Matching Items (4)

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Modeling Volatiles at the Lunar Poles

Description

The lunar poles have hydrated materials in their permanently shadowed regions (PSRs), also known as lunar cold traps. These cold traps exist because of the Moon’s slight tilt of 1.5,

The lunar poles have hydrated materials in their permanently shadowed regions (PSRs), also known as lunar cold traps. These cold traps exist because of the Moon’s slight tilt of 1.5, which consequently creates these PSRs. In these shadows, the temperature remains cold enough to prevent the sublimation of volatile materials for timescales spanning that of geologic times [Hayne et. al 2015]. PSRs are significant because they create an environment where water ice can exist within the first meter of regolith at the lunar poles, where many cold traps are present. These volatile materials can be observed through a process called neutron spectroscopy. Neutron spectroscopy is a method of observing the neutron interactions caused by galactic and extragalactic cosmic ray proton collisions. Neutron interactions are more sensitive to hydrogen than other elements found in the regolith, and thus are a good indicator of hydrated materials. Using neutron spectroscopy, it is possible to detect the hydrogen in these cold traps up to a meter deep in the regolith, thus detecting the presence of hydrated materials, water, or ice.
For this study, we used the Monte Carlo Neutral Particle Transport Code (MCNP6) to create a homogenous sphere that represented the PSRs on Moon, and then modeled five differing water contents for the lunar regolith ranging from 0-20 percent weight. These percent weights were modeled after the estimates for Shackleton crater, data from Lunar Reconnaissance Orbiter (LRO) mission, and data from Lunar Orbiter Laser Altimeter (LOLA).
This study was created with the LunaH-Map mission as motivation, seeking to exhibit what neutron data might be observed. The LunaH-Map mission is an array of mini-Neutron Spectrometers that will orbit the Moon 8-20 km away from the lunar surface and map the spatial
distribution of hydrogen at the lunar poles. The plots generated show the relationship between neutron flux and energy from the surface of the Moon as well as from 10km away. This data provides insight into the benefits of collecting orbital data versus surface data, as well as illustrating what LunaH-Map might observe within a PSR.

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Date Created
  • 2020-05

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Front End Electronics for Neutron- Gamma Spectrometer Device

Description

With the natural resources of earth depleting very fast, the natural resources of other celestial bodies are considered a potential replacement. Thus, there has been rise of space missions constantly

With the natural resources of earth depleting very fast, the natural resources of other celestial bodies are considered a potential replacement. Thus, there has been rise of space missions constantly and with it the need of more sophisticated spectrometer devices has increased. The most important requirement in such an application is low area and power consumption.

To save area, some scintillators have been developed that can resolve both neutrons and gamma events rather than traditional scintillators which can do only one of these and thus, the spacecraft needs two such devices. But with this development, the requirements out of the readout electronics has also increased which now need to discriminate between neutron and gamma events.

This work presents a novel architecture for discriminating such events and compares the results with another approach developed by a partner company. The results show excellent potential in this approach for the neutron-gamma discrimination and the team at ASU is going to expand on this design and build up a working prototype for the complete spectrometer device.

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Date Created
  • 2017

Systematics of giant impacts in late-stage planet formation and active neutron experiments on the surface of Mars

Description

Part I – I analyze a database of Smoothed Particle Hydrodynamics (SPH) simulations of collisions between planetary bodies and use the data to define semi-empirical models that reproduce remant masses.

Part I – I analyze a database of Smoothed Particle Hydrodynamics (SPH) simulations of collisions between planetary bodies and use the data to define semi-empirical models that reproduce remant masses. These models may be leveraged when detailed, time-dependent aspects of the collision are not paramount, but analytical intuition or a rapid solution is required, e.g. in ‘N-body simulations’. I find that the stratification of the planet is a non-negligible control on accretion efficiency. I also show that the absolute scale (total mass) of the collision may affect the accretion efficiency, with larger bodies more efficiently disrupting, as a function of gravitational binding energy. This is potentially due to impact velocities above the sound speed. The interplay of these dependencies implies that planet formation, depending on the dynamical environment, may be separated into stages marked by differentiation and the growth of planets more massive than the Moon.

Part II – I examine time-resolved neutron data from the Dynamic Albedo of Neutrons (DAN) instrument on the Mars Science Laboratory (MSL) Curiosity rover. I personally and independently developed a data analysis routine (described in the supplementary material in Chapter 2) that utilizes spectra from Monte Carlo N-Particle Transport models of the experiment and the Markov-chain Monte Carlo method to estimate bulk soil/rock properties. The method also identifies cross-correlation and degeneracies. I use data from two measurement campaigns that I targeted during remote operations at ASU. I find that alteration zones of a sandstone unit in Gale crater are markedly elevated in H content from the parent rock, consistent with the presence of amorphous silica. I posit that these deposits were formed by the most recent aqueous alteration events in the crater, since subsequent events would have produced matured forms of silica that were not observed. I also find that active dunes in Gale crater contain minimal water and I developed a Monte Carlo phase analysis routine to understand the amorphous materials in the dunes.

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Date Created
  • 2019

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Limitations of Classical Tomographic Reconstructions from Restricted Measurements and Enhancing with Physically Constrained Machine Learning

Description

This work is concerned with how best to reconstruct images from limited angle tomographic measurements. An introduction to tomography and to limited angle tomography will be provided and a

This work is concerned with how best to reconstruct images from limited angle tomographic measurements. An introduction to tomography and to limited angle tomography will be provided and a brief overview of the many fields to which this work may contribute is given.

The traditional tomographic image reconstruction approach involves Fourier domain representations. The classic Filtered Back Projection algorithm will be discussed and used for comparison throughout the work. Bayesian statistics and information entropy considerations will be described. The Maximum Entropy reconstruction method will be derived and its performance in limited angular measurement scenarios will be examined.

Many new approaches become available once the reconstruction problem is placed within an algebraic form of Ax=b in which the measurement geometry and instrument response are defined as the matrix A, the measured object as the column vector x, and the resulting measurements by b. It is straightforward to invert A. However, for the limited angle measurement scenarios of interest in this work, the inversion is highly underconstrained and has an infinite number of possible solutions x consistent with the measurements b in a high dimensional space.

The algebraic formulation leads to the need for high performing regularization approaches which add constraints based on prior information of what is being measured. These are constraints beyond the measurement matrix A added with the goal of selecting the best image from this vast uncertainty space. It is well established within this work that developing satisfactory regularization techniques is all but impossible except for the simplest pathological cases. There is a need to capture the "character" of the objects being measured.

The novel result of this effort will be in developing a reconstruction approach that will match whatever reconstruction approach has proven best for the types of objects being measured given full angular coverage. However, when confronted with limited angle tomographic situations or early in a series of measurements, the approach will rely on a prior understanding of the "character" of the objects measured. This understanding will be learned by a parallel Deep Neural Network from examples.

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Created

Date Created
  • 2020