An application of semiparametric Bayesian isotonic regression to the study of radiation effects in spaceborne microelectronics

作者：Farah Marian; Kottas Athanasios^*; Morris Robin D

来源：Journal of the Royal Statistical Society - Series C: Applied Statistics , 2013, 62(1): 3-24.

DOI：10.1111/j.1467-9876.2012.01052.x

• Cross-section versus linear energy transfer curve
• Dirichlet process prior
• Markov chain Monte Carlo methods
• On-orbit upset rate

This work is concerned with the vulnerability of spaceborne microelectronics to single-event upset, which is a change of state caused by high-energy charged particles in the solar wind or the cosmic ray environment striking a sensitive node. To measure the susceptibility of a semiconductor device to single-event upsets, testing is conducted by exposing it to high-energy heavy ions or protons produced in a particle accelerator. The number of upsets is characterized by the interaction cross-section, which is an increasing function of linear energy transfer. The prediction of the on-orbit upset rate is made by combining the device geometry and cross-section versus linear energy transfer curve with a model for the orbit-specific radiation environment. We develop a semiparametric isotonic regression method for the upset count responses, based on a Dirichlet process prior for the cross-section curve. The methodology proposed allows the data to drive the shape of the cross-section versus linear energy transfer relationship, resulting in more robust predictive inference for the on-orbit upset rate than conventional models based on Weibull or log-normal parametric forms for the cross-section curve. We illustrate the modelling approach with data from two particle accelerator experiments.

• 出版日期2013