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Variability of the space radiation environment is investigated with regard to parts categorization for total dose hardness assurance methods. It is shown that it can have a significant impact. A modified approach is developed that uses current environment models more consistently and replaces the design margin concept with one of failure probability.
Radiation Hardness Assurance (RHA) methodologies need to evolve to capitalize on the increased flexibility introduced by new models of space radiation environments. This presentation examines the characteristics of various radiation threats, the sources of error that RHA methodologies seek to control and the contributions of environment models to those errors. The influence of trends in microelectronic device technology is also considered.
Radiation Hardness Assurance (RHA) methodologies against Total Ionizing Dose (TID) degradation impose rigorous statistical treatments for data from a part's Radiation Lot Acceptance Test (RLAT) and/or its historical performance. However, no similar methods exist for using "similarity" data - that is, data for similar parts fabricated in the same process as the part under qualification. This is despite the greater difficulty and potential risk in interpreting of similarity data. In this work, we develop methods to disentangle part-to-part, lot-to-lot and part-type-to-part-type variation. The methods we develop apply not just for qualification decisions, but also for quality control and detection of process changes and other "out-of-family" behavior. We begin by discussing the data used in ·the study and the challenges of developing a statistic providing a meaningful measure of degradation across multiple part types, each with its own performance specifications. We then develop analysis techniques and apply them to the different data sets.
Variability of the solar energetic particle environment is investigated for single-event-burnout reliability of silicon-carbide power metal-oxide-semiconductor field effect transistors. A probabilistic assessment of failure evaluates the benefits of de-rating voltage, shielding, and mission length. The Prediction of Solar particle Yields for Characterizing Integrating Circuits code is used to calculate a cumulative density function for the fluence of the environment. The lethal ion method is then used to determine what proportion of the environment will cause single-event-burnout. The operating voltage determines the lowest linear-energy-transfer particle that will cause single-event-burnout and that should be included in the environment distribution. The shielding and mission length also determine the final environment distribution of the mission fluence. Through calculating the reliability for different operating voltages, shielding, and mission length for a specific device, it is shown that shielding thickness and operating voltage have a large effect on reliability and can be traded off during the design.
Functional models are used to identify possible faults and system-level fault consequences. A risk factor is calculated to evaluate mitigation. The risk factor from different radiation-induced faults is compared with system telemetry from on-orbit data.
SEAM is a useful resource for model-based radiation hardness assurance but can be technically challenging for new users. R-Gentic is a NASA developed website that aims at assisting engineers better understand the radiation concerns in their EEE parts. This work aims at providing an update on an ongoing effort to interface R-Gentic with SEAM. Once integration is completed, R-Gentic can be used to seed new SEAM projects, making project creation easier and more accessible.
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We develop methods for bounding part-to-part variation in TID data. When used in conjunction with statistical radiation environment models, these methods allow development of RHA that deliver estimated piece part reliability for any desired confidence level, moving beyond risk avoidance methodologies based on radiation design margin. Two methods are developed, and their results compared for realistic data.
We develop methods for bounding part-to-part variation in TID data. When used in conjunction with statistical radiation environment models, these methods allow development of RHA that deliver estimated piece part reliability for any desired confidence level, moving beyond risk avoidance methodologies based on radiation design margin. Two methods are developed, and their results compared for realistic data.
Presents a methodology for modeling radiation hardness assurance activities into MBSE throughout the NASA project life cycle. Also includes information about quantitatively and qualitatively modeling radiation-induced failures with system models.
We review the Artemis-I mission and corresponding radiation-hardness assurance (RHA) process. We discuss the RHA methodologies employed, design challenges, culture challenges and some flight data vs. rate estimations.
We review the Artemis-I mission and corresponding radiation-hardness assurance (RHA) process. We discuss the RHA methodologies employed, design challenges, culture challenges and some flight data vs. rate estimations.
The space radiation environment can lead to extremely harsh operating conditions for spacecraft electronic systems. A hardness assurance methodology must be followed to assure that the space radiation environment does not compromise the functionality and performance of space-based systems during the mission lifetime. The methodology includes a definition of the radiation environment, assessment of the radiation sensitivity of parts, worst-case analysis of the impact of radiation effects, and part acceptance decisions which are likely to include mitigation measures.
The space radiation environment can lead to extremely harsh operating conditions for spacecraft electronic systems. A hardness assurance methodology must be followed to assure that the space radiation environment does not compromise the functionality and performance of space-based systems during the mission lifetime. The methodology includes a definition of the radiation environment, assessment of the radiation sensitivity of parts, worst-case analysis of the impact of radiation effects, and part acceptance decisions which are likely to include mitigation measures.
Radiation Hardness Assurance (RHA) is the process of ensuring space system performance in the presence of a space radiation environment. Herein, we present an updated NASA methodology for RHA focusing on content, deliverables and timeframes.
The space radiation environment can lead to extremely harsh operating conditions for on-board electronic box and systems. The characteristics of the radiation environment are highly dependent on the type of mission (date, duration and orbit). Radiation accelerates the aging of the electronic parts and material and can lead to a degradation of electrical performance; it can also create transient phenomena on parts. Such damage at the part level can induce damage or functional failure at electronic box, subsystem, and system levels. A rigorous methodology is needed to ensure that the radiation environment does not compromise the functionality and performance of the electronics during the system life. This methodology is called hardness assurance. It consists of those activities undertaken to ensure that the electronic piece parts placed in the space system perform to their design specifications after exposure to the space environment. It deals with system requirements, environmental definitions, part selection, part testing, shielding and radiation tolerant design. All these elements should play together in order to produce a system tolerant to.the radiation environment. An overview of the different steps of a space system hardness assurance program is given in section 2. In order to define the mission radiation specifications and compare these requirements to radiation test data, a detailed knowledge of the space environment and the corresponding electronic device failure mechanisms is required. The presentation by J. Mazur deals with the Earth space radiation environment as well as the internal environment of a spacecraft. The presentation by J. Schwank deals with ionization effects, and the presentation by T. Weatherford deals with Single particle Event Phenomena (SEP) in semiconductor devices and microcircuits. These three presentations provide more detailed background to complement the sections 3 and 4. Part selection and categorization are discussed in section 5. Section 6 presents the organization of the hardness assurance within a project. Section 7 discusses emerging radiation hardness assurance issues.
A probabilistic total ionizing dose (TID) failure assessment is extended to include survivor data, enabling the bounding of failure probability to a desired confidence level (CL) without failure data. The extension provides an avenue for analyzing microelectronics tested for TID without reaching a failure mode, a scenario often encountered by missions utilizing commercial-off-the-shelf (COTS) technologies. Using the type-I censored likelihood formulation and a realistic upper bound on expected device performance, the failure probability space is bounded by confidence contours within the context of a variable environment. The framework accommodates any type of distribution assumed for the part failure or the environment under consideration. Furthermore, the framework can be utilized pre-emptively to plan future device TID tests, minimizing costs while meeting survival requirements. Heritage data may also be used as survivors to further minimize testing costs when parts are from the same lot, but the amount of constraint derived from heritage is limited. Altogether, the framework enables a formal, mathematically rigorous analysis of radiation tolerant devices tested to a maximum dose, as well as flight heritage, in a hardness assurance methodology.
Radiation Hardness Assurance (RHA) is the process of ensuring space system performance in the presence of a space radiation environment. Herein, we present an updated NASA methodology for RHA focusing on content, deliverables and timeframes.