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This paper is concerned with a series of three important problems on reliability where complete solutions are still unavailable. These problems have all been researched and approximate solutions are outlined. The three areas of interest are 1. The government requirement of assurance of high reliability of complex items where the cost of sampling is extremely high. 2. Confidence intervals for a system in series where component data are available, and 3. Estimation of the parameters of the Weibull distribution when sampling terminates after the rth failure is observed in a sample of size n.

Internal combustion engines are routinely developed using 1D engine simulation tools. A well-known limitation is the accuracy of the turbocharger compressor and turbine sub-models, which rely on hot gas bench-measured maps to characterize performance. Such discrete map data is inherently too sparse to be used directly in simulation, and so a preprocessing algorithm interpolates and extrapolates the data to generate a wider, more densely populated map. Methods used for compressor map interpolation vary. They may be mathematical or physical in nature, but there is no unified approach, except that they typically operate on input map data in SAE format. For decades it has been common practice for turbocharger suppliers to share performance data with engine OEMs in this form. This paper describes a compressor map interpolation technique based on the nondimensional compressor flow and loading coefficients, instead of SAE-format data.