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Confidence Limits Program (CLP) calculates upper and lower confidence limits associated with observed outcome of N independent trials with M occurrences of event of interest. Calculates probability of event of interest for confidence levels of 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 96, 97, 98, and 99 percent. Provides graphical presentation of all limits and how they relate to maximum-likelihood value. Written in IBM PC BASIC.
The recognition of the roles of chlorine and bromine compounds in ozone depletion has led to the regulation or their source gases. Some source gases are expected to be more damaging to the ozone layer than others, so that scientific guidance regarding their relative impacts is needed for regulatory purposes. Parameters used for this purpose include the steady-state and time-dependent chlorine loading potential (CLP) and the ozone depletion potential (ODP). Chlorine loading potentials depend upon the estimated value and accuracy of atmospheric lifetimes and are subject to significant (approximately 20-50 percent) uncertainties for many gases. Ozone depletion potentials depend on the same factors, as well as the evaluation of the release of reactive chlorine and bromine from each source gas and corresponding ozone destruction within the stratosphere.
Traditionally fault models are represented by trees. Recently, digraph models have been proposed (Sack). Digraph models closely imitate the real system dependencies and hence are easy to develop, validate and maintain. However, they can also contain directed cycles and analysis algorithms are hard to find. Available algorithms tend to be complicated and slow. On the other hand, the tree analysis (VGRH, Tayl) is well understood and rooted in vast research effort and analytical techniques. The tree analysis algorithms are sophisticated and orders of magnitude faster. Transformation of a digraph (cyclic) into trees (CLP, LP) is a viable approach to blend the advantages of the representations. Neither the digraphs nor the trees provide the ability to handle heuristic knowledge. An expert system, to capture the engineering knowledge, is essential. We propose an approach here, namely, expert network analysis. We combine the digraph representation and tree algorithms. The models are augmented by probabilistic and heuristic knowledge. CLIPS, an expert system shell from NASA-JSC will be used to develop a tool. The technique provides the ability to handle probabilities and heuristic knowledge. Mixed analysis, some nodes with probabilities, is possible. The tool provides graphics interface for input, query, and update. With the combined approach it is expected to be a valuable tool in the design process as well in the capture of final design knowledge.
The Sample Analysis at Mars (SAM) instrument onboard the Curiosity rover, is specifically designed for in situ molecular and isotopic analyses of martian surface materials and atmosphere. It contributes to the Mars Science Laboratory (MSL) missions primary scientific goal to characterize the potential past, present or future habitability of Mars. In all of the analyses of solid samples delivered to SAM so far, chlorinated organic compounds have been detected above instrument background levels and identified by gas chromatography coupled to mass spectrometry (GC-MS) (Freissinet et al., 2015; Glavin et al., 2013). While some of these may originate from reactions between oxychlorines and terrestrial organic carbon present in the instrument background (Glavin et al., 2013), others have been demonstrated to originate from indigenous organic carbon present in samples (Freissinet et al., 2015). We present here laboratory calibrations that focused on the analyses performed with the MXT-CLP GC column (SAM GC-5 channel) used for nearly all of the GC-MS analyses of the martian soil samples carried out with SAM to date. Complementary to the mass spectrometric data, gas chromatography allows us to separate and identify the species analyzable in a nominal SAM-GC run time of about 21 min. To characterize the analytical capabilities of this channel within the SAM Flight Model (FM) operating conditions on Mars, and their implications on the detection of organic matter, it is required to perform laboratory experimental tests and calibrations on spare model components. This work assesses the SAM flight GC-5 column efficiency, confirms the identification of the molecules based on their retention time, and enables a better understanding of the behavior of the SAM injection trap (IT) and its release of organic molecules. This work will enable further optimization of the SAM-GC runs for additional samples to be analyzed during the MSL mission.