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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

Now showing 1 - 10 of 37

Fourier-based design of acoustic transducers

(Georgia Institute of Technology, 2015-12-16) Carrara, Matteo

The work presented in this thesis investigates novel transducer implementations that take advantage of directional sensing and generation of acoustic waves. These transducers are conceived by exploiting a Fourier-based design methodology. The proposed devices find application in the broad field of Structural Health Monitoring (SHM), which is a very active research area devoted to the assessment of the structural integrity of critical components in aerospace, civil and mechanical systems. Among SHM schemes, Guided Waves (GWs) testing has emerged as a prominent option for inspection of plate-like structures using permanently attached piezoelectric transducers. GWs-based methods rely on the generation and sensing of elastic waves to evaluate structural integrity. They offer an effective method to estimate location, severity and type of damage. It is widely acknowledged among the GWs-SHM community that effective monitoring of structural health is facilitated by sensors and actuators designed with ad hoc engineered capabilities. The objective of this research is to design innovative piezoelectric transducers by specifying their electrode patterns in the Fourier domain. Taking advantage of the Fourier framework, transducer design procedures are outlined and tailored to relevant SHM applications, such as (i) directional actuation and sensing of GWs, (ii) simultaneous sensing of multiple strain components with a single device, and (iii) estimation of the location of impact sites on structural components. The proposed devices enable significant reductions in cost, hardware, and power requirements for advanced SHM schemes when compared to current technologies.
A quantitative real options method for aviation technology decision-making in the presence of uncertainty

(Georgia Institute of Technology, 2015-11-17) Justin, Cedric Y.

The developments of new technologies for commercial aviation involve significant risk for technologists as these programs are often driven by fixed assumptions regarding future airline needs, while being subject to many uncertainties at the technical and market levels. To prioritize these developments, technologists must assess their economic viability even though standard methods used for capital budgeting are not well suited to handle the overwhelming uncertainty surrounding such developments. This research proposes a framework featuring real options to overcome this challenge. It is motivated by three observations: disregarding the value of managerial flexibility undervalues long-term research and development (R&D) programs; windows of opportunities emerge and disappear and manufacturers can derive significant value by exploiting their upside potential; integrating competitive aspects early in the design ensures that development programs are robust with respect to moves by the competition. Real options analyses have been proposed to address some of these points but the adoption has been slow, hindered by constraining frameworks. A panel of academics and practitioners has identified a set of requirements, known as the Georgetown Challenge, that real options analyses must meet to get more traction amongst practitioners in the industry. In a bid to meet some of these requirements, this research proposes a novel methodology, cross-fertilizing techniques from financial engineering, actuarial sciences, and statistics to evaluate and study the timing of technology developments under uncertainty. It aims at substantiating decision making for R&D while having a wider domain of application and an improved ability to handle a complex reality compared to more traditional approaches. The method named FLexible AViation Investment Analysis (FLAVIA) uses first Monte Carlo techniques to simulate the evolution of uncertainties driving the value of technology developments. A non-parametric Esscher transform is then applied to perform a change of probability measure to express these evolutions under the equivalent martingale measure. A bootstrap technique is suggested next to construct new non-weighted evolutions of the technology development value under the new measure. A regression-based technique is finally used to analyze the technology development program and to discover trigger boundaries which help define when the technology development program should be launched. Verification of the method is performed on several canonical examples and indicates good accuracy and competitive execution time. It is applied next to the analysis of a performance improvement package (PIP) development using the Integrated Cost And Revenue Estimation method (i-CARE) developed as part of this research. The PIP can be retrofitted to currently operating turbofan engines in order to mitigate the impact of the aging process on their operating costs. The PIP is subject to market uncertainties, such as the evolution of jet-fuel prices and the possible taxation of carbon emissions. The profitability of the PIP development is investigated and the value of managerial flexibility and timing flexibility are highlighted.The developments of new technologies for commercial aviation involve significant risk for technologists as these programs are often driven by fixed assumptions regarding future airline needs, while being subject to many uncertainties at the technical and market levels. To prioritize these developments, technologists must assess their economic viability even though standard methods used for capital budgeting are not well suited to handle the overwhelming uncertainty surrounding such developments. This research proposes a framework featuring real options to overcome this challenge. It is motivated by three observations: disregarding the value of managerial flexibility undervalues long-term research and development (R&D) programs; windows of opportunities emerge and disappear and manufacturers can derive significant value by exploiting their upside potential; integrating competitive aspects early in the design ensures that development programs are robust with respect to moves by the competition. Real options analyses have been proposed to address some of these points but the adoption has been slow, hindered by constraining frameworks. A panel of academics and practitioners has identified a set of requirements, known as the Georgetown Challenge, that real options analyses must meet to get more traction amongst practitioners in the industry. In a bid to meet some of these requirements, this research proposes a novel methodology, cross-fertilizing techniques from financial engineering, actuarial sciences, and statistics to evaluate and study the timing of technology developments under uncertainty. It aims at substantiating decision making for R&D while having a wider domain of application and an improved ability to handle a complex reality compared to more traditional approaches. The method named FLexible AViation Investment Analysis (FLAVIA) uses first Monte Carlo techniques to simulate the evolution of uncertainties driving the value of technology developments. A non-parametric Esscher transform is then applied to perform a change of probability measure to express these evolutions under the equivalent martingale measure. A bootstrap technique is suggested next to construct new non-weighted evolutions of the technology development value under the new measure. A regression-based technique is finally used to analyze the technology development program and to discover trigger boundaries which help define when the technology development program should be launched. Verification of the method is performed on several canonical examples and indicates good accuracy and competitive execution time. It is applied next to the analysis of a performance improvement package (PIP) development using the Integrated Cost And Revenue Estimation method (i-CARE) developed as part of this research. The PIP can be retrofitted to currently operating turbofan engines in order to mitigate the impact of the aging process on their operating costs. The PIP is subject to market uncertainties, such as the evolution of jet-fuel prices and the possible taxation of carbon emissions. The profitability of the PIP development is investigated and the value of managerial flexibility and timing flexibility are highlighted.
A sizing and vehicle matching methodology for boundary layer ingesting propulsion systems

(Georgia Institute of Technology, 2015-11-16) Gladin, Jonathan Conrad

Boundary layer ingesting (BLI) propulsion systems offer potential fuel burn reduction for civil aviation and synergize with new advanced airframe concepts. However, the distorted inlet flow for BLI systems can cause performance and stability margin loss. System level analyses generally size a single engine at a fixed design point which ignores the distributed nature of many BLI architectures. Furthermore, operability and performance during o design are generally not considered during the sizing process. In this thesis, a methodology is developed for multi-design point sizing of BLI propulsion systems for specific vehicle geometry including an operability constraint. The methodology is applied to a 300 passenger hybrid-wing body vehicle with embedded turbofan engines. The methodology required investigations into three main areas of research. The first was the modeling of BLI impacts over a range of flight conditions. A BLI analysis tool was developed which models the vehicle boundary layer, pre-entry region, inlet, and fan losses throughout the entire flight envelope. An experiment investigating the impact of the modeling approach is conducted, and results show that proper mapping of the fan, inlet, and BLI propulsive benefit is crucially important for making proper design decisions. The impact of BLI on the system was found to vary significantly during o ff design and especially with changes in vehicle angle of attack. The operability constraint is investigated using a parallel compressor model and was found to place a minimum limit on the propulsor height. The second area of investigation was the creation of a multi-propulsor sizing methodology which accounts for diff erences between propulsors during flight that is induced by their interaction with the vehicle. A modified multi-design point approach was used which employs a set of design and power management rules to relate the operation of the propulsors. A performance comparison of this methodology with the standard single propulsor approach showed a signicant difference. The final area of investigation was the determination of critical o ff-design conditions for the sizing procedure. A screening process is developed which tests all off -design conditions for a subset of the design space to find conditions which are stall margin or thrust deficient. The experiment showed that it is necessary to consider the high angle of attack take-off condition during sizing for the HWB vehicle and that a variable area nozzle is required to meet the operability constraint. A follow on experiment showed that the inclusion of this point reduced the achievable fuel burn benefit for more aggressive BLI designs.Boundary layer ingesting (BLI) propulsion systems offer potential fuel burn reduction for civil aviation and synergize with new advanced airframe concepts. However, the distorted inlet flow for BLI systems can cause performance and stability margin loss. System level analyses generally size a single engine at a fixed design point which ignores the distributed nature of many BLI architectures. Furthermore, operability and performance during o design are generally not considered during the sizing process. In this thesis, a methodology is developed for multi-design point sizing of BLI propulsion systems for specific vehicle geometry including an operability constraint. The methodology is applied to a 300 passenger hybrid-wing body vehicle with embedded turbofan engines. The methodology required investigations into three main areas of research. The first was the modeling of BLI impacts over a range of flight conditions. A BLI analysis tool was developed which models the vehicle boundary layer, pre-entry region, inlet, and fan losses throughout the entire flight envelope. An experiment investigating the impact of the modeling approach is conducted, and results show that proper mapping of the fan, inlet, and BLI propulsive benefit is crucially important for making proper design decisions. The impact of BLI on the system was found to vary significantly during o ff design and especially with changes in vehicle angle of attack. The operability constraint is investigated using a parallel compressor model and was found to place a minimum limit on the propulsor height. The second area of investigation was the creation of a multi-propulsor sizing methodology which accounts for diff erences between propulsors during flight that is induced by their interaction with the vehicle. A modified multi-design point approach was used which employs a set of design and power management rules to relate the operation of the propulsors. A performance comparison of this methodology with the standard single propulsor approach showed a signicant difference. The final area of investigation was the determination of critical o ff-design conditions for the sizing procedure. A screening process is developed which tests all off -design conditions for a subset of the design space to find conditions which are stall margin or thrust deficient. The experiment showed that it is necessary to consider the high angle of attack take-off condition during sizing for the HWB vehicle and that a variable area nozzle is required to meet the operability constraint. A follow on experiment showed that the inclusion of this point reduced the achievable fuel burn benefit for more aggressive BLI designs.
A methodology for modeling the verification, validation, and testing process for launch vehicles

(Georgia Institute of Technology, 2015-11-16) Sudol, Alicia

Completing the development process and getting to first flight has become a difficult hurdle for launch vehicles. Program cancellations in the last 30 years were largely due to cost overruns and schedule slips during the design, development, testing and evaluation (DDT&E) process. Unplanned rework cycles that occur during verification, validation, and testing (VVT) phases of development contribute significantly to these overruns, accounting for up to 75% of development cost. Current industry standard VVT planning is largely subjective with no method for evaluating the impact of rework. The goal of this research is to formulate and implement a method that will quantitatively capture the impact of unplanned rework by assessing the reliability, cost, schedule, and risk of VVT activities. First, the fidelity level of each test is defined and the probability of rework between activities is modeled using a dependency structure matrix. Then, a discrete event simulation projects the occurrence of rework cycles and evaluates the impact on reliability, cost, and schedule for a set of VVT activities. Finally, a quadratic risk impact function is used to calculate the risk level of the VVT strategy based on the resulting output distributions. This method is applied to alternative VVT strategies for the Space Shuttle Main Engine to demonstrate how the impact of rework can be mitigated, using the actual test history as a baseline. Results indicate rework cost to be the primary driver in overall project risk, and yield interesting observations regarding the trade-off between the upfront cost of testing and the associated cost of rework. Ultimately, this final application problem demonstrates the merits of this methodology in evaluating VVT strategies and providing a risk-informed decision making framework for the verification, validation, and testing process of launch vehicle systems.
A framework for technology exploration of aviation environmental mitigation strategies

(Georgia Institute of Technology, 2015-11-16) Levine, Matthew Jason

The goal of this thesis was to develop a framework for modeling relevant environmental performance metrics and objectively simulating the future environmental impacts of aviation given the evolution of the fleet, the development of new technologies, and the expansion of airports. By exchanging fidelity for computational speed, a screening-level framework for assessing aviation's environmental impacts can be developed to observe new insights on fleet-level trends and inform environmental mitigation strategies. This was accomplished by developing per class average ``generic-vehicle" models that can reduce the fleet to a few representative aircraft models for predicting fleet results with reasonable accuracy. The method for Generating Emissions and Noise, Evaluating Residuals and using Inverse method for Choosing the best Alternatives (GENERICA) expands a previous generic vehicle formulation to additionally match DNL contours across a subset of airports. Designs of experiments, surrogate models, Monte Carlo simulations, and ``desirability" scores were combined to set the vehicle design parameters and reduce the mean relative error across the subset of airports. Results show these vehicle models more accurately represented contours at busy airports operating a wide variety of aircraft as compared to a traditional representative-in-class approach. Additionally, a rapid method for assessing population exposure counts was developed and incorporated into the noise tool, and the generic vehicles demonstrated accuracy with respect to population exposure counts for the actual fleet in the baseline year. The capabilities of the enabled framework were demonstrated to show fleet-level trends and explore placement of new runways at capacity constrained airports.
Subsystem architecture sizing and analysis for aircraft conceptual design

(Georgia Institute of Technology, 2015-11-13) Chakraborty, Imon

In traditional aircraft conceptual design, subsystems are largely accounted for implicitly based on available historical data and trends. Such an approach has limitations when novel subsystem architectures such as More Electric or All Electric aircraft are considered, since historical data regarding such architectures is either limited or non-existent. In such cases, the incorporation of more thorough and explicit consideration of the aircraft subsystems into the conceptual design phase is warranted. The first objective of this dissertation is to integrate subsystem sizing and analysis methods that are suitable for the early design phases with the traditional aircraft sizing methodology. The goal is to facilitate the assessment subsystem architecture performance with respect to vehicle and mission level metrics. The second objective is to investigate how the performance of different subsystem architectures varies with aircraft size. The third and final objective is to assess the sensitivity of architecture performance to epistemic and technological uncertainty. These objectives are pursued through the development of an integrated sizing and analysis environment where the subsystems are sized in parallel with the aircraft itself using subsystem models that are computationally inexpensive and do not require detailed aircraft definition. The effects of subsystem mass, secondary power requirements, and drag increments are propagated to the mission performance analysis following which the vehicle and subsystems are re-sized. A number of experiments are performed to first test the capabilities of the developed environment and subsequently assess the performance of numerous subsystem architectures and the sensitivity of select architectures to epistemic and technological uncertainty.
Fuzzy framework for robust architecture identification in concept selection

(Georgia Institute of Technology, 2015-11-10) Patterson, Frank H.

An evolving set of modern physics-based, multi-disciplinary conceptual design methods seek to explore the feasibility of a new generation of systems, with new capabilities, capable of missions that conventional vehicles cannot be empirically redesigned to perform. These methods provide a more complete understanding of a concept's design space, forecasting the feasibility of uncertain systems, but are often computationally expensive and time consuming to prepare. This trend creates a unique and critical need to identify a manageable number of capable concept alternatives early in the design process. Ongoing efforts attempting to stretch capability through new architectures, like the U.S. Army's Future Vertical Lift effort and DARPA's Vertical Takeoff and Landing (VTOL) X-plane program highlight this need. The process of identifying and selecting a concept configuration is often given insufficient attention, especially when a small subset of favorable concept families is not immediately apparent. Commonly utilized methods for concept generation, like filtered morphological analysis, often identify an exponential number of alternatives. Simple approaches to concept selection then rely on designers to identify a relatively small subset of alternatives for comparison through simple methods regularly related to decision matrices (Pugh, TOPSIS, AHP, etc.). More in-depth approaches utilize modeling and simulation to compare concepts with techniques such as stochastic optimization or probabilistic decision making, but a complicated setup limits these approaches to just a discrete few alternatives. A new framework to identify and select promising, robust concept configurations utilizing fuzzy methods is proposed in this research and applied to the example problem of concept selection for DARPA's VTOL Xplane program. The framework leverages fuzzy systems in conjunction with morphological analysis to assess large design spaces of potential architecture alternatives while capturing the inherent uncertainty and ambiguity in the evaluation of these early concepts. Experiments show how various fuzzy systems can be utilized for evaluating criteria of interest across disparate architectures by modeling expert knowledge as well as simple physics-based data. The models are integrated into a single environment and variations on multi-criteria optimization are tested to demonstrate an ability to identify a non-dominated set of architectural families in a large combinatorial design space. The resulting framework is shown to provide an approach to quickly identify promising concepts in the face of uncertainty early in the design process.An evolving set of modern physics-based, multi-disciplinary conceptual design methods seek to explore the feasibility of a new generation of systems, with new capabilities, capable of missions that conventional vehicles cannot be empirically redesigned to perform. These methods provide a more complete understanding of a concept's design space, forecasting the feasibility of uncertain systems, but are often computationally expensive and time consuming to prepare. This trend creates a unique and critical need to identify a manageable number of capable concept alternatives early in the design process. Ongoing efforts attempting to stretch capability through new architectures, like the U.S. Army's Future Vertical Lift effort and DARPA's Vertical Takeoff and Landing (VTOL) X-plane program highlight this need. The process of identifying and selecting a concept configuration is often given insufficient attention, especially when a small subset of favorable concept families is not immediately apparent. Commonly utilized methods for concept generation, like filtered morphological analysis, often identify an exponential number of alternatives. Simple approaches to concept selection then rely on designers to identify a relatively small subset of alternatives for comparison through simple methods regularly related to decision matrices (Pugh, TOPSIS, AHP, etc.). More in-depth approaches utilize modeling and simulation to compare concepts with techniques such as stochastic optimization or probabilistic decision making, but a complicated setup limits these approaches to just a discrete few alternatives. A new framework to identify and select promising, robust concept configurations utilizing fuzzy methods is proposed in this research and applied to the example problem of concept selection for DARPA's VTOL Xplane program. The framework leverages fuzzy systems in conjunction with morphological analysis to assess large design spaces of potential architecture alternatives while capturing the inherent uncertainty and ambiguity in the evaluation of these early concepts. Experiments show how various fuzzy systems can be utilized for evaluating criteria of interest across disparate architectures by modeling expert knowledge as well as simple physics-based data. The models are integrated into a single environment and variations on multi-criteria optimization are tested to demonstrate an ability to identify a non-dominated set of architectural families in a large combinatorial design space. The resulting framework is shown to provide an approach to quickly identify promising concepts in the face of uncertainty early in the design process.
Development of a physics based methodology for the prediction of rotor blade ice formation

(Georgia Institute of Technology, 2015-11-10) Kim, Jee Woong

Modern helicopters, civilian and military alike, are expected to operate in all weather conditions. Ice accretion adversely affects the availability, affordability, safety and survivability. Availability of the vehicle may be compromised if the ice formation requires excessive torque to overcome the drag needed to operate the rotor. Affordability is affected by the power requirements and cost of ownership of the deicing systems needed to safely operate the vehicle. Equipment of the rotor blades with built-in heaters greatly increases the cost of the helicopter and places further demands on the engine. The safety of the vehicle is also compromised due to ice shedding events, and the onset of abrupt, unexpected stall phenomena attributable to ice formation. Given the importance of understanding the effects of icing on aircraft performance and certification, considerable work has been done on the development of analytical and empirical tools, accompanied by high quality wind tunnel and flight test data. In this work, numerical studies to improve ice growth modeling have been done by reducing limitations and empiricism inherent in existing ice accretion models. In order to overcome the weakness of Lagrangian approach in unsteady problem such as rotating blades, a water droplet solver based on 3-D Eulerian method is developed and integrated into existing CFD solver. Also, the differences between the industry standard ice accretion analyses such as LEWICE and the ice accretion models based on the extended Messinger model are investigated through a number of 2-D airfoil and 3-D rotor blade ice accretion studies. The developed ice accretion module based on 3-D Eulerian water droplet method and the extended Messinger model is also coupled with an existing empirical ice shedding model. A series of progressively challenging simulations have been carried out. These include ability of the solvers to model airloads over an airfoil with a prescribed/simulated ice shape, collection efficiency modeling, ice growth, ice shedding, de-icing modeling, and assessment of the degradation of airfoil or rotor performance associated with the ice formation. While these numerical simulation results are encouraging, much additional work remains in modeling detailed physics important to rotorcraft icing phenomena. Despite these difficulties, progress in assessing helicopter ice accretion has been made and tools for initial analyses have been developed.Modern helicopters, civilian and military alike, are expected to operate in all weather conditions. Ice accretion adversely affects the availability, affordability, safety and survivability. Availability of the vehicle may be compromised if the ice formation requires excessive torque to overcome the drag needed to operate the rotor. Affordability is affected by the power requirements and cost of ownership of the deicing systems needed to safely operate the vehicle. Equipment of the rotor blades with built-in heaters greatly increases the cost of the helicopter and places further demands on the engine. The safety of the vehicle is also compromised due to ice shedding events, and the onset of abrupt, unexpected stall phenomena attributable to ice formation. Given the importance of understanding the effects of icing on aircraft performance and certification, considerable work has been done on the development of analytical and empirical tools, accompanied by high quality wind tunnel and flight test data. In this work, numerical studies to improve ice growth modeling have been done by reducing limitations and empiricism inherent in existing ice accretion models. In order to overcome the weakness of Lagrangian approach in unsteady problem such as rotating blades, a water droplet solver based on 3-D Eulerian method is developed and integrated into existing CFD solver. Also, the differences between the industry standard ice accretion analyses such as LEWICE and the ice accretion models based on the extended Messinger model are investigated through a number of 2-D airfoil and 3-D rotor blade ice accretion studies. The developed ice accretion module based on 3-D Eulerian water droplet method and the extended Messinger model is also coupled with an existing empirical ice shedding model. A series of progressively challenging simulations have been carried out. These include ability of the solvers to model airloads over an airfoil with a prescribed/simulated ice shape, collection efficiency modeling, ice growth, ice shedding, de-icing modeling, and assessment of the degradation of airfoil or rotor performance associated with the ice formation. While these numerical simulation results are encouraging, much additional work remains in modeling detailed physics important to rotorcraft icing phenomena. Despite these difficulties, progress in assessing helicopter ice accretion has been made and tools for initial analyses have been developed.
A complex networks approach to designing resilient system-of-systems

(Georgia Institute of Technology, 2015-11-09) Tran, Huy T.

This thesis develops a methodology for designing resilient system-of-systems (SoS) networks. This methodology includes a capability-based resilience assessment framework, used to quantify SoS resilience. A complex networks approach is used to generate potential SoS network designs, focusing on scale-free and random network topologies, degree-based and random rewiring adaptation, and targeted and random node removal threats. Statistical design methods, specifically response surface methodology, are used to evaluate SoS networks and provide an understanding of the advantages and disadvantages of potential designs. Linear regression is used to model a continuous representation of the network design space, and determine optimally resilient networks for particular threat types. The methodology is applied to an information exchange (IE) network model (i.e., a message passing network model) and military command and control (C2) model. Results show that optimally resilient IE network topologies are random for networks with adaptation, regardless of the threat type. However, the optimally resilient adaptation method sharply transitions from being fully random to fully degree-based as threat randomness increases. These findings suggest that intermediately defined networks should not be considered when designing for resilience. Cost-benefit analysis of C2 networks suggests that resilient C2 networks are more cost-effective than robust ones, as long as the cost of rewiring network links is less than three-fourths the cost of creating new links. This result identifies a threshold for which a resilient network design approach is more cost-effective than a robust one.This thesis develops a methodology for designing resilient system-of-systems (SoS) networks. This methodology includes a capability-based resilience assessment framework, used to quantify SoS resilience. A complex networks approach is used to generate potential SoS network designs, focusing on scale-free and random network topologies, degree-based and random rewiring adaptation, and targeted and random node removal threats. Statistical design methods, specifically response surface methodology, are used to evaluate SoS networks and provide an understanding of the advantages and disadvantages of potential designs. Linear regression is used to model a continuous representation of the network design space, and determine optimally resilient networks for particular threat types. The methodology is applied to an information exchange (IE) network model (i.e., a message passing network model) and military command and control (C2) model. Results show that optimally resilient IE network topologies are random for networks with adaptation, regardless of the threat type. However, the optimally resilient adaptation method sharply transitions from being fully random to fully degree-based as threat randomness increases. These findings suggest that intermediately defined networks should not be considered when designing for resilience. Cost-benefit analysis of C2 networks suggests that resilient C2 networks are more cost-effective than robust ones, as long as the cost of rewiring network links is less than three-fourths the cost of creating new links. This result identifies a threshold for which a resilient network design approach is more cost-effective than a robust one.
Effects of electron emission on plasma sheaths

(Georgia Institute of Technology, 2015-10-07) Langendorf, Samuel J.

Current state-of-the-art plasma thrusters are limited in power density and thrust density by power losses to plasma-facing walls and electrodes. In the case of Hall effect thrusters, power deposition to the discharge channel walls and anode negatively impact the efficiency of the thruster and limit the attainable power density and thrust density. The current work aims to recreate thruster-relevant wall-interaction physics in a quiescent plasma and investigate them using electrostatic probes, in order to inform the development of the next generation of high-power-density / high-thrust-density propulsion devices. Thruster plasma-wall interactions are complicated by the occurrence of the plasma sheath, a thin boundary layer that forms between a plasma and its bounding wall where electrostatic forces dominate. Sheaths have been recognized since the seminal work of Langmuir in the early 1900’s, and the theory of sheaths has been greatly developed to the present day. The theories are scalable across a wide range of plasma parameters, but due to the difficulty of obtaining experimental measurements of plasma properties in the sheath region, there is little experimental data available to directly support the theoretical development. Sheaths are difficult to measure in situ in thrusters due to the small physical length scale of the sheath (order of micrometers in thruster plasmas) and the harsh plasma environment of the thruster. Any sufficiently small probe will melt, and available optical plasma diagnostics do not have the sensitivity and/or spatial resolution to resolve the sheath region. The goal of the current work is to experimentally characterize plasma sheaths xxvi in a low-density plasma that yields centimeter-thick sheath layers. By generating thick sheaths, spatially-resolved data can obtained using electrostatic probes. The investigation focuses on the effects of electron emission from the wall and several factors that influence it, including wall material, wall temperature, wall surface roughness and topology, as well as the scaling of sheaths from the low-density plasma environment towards thruster conditions. The effects of electron emission and wall material are found to agree with classical fluid and kinetic theory extended from literature. In conditions of very strong emission from the wall, evidence is found for a full transition in sheath polarities rather than a non-monotonic structure. Wall temperature is observed to have no effect on the sheath over boron nitride walls independent of outgassing on initial heat-up, for sub-thermionic temperatures. Wall roughness is observed to postpone the effects of electron emission to higher plasma temperatures, indicating that the rough wall impairs the wall’s overall capacity to emit electrons. Reductions in electron yield are not inconsistent with a diffuse-emission geometric trapping model. Collectively, the experimental data provide an improved grounding for thruster modeling and design.Current state-of-the-art plasma thrusters are limited in power density and thrust density by power losses to plasma-facing walls and electrodes. In the case of Hall effect thrusters, power deposition to the discharge channel walls and anode negatively impact the efficiency of the thruster and limit the attainable power density and thrust density. The current work aims to recreate thruster-relevant wall-interaction physics in a quiescent plasma and investigate them using electrostatic probes, in order to inform the development of the next generation of high-power-density / high-thrust-density propulsion devices. Thruster plasma-wall interactions are complicated by the occurrence of the plasma sheath, a thin boundary layer that forms between a plasma and its bounding wall where electrostatic forces dominate. Sheaths have been recognized since the seminal work of Langmuir in the early 1900’s, and the theory of sheaths has been greatly developed to the present day. The theories are scalable across a wide range of plasma parameters, but due to the difficulty of obtaining experimental measurements of plasma properties in the sheath region, there is little experimental data available to directly support the theoretical development. Sheaths are difficult to measure in situ in thrusters due to the small physical length scale of the sheath (order of micrometers in thruster plasmas) and the harsh plasma environment of the thruster. Any sufficiently small probe will melt, and available optical plasma diagnostics do not have the sensitivity and/or spatial resolution to resolve the sheath region. The goal of the current work is to experimentally characterize plasma sheaths xxvi in a low-density plasma that yields centimeter-thick sheath layers. By generating thick sheaths, spatially-resolved data can obtained using electrostatic probes. The investigation focuses on the effects of electron emission from the wall and several factors that influence it, including wall material, wall temperature, wall surface roughness and topology, as well as the scaling of sheaths from the low-density plasma environment towards thruster conditions. The effects of electron emission and wall material are found to agree with classical fluid and kinetic theory extended from literature. In conditions of very strong emission from the wall, evidence is found for a full transition in sheath polarities rather than a non-monotonic structure. Wall temperature is observed to have no effect on the sheath over boron nitride walls independent of outgassing on initial heat-up, for sub-thermionic temperatures. Wall roughness is observed to postpone the effects of electron emission to higher plasma temperatures, indicating that the rough wall impairs the wall’s overall capacity to emit electrons. Reductions in electron yield are not inconsistent with a diffuse-emission geometric trapping model. Collectively, the experimental data provide an improved grounding for thruster modeling and design.