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Analysis of hybrid satellite-to-satellite tracking and quantum gravity gradiometry architecture for time-variable gravity sensing missions
The Gravity Recovery and Climate Experiment (GRACE) mission, its follow on (GRACE-FO) and the Gravity-field and steady-state Ocean Circulation Experiment (GOCE) mission have been key contributors to the advancement of the study of Earth's gravity field in the 21st century. The gravity gradiometers on GOCE are limited in their sensitivity and are therefore limited to studying the Earth's static gravity field. However, recent advancements in atomic interferometry have increased the feasibility of implementing this technology to the study of time-variable aspects of the Earth's gravity field, as with the GRACE satellite-to-satellite tracking technology. It is anticipated that these measurement types will provide information about the time-variable gravity field at different wavelengths, and as such a hybrid architecture mission implementing both has been presented. A measurement proof of concept study is performed for this proposed architecture, analyzing the possible improvements over current best time-variable gravity models at mid and small spatial scales and the effects of prominent sources of error.
A series of simulations is performed through an orbit that is nearly polar, nearly circular, with an altitude of 450 km and the satellites spaced 220 km apart. The noises present in the gradiometer and pointing knowledge, which serves as a second form of gradiometer error, are tested in combination at varying levels to gain insight into their impact upon the accuracy of the resulting estimated gravity field. The impact of aliasing error upon this hybrid architecture is also tested and analyzed. The results demonstrate clear improvement over the GRACE-FO architecture when the gradiometer noise is sufficiently small. Even at the largest gradiometer noise levels, the inclusion of the gravity gradient data greatly reduces the impact of aliasing error. At varying noise levels, it is shown that either the gradiometer or attitude determination system can become the limiting factor of the architecture.
This analysis serves to quantify the improvements in gravity field recovery a hybrid architecture can create with both current and under-development technologies.Aerospace Engineerin
Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity
Due to the significant increase in the availability of new data in recent years, as a result of the expansion of available seismic stations, laboratory experiments, and the availability of increasingly reliable synthetic catalogs, considerable progress has been made in understanding the spatiotemporal properties of earthquakes. The study of the preparatory phase of earthquakes and the analysis of past seismicity has led to the formulation of seismicity models for the forecasting of future earthquakes or to the development of seismic hazard maps. The results are tested and validated by increasingly accurate statistical methods. A relevant part of the development of many models is the correct identification of seismicity clusters and scaling laws of background seismicity. In this collection, we present eight innovative papers that address all the above topics. The occurrence of strong earthquakes (mainshocks) is analyzed from different perspectives in this Special Issue
AFIT School of Engineering Contributions to Air Force Research and Technology Calendar Year 1973
This report contains abstracts of Master of Science Theses, Doctoral dissertations, and selected faculty publications completed during the 1973 calendar year at the School of Engineering, Air Force Institute of Technology, at Wright-Patterson Air Force Base, Ohio
AFIT School of Engineering Contributions to Air Force Research and Technology Calendar Year 1973
This report contains abstracts of Master of Science Theses, Doctoral dissertations, and selected faculty publications completed during the 1973 calendar year at the School of Engineering, Air Force Institute of Technology, at Wright-Patterson Air Force Base, Ohio
Ionospheric Multi-Spacecraft Analysis Tools
This open access book provides a comprehensive toolbox of analysis techniques for ionospheric multi-satellite missions. The immediate need for this volume was motivated by the ongoing ESA Swarm satellite mission, but the tools that are described are general and can be used for any future ionospheric multi-satellite mission with comparable instrumentation. In addition to researching the immediate plasma environment and its coupling to other regions, such a mission aims to study the Earth’s main magnetic field and its anomalies caused by core, mantle, or crustal sources. The parameters for carrying out this kind of work are examined in these chapters. Besides currents, electric fields, and plasma convection, these parameters include ionospheric conductance, Joule heating, neutral gas densities, and neutral winds.
Analysis and modeling of structure formation in granular and fluid-solid flows
Granular and multiphase flows are encountered in a number of industrial processes with particular emphasis in this manuscript given to the particular applications in cement pumping, pneumatic conveying, fluid catalytic cracking, CO2 capture, and fast pyrolysis of bio-materials. These processes are often modeled using averaged equations that may be simulated using computational fluid dynamics. Closure models are then required that describe the average forces that arise from both interparticle interactions, e.g. shear stress, and interphase interactions, such as mean drag. One of the biggest hurdles to this approach is the emergence of non-trivial spatio-temporal structures in the particulate phase, which can significantly modify the qualitative behavior of these forces and the resultant flow phenomenology. For example, the formation of large clusters in cohesive granular flows is responsible for a transition from solid-like to fluid-like rheology. Another example is found in gas-solid systems, where clustering at small scales is observed to significantly lower in the observed drag. Moreover, there remains the possibility that structure formation may occur at all scales, leading to a lack of scale separation required for traditional averaging approaches. In this context, several modeling problems are treated 1) first-principles based modeling of the rheology of cement slurries, 2) modeling the mean solid-solid drag experienced by polydisperse particles undergoing segregation, and 3) modeling clustering in homogeneous gas-solid flows. The first and third components are described in greater detail.
In the study on the rheology of cements, several sub-problems are introduced, which systematically increase in the number and complexity of interparticle interactions. These interparticle interactions include inelasticity, friction, cohesion, and fluid interactions. In the first study, the interactions between cohesive inelastic particles was fully characterized for the first time. Next, kinetic theory was used to predict the cooling of a gas of such particles. DEM was then used to validate this approach. A study on the rheology of dry cohesive granules with and without friction was then carried out, where the physics of different flow phenomenology was exhaustively explored. Lastly, homogeneous cement slurry simulations were carried out, and compared with vane-rheometer experiments. Qualitative agreement between simulation and experiment were observed.
Lastly, the physics of clustering in homogeneous gas-solid flows is explored in the hopes of gaining a mechanistic explanation of how particle-fluid interactions lead to clustering. Exact equations are derived, detailing the evolution of the two particle density, which may be closed using high-fidelity particle-resolved direct numerical simulation. Two canonical gas-solid flows are then addressed, the homogeneously cooling gas-solid flow (HCGSF) and sedimenting gas-solid flow (SGSF). A mechanism responsible for clustering in the HCGSF is identified. Clustering of plane-wave like structures is observed in the SGSF, and the exact terms are quantified. A method for modeling the dynamics of clustering in these systems is proposed, which may aid in the prediction of clustering and other correlation length-scales useful for less expensive computations