Fabrication of High Thermal Conductivity NARloy-Z-Diamond Composite Combustion Chamber Liner for Advanced Rocket Engines
No abstract available
Bhat, Biliyar N.↗
Engineering topics
Coston, James
Publications and source records attributed to Coston, James.
Probabilistic Classification Using Elemental Abundance Distributions and Lossless Image Compression in Apollo 17 Lunar Dust Samples from Mare Serenitatis
We have previously outlined a strategy for the detection of fossils [Storrie-Lombardi and Hoover, 2004] and extant microbial life [Storrie-Lombaudi and Hoover, 20051 during robotic missions to Mars using co-registered structural and chemical signatures. Data inputs included image lossless compression indices to estimate relative textural complexity and elemental abundance distributions. Two exploratory classification algorithms (principal component analysis and hierarchical cluster analysis) provide an initial tentative classification of all targets. Nonlinear stochastic neural networks are then trained to produce a Bayesian estimate of algorithm classification accuracy. The strategy previously has been successful in distinguishing regions of biotic and abiotic alteration of basalt glass from unaltered samples. [Storrie-Lombardi and Fisk, 2004; Storrie-Lombardi and Fisk, 2004] Such investigations of abiotic versus biotic alteration of terrestrial mineralogy on Earth are compromised by .the difficulty finding mineralogy completely unaffected by the ubiquitous presence of microbial life on the planet. The renewed interest in lunar exploration offers an opportunity to investigate geological materials that may exhibit signs of aqueous alteration, but are highly unlikely to contain contaminating biological weathering signatures. We here present an extension of our earlier data set to include lunar dust samples obtained during the Apollo 17 mission. Apollo 17 landed in the Taurus-Littrow Valley in Mare Serenitatis. Most of the rock samples from this region of the lunar highlands are basalts comprised primarily of plagioclase and pyroxene and selected examples of orange and black volcanic glass. SEM images and elemental abundances (C6, N7, O8, Na11, Mg12, Al13, Si14, P15, S16, Cll7, K19, Ca20, Fe26) for a series of targets in the lunar dust samples are compared to the extant cyanobacteria, fossil trilobites, Orgueil meteorite, and terrestrial basalt targets previously discussed. The data set provides a first step in producing a quantitative probabilistic methodology for geobiological analysis of returned lunar samples or in situ exploration.
Storrie-Lombardi, Michael C.↗
Unlocking the Mystery of Columbia's Tragic Accident Through Materials Characterization
The wing and underbelly reconstruction of Space Shuttle Columbia took place at the Shuttle Landing Facility Hangar after the accident which destroyed STS-107. Fragments were placed on a grid according to their original location on the orbiter. Some Reinforced Carbon-Carbon (RCC) panels of the left wing leading edge and other parts from both leading edges were recovered and incorporated into the reconstruction. The recovered parts were tracked on a database according to a number and also tracked on a map of the orbiter. This viewgraph presentation describes the process of failure analysis undertaken by the Materials and Processes (M&P) Problem Resolution Team. The team started with factual observations about the accident, and identified highest level questions for it to answer in order to understand where on the orbiter failure occured, what component(s) failed, and what was the sequence of events. The finding of Columbia's MADS/OEX data recorder shifted the focus of the team's analysis to the left wing leading edge damage. The team placed particular attention on slag deposits on some of the RCC panels. The presentation lists analysis techniques, and lower level questions for the team to answer.
Shah, Sandeep↗