Rebekah Austin

The Contribution of Low-Energy Protons to the Total On-Orbit SEU Rate

Low- and high-energy proton experimental data and error rate predictions are presented for many bulk Si and SOI circuits from the 20-90 nm technology nodes to quantify how much low-energy protons (LEPs) can contribute to the total on-orbit single-event upset (SEU) rate. Every effort was made to predict LEP error rates that are conservatively high; even secondary protons generated in the spacecraft shielding have been included in the analysis. Across all the environments and circuits investigated, and when operating within 10% of the nominal operating voltage, LEPs were found to increase the total SEU rate to up to 4.3 times as high as it would have been in the absence of LEPs. Therefore, the best approach to account for LEP effects may be to calculate the total error rate from high-energy protons and heavy ions, and then multiply it by a safety margin of 5. If that error rate can be tolerated then our findings suggest that it is justified to waive LEP tests in certain situations. Trends were observed in the LEP angular responses of the circuits tested. Grazing angles were the worst case for the SOI circuits, whereas the worst-case angle was at or near normal incidence for the bulk circuits.

CubeSats and Crowd-Sourced Monitoring for Single Event Effects Hardness Assurance

New mechanisms of radiation sensitivity, such as low-energy proton SEU, potentially hinder the ability to define part-level failure rates and perform worst-case analysis. Ground-based radiation testing demonstrates sensitivity and is useful for understanding mechanisms, but alone is not enough to quantify error rates. If radiation-induced error rates cannot be obtained through direct integration of the part response with the space environment, validated models must be developed. Models for SEU rate predictions for memories sensitive to low-energy protons have been proposed in a number of recent publications. In this paper, we use a CubeSat platform and crowd-sourced monitoring by the worldwide amateur radio community to measure the on-orbit response of a memory useful for evaluation of these models. We find that even for memories with no discernible proton SEU threshold, classical models for proton rate prediction perform well. This illustrates the capability of small satellite missions to complement ground based tests.

A Framework for Reliability and Safety Analysis of Complex Space Missions

Long duration and complex mission scenarios are characteristics of NASA’s human exploration of Mars, and will provide unprecedented challenges. Systems reliability and safety will become increasingly demanding and management of uncertainty will be increasingly important. NASA’s current pioneering strategy recognizes and relies upon assurance of crew and asset safety. In this regard, flexibility to develop and innovate in the emergence of new design environments and methodologies, encompassing modeling of complex systems, is essential to meet the challenges.

A CubeSat-payload radiation-reliability assurance case using goal structuring notation

CubeSats have become an attractive platform for universities, industry, and government space missions because they are cheaper and quicker to develop than full-scale satellites. One way CubeSats keep costs low is by using commercial off-the-shelf parts (COTS) instead of space-qualified parts. Space-qualified parts are often costlier, larger, and consume more power than their commercial counterparts precluding their use within the CubeSat form-factor. Given typical power budgets, monetary budgets, and timelines for CubeSat missions, conventional radiation hardness assurance, like the use of space-qualified parts and radiation testing campaigns of COTS parts, is not practical. Instead, a system-level approach to radiation effects mitigation is needed. In this paper an assurance case for a system-level approach to mitigate radiation effects of a CubeSat science experiment is expressed using Goal Structuring Notation (GSN), a graphical argument standard. The case specifically looks at three main mitigation strategies for the radiation environment: total ionizing dose (TID) screening of parts, detection and recovery from single-event latch-ups (SEL) and single-event functional interrupts (SEFI). The graphical assurance case presented makes a qualitative argument for the radiation reliability of the CubeSat experiment using part and system-level mitigation strategies.

CubeSat: Real-time soft error measurements at low earth orbits

Vanderbilt has developed a low-cost on-orbit system to assess the radiation reliability and survivability of advanced semiconductor components in space. This system was integrated into the AO-85 CubeSat to enable comparisons between measured data and proton error rate predictions. The Vulcan payload includes the Low-Energy Proton (LEP) Experiment that provides data on the single-event-upset rate of a commercial SRAM. Three additional missions are underway to investigate the upset rate of various technology nodes.

Towards a Framework for Reliability and Safety Analysis of Complex Space Missions

Long duration and complex mission scenarios are characteristics of NASA’s human exploration of Mars, and will provide unprecedented challenges. Systems reliability and safety will become increasingly demanding and management of uncertainty will be increasingly important. NASA’s current pioneering strategy recognizes and relies upon assurance of crew and asset safety. In this regard, flexibility to develop and innovate in the emergence of new design environments and methodologies, encompassing modeling of complex systems, is essential to meet the challenges.

Predicting the vulnerability of memories to muon-induced SEUs with low-energy proton tests informed by Monte Carlo simulations

A method for predicting device vulnerability to muon induced single event upsets (SEUs) using proton tests and Monte Carlo simulations was developed and validated using a 28 nm commercial static random access memory (SRAM). This method replaces testing with muon beams while still incorporating the devices response to stopping charged particles. Monte Carlo simulations are used to relate energy deposition by stopping protons to that of muons. This mapping can be employed to determine the proton test energies required to simulate exposure to a muon environment. This method is superior to simulations since the devices empirical response to proton exposure is used to determine upper and lower particle energy bounds for muon susceptibility. This window of vulnerability can then be used to predict a conservative estimate of the soft error rate for muon exposures.

Outstanding Conference Paper Award: 2015 IEEE Nuclear and Space Radiation Effects Conference

In this work, experimental results are presented on single-bit-upsets (SBU) and multiple-bit-upsets (MBU) on a 45 nm SOI SRAM. The upset cross-sections were obtained with accelerated testing using both protons and heavy ions. The proton upset cross-sections were obtained using proton energies ranging from 1 to 500 MeV and the heavy ion data were obtained using ions with effective linear energy transfer (LET) values from 0.6 to 100 . Overall, the SBU data on the 45 nm SOI SRAM showed upset cross-sections-per-bit that were very similar to the cross-sections-per-bit on a 65 nm SOI SRAM for both heavy ion and proton testing. This result continues a trend that has been observed with advanced SOI CMOS SRAMs. In contrast to the SBU data, the MBU data on the 45 nm SRAM showed significantly higher upset cross-sections relative to the 65 nm SRAM. The higher MBU cross-sections were also expected based upon the closer spacing of the nodes in adjacent cells. While the overall trends were anticipated, the major focus of the paper was to understand a diverse range of single event effects that were contributing to the measured upsets. As a function of the incident proton energy, both scattering events and direct ionization upsets were observed. The data also highlighted the unique upset results that are produced at a 90 degree tilt angle. The MBU data showed a very large dependence on the data stored in the SRAM. The data dependence was understood based upon the layout of the SRAM cells and the MBU upsets produced by strikes in common diffusion regions. A detailed analysis of the MBU data showed that almost all of the MBU events occurred in adjacent cells along the bit-lines of the array. This result is very important since the MBU events along the same bit-line will be effectively corrected by error-correctingcode (ECC) circuits. Thus, the higher overall MBU cross-sections that were observed with technology scaling are not a critical issue in SOI SRAMs that use ECC circuits. David F. Heidel received his B.S. degree in physics from Miami University in 1974, and his M.S. and Ph.D. degrees in physics from The Ohio State University in 1976 and 1980 respectively. In 1980, he joined IBM’s Research Division, at the Thomas J. Watson Research Center in Yorktown Heights, NY, working on Josephson superconducting technology. Since