Blast Wave Reconstruction via Pressure Sensor Data Analysis
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Solution Overview
Problem
Current technologies lack effective methods to quickly identify the location and explosion charge mass of improvised explosive devices (IEDs), which hinders military preparedness, law enforcement investigations, protective gear design, and medical response to IED-related injuries.
Innovation Solution
A system utilizing at least two pressure sensors and a computing system to receive and process sensor data, compute the explosion location and charge mass, and simulate blast loading on subjects, incorporating inverse and forward problem solvers, as well as anthropometric data for injury assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used for identifying IED location and charge mass, then the analysis process is simple, but the identification speed and accuracy are insufficient
Solution Approach 1:
The system segments the complex IED identification problem into multiple components: pressure sensor data collection, blast wave reconstruction, location calculation, and charge mass determination. Each component is processed separately through specialized algorithms, improving overall accuracy while managing system complexity through modular processing stages.
Solution Approach 2:
The system transitions from traditional single-point measurements to multi-dimensional pressure field analysis by deploying multiple pressure sensors in three-dimensional space. This spatial dimensionality enhancement enables precise localization and charge mass calculation through volumetric blast wave reconstruction.
2Loss of time
If rapid identification of IED parameters is implemented, then response time is reduced, but computational complexity increases
Solution Approach 1:
The system performs preliminary blast wave reconstruction and parameter extraction immediately upon receiving pressure sensor data, before full analysis is required. Pre-computed lookup tables and calibrated algorithms enable rapid identification by preparing computational frameworks in advance, reducing real-time processing demands.
Solution Approach 2:
The system replaces traditional mechanical and manual analysis methods with computational algorithms and digital processing. Automated inverse problem solvers and blast wave simulation models substitute for manual calculation, enabling rapid IED parameter identification while managing computational complexity through efficient numerical methods.
3Measurement precision
If detailed blast loading simulation on subjects is performed, then injury prediction accuracy is improved, but computational resources required increase
Solution Approach 1:
The system applies local quality by focusing computational resources on critical body regions and organs most susceptible to blast injury. Rather than simulating entire bodies with uniform detail, the model concentrates high-resolution analysis on vulnerable areas such as the head, thorax, and abdomen, improving injury prediction accuracy while reducing overall computational energy requirements.
Solution Approach 2:
The system utilizes parameter changes by adjusting simulation fidelity dynamically based on blast characteristics and subject distance. For distant or low-energy blasts, simplified models are used; for close-range high-energy events, more detailed tissue-level simulations are activated. This adaptive parameter adjustment maintains accuracy where needed while conserving computational resources.
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 rapid identification of IED locations and charge masses, facilitating forensic analysis, injury prediction, and improved protective measures, enhancing military and medical responses to IED incidents.
Implementation Method 1
receive sensor data from the at least two pressure sensors, the sensor data being generated in response to an explosion blast wave
Data Source
AI summary
A system for reconstruction of an explosion blast loading on a subject can include at least two pressure sensors and a computing system configured to: receive sensor data from the at least two pressure sensors, the sensor data being generated in response to an explosion blast wave; compute an explosion location and explosive charge mass of an explosive that caused the explosion blast wave based on the sensor data; and compute explosion blast loading on a subject from the explosion location and explosive charge mass. The pressure sensors can be configured as wearable pressure sensors or on equipment. The computing of the explosion location and explosive charge mass includes processing the sensor data through an inverse problem solver (IPS); and/or the computing of the explosion blast loading on the subject includes simulating the explosion blast wave with a forward problem solver (FPS).