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In the process of conducting a reliability analysis of a system, quite often the population of interest is not homogenous; consisting of sub-populations which arise as production operations are adjusted, component suppliers are changed, etc. While these sub-populations are each unique in many ways, they also have much in common. It is also common for data to be available from a variety of different test regimes, e.g. environmental testing and fleet maintenance observations. Hierarchical Bayesian methods provide an organized, objective means of estimating the reliability of the individual systems, the sub-population reliability as well as the reliability of the entire population. This paper provides an introduction to a Bayesian approach that can be extended for more complicated situations.

This paper discusses the treatment of uncertainties corresponding to relatively few samples of random-variable quantities. The importance of this topic extends beyond experimental data uncertainty to situations involving uncertainty in model calibration, validation, and prediction. With very sparse samples it is not practical to have a goal of accurately estimating the underlying variability distribution (probability density function, PDF). Rather, a pragmatic goal is that the uncertainty representation should be conservative so as to bound a desired percentage of the actual PDF, say 95% included probability, with reasonable reliability. A second, opposing objective is that the representation not be overly conservative; that it minimally over-estimate the random-variable range corresponding to the desired percentage of the actual PDF. The presence of the two opposing objectives makes the sparse-data uncertainty representation problem an interesting and difficult one.

The Federal Aviation Administration Airworthiness Assurance Nondestructive Inspection Validation Center (FAA-AANC) is currently conducting a detection reliability study pertaining to the detection of cracks in multi-layered aluminum sheets. This paper describes the design, production and characterization of test specimens that are currently being used to conduct third layer Probability of Detection (PoD) experiments. Pertinent aspects of the lap splice joints for Boeing 737 aircraft, Line Numbers 292 - 2565 are included in the test specimens. A preliminary analysis of the data indicates that for some inspectors, traditional measures of performance - in particular PoD curves based on maximum likelihood fit to two-parameter lognormal curve - may be misleading.

This study summarizes the peer-reviewed literature regarding the use of raw pyrolysis liquids (PLs) created from woody biomass as fuels for compression-ignition (CI) engines. First, a brief overview is presented of fast pyrolysis and the potential advantages of PLs as fuels for CI engines. Second, a discussion of the general composition and properties of PLs relative to conventional, petroleum-derived diesel fuels is provided, with emphasis on the differences that are most likely to affect PL performance in CI-engine applications. Next, a synopsis is given of the peer-reviewed literature describing experimental studies of CI engines operated using neat PLs and PLs combined in various ways with other fuels. This literature conclusively indicates that raw PLs and PL blends cannot be used as “drop-in replacements” for diesel fuel in CI engines, which is reflected in part by none of the cited studies reporting successful operation on PL fuels for more than twelve consecutive hours.