Gas Plume Distance Estimation via Spatial Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for estimating gas plume emissions are either overly complex due to detailed atmospheric modeling or require direct access to the leak, leading to biases and inefficiencies.
Innovation Solution
Estimating the lateral spatial extent of a gas plume through repeated simultaneous concentration measurements at spatially separated points, using a time-independent plume model that accounts for meandering, allowing for the estimation of plume emission without needing detailed atmospheric knowledge or direct access to the source.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed atmospheric modeling is used to estimate plume emissions, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for plume emission estimation from the complex atmospheric environment. By using multi-point concentration measurements and calculating spatial correlations, the method isolates the plume's lateral extent from the complicated atmospheric conditions, eliminating the need for complex turbulence models while maintaining estimation accuracy.
Solution Approach 2:
The patent creates a simplified representation of the plume's spatial structure by measuring concentration fields at multiple points and computing correlation matrices. This copying approach captures the essential plume geometry without requiring direct modeling of complex atmospheric physics, thus reducing device complexity while preserving measurement precision.
2Measurement precision
If long-term averaging of concentration measurements is used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent segments the plume characterization task into simultaneous multi-point measurements rather than requiring long-term temporal averaging. By measuring concentration at multiple spatial points at the same time and analyzing their spatial correlations, the method achieves accurate plume extent estimation without the time loss associated with prolonged single-point measurements.
Solution Approach 2:
The patent transitions from temporal averaging (one-dimensional time domain) to spatial correlation analysis (multi-dimensional space domain). By measuring concentration fields at multiple spatial points simultaneously and analyzing their correlations, the method captures plume characteristics in the spatial domain, eliminating the need for long measurement durations while maintaining precision.
3Measurement precision
If direct measurement of emission rate by enclosing the leak is used, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent uses concentration measurements at remote spatial points as intermediaries to indirectly determine emission rate. Instead of directly enclosing the leak source, the method measures gas concentrations at multiple points downwind and uses their spatial correlations to infer plume dimensions and emission characteristics, thereby maintaining precision while eliminating the need for direct physical access to the leak.
4Measurement precision
If multi-point concentration measurements are used to estimate plume emission, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent makes the multi-point measurement system universal by using the same concentration sensors and correlation analysis method to achieve multiple objectives: determining plume lateral extent, estimating emission rate, and characterizing plume geometry. This multi-functionality justifies the added complexity by providing comprehensive plume information from a single measurement campaign.
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
This approach provides accurate and efficient estimation of gas plume emissions by leveraging the spatial correlation of concentration measurements, reducing complexity and bias, and allowing for distance estimation to the source without requiring precise atmospheric data or direct access.
Implementation Method 1
The spatial correlation of these concentrations (as can be visualized using a scatter plot of CAj vs. CBj) can be used to estimate the vertical extent of the plume
Implementation Method 2
Repeated simultaneous concentration measurements at spatially separated points can provide information on the lateral spatial extent of the plume
Data Source
AI summary
Repeated simultaneous concentration measurements at spatially separated points are used to provide information on the lateral spatial extent of a gas plume. More specifically the spatial correlations in this data provide this information. Fitting a gas plume model directly to this multi-point data can provide good estimates of total plume emission. The distance between the plume source and the measurement points does not need to be known to provide these estimates. It is also not necessary to perform any detailed atmospheric modeling. These estimates of the lateral spatial extent of a gas plume can also be used to provide a distance estimate to the source of the gas plume.