Remote Gas Sensing PoD Modeling for Emission Rate Detection
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Solution Overview
Problem
Existing methods for determining gas emission rate detection sensitivity face challenges due to a multi-dimensional and statistical parameter space that is complex, intractable, and often inaccurate, making it difficult to reliably and accurately estimate emission rates, especially in large geographic areas.
Innovation Solution
A method and system that utilize a remote gas sensor to collect gas concentration measurements, determine true positive anomalous gas concentrations, and generate a generalized probability of detection (PoD) function based on gas flow speed and concentration noise, allowing for the characterization of emission rate detection sensitivity performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine emission rate detection sensitivity, then the measurement process is simple, but the accuracy and reliability are poor due to complex multi-dimensional parameter space
Solution Approach 1:
The patent extracts and isolates the critical parameters (gas flow speed and concentration noise) from the complex multi-dimensional parameter space. By identifying and focusing on these key factors, the system can determine emission rate detection sensitivity without needing to account for all possible environmental and operational variables simultaneously, thus reducing complexity while maintaining precision.
Solution Approach 2:
The patent segments the complex parameter space into distinct, manageable components: gas flow speed parameters and concentration noise parameters. This segmentation allows the system to handle each parameter separately through standardized relationships, transforming the intractable multi-dimensional problem into a series of simpler, solvable relationships that can be processed systematically.
2Area of stationary object
If remote gas concentration measurements are used, then spatial coverage is improved, but measurement accuracy decreases due to path-integrated averaging
Solution Approach 1:
The patent introduces gas flow speed and concentration noise as intermediary parameters that mediate between the path-integrated measurement and the desired point-source emission rate. These intermediaries allow the system to translate the averaged remote sensing data into accurate emission rate estimates by accounting for the effects of gas dispersion and measurement variability along the measurement path.
3Reliability
If multiple environmental and operational parameters are considered, then detection reliability improves, but system complexity and computational burden increase
Solution Approach 1:
The patent changes the approach from considering multiple fixed environmental and operational parameters to using dynamic, measurable parameters (gas flow speed and concentration noise) that automatically adapt to changing conditions. This parameter transformation allows the system to maintain high reliability across varying conditions without requiring complex pre-configured adjustments for each specific environmental scenario.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables reliable and accurate determination of emission rate detection sensitivity by accounting for operational and environmental factors, improving the confidence in gas emission rate measurements and reducing false negative detections.
Implementation Method 1
remote gas sensing techniques, such as light detection and ranging (lidar) and open path spectroscopy systems
Implementation Method 2
active remote gas sensing techniques, such as light detection and ranging (lidar)
Data Source
AI summary
Apparatuses systems and methods for gas emission rate detection sensitivity and probability of detection (PoD) based on emission rate. A measurement system may be characterized by its ability to detect gas plumes as a function of the emission rate of those plumes. The measurement system may be characterized based on a generalized PoD function which expresses PoD relative to emission rate as a function of gas concentration noise and gas flow speed. In an example application, the PoD may be used to estimate a cumulative distribution of gas plumes which were not detected based on a cumulative distribution of measured gas plumes. In another example application, the PoD may be used to refine an estimate for a measured emission rate.