Statistical Modeling for Radiation Hardness Assurance: Toward Bigger Data

New approaches to statistical modeling in radiation hardness assurance are discussed. These approaches yield quantitative bounds on flight-part radiation performance even in the absence of conventional data sources. This allows the analyst to bound radiation risk at all stages and for all decisions in the RHA process. It also allows optimization of RHA procedures for the project's risk tolerance

Statistical Methods for Large Flight Lots and Ultra-high Reliability Applications

We present statistical techniques for evaluating random and systematic errors for use in flight performance predictions for large flight lots and ultra-high reliability applications

Evaluating Constraints on Heavy-Ion SEE Susceptibility Imposed by Proton SEE Testing and Other Mixed Environments

We develop metrics for assessing the effectiveness of proton SEE data for bounding heavy-ion SEE susceptibility. The metrics range from simple geometric criteria requiring no knowledge of the test articles to bounds of SEE rates

Statistical Model Selection for TID Hardness Assurance

Radiation Hardness Assurance (RHA) methodologies against Total Ionizing Dose (TID) degradation impose rigorous statistical treatments for data from a part's Radiation Lot Acceptance Test (RLAT) and/or its historical performance. However, no similar methods exist for using "similarity" data - that is, data for similar parts fabricated in the same process as the part under qualification. This is despite the greater difficulty and potential risk in interpreting of similarity data. In this work, we develop methods to disentangle part-to-part, lot-to-lot and part-type-to-part-type variation. The methods we develop apply not just for qualification decisions, but also for quality control and detection of process changes and other "out-of-family" behavior. We begin by discussing the data used in the study and the challenges of developing a statistic providing a meaningful measure of degradation across multiple part types, each with its own performance specifications. We then develop analysis techniques and apply them to the different data sets

A study of uncertainty models in a reverberation chamber at NIST

The reverberation chamber has become a good alternative for over-the-air (OTA) testing of small antennas. Here the uncertainty of total radiated power measurements is evaluated for a reverberation chamber at National Institute of Standards and Technology (NIST), Boulder, Colorado. A procedure for measuring the uncertainty based on the standard deviation of nine different antenna orientations in the RC has been used

StpA protein from Escherichia coli condenses supercoiled DNA in preference to linear DNA and protects it from digestion by DNase I and EcoKI

The nucleoid-associated protein, StpA, of Escherichia coli binds non-specifically to double-stranded DNA (dsDNA) and apparently forms bridges between adjacent segments of the DNA. Such a coating of protein on the DNA would be expected to hinder the action of nucleases. We demonstrate that StpA binding hinders dsDNA cleavage by both the non-specific endonuclease, DNase I, and by the site-specific type I restriction endonuclease, EcoKI. It requires approximately one StpA molecule per 250–300 bp of supercoiled DNA and approximately one StpA molecule per 60–100 bp on linear DNA for strong inhibition of the nucleases. These results support the role of StpA as a nucleoid-structuring protein which binds DNA segments together. The inhibition of EcoKI, which cleaves DNA at a site remote from its initial target sequence after extensive DNA translocation driven by ATP hydrolysis, suggests that these enzymes would be unable to function on chromosomal DNA even during times of DNA damage when potentially lethal, unmodified target sites occur on the chromosome. This supports a role for nucleoid-associated proteins in restriction alleviation during times of cell stress

Bayesian Methods for Bounding Single-Event Related Risk in Low-Cost Satellite Missions

We develop single-event risk Prior probability distributions based on historical and heritage data. The Priors can be used to bound single-event effects risk for testing, part selection and design