<p> This dissertation presents a data assimilation method for estimating the physical drivers of the Earth's ionosphere layer through the combination of Global Navigation Satellite System based (GNSS) ionospheric density measurements, Fabry-Perot interferometer (FPI) neutral wind measurements and several empirical models. The main contributions include: 1) Kalman filtering for multi-observation ingestion and multi-state estimation, 2) ingestion of FPI neutral wind measurements, 3) spherical harmonic basis functions for global electric potential estimation and 4) a study of storm-time ion drifts using globally ingested data. </p><p> The thermosphere is a region of Earth's atmosphere (80-1000 km) that contains a balance of particle density and solar ionizing radiation such that an ionosphere can form. During geomagnetic storm events, the ionosphere can be disturbed causing abrupt redistribution of the ionospheric plasma. These disruptions can cause blackouts for radio wave-based communications and navigation systems. Understanding what causes the ionosphere to change is therefore necessary as society becomes more dependent on navigation and communication technologies. </p><p> The first step in understanding the ionosphere is to quantify its physical drivers. Measurements of the ionosphere are limited both spatially and temporally because the region is so vast. Models, on the other hand, provide our best understanding and capability to simulate the ionosphere and its drivers but often fall short in capturing certain phenomena during severe geomagnetic storms. In this work, a data assimilation algorithm called Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE) is further developed to combine both measurements and simulation data sets for estimating ionospheric drivers globally. EMPIRE ingests ionosphere plasma density rate measurements and subtracts model simulation results to produce an observation of the difference between measurements and simulation. EMPIRE then fits basis functions which represent physical drivers to the measurement-simulation discrepancy. The mapping from observation to physical driver happens using the ion continuity governing equation as a model. </p><p> The EMPIRE algorithm was originally developed in 2009 to perform regional data assimilation and used only plasma density measurements. In this work, EMPIRE is modified to use a Kalman filter so measurements and models can be ingested in an efficient and systematic manner. Direct physical driver measurements are provided by FPI neutral wind measurements using the newly developed Kalman filter. This thesis demonstrates the first ever use of FPIs and plasma density measurements in a data assimilative environment. Next, EMPIRE is modified to estimate coefficients to spherical harmonic basis functions rather than power series basis functions. Spherical harmonic functions allow EMPIRE to provide global estimates because they are continuous and orthogonal on a spherical domain (such as Earth). A study is then conducted to ingest global plasma density rate measurements and neutral winds to estimate ion drifts across the globe.</p><p>

<p> The space industry is dominated by chemical propulsion systems that increase the cost of space travel. The dependence of these conventional methods of propulsion on propellants is overcome by using a solar sail that works on the principle of production of thrust based on the solar radiation pressure from the Sun. Solar sails, being a low thrust form of propulsion, need to be optimized to produce reasonable time trajectories. This paper presents the minimum time transfer for a solar sail interplanetary trajectory between Earth and Mars. Therefore, an optimization tool is introduced that can ensure minimum time trajectories for the sail. A hybrid optimization tool is developed between two direct methods, one that uses a global optimization technique and another one that uses a local optimization technique for the problem. Global optimization is carried out using Genetic Algorithm (GA), and local optimization is carried out using a Sparse Nonlinear Optimizer (SNOPT). The GA is run for 300 generations with a population size of 2000, and the SNOPT continues from the point where the GA is terminated using the results from the GA as the initial start point for the optimization. The steering angles of the sail are used as the control parameters. To minimize time, the problem is implemented as a parameter optimization method and the trajectory is discretized into multiple segments. The control angles are defined for each segment of the transfer. The transfer time was optimized to 331 days and on comparing the solution with earlier studies this method provides a better optimal solution. </p><p>

<p> The TNO model, a trailing edge noise prediction method, is validated, modified, and analyzed for various input formats. Two different methods are used to calculate the flow field for this model: Reynolds averaged Navier-Stokes (RANS) and a viscous panel method, XFOIL. It is found that the RANS-based TNO model show good agreement with the experiments but the XFOIL-based TNO was found to overpredict the turbulence kinetic energy and, consequently, the sound pressure level. A modification is made in the XFOIL-based TNO model by substituting Prandtl's mixing length hypothesis from the original model with a new blended model consisting of the mixing length hypothesis and the Cebeci-Smith eddy viscosity model. Twenty-six different test cases are tested with airfoils: NACA 0012, NACA 0015, NACA 64-618, NACA 64₃-418, and DU 96-w-180. RANS input to the TNO model is able to predict the sound pressure spectrum to within 3 dB for the frequency range of 800Hz to 2000Hz in 16 of the 26 cases. The new blended model is found to show clear improvements to the prediction for 14 out of the 26 cases when compared to the original XFOIL input. Moreover, the new XFOIL input was able to predict sound pressure level to within 3 dB for 14 of the 26 cases. Overall, the new proposed model improves the prediction for the XFOIL-based TNO model.</p><p>

Since the beginning of space exploration, the amount of space debris has increased with thedevelopment of new space technologies. In fact, when a collision happens, new space debris aregenerated. Hence, collision risk between space debris and operational satellites rises. The purpose ofa surveillance network system consists of the detection of space objects, their classification and theirtracking. To avoid collisions, space debris objects’ orbit must be computed with sufficient accuracy. The goal of this thesis is the improvement of a pre-existing Space Surveillance and Tracking AnalysisTool. The tool is able to simulate different observation scenarios for radar or optical observer,which can be space-based or ground-based. To enhance the orbit determination, an ExtendedSquare Root Information Filter is implemented and incremented with a Smoother. Smoothers havebeen implemented for the existing filters as well, such as the Extended Kalman Filter and theUnscented Kalman Filter. A bias estimation method was added as part of the OD for all filter types.Additionally, different outlier detection methods were implemented for the automatic detection ofoutliers within the measurement data. To find the optimum orbit determination interval, differentscenarios were considered in LEO, MEO and GEO orbits. The methods were implemented anddifferent scenarios for validation will be discussed. A wide discussion on the methods implementationand their validation on different scenarios is presented, together with a comparison of the orbitdetermination results with the other filters. All the recently implemented features increase the efficiency of the tool to simulate the differentscenarios and enhance the tracking of space debris objects.

<p> Numerical investigations of flow past rotating circular cylinders with and without wires wrapped on the surface of the cylinder were studied using Computational Fluid Dynamics (CFD). The flow characteristics such as flow separation, shedding of the primary and secondary vortices, and drag coefficients were investigated. The software STAR CCM+ from Siemens PLM was used in all investigations. Three-dimensional Unsteady Reynolds Average Navier Stokes (URANS) equations were utilized. The free stream mean velocity was constant at 10 m/sec, which corresponded to an approximate Reynolds number based on cylinder&rsquo;s diameter of 32,000. The results are presented for cylinders with and without wires at varying rotation rates &alpha; of 0, 0.5, and 1. This is represented by &alpha;, the ratio of the tangential velocity at the cylinder to that of the free stream velocity of the flow. As the rotation rate increased from 0 to 1, the drag coefficient for the smooth rotating cylinder reduced, while the drag coefficient for the wire-wrapped cylinder increased. The wire-wrapped cylinder produced significantly higher lift when compared with the corresponding value for the smooth cylinder. Increasing the rotation rate increases the lift and lift to drag ratio.</p><p>

abstract: Advanced aerospace materials, including fiber reinforced polymer and ceramic matrix composites, are increasingly being used in critical and demanding applications, challenging the current damage prediction, detection, and quantification methodologies. Multiscale computational models offer key advantages over traditional analysis techniques and can provide the necessary capabilities for the development of a comprehensive virtual structural health monitoring (SHM) framework. Virtual SHM has the potential to drastically improve the design and analysis of aerospace components through coupling the complementary capabilities of models able to predict the initiation and propagation of damage under a wide range of loading and environmental scenarios, simulate interrogation methods for damage detection and quantification, and assess the health of a structure. A major component of the virtual SHM framework involves having micromechanics-based multiscale composite models that can provide the elastic, inelastic, and damage behavior of composite material systems under mechanical and thermal loading conditions and in the presence of microstructural complexity and variability. Quantification of the role geometric and architectural variability in the composite microstructure plays in the local and global composite behavior is essential to the development of appropriate scale-dependent unit cells and boundary conditions for the multiscale model. Once the composite behavior is predicted and variability effects assessed, wave-based SHM simulation models serve to provide knowledge on the probability of detection and characterization accuracy of damage present in the composite. The research presented in this dissertation provides the foundation for a comprehensive SHM framework for advanced aerospace materials. The developed models enhance the prediction of damage formation as a result of ceramic matrix composite processing, improve the understanding of the effects of architectural and geometric variability in polymer matrix composites, and provide an accurate and computational efficient modeling scheme for simulating guided wave excitation, propagation, interaction with damage, and sensing in a range of materials. The methodologies presented in this research represent substantial progress toward the development of an accurate and generalized virtual SHM framework. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2015

abstract: In today’s day and age, the use of automated technology is becoming increasingly prevalent. Throughout the aerospace industry, we see the use of automated systems in manufacturing, testing, and, progressively, in design. This thesis focuses on the idea of automated structural design that can be directly coupled with parametric Computer-Aided Drafting (CAD) and used to support aircraft conceptual design. This idea has been around for many years; however, with the advancement of CAD technology, it is becoming more realistic. Having the ability to input design parameters, analyze the structure, and produce a basic CAD model not only saves time in the design process but provides an excellent platform to communicate ideas. The user has the ability to change parameters and quickly determine the effect on the structure. Coupling this idea with automated parametric CAD provides visual verification and a platform to export into Finite Element Analysis (FEA) for further verification. / Dissertation/Thesis / Masters Thesis Aerospace Engineering 2017

No description available.

<p> A fourth-order accurate finite volume method for curvilinear grids based on Hermitian interpolation and splines is here presented in one and two dimensions. The finite volume method is derived in detail starting in one dimension and then extended to two dimensions using isoparametric mapping. The method is applied to the quasi-one-dimensional Euler equations through a converging-diverging nozzle as well as the heat conduction equation through a body-fitted non-orthogonal grid. Comparisons are made between the methods presented here and similar techniques in the literature. Lastly, possible ways to improve the method&rsquo;s computational efficiency are discussed. </p><p>

abstract: The presented work in this report is about Real time Estimation of wind and analyzing current wind correction algorithm in commercial off the shelf Autopilot board. The open source ArduPilot Mega 2.5 (APM 2.5) board manufactured by 3D Robotics is used. Currently there is lot of development being done in the field of Unmanned Aerial Systems (UAVs), various aerial platforms and corresponding; autonomous systems for them. This technology has advanced to such a stage that UAVs can be used for specific designed missions and deployed with reliability. But in some areas like missions requiring high maneuverability with greater efficiency is still under research area. This would help in increasing reliability and augmenting range of UAVs significantly. One of the problems addressed through this thesis work is, current autopilot systems have algorithm that handles wind by attitude correction with appropriate Crab angle. But the real time wind vector (direction) and its calculated velocity is based on geometrical and algebraic transformation between ground speed and air speed vectors. This method of wind estimation and prediction, many a times leads to inaccuracy in attitude correction. The same has been proved in the following report with simulation and actual field testing. In later part, new ways to tackle while flying windy conditions have been proposed. / Dissertation/Thesis / M.S. Mechanical Engineering 2014