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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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Design strategies for rotorcraft blades and HALE aircraft wings applied to damage tolerant wind turbine blade design

(Georgia Institute of Technology, 2014-12-15) Richards, Phillip W.

Offshore wind power production is an attractive clean energy option, but the difficulty of access can lead to expensive and rare opportunities for maintenance. Smart loads management (controls) are investigated for their potential to increase the fatigue life of damaged offshore wind turbine rotor blades. This study will consider two commonly encountered damage types for wind turbine blades, the trailing edge disbond (bond line failure) and shear web disbond, and show how 3D finite element modeling can be used to quantify the effect of operations and control strategies designed to extend the fatigue life of damaged blades. Modern wind turbine blades are advanced composite structures, and blade optimization problems can be complex with many structural design variables and a wide variety of aeroelastic design requirements. The multi-level design method is an aeroelastic structural design technique for beam-like structures in which the general design problem is divided into a 1D beam optimization and a 2D section optimization. As a demonstration of aeroelastic design, the multi-level design method is demonstrated for the internal structural design of a modern composite rotor blade. Aeroelastic design involves optimization of system geometry features as well as internal features, and this is demonstrated in the design of a flying wing aircraft. Control methods such as feedback control also have the capability alleviate aeroelastic design requirements and this is also demonstrated in the flying wing aircraft example. In the case of damaged wind turbine blades, load mitigation control strategies have the potential to mitigate the effects of damage, and allow partial operation to avoid shutdown. The load mitigation strategies will be demonstrated for a representative state-of-the-art wind turbine (126m rotor diameter). An economic incentive will be provided for the proposed operations strategies, in terms of weighing the cost and risk of implementation against the benefits of increased revenue due to operation of damaged turbines. The industry trend in wind turbine design is moving towards very large blades, causing the basic design criterion to change as aeroelastic effects become more important. An ongoing 100 m blade (205 m rotor diameter) design effort intends to investigate these design challenges. As a part of that effort, this thesis will investigate damage tolerant design strategies to ensure next-generation blades are more reliable.
Testing the effects of violating component axioms in validation of complex aircraft systems

(Georgia Institute of Technology, 2014-12-08) Kansal, Aparna

This thesis focuses on estimating faults in complex large-scale integrated aircraft systems, especially where they interact with, and control, the aircraft dynamics. A general assumption considered in the reliability of such systems is that any component level fault will be monitored, detected and corrected by some fault management capability. However, a reliance on fault management assumes not only that it can detect and manage all faults, but also that it can do so in sufficient time to recover from any deviation in the aircraft dynamics and flight path. Testing for system-level effects is important to ensure better reliability of aircraft systems. However, with existing methods for validation of complex aircraft systems, it is difficult and impractical to set up a finite test suite to enable testing and integration of all the components of a complex system. The difficulty lies in the cost of modelling every aspect of every component given the large number of test cases required for sufficient coverage. Just having a good simulator, or increasing the number of test cases is not sufficient; it is also important to know which simulation runs to conduct. For this purpose, the thesis proposes simulating faults in the system through the violation of “axiomatic conditions” of the system components, which are conditions on the functioning of these components introduced during their development. The thesis studies the effect, on the aircraft dynamics, of simulating such faults when reference models of the components representing their key functions are integrated.
Developing a computational model of the pilot's best possible expectation of aircraft state given vestibular and visual cues

(Georgia Institute of Technology, 2014-12-05) Onur, Can

Loss of Control (LOC) accidents are a major threat for aviation, and contribute the highest risk for fatalities in all aviation accidents. The major contributor to LOC accidents is pilot spatial disorientation (SD), which accounts for roughly 32% of all LOC accidents. A pilot experiences SD during flight when the pilot's expectation of the aircraft's state deviates from reality. This deviation results from a number of underlying mechanisms, such as distraction, failure to monitor flight instruments, and vestibular illusions. Previous researchers have developed computational models to understand those mechanisms. However, these models are limited in scope as they do not model the pilot's knowledge of the aircraft dynamics. This research proposes a novel model to predict the best-possible-pilot-expectation of the aircraft state given vestibular and visual cues. The proposed model uses a Model-Based Observer (MBO) as the infrastructure needed to establish an “expert pilot”. Expert pilots are known to form an internal model of the operated system through training and experience, which allows the expert to generate better internal expectations of the system states. Pilots' internal expectations are enhanced by the presence of information fed through the pilots̕ sensory systems. Thus, the proposed model integrates pilot's knowledge of the system dynamics (i.e. an aircraft model) with a continuous vestibular sensory model and a discrete visual-sampling sensory model. The computational model serves to investigate the underlying mechanisms of SD during flight and provide a quantitative analysis tool to support flight deck and countermeasure designs.
Prox-1 Guidance, Navigation, & Control Overview: Development, Algorithms, and Integrated Simulation

(Georgia Institute of Technology, 2014-12-01) Schulte, Peter Z.

This report describes the development and validation process of a highly automated Guidance, Navigation, & Control (GN&C) subsystem for a small satellite on-orbit inspection application. The resulting GN&C subsystem performs proximity operations (ProxOps) without human-in the-loop interaction. The report focuses on the description of the GN&C algorithms, the integration and testing of GN&C software, and the development of decision logic to address the question of how such a system can be effectively implemented for full automation. This process is unique because a multitude of operational scenarios must be considered and a set of complex interactions between various GN&C components must be defined to achieve the automation goal. The GN&C subsystem for the Prox-1 satellite is currently under development within the Space Systems Design Laboratory at the Georgia Institute of Technology. The Prox-1 mission involves deploying the LightSail 3U CubeSat, entering into a leading or trailing orbit of LightSail using ground-in-the-loop commands, and then performing automated ProxOps through formation flight and natural motion circumnavigation maneuvers. Operations such as these may be utilized for many scenarios including on-orbit inspection, refueling, repair, construction, reconnaissance, docking, and debris mitigation activities. Prox-1 uses onboard sensors and imaging instruments to perform its GN&C operations during on-orbit inspection of LightSail. Navigation filters perform relative orbit determination based on images of the target spacecraft, and guidance algorithms conduct automated maneuver planning. A slew and tracking controller sends attitude actuation commands to a set of control moment gyroscopes, and other controllers manage desaturation, detumble, and target acquisition/recovery. All Prox-1 GN&C components are developed in a MATLAB/Simulink six degree-of-freedom simulation environment and are integrated using decision logic to autonomously determine when certain actions should be performed. The complexity of this decision logic is the main challenge of this process, and the Stateflow tool in Simulink is used to establish logical relationships and manage data flow between each of the individual GN&C hardware and software components. Once the integrated GN&C simulation is fully developed in MATLAB/Simulink, the algorithms are autocoded to C/C++ and integrated into flight software. The subsystem is tested using hardware-in-the-loop on the flight computers and other hardware
Architecting aircraft power distribution systems via redundancy allocation

(Georgia Institute of Technology, 2014-11-17) Campbell, Angela Mari

Recently, the environmental impact of aircraft and rising fuel prices have become an increasing concern in the aviation industry. To address these problems, organizations such as NASA have set demanding goals for reducing aircraft emissions, fuel burn, and noise. In an effort to reach the goals, a movement toward more-electric aircraft and electric propulsion has emerged. With this movement, the number of critical electrical loads on an aircraft is increasing causing power system reliability to be a point of concern. Currently, power system reliability is maintained through the use of back-up power supplies such as batteries and ram-air-turbines (RATs). However, the increasing power requirements for critical loads will quickly outgrow the capacity of the emergency devices. Therefore, reliability needs to be addressed when designing the primary power distribution system. Power system reliability is a function of component reliability and redundancy. Component reliability is often not determined until detailed component design has occurred; however, the amount of redundancy in the system is often set during the system architecting phase. In order to meet the capacity and reliability requirements of future power distribution systems, a method for redundancy allocation during the system architecting phase is needed. This thesis presents an aircraft power system design methodology that is based upon the engineering decision process. The methodology provides a redundancy allocation strategy and quantitative trade-off environment to compare architecture and technology combinations based upon system capacity, weight, and reliability criteria. The methodology is demonstrated by architecting the power distribution system of an aircraft using turboelectric propulsion. The first step in the process is determining the design criteria which includes a 40 MW capacity requirement, a 20 MW capacity requirement for the an engine-out scenario, and a maximum catastrophic failure rate of one failure per billion flight hours. The next step is determining gaps between the performance of current power distribution systems and the requirements of the turboelectric system. A baseline architecture is analyzed by sizing the system using the turboelectric system power requirements and by calculating reliability using a stochastic flow network. To overcome the deficiencies discovered, new technologies and architectures are considered. Global optimization methods are used to find technology and architecture combinations that meet the system objectives and requirements. Lastly, a dynamic modeling environment is constructed to study the performance and stability of the candidate architectures. The combination of the optimization process and dynamic modeling facilitates the selection of a power system architecture that meets the system requirements and objectives.
Sustainability of multimodal intercity transportation using a hybrid system dynamics and agent-based modeling approach

(Georgia Institute of Technology, 2014-11-17) Hivin, Ludovic F.

Demand for intercity transportation has increased significantly in the past decades and is expected to continue to follow this trend in the future. In the meantime, concern about the environmental impact and potential climate change associated with this demand has grown, resulting in an increasing importance of climate impact considerations in the overarching issue of sustainability. This results in discussions on new regulations, policies and technologies to reduce transportation's climate impact. Policies may affect the demand for the different transportation modes through increased travel costs, increased market share of more fuel efficient vehicles, or even the introduction of new modes of transportation. However, the effect of policies and technologies on mobility, demand, fleet composition and the resulting climate impact remains highly uncertain due to the many interdependencies. This motivates the creation of a parametric modeling and simulation environment to explore a wide variety of policy and technology scenarios and assess the sustainability of transportation. In order to capture total transportation demand and the potential mode shifts, a multimodal approach is necessary. The complexity of the intercity transportation System-of-Systems calls for a hybrid Agent-Based Modeling and System Dynamics paradigm to better represent both micro-level and macro-level behaviors. Various techniques for combining these paradigms are explored and classified to serve as a hybrid modeling guide. A System Dynamics approach is developed, that integrates socio-economic factors, mode performance, aggregated demand and climate impact. It is used to explore different policy and technology scenarios, and better understand the dynamic behavior of the intercity transportation System-of-Systems. In order to generate the necessary data to create and validate the System Dynamics model, an Agent-Based model is used due to its capability to better capture the behavior of a collection of sentient entities. Equivalency of both models is ensured through a rigorous cross-calibration process. Through the use of fleet models, the fuel burn and life cycle emissions from different modes of transportation are quantified. The radiative forcing from the main gaseous and aerosol species is then obtained through radiative transfer calculations and regional variations are discussed. This new simulation environment called the environmental Ground and Air Mode Explorer (eGAME) is then used to explore different policy and technology scenarios and assess their effect on transportation demand, fleet efficiencies and the resulting climate impact. The results obtained with this integrated assessment tool aim to support a scenario-based decision making approach and provide insight into the future of the U.S. transportation system in a climate constrained environment.
CONTRAST: A conceptual reliability growth approach for comparison of launch vehicle architectures

(Georgia Institute of Technology, 2014-11-17) Zwack, Mathew R.

In 2004, the NASA Astronaut Office produced a memo regarding the safety of next generation launch vehicles. The memo requested that these vehicles have a probability of loss of crew of at most 1 in 1000 flights, which represents nearly an order of magnitude decrease from current vehicles. The goal of LOC of 1 in 1000 flights has since been adopted by the launch vehicle design community as a requirement for the safety of future vehicles. This research addresses the gap between current vehicles and future goals by improving the capture of vehicle architecture effects on reliability and safety. Vehicle architecture pertains to the physical description of the vehicle itself, which includes manned or unmanned, number of stages, number of engines per stage, engine cycle types, redundancy, etc. During the operations phase of the vehicle life-cycle it is clear that each of these parameters will have an inherent effect on the reliability and safety of the vehicle. However, the vehicle architecture is typically determined during the early conceptual design phase when a baseline vehicle is selected. Unless a great amount of money and effort is spent, the architecture will remain relatively constant from conceptual design through operations. Due to the fact that the vehicle architecture is essentially “locked-in” during early design, it is expected that much of the vehicle's reliability potential will also be locked-in. This observation leads to the conclusion that improvement of vehicle reliability and safety in the area of vehicle architecture must be completed during early design. Evaluation of the effects of different architecture decisions must be performed prior to baseline selection, which helps to identify a vehicle that is most likely to meet the reliability and safety requirements when it reaches operations. Although methods exist for evaluating reliability and safety during early design, weaknesses exist when trying to evaluate all architecture effects simultaneously. The goal of this research was therefore to formulate and implement a method that is capable of quantitatively evaluating vehicle architecture effects on reliability and safety during early conceptual design. The ConcepTual Reliability Growth Approach for CompariSon of Launch Vehicle ArchiTectures (CONTRAST) was developed to meet this goal. Using the strengths of existing techniques a hybrid approach was developed, which utilizes a reliability growth projection to evaluate the vehicles. The growth models are first applied at the subsystem level and then a vehicle level projection is generated using a simple system level fault tree. This approach allows for the capture of all trades of interest at the subsystem level as well as many possible trades at the assembly level. The CONTRAST method is first tested on an example problem, which compares the method output to actual data from the Space Transportation System (STS). This example problem illustrates the ability of the CONTRAST method to capture reliability growth trends seen during vehicle operations. It also serves as a validation for the development of the reliability growth model assumptions for future applications of the method. The final chapter of the thesis applies the CONTRAST method to a relevant launch vehicle, the Space Launch System (SLS), which is currently under development. Within the application problem, the output of the method is first used to check that the primary research objective has been met. Next, the output is compared to a state-of-the-art tool in order to demonstrate the ability of the CONTRAST method to alleviate one of the primary consequences of using existing techniques. The final section within this chapter presents an analysis of the booster and upper stage block upgrade options for the SLS vehicle. A study of the upgrade options was carried out because the CONTRAST method is uniquely suited to look at the effects of such strategies. The results from the study of SLS block upgrades give interesting observations regarding the desired development order and upgrade strategy. Ultimately this application problem demonstrates the merits of applying the CONTRAST method during early design. This approach provides the designer with more information in regard to the expected reliability of the vehicle, which will ultimately enable the selection of a vehicle baseline that is most likely to meet the future requirements.
A methodology for evaluating fleet implications of mission specification changes

(Georgia Institute of Technology, 2014-11-17) Brett, Paul S.

Civil aviation has matured to become a vital piece of the global economy, providing the rapid movement of goods and people to all regions. This has already led to significant growth and expectations of further growth are on the rate of 5% per year. Given the high projected rate of growth, environmental consequences of commercial aviation are expected to rise. To mitigate the increase of noise and emissions, governing bodies such as ICAO and the FAA have established and are considering additional regulation of noise, NOₓ, and CO₂ while the European Union has integrated aviation into their Environmental Trading Scheme. The traditional response to new regulation is to integrate technologies into the aircraft to reduce environmental footprint. While these benefits are positive on the aircraft level, fleet growth is projected to outpace benefits provided by technology alone. To further reduce environmental footprint, a number of mitigation strategies are being explored to determine the impact. One of those strategies involves changing the mission specifications of today's aircraft by reducing range, speed, or payload in an effort to reduce fuel consumption and has been predominantly focused at the vehicle level. This research proposes an approach that evaluates mission specification changes from the aircraft design level up to the fleet level, forecasted into the future, to assess the impact over a number of metrics to fully understand the implications of mission specification changes. The methodology Mission Specifications and Fleet Implications Technique (MS-FIT) identifies stakeholder requirements that will be tracked at either the vehicle or fleet level and leverages them to build an environment that will allow joint evaluation to facilitate increased knowledge about the full implications of mission specification adoption. Additionally laid out is an approach on how to select prospective routes for intermediate stops based on fuel burn and operating cost considerations. Guidance is provided on how to filter down a list of candidate airports to those most viable as well as regions of the world most likely to benefit from intermediate stops. Three sample problems were used to demonstrate the viability of MS-FIT: cruise speed reduction, design mission range reduction, and the combination of speed and range reduction. Each problem was able to demonstrate different implications from the implementation of the different specification changes. Speed reduction can negatively impacts cost while range reduction has consequences to noise at the intermediate airports. The combination of the two draws in negative implications from both even though the environmental benefits are better. Finally, an analysis of some of the assumptions was conducted to examine the sensitivity to the results of speed and range reduction. These include variation in costs, reductions in annual utilization of aircraft, and variation in intermediate stop adoption. Speed reduction is strongly sensitive to increases in crew and maintenance rates while landing fees significantly eat into the benefits of range reduction and intermediate stops. Minor utilization reductions can significantly reduce the viability of speed reduction as the increase in capital costs offset all the savings from fuel reduction while range reduction is a little less sensitive. Intermediate stop variation does not eliminate the benefits of range reduction and even can provide cost savings depending on the design range of the reduced variant but it can have consequences to airport noise to higher traffic airports. With the proposed framework, additional information is available to fully understand the implications with respect to fuel burn, NOₓ emissions, operating cost, capital cost, noise, and safety. This can then inform decision makers on whether pursuing a particular mission specification strategy is advantageous or not.
Stochastic feasibility assessments of orbital propellant depot and commercial launch enabled space exploration architectures

(Georgia Institute of Technology, 2014-11-13) Chai, Patrick R.

The 2010 National Space Policy of the United State of America introduced by President Obama directed NASA to set far reaching exploration milestones that included a crewed mission to a Near Earth Asteroid by 2025 and a crewed mission to Martian orbit by the mid-2030s. The policy was directly influenced by the recommendations of the 2009 Review of United States Human Space Flight Plans Committee, which called for an evolutionary approach to human space exploration and emphasized the criticality of budgetary, programmatic, and program sustainability. One potential method of improving the sustainability of exploration architectures is the utilization of orbital propellant depots with commercial launch services. In any exploration architecture, upwards of seventy percent of the mass required in orbit is propellant. A propellant depot based architecture allows propellant to be delivered in small increments using existing commercial launch vehicles, but will require three to five times the number of launches as compared to the using the NASA planned 70 to 130 metric ton heavy lift launch system. Past studies have shown that the utilization of propellant depots in exploration architectures have the potential of providing the sustainability that the Review of United States Human Space Flight Plans Committee emphasized. However, there is a lack of comprehensive analysis to determine the feasibility of propellant depots within the framework of human space exploration. The objective of this research is to measure the feasibility of a propellant depot and commercial launch based exploration architecture by stochastic assessment of technical, reliability, and economic risks. A propellant depot thermal model was developed to analyze the effectiveness of various thermal management systems, determine their optimal configuration, quantify the uncertainties in the system models, and stochastically compute the performance feasibility of the propellant depot system. Probabilistic cost analysis captured the uncertainty in the development cost of propellant depots and the fluctuation of commercial launch prices, and, along with the cost of launch failures, provided a metric for determining economic feasibility. Probabilistic reliability assessments using the launch schedule, launch reliability, and architecture requirements of each phase of the mission established launch success feasibility. Finally, an integrated stochastic optimization was performed to determine the feasibility of the exploration architecture. The final product of this research is an evaluation of propellant depots and commercial launch services as a practical method to achieving economic sustainability for human space exploration. A method for architecture feasibility assessment is demonstrated using stochastic system metrics and applied in the evaluation of technical, economic, and reliability feasibility of orbital propellant depots and commercial launch based exploration architectures. The results of the analysis showed the propellant depots based architectures to be technically feasible using current commercial launch vehicles, economically feasible for having a program budget less than $4 billion per year, and have launch reliability approaching the best single launch vehicle, Delta IV, with the use of redundant vehicles. These results serve to provide recommendations on the use of propellant depots in exploration architectures to the Moon, Near Earth Objects, Mars, and beyond.The 2010 National Space Policy of the United State of America introduced by President Obama directed NASA to set far reaching exploration milestones that included a crewed mission to a Near Earth Asteroid by 2025 and a crewed mission to Martian orbit by the mid-2030s. The policy was directly influenced by the recommendations of the 2009 Review of United States Human Space Flight Plans Committee, which called for an evolutionary approach to human space exploration and emphasized the criticality of budgetary, programmatic, and program sustainability. One potential method of improving the sustainability of exploration architectures is the utilization of orbital propellant depots with commercial launch services. In any exploration architecture, upwards of seventy percent of the mass required in orbit is propellant. A propellant depot based architecture allows propellant to be delivered in small increments using existing commercial launch vehicles, but will require three to five times the number of launches as compared to the using the NASA planned 70 to 130 metric ton heavy lift launch system. Past studies have shown that the utilization of propellant depots in exploration architectures have the potential of providing the sustainability that the Review of United States Human Space Flight Plans Committee emphasized. However, there is a lack of comprehensive analysis to determine the feasibility of propellant depots within the framework of human space exploration. The objective of this research is to measure the feasibility of a propellant depot and commercial launch based exploration architecture by stochastic assessment of technical, reliability, and economic risks. A propellant depot thermal model was developed to analyze the effectiveness of various thermal management systems, determine their optimal configuration, quantify the uncertainties in the system models, and stochastically compute the performance feasibility of the propellant depot system. Probabilistic cost analysis captured the uncertainty in the development cost of propellant depots and the fluctuation of commercial launch prices, and, along with the cost of launch failures, provided a metric for determining economic feasibility. Probabilistic reliability assessments using the launch schedule, launch reliability, and architecture requirements of each phase of the mission established launch success feasibility. Finally, an integrated stochastic optimization was performed to determine the feasibility of the exploration architecture. The final product of this research is an evaluation of propellant depots and commercial launch services as a practical method to achieving economic sustainability for human space exploration. A method for architecture feasibility assessment is demonstrated using stochastic system metrics and applied in the evaluation of technical, economic, and reliability feasibility of orbital propellant depots and commercial launch based exploration architectures. The results of the analysis showed the propellant depots based architectures to be technically feasible using current commercial launch vehicles, economically feasible for having a program budget less than $4 billion per year, and have launch reliability approaching the best single launch vehicle, Delta IV, with the use of redundant vehicles. These results serve to provide recommendations on the use of propellant depots in exploration architectures to the Moon, Near Earth Objects, Mars, and beyond.
An adaptive atmospheric prediction algorithm to improve density forecasting for aerocapture guidance processes

(Georgia Institute of Technology, 2014-11-12) Wagner, John Joseph

Many modern entry guidance systems depend on predictions of atmospheric parameters, notably atmospheric density, in order to guide the entry vehicle to some desired final state. However, in highly dynamic atmospheric environments such as the Martian atmosphere, the density may vary by as much as 200% from predicted pre-entry trends. This high level of atmospheric density uncertainty can cause significant complications for entry guidance processes and may in extreme scenarios cause complete failure of the entry. In the face of this uncertainty, mission designers are compelled to apply large trajectory and design safety margins which typically drive the system design towards less efficient solutions with smaller delivered payloads. The margins necessary to combat the high levels of atmospheric uncertainty may even preclude scientifically interesting destinations or architecturally useful mission modes such as aerocapture. Aerocapture is a method for inserting a spacecraft into an orbit about a planetary body with an atmosphere without the need for significant propulsive maneuvers. This can reduce the required propellant and propulsion hardware for a given mission which lowers mission costs and increases the available payload fraction. However, large density dispersions have a particularly acute effect on aerocapture trajectories due to the interaction of the high required speeds and relatively low densities encountered at aerocapture altitudes. Therefore, while the potential system level benefits of aerocapture are great, so too are the risks associated with this mission mode in highly uncertain atmospheric environments such as Mars. Contemporary entry guidance systems utilize static atmospheric density models for trajectory prediction and control. These static models are unable to alter the fundamental nature of the underlying state equations which are used to predict atmospheric density. This limits both the fidelity and adaptive freedom of these models and forces the guidance system to retroactively correct for the density prediction errors after those errors have already impacted the trajectory. A new class of dynamic density estimator called a Plastic Ensemble Neural System (PENS) is introduced which is able to generate high fidelity, adaptable density forecast models by altering the underlying atmospheric state equations to better agree with observed atmospheric trends. A new construct called an ensemble echo is also introduced which creates an associative learning architecture, permitting PENS to evolve with increasing atmospheric exposure. The PENS estimator is applied to a numerical guidance system and the performance of the composite system is investigated with over 144,000 guided trajectory simulations. The results demonstrate that the PENS algorithm achieves significant reductions in both the required post-aerocapture performance, and the aerocapture failure rates relative to historical density estimators.