Engineering topics

Smotherman, M.

Publications and source records attributed to Smotherman, M..

3 records

NASA NTRS1986

Provably conservative approximations to complex reliability models

Complex models can be the bases for derivation of provably conservative and optimistic reliability models that incorporate a reduced state space and fewer transitions; they accordingly possess solutions that are more cost-effective than those of the original complex models. Design space can thereby be extensively explored without incurring the expense of multiple complex model solutions. A conservative-optimistic pair of derived models produces a band that includes the solution to the complex model. Sensitivity analysis can be performed on this pair of models to determine those parameters of the original model that are most sensitive to change and therefore require further expense in obtaining tighter specifications.

Smotherman, M.↗

NASA NTRS1985

The conservativeness of reliability estimates based on instantaneous coverage

Reliability modeling must take into account two different types of phenomena, including the fault-occurrence behavior and the fault/error-handling behavior of a system. The effectiveness of the fault/error-handling behavior can be captured by instantaneous coverage probabilities. This paper has the objective to show that the assumption of instantaneous coverage leads to conservative predictions of system reliability for systems characterized by relatively long interevent times for fault occurrences and relatively short interevent times for fault/error-handling actions. The importance of this result is related to the fact that it can now be shown that model predictions based on instantaneous coverage are lower bounds on the true system reliability. Attention is given to a semi-Markov reliability model, instantaneous coverage approximations, the proof of conservative prediction, and the computation of coverage probabilities.

Mcgough, J.↗

NASA NTRS1983

Design of the hybrid automated reliability predictor

The design of the Hybrid Automated Reliability Predictor (HARP), now under development at Duke University, is presented. The HARP approach to reliability prediction is characterized by a decomposition of the overall model into fault-occurrence and fault-handling sub-models. The fault-occurrence model is a non-homogeneous Markov chain which is solved analytically, while the fault-handling model is a Petri Net which is simulated. HARP provides automated analysis of sensitivity to uncertainties in the input parameters and in the initial state specifications. It then produces a predicted reliability band as a function of mission time, as well as estimates of the improvement (narrowing of the band) to be gained by a specified amount of reduction in uncertainty.

Geist, R.↗