coaxially with the swirling liquid towards the injector exit. Unlike a recessed coaxial injector, the gas immediately interacts with the tangentially injected liquid into the chamber where the gas is flowing. The comprehensive review of classical steady-state and transient theories on swirl injectors led to the identification and resolution of inconsistencies. The analytical inclusion of shear stress at the liquid-wall and gas-liquid interfaces produced a modified wave equation, and the new solution was employed to extend the classical theory to Open-Head-Open-End injectors. A parametric study for frequencies up to 2000 Hz involving gas flow velocity, injector pressure drop, and geometric parameters highlighted the significance of friction coefficients tuning for an accurate calculation of the injector transfer function. Computational Fluid Dynamics provided a qualitative description of the flow physics involved in the injector configuration of interest.
Experimental and Computational Analysis of Multi-Rotor Aerodynamic Interactions

(Georgia Institute of Technology, 2023-06-29) Wylie, Daley

This study aims to perform a comparative analysis of rotor–rotor aerodynamic interac- tions. This work details an investigation that was performed into the aerodynamic inter- actions between the rotors of multi-rotor vehicles in different configurations. The effects of these interactions on the thrust and torque of all individual rotors were quantified in wind tunnel tests. The effects of the changes in hub spacings, rotor rotational speeds, and freestream velocities were investigated for isolated, tandem, quad-rotor plus and X con- figurations. The maximum and minimum tip chord Reynolds numbers were 118,000 and 73,000, respectively. In addition to the experimental work conducted, the investigation was completed com- putationally as well. This served as a validation tool for the computational solver, a method of looking deeper into the conclusions drawn from the experimental investigation, and a way to investigate other phenomena not completed experimentally. Cartesian Grid Euler Solver (CGE), an advanced adaptive CFD solver that rapidly resolves three-dimensional configurations during design, was used. CGE uses state-of-the-art flux splitting routines, implicit time marching algorithms, higher order interpolation methods and multigrid-based acceleration schemes together with flow-based adaptive mesh routines. It has been vali- dated for complicated geometries. Experimental and computational results showed that the aft rotors experienced detri- mental aerodynamic interactions in all configurations. In all examined multi-rotor config- urations, an increase in the hub spacing caused a decrease in the thrust deficit between the aft rotor and the isolated rotor. However, the differences in the configurations also affected the measured loads. In the tandem configuration, the aft rotor experienced up to 24% re- duction in the thrust coefficient at a hub spacing of 2.1R when compared to the isolated rotor at the same rotor rotational speed and freestream velocity. The aft-most rotor in the plus configuration experienced as large as a 28% decrease in the thrust coefficient when compared to one of the aft rotors in the X configuration for the same hub spacing and flight conditions. Good correlation was found between these wind tunnel experiments and flight tests for the fore and side rotors in X and plus configurations (7.9–14.2% difference), but a larger difference of 30–41.9% was found for the aft rotors, which is due to the different rotor trim conditions. The flow solver was found to over-predict the thrust and under-predict the torque due to a thin airfoil assumption and the lack of implementation of a formal tip loss function. Nevertheless, the same trends were followed as the experimental results. The effects of the flight test vehicle fuselage were investigated computationally. It was found that the aft rotors in both the plus and X configurations experienced a decrease in per- formance when the fuselage was added to the computational model, with thrust decreases of 4.4% and 7%, respectively. The results also show that there was a 37% difference be- tween the flight tests and computational data when using the same trim conditions. This indicates that the cause of the difference in wind tunnel experiments and flight tests remains unknown, and should be further investigated. Finally, the effects of the wind tunnel facility were investigated. The same conditions were modeled with and without the presence of wind tunnel walls numerically, and it was found that the presence of the wind tunnel surface mesh caused the actuator disks to be less refined, as an artifact of the automatic mesh refinement in CGE associated with the relationship it defines between the internal and external mesh. These challenges made it difficult to compare the computational results with and without the wind tunnel test sec- tion. It was shown that the presence of the side walls caused a drop in performance of the side rotors. However, given the aforementioned meshing complications, this finding needs further investigation, numerically and experimentally.
Differentiable and tolerant barrier states for improved exploration of safety-embedded differential dynamic programming with chance constraints

(Georgia Institute of Technology, 2023-05-10) Kuperman, Joshua Ethan

A great challenge exists at the intersection of perception and controls – integrating the uncertainty present in perception-based state and obstacle estimation into safe control and trajectory optimization. First, we present the tolerant discrete barrier state (T-DBaS), a novel safety-embedding technique for trajectory optimization with enhanced exploratory capabilities. This approach generalizes the standard discrete barrier state (DBaS) method by accommodating temporary constraint violation during the optimization process while still approximating its safety guarantees. Towards applying T-DBaS to safety-critical au- tonomous robotics, we combine it with Differential Dynamic Programming (DDP), leading to the proposed safe trajectory optimization method T-DBaS-DDP, which inherits the con- vergence and scalability properties of the solver. Despite this, the tolerant barrier function parameters require tuning to reach peak performance for a wide array of constraints. To alleviate this requirement, we tune the T-DBaS parameters with the parameterized trajec- tory optimizer Pontryagin Differentiable Programming (PDP), proposing T-DBaS-PDP, an interpretable and generalizable solver for a variety of optimal control problems. In order to integrate perception uncertainty into safe optimal control, we learn the safety of the sys- tem via gaussian processes to create an interpretable, data-driven, and safety-guaranteeable framework. We implement this framework on differential drive and quadrotor dynamics and show its improvement over hand-tuned T-DBaS-DDP.
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)