Neutron Detection via Correlation Analysis Independent of Count Rate
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Solution Overview
Problem
Current methods for detecting neutron emission from fissile materials are prone to errors due to variations in background count rates and environmental conditions, leading to incorrect identification of fissile materials.
Innovation Solution
A neutron detection system that normalizes multiplicity count distributions to derive a correlation indicator, allowing for the discrimination of fissile materials by comparing normalized source multiplets to background multiplets, and eliminating count rate factors to accurately assess excess correlation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional neutron detection methods are used to detect neutron emission from fissile materials, then detection capability is provided, but detection accuracy deteriorates due to variations in background count rates and environmental conditions leading to false alarms
Solution Approach 1:
The patent transforms the detection approach by changing from absolute count rate measurement to correlation coefficient measurement. The system calculates correlation coefficients between detected neutron signals and reference signals, thereby changing the measurement parameter from raw count rates (which vary with environmental conditions) to correlation metrics (which are invariant to count rate variations). This resolves the contradiction by making detection accuracy independent of background count rate fluctuations.
Solution Approach 2:
The patent introduces correlation coefficients as an intermediary parameter between the raw neutron detection signals and the final identification decision. Instead of directly comparing absolute count rates, the system uses correlation coefficients as a mediator that eliminates the influence of environmental variations and background radiation, thereby improving both detection accuracy and reducing false alarms.
2Measurement precision
If count rate based detection methods are used, then neutron emission detection is enabled, but measurement reliability worsens due to dependence on background count rate variations
Solution Approach 1:
The patent converts the harmful effect of background radiation and count rate variations into a beneficial feature by using correlation analysis. The system detects that both signal and background vary together in time, and by measuring their correlation coefficient, the background variations become a reference for normalization rather than a source of error. This transforms the harmful count rate dependence into a useful normalization mechanism.
Solution Approach 2:
Instead of trying to eliminate or subtract background count rates (the conventional approach), the patent inverts the approach by using the background variations themselves as a reference signal. The correlation coefficient method exploits the fact that background and signal vary together, turning the background from a nuisance into a useful reference that improves measurement reliability when properly accounted for in the correlation calculation.
Data Source
AI summary
Embodiments are directed to comparison-based methods of conditionally assessing the excess in correlation of an unknown neutron count measurement compared to the correlation present in a data defined as background, and to providing a technical definition of excess correlation intended to properly handle the measured excess correlation. The degree of correlation between an unknown source and background can be used to prevent masking of neutron count data for the source by background radiation.