Subsurface Tunnel Detection via Pressure Model Deviation
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Solution Overview
Problem
Current tunnel detection methods, both active and passive, face challenges such as difficulty in clandestine application, signal penetration issues with depth, interference from urban clutter, high computational burdens, and variability in geologic settings, making it difficult to detect all subterranean tunnels effectively.
Innovation Solution
A passive sensing system that measures and analyzes fluctuations in subsurface soil gas pressure in relation to atmospheric pressure fluctuations, using numerical models to determine when and where tunneling activity has altered the subsurface regime, by calibrating a lumped parameter model to represent local geology and detect changes over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If active detection methods (GPR, seismic interrogation) are used, then detection capability is improved, but signal penetration and imaging resolution diminish with depth
Solution Approach 1:
The patent replaces active mechanical/geophysical interrogation systems (GPR, seismic methods) with a passive acoustic detection system that listens for tunneling sounds. This substitution eliminates signal penetration limitations by not relying on active signals that attenuate with depth, instead using passive acoustic emissions that can be detected through the ground at greater depths.
Solution Approach 2:
The patent introduces acoustic sensors as intermediaries that detect tunneling activity by listening for characteristic sounds of tunneling operations. These sensors act as mediators between the tunneling activity and the detection system, enabling indirect detection without requiring direct line-of-sight or signal penetration through deep subsurface layers.
2Loss of information
If geophysical inversion techniques are used, then 3D imaging of subsurface structure is achieved, but computational burden increases and real-time detection is prevented
Solution Approach 1:
The patent extracts only the essential detection function from complex geophysical inversion systems by using simple acoustic sensors that directly detect tunneling sounds. This extraction eliminates the need for computationally intensive 3D imaging and inversion techniques, providing real-time detection capability with minimal processing requirements.
Solution Approach 2:
The patent employs simple, low-cost acoustic sensors instead of expensive geophysical inversion systems. These sensors provide sufficient detection capability without requiring complex computational resources, enabling deployment in resource-constrained environments and real-time operation.
3Ease of operation
If passive detection methods are used, then clandestine application is improved, but signal strength diminishes as tunnel depth increases
Solution Approach 1:
The patent uses an array of acoustic sensors that can be dynamically deployed and repositioned to optimize detection of tunnels at various depths. The system adapts to different operational conditions by adjusting sensor placement and configuration, maintaining effectiveness across varying tunnel depths while preserving clandestine capabilities.
4Adaptability or versatility
If urban clutter and cultural noise are present, then detection environment is improved for infrastructure monitoring, but signal interpretation is confounded
Solution Approach 1:
The patent uses multiple acoustic sensors in an array configuration, detecting more signals than strictly necessary. This excessive sensing capability allows the system to distinguish tunneling signals from urban clutter and cultural noise through pattern recognition and signal processing, improving interpretation accuracy in complex environments.
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 allows for effective detection of tunneling activity by identifying deviations in subsurface pressure dynamics, indicating the presence or introduction of tunnels, with improved spatial and temporal accuracy, and reduced interference from environmental noise.
Implementation Method 1
measuring and analyzing fluctuations in subsurface soil gas pressure in relation to the fluctuations in surface atmospheric pressure that induce such subsurface fluctuations
Data Source
AI summary
Apparatus and methods for detecting subsurface tunnels employ an aboveground air pressure sensor and one or more subsurface air pressure sensors. The output of the aboveground sensor forms the input to a numerical model whose input parameters account for the effects of depth and permeability and porosity of the earth on the propagation of pressure variations from the surface to the location of each subsurface sensor. Tunnels are detected on the basis of a growing deviation between measured and modeled subsurface pressures using static model input parameters, or on the basis of changes in the model input parameters required to continue accurately approximating measured subsurface pressures, or on the basis of spatially anomalous values of the model input parameters corresponding to multiple horizontally separated subsurface sensors.