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Results for “proton single event effects (SEE) testing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Use of Proton SEE Data as a Proxy for Bounding Heavy-Ion SEE Susceptibility

Although heavy-ion single-event effects (SEE) pose serious threats to semiconductor devices in space, many missions face difficulties testing such devices at heavy-ion accelerators. Low-cost missions often find such testing too costly. Even well funded missions face issues testing commercial off the shelf (COTS) due to packaging and integration. Some missions wish to fly COTS systems with little insight into their components. Heavy-ion testing such parts and systems requires access to expensive and hard-to-access ultra-high energy ion accelerators, or significant system modification. To avoid these problems, some have proposed using recoil ions from high-energy protons as a proxy to bound heavy-ion SEE rates.

reliability estimation↗
NASA NTRS2016

What Can We Learn From Proton Recoils about Heavy-Ion SEE Sensitivity?

The fact that protons cause single-event effects (SEE) in most devices through production of light-ion recoils has led to attempts to bound heavy-ion SEE susceptibility through use of proton data. Although this may be a viable strategy for some devices and technologies, the data must be analyzed carefully and conservatively to avoid over-optimistic estimates of SEE performance. We examine the constraints that proton test data can impose on heavy-ion SEE susceptibility.

probabilistic risk assessment↗
NASA NTRS1993

Test report for single event effects of the 80386DX microprocessor

The Jet Propulsion Laboratory Section 514 Single Event Effects (SEE) Testing and Analysis Group has performed a series of SEE tests of certain strategic registers of Intel's 80386DX CHMOS 4 microprocessor. Following a summary of the test techniques and hardware used to gather the data, we present the SEE heavy ion and proton test results. We also describe the registers tested, along with a system impact analysis should these registers experience a single event upset.

Watson, R. Kevin↗
NASA NTRS1997

Antifuse FPGA for Space Applications

This paper presents viewgraphs of Antifuse FPGA (Field Programmable Gate Array) for Space Applications. The topics include: 1) A32140DX TID Test; 2) A1280XL Proton Test; 3) SEU (Single Event Upsets) Rate Calculation; 4) Recent Products Test; 5) A1460A TID (Traveling Ionospheric Disturbances) Test; 6) I100 Proton Test; 7) 100/RHI100 SEU Test; 8) I100/RH100 TID Test; 9) A1020S TID Test; 10) TID Charge Pump Failure; 11) Radiation Testing; and SEE (Single Event Effects) Test Setup.

Wang, Jih-Jong↗
NASA NTRS2018

Lessons and Recommendations for Board-Level Testing with Protons

Protons with sufficiently high energy, provided in a broad field covering on the order of 0.1m2 can be used to perform board-level testing for single event effects (SEE). NASA has used this approach for board-level testing over the last 20 years. Although many difficulties inherent in SEE testing are simplified when using a board-level test, including reduced cost, the method is inherently risky because of the limited value of the collected data and the potential to make critical mistakes when performing SEE testing this way, leading to data of less value. Historically, NASA’s approach to proton board-level testing has been limited to lower criticality applications. However, with users both inside and outside NASA using this method for higher levels of mission assurance, we have put together a set of lessons and recommendations to improve the value of data collected using this method. Focus areas covered include test preparation, test execution, and interpretation of results.

Guertin, Steven M.↗
NASA NTRS2024

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗
NASA NTRS2018

NASA Electronic Parts and Packaging (NEPP) Field Programmable Gate Array (FPGA) Single Event Effects (SEE) Test Guideline Update

The following are updated or new subjects added to the FPGA SEE Test Guidelines manual: academic versus mission specific device evaluation, single event latch-up (SEL) test and analysis, SEE response visibility enhancement during radiation testing, mitigation evaluation (embedded and user-implemented), unreliable design and its affects to SEE Data, testing flushable architectures versus non-flushable architectures, intellectual property core (IP Core) test and evaluation (addresses embedded and user-inserted), heavy-ion energy and linear energy transfer (LET) selection, proton versus heavy-ion testing, fault injection, mean fluence to failure analysis, and mission specific system-level single event upset (SEU) response prediction. Most sections within the guidelines manual provide information regarding best practices for test structure and test system development. The scope of this manual addresses academic versus mission specific device evaluation and visibility enhancement in IP Core testing.

Test guidelines↗
NASA NTRS2018

NASA Electronic Parts and Packaging Field Programmable Gate Array Single Event Effects Test Guideline Update

The following are updated or new subjects added to the FPGA SEE Test Guidelines manual: academic versus mission specific device evaluation, single event latch-up (SEL) test and analysis, SEE response visibility enhancement during radiation testing, mitigation evaluation (embedded and user-implemented), unreliable design and its affects to SEE Data, testing flushable architectures versus non-flushable architectures, intellectual property core (IP Core) test and evaluation (addresses embedded and user-inserted), heavy-ion energy and linear energy transfer (LET) selection, proton versus heavy-ion testing, fault injection, mean fluence to failure analysis, and mission specific system-level single event upset (SEU) response prediction. Most sections within the guidelines manual provide information regarding best practices for test structure and test system development. The scope of this manual addresses academic versus mission specific device evaluation and visibility enhancement in IP Core testing.

Field Programmable Gate Array (FPGA)↗
NASA NTRS2016

Resources for Radiation Test Data

The performance of electronic devices in a space radiation environment is often limited by susceptibility to single-event effects (SEE), total ionizing dose (TID), and displacement damage (DD). Interpreting the results of SEE, TID, and DD testing of complex devices is quite difficult given the rapidly changing nature of both technology and the related radiation issues. Radiation testing is performed to establish the sensitivities of candidate spacecraft electronics to single-event upset (SEU), single-event latchup (SEL), single-event gate rupture (SEGR), single-event burnout (SEB), single-event transients (SETs), TID, and DD effects. Knowing where to search for these test results is a valuable resource for the aerospace engineer or spacecraft design engineer. This poster is intended to be a resource tool for finding radiation test data.

Single Event Effects (SEE)↗