
doi: 10.1109/23.211340
The authors review various single event effects (SEE) testing and rate prediction methodologies and recommend standard approaches. This discussion is limited to single event upset (SEU) rate prediction for direct-ionization-induced effects. The standard approach being recommended is based partially on a different way of viewing the results of SEU cross-section measurements. The measurements are not measuring a distribution of cross-sections. They are measuring a distribution of device sensitivities, due to differences of sensitive region critical charges and to differences of charge collection. The linear energy transfer (LET), at which 50% of the cell population upsets, corresponds to the charge deposition necessary to upset the median cell in the circuit array. The threshold LET corresponds to the most sensitive region being hit in its most sensitive location, and does not represent the entire array. The shape of the cross-section curve is described by an integral Weibull distribution. The upset rate for a device should then be calculated using the differential rate of each sensitive region, combined with an integral weighting given by the Weibull distribution that describes the measured cross-section curve. >
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 228 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
