Our company revolves around taking technology from the laboratory and migrating it into real-world applications. Our research has led to the development of a revolutionary spray characterization device, the Spatially-resolved Spray Scanning System (4S), that allows for a complete description of the spray to be developed. Spray angle, droplet size, and detailed spatial data is captured at the rate of 100GB per nozzle. This data is then compressed into a set of physically meaningful basis functions which allows us to predict the nozzle spray and resulting wetted surface in complex environments.

The spray problem is an inherently complex knot to try and solve. It involves resolving a dynamic, 3D, multi-phase flow problem such that it can accurately be modeled using software tools.

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Our approach follows a specific roadmap that allows us to unravel the complexities associated with sprays and to arrive at our destination: the ability to quickly and accurately model sprays and their interaction with the environment and to output 3D visualizations of the all important actual delivered density (ADD).

See below for an overview of the roadmap and our process.

PROCESS: Spray Initiation

The process begins by characterizing the initiation of the spray. A spray nozzle is placed into the spray scanning system and detailed measurements of the spray are made using shadowgraphy, laser, and other techniques. Depending on the nature of the nozzle (tines/slots or not) the characterization may vary in complexity.

 

 

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PROCESS: Derivation of Basis Functions

Next the data is processed and analyzed to derive a set of physically meaningful basis functions which describe the spray. This set of basis functions defines the entirety of each droplet from the nozzle including its size, velocity, and trajectory. Using these basis functions we can completely model the spray nozzle.

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PROCESS: Software

Our software allows, for the first time, visualization of detailed spray patterns, spray dispersion, and wetting performance in complex building configurations. Using the basis functions derived earlier we can compare nozzles, change input pressure, add obstructions, and alter the orientation of the nozzle. Each of these variables impacts the actual delivered density (ADD) of water to the desired surface.