Single Event Effect Prediction Model for Space Hardware Trajectories
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Solution Overview
Problem
Current methods for evaluating Single Event Effects (SEEs) on hardware in space are inadequate as they only provide effects for a single slice of time, failing to accurately predict the impact of positively and negatively charged particles on electronic components, leading to difficulties in device design and mission planning.
Innovation Solution
A model that utilizes flux lookup tables, shielding effects, parts models, and trajectory data to determine the probability of device upset by SEEs at multiple hardware levels over time, incorporating expert knowledge on component power states and leveraging parallel computing for efficient simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used to evaluate SEEs, then the evaluation process is simple, but the accuracy and completeness of SEE effects prediction is insufficient
Solution Approach 1:
The patent segments the trajectory into multiple time slices and evaluates SEE effects at different hardware levels (device, board, component) separately. This segmentation allows comprehensive coverage of all hardware levels over time while maintaining manageable complexity through modular evaluation of each segment.
Solution Approach 2:
The patent adds temporal dimension by evaluating SEE effects across multiple time slices rather than a single moment. It also adds hardware level dimension by evaluating at device, board, and component levels simultaneously, transforming a single-point evaluation into a multi-dimensional analysis that comprehensively captures SEE effects.
2Reliability
If comprehensive modeling at multiple hardware levels over time is implemented, then SEE effects prediction accuracy is improved, but computational complexity and resource requirements increase
Solution Approach 1:
The patent performs preliminary actions by pre-segmenting the trajectory into time slices and pre-identifying hardware levels to be evaluated. This preparation enables the subsequent comprehensive evaluation to proceed systematically, improving reliability while managing computational resources through organized preprocessing.
Solution Approach 2:
The patent creates a universal evaluation framework that can assess SEE effects across multiple hardware levels (device, board, component) and multiple time slices using the same methodology. This multi-functional approach ensures comprehensive reliability assessment while avoiding redundant computations through consistent application of the evaluation model.
Data Source
AI summary
Discussed herein are devices, systems, and methods for determining whether to conduct a mission. A method can include partitioning, by processing circuitry configured to implement a model for determining a value representing a probability that operation of an electronic part of a device will be upset by a single event effect (SEE), a trajectory of the device into disjoint time segments. The method can include determining, based on an effective shielding of the device and one or more flux lookup tables (LUTs) for each of the time segments, respective SEE rates experienced by the electronic part for each time segment. The method can include determining, based on the determined respective SEE rates and using the model, the probability. The method can include permitting the device to traverse the trajectory only if the determined probability is less than a specified threshold.