<p> This project was started in the interest of supplementing existing data on additives to composite solid propellants. The study on the addition of iron and aluminum nanoparticles to composite AP/HTPB propellants was conducted at the Combustion and Energy Systems Laboratory at RPI in the new strand-burner experiment setup. For this study, a large literature review was conducted on history of solid propellant combustion modeling and the empirical results of tests on binders, plasticizers, AP particle size, and additives. </p><p> The study focused on the addition of nano-scale aluminum and iron in small concentrations to AP/HTPB solid propellants with an average AP particle size of 200 microns. Replacing 1% of the propellant's AP with 40-60 nm aluminum particles produced no change in combustive behavior. The addition of 1% 60-80 nm iron particles produced a significant increase in burn rate, although the increase was lesser at higher pressures. These results are summarized in Table 2. The increase in the burn rate at all pressures due to the addition of iron nanoparticles warranted further study on the effect of concentration of iron. Tests conducted at 10 atm showed that the mean regression rate varied with iron concentration, peaking at 1% and 3%. Regardless of the iron concentration, the regression rate was higher than the baseline AP/HTPB propellants. These results are summarized in Table 3.</p>

<p> Within the field of Guidance, Navigation, and Control, the navigation process refers to accurately determining one's position in space. The quest of accurate navigation has shaped human history. Early navigation techniques involved dead reckoning with infrequent measurement updates from line-of-sights to stars or landmarks on the shore. The first practical inertial navigation system (INS) attributed to the German V-2 missile in 1942. In the early 1960's the Kalman filter was developed to aid in the merging of mathematical models and measurement updating. Throughout the space age and continuing into today's remote systems the hardware has made vast improvements; however, the navigation filtering theory has remained mostly stagnant with the multiplicative Extended Kalman Filter (MEKF) still being the workhorse of most modern INS applications. </p><p> In most INS applications, the state vector usually consists of the attitude, position, velocity, and Inertial Measurement Unit (IMU) calibration parameters such as biases and scale factors. Because position-type measurements are usually only given, such as pseudoranges to GPS satellites, the observability of the attitude and gyroscope calibration parameters is weak. Since the early days of employing the MEKF for INS applications, and even modern-day applications, the state errors are defined as a simple algebraic difference between the truth and the estimate. </p><p> It has been argued that a new state-error definition is required in which state-error quantities are defined using elements expressed in a common frame. This provides a realistic framework to describe the actual errors. In previous work, the errors were put into a common frame using the estimated attitude error, which led to the ``geometric EKF'' (GEKF). The GEKF provides extra transport terms, due to error-attitude coupling with the states, in the filter. This previous work focused strictly on attitude estimation, which incorporated only ``body-frame" errors. In this work the GEKF is extended to the INS formulation. Here, errors are considered for both the body frame and the filter's navigation frame. </p><p> In this work, it is shown how these body-frame and navigation-frame errors are related through a similarity transformation. The body-frame error, and the navigation-frame error through this similarity transformation, are first examined in a Planar Inertial Navigation (PIN) problem. For the PIN problem, the MEKF and GEKF algorithms are derived using the same kinematic and measurement models. These algorithms are then studied for a single simulation test case; these results were then verified via Monte Carlo analysis. For this example, it was shown that the body-frame errors had a faster convergence for the GEKF; however, the navigation-frame states showed slower convergence. It is argued here that the direct comparison of these results is inconclusive since both filters employ different error definitions; therefore, the errors being examined utilize a different error metric. It can be stated that the errors realized by the GEKF are more representative of the real errors experienced by the system. </p><p> The body-frame and navigation-frame errors are also used to derive the GEKF for three navigation filters. Specifically, this work examines the absolute Earth-Centered-Earth-Fixed (ECEF) navigation, relative ECEF navigation, and North-East-Down (NED) navigation filters. The counterpart MEKF filters are also derived in this work to illustrate the differences seen in the state matrices due to the additional coupling terms. These filters are also studied via simulation studies. However, now the body-framed vectors do not show faster convergence for the GEKF. This is because the measurement update for this specific example is unaffected by the new error definition. The measurements are not affected by the new error definition because these filters only utilize pseudo-GPS position measurements, and it is shown that the position error still utilizes the old error definition due to its kinematic relation to the velocity error. </p><p> Finally, this work conducts a linearize analysis of a simplified INS where the GEKF in the NED frame is considered. It is shown via a stationary analysis that the fundamental frequencies of the GEKF are the same as those of the MEKF. This is because during the stationary analysis all of the additional coupling terms seen in the state error matrix are neglected due to assumptions made about the vehicle's motion.</p><p>

<p> This thesis studies the feasibility of using neural networks to ''learn" the vortex panel method. This study is motivated by the desire for the rapid and accurate prediction of fluid flows during the preliminary design of engineering systems, where traditional computational fluid dynamics (CFD) are too computationally costly. The results show that a two-layer neural network can estimate the pressure coefficient and elements in the vortex-panel influence-coefficient matrix. However, when the neural-network-predicted influence-coefficient matrix is used to estimate the pressure coefficients, the results are in poor agreement with the baseline prediction, although general trends are captured. </p><p>

<p> The variable pitch quadrotor is not a new concept but has been largely ignored in small unmanned aircraft, unlike the fixed pitch quadcopter which is controlled only by changing the RPM of the motors and only has about 30 minutes of total flight time. The variable pitch quadrotor can be controlled either by the change of the motor RPM or rotor blade pitch angle or by the combination of both. This gives the variable pitch quadrotor potential advantages in payload, maneuverability and long endurance flight. This research is focused on the design methodology for a variable pitch quadrotor using a single motor with potential applications for a long endurance flight. This variable pitch quadcopter uses a single power plant to power all four rotors through a power transmission system. All four rotors have the same rpm but vary the blade pitch angle to control its attitude in the air. A proof of concept variable pitch quadcopter is developed for testing the drivetrain mechanism on the vehicle and evaluating performance of the vehicle through numbers of testing. </p><p>

<p> In today&rsquo;s space industry, satellite formation flying has become a cost-efficient alternative solution for science, on-orbit repair and military time-critical missions. While in orbit, the satellites are exposed to the space environment and unpredictable spacecraft on-board disturbances that negatively affect the attitude control system&rsquo;s ability to reduce relative position and velocity error. Satellites utilizing a PID or adaptive controller are typically tune to reduce the error induced by space environment disturbances. However, in the case of an unforeseen spacecraft disturbance, such as a fault in an IMU, the PID based attitude control system effectiveness will deteriorate and will not be able to reduce the error to an acceptable magnitude. </p><p> In order to address the shortcomings a PID-Extended Memory RNN (EMRNN) adaptive controller is proposed. A PID-EMRNN with a short memory of multiple time steps is capable of producing a control input that improves the translational position and velocity error transient response compared to a PID. The results demonstrate the PID-EMRNN controller ability to generate a faster settling and rise time for control signal curves. The PID-EMRNN also produced similar results for an altitude range of 400 km to 1000 km and inclination range of 40 to 65 degrees angles of inclination. The proposed PID-EMRNN adaptive controller has demonstrated the capability of yielding a faster position error and control signal transient response in satellite formation flying scenario. </p><p>

<p> Carbon-Fiber Reinforced Polymers (CFRPs) provides superior mechanical properties and low weight, enabling their extensive use in the aerospace industry. Susceptibility to internal damage due to out-of-plane loads and poor electrical properties are some of their major challenges that require to be addressed in order to increase the utilization of composites in further aerospace structures. Lightning strikes can lead to catastrophic damage, inflicting high repair and certification costs. Lightning Strike Protection (LSP) solutions such as integration of metallic meshes or foils into the composite structures, even though effective, impose extra costs and hinders the aircraft performance due to the increased weight of the aircraft. </p><p> This research aims at the development of a different LSP solution, by enhancing the electrical conductivity of composite, while maintaining a sufficient degree of mechanical properties. The use of non-woven conductive interlayers was proposed for manufacturing of conductive composites. Highly-conductive, low-aerial-weight carbon veil was utilized to manufacture prepreg-based CF/Epoxy laminates, which are generally toughened, in order to improve their conductivity using vacuum bag only (VBO) and heat-pressing techniques. Further, a bi-functional interlayer of graphene coated Polyamide (PA) was developed using interfacial trapping method. This conductive thermoplastic interlayer was then utilized for manufacturing Benzoxazine (BZ) infused carbon fabric laminate with Vacuum-assisted resin transfer molding (VARTM) method, which acted as a conductive toughener and improves the Inter-laminar Fracture Toughness (ILFT) as well as to increase the electrical conductivity. </p><p> The effects of the incorporation of non-woven interlayers on the electrical conductivity, thermal behavior of composites, and mechanical properties such as shear strength, compressive strength, and the ILFT (Mode-I and Mode-II) were investigated in this study. In both types of composites, an increase in electrical properties, as well as mechanical properties, were observed. The only exception was in the Mode-I ILFT of the CF/Epoxy prepregs, which decreased with the increase of the areal weight of the interleaved carbon veils. The mechanical properties increased in the range of 9%&ndash;138% with the only decrement observed in Mode-I ILFT of CF/Epoxy with carbon veils of 25%. The volume resistivity of the CF/Epoxy samples decreased significantly by approximately 50% due to the incorporation of the conductive interlayer. This added feature was used to develop a structural health monitoring (SHM) procedure. The conductive composite showed an increased sensitivity in detecting the pre-identified damage location in the composites.</p><p>

Prevailing Torque Locking Feature Wear-out

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3623. Adviser: Eric Loth. Includes bibliographical references (leaves 160-165) Available on microfilm from Pro Quest Information and Learning.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3755. Adviser: Jonathan Freund. Includes bibliographical references (leaves 107-110) Available on microfilm from Pro Quest Information and Learning.

<p> A comprehensive survey of available numerical methods and models was performed on the open source computational fluid dynamics solver OpenFOAM version 2.0 for incompressible turbulent bluff body flows. Numerical methods are illuminated using source code for side-by-side comparison. For validation, the accuracy of flow predictions over a sphere in the subcritical regime and delta wing with sharp leading edge is assessed. Solutions show mostly good agreement with experimental data and data obtained from commercial software. A demonstration of the numerical implementation of a dynamic hybrid RANS/LES framework is also presented, including results from test studies. </p>