• Nuclear Engineering and Technology
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• 제54권11호
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• pp.3985-3995
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• 2022

The emergence of new nanoscale technologies has imposed significant challenges to designing reliable electronic systems in radiation environments. A few types of radiation like Total Ionizing Dose (TID) can cause permanent damages on such nanoscale electronic devices, and current state-of-the-art technologies to tackle TID make use of expensive radiation-hardened devices. This paper focuses on a novel and different approach: using machine learning algorithms on consumer electronic level Field Programmable Gate Arrays (FPGAs) to tackle TID effects and monitor them to replace before they stop working. This condition has a research challenge to anticipate when the board results in a total failure due to TID effects. We observed internal measurements of FPGA boards under gamma radiation and used three different anomaly detection machine learning (ML) algorithms to detect anomalies in the sensor measurements in a gamma-radiated environment. The statistical results show a highly significant relationship between the gamma radiation exposure levels and the board measurements. Moreover, our anomaly detection results have shown that a One-Class SVM with Radial Basis Function Kernel has an average recall score of 0.95. Also, all anomalies can be detected before the boards are entirely inoperative, i.e. voltages drop to zero and confirmed with a sanity check.

• Nuclear Engineering and Technology
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• 제49권8호
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• pp.1589-1599
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• 2017

Field programmable gate arrays (FPGAs) are getting more attention in safety-related and safety-critical application development of nuclear power plant instrumentation and control systems. The high logic density and advancements in architectural features make static random access memory (SRAM)-based FPGAs suitable for complex design implementations. Devices deployed in the nuclear environment face radiation particle strike that causes transient and permanent failures. The major reasons for failures are total ionization dose effects, displacement damage dose effects, and single event effects. Different from the case of space applications, soft errors are the major concern in terrestrial applications. In this article, a review of radiation effects on FPGAs is presented, especially soft errors in SRAM-based FPGAs. Single event upset (SEU) shows a high probability of error in the dependable application development in FPGAs. This survey covers the main sources of radiation and its effects on FPGAs, with emphasis on SEUs as well as on the measurement of radiation upset sensitivity and irradiation experimental results at various facilities. This article also presents a comparison between the major SEU mitigation techniques in the configuration memory and user logics of SRAM-based FPGAs.