Spatially-Resolved Spray Scanning System for Fire Suppression Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for characterizing sprays produced by nozzles, particularly in fire suppression systems, lack precision and accuracy, relying on empirical approaches and failing to effectively model initial spray characteristics, which hinders the development of advanced spray technologies and fire suppression systems.
Innovation Solution
A Spatially-resolved Spray Scanning System (SSSS) that uses minimally intrusive diagnostics and laser-based measurements to perform complete direct scanning of sprays, converting measurements into compact basis functions for accurate representation and prediction of spray dispersion, enabling detailed characterization and modeling of near-field sprays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional empirical methods are used for spray characterization, then the measurement process is simple, but the measurement precision and accuracy are insufficient
Solution Approach 1:
The spray characterization process is divided into multiple measurement stations arranged along the spray trajectory, with each station focusing on specific parameters (drop size, velocity, concentration) at different spatial locations. This segmentation allows comprehensive 3D characterization while maintaining manageable system complexity through modular measurement units.
Solution Approach 2:
A coordinate system transformation and data processing system acts as an intermediary between the distributed measurement stations and the final spray characterization results. This intermediary integrates data from multiple stations, performs spatial registration, and reconstructs the complete 3D spray structure, resolving the complexity of combining multiple measurements into coherent results.
2Measurement precision
If complete direct scanning of sprays is performed to achieve high resolution characterization, then the measurement precision improves, but the measurement time and complexity increase
Solution Approach 1:
The measurement system is pre-configured with multiple stations positioned at predetermined locations along the expected spray trajectory. This preliminary arrangement of measurement points allows the system to capture complete 3D spray characteristics without requiring time-consuming sequential scanning, as all measurement locations are prepared in advance.
Solution Approach 2:
The spray is characterized through periodic sampling at multiple fixed stations simultaneously, rather than continuous scanning. Each station performs rapid measurements at its fixed location, and the periodic data from all stations combined provides complete spatial coverage, reducing total measurement time while maintaining high spatial resolution.
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
The SSSS provides unprecedented accuracy in characterizing initial sprinkler sprays, enabling precise prediction of dispersion and wetting performance, facilitating the development of high-fidelity spray models and improving fire suppression system design.
Implementation Method 1
laser-based drops' parameters measurement sub-system
Implementation Method 2
laser-based measurements of sprays' characteristics
Data Source
AI summary
Near-field spray characteristics are established from local measurements which are acquired by data acquisition sub-system capable of complete scanning of the area (volume) of interest in the spray which uses different laser-based probes (shadowgraphy, PIV, diffraction) to obtain drops related measurements. A mechanical patternator measures volume flux distribution of the spray under study. The measurement data are post-processed to obtain spatially-resolved spray characteristics which are mapped in a spherical coordinate system consistent with the kinematics of the spray. A data compression scheme is used to generate compact analytical functions describing the nozzle spray based on the measurement data. These analytical functions may be useful for initiating the nozzle spray in computational fluid dynamics (CFD) based spray dispersion and fire suppression modeling.