Research Category

Understanding Spray Drift

This research studies how sprays form, deform, and disperse in complex aerodynamic environments. The work connects droplet generation, propeller-wake interaction, and transport physics to build a clearer picture of how drift develops and how it can be measured. Taken together, these papers link fundamental multiphase flow behavior to practical questions in agricultural spray applications.

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Atomization Characterization and Spray Classification

This research examines how agricultural sprays are formed at the moment of atomization, where nozzle geometry, operating pressure, and liquid formulation determine the droplet population that enters the surrounding flow. Using shadowgraph imaging and data-driven interpretation, the work studies how sprays from standard ASABE nozzle classes change across coarse-to-fine atomization regimes and how those changes can be recognized from the spray structure itself. A central contribution is showing that image-based methods can recover meaningful information about atomization state, including nozzle class and pressure condition, without relying exclusively on expensive laboratory droplet-sizing systems.

3 papers
Open Subcategory

Propeller-Wake Spray Transport and Distortion

This research studies what happens when an agricultural spray is released into the highly unsteady, three-dimensional wake of a propeller. Rather than treating the nozzle as an isolated spray source, the work examines how rotor-induced flow reshapes the plume after atomization, altering its width, depth, concentration field, and downstream coherence. Across flat-fan nozzles and rotary atomizers, the studies show that propeller wakes do not merely advect droplets; they actively reorganize the spray, sometimes widening the plume, flattening or contracting its natural shape, and redistributing where deposition-relevant droplets remain concentrated.

3 papers
Open Subcategory
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0188

Students

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Citation
  • 0188. 2022.

Deep Learning Algorithm for Atomization Characterization using Shadowgraph Images

Students
Citation
  • B. N. Narayanan, Joseph Ivarson, Lars Maneck, Sidaard Gunasekaran , “Deep Learning Algorithm for Atomization Characterization using Shadowgraph Images”, 2021 IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, 2021. 10.1109/NAECON49338.2021.9696443

Naecondeeplearningalgorithmforatomizationcharacterizationusingshadowgraphimages

Students

Student contributors are listed where available.

Citation
  • Naecondeeplearningalgorithmforatomizationcharacterizationusingshadowgraphimages. 2021.

Characterization of Agricultural Nozzle Spray Geometry in Propeller Wake

Students
Citation
  • Greenwood, Brock A., Abdul Khan, and Sidaard Gunasekaran. "Characterization of Agricultural Nozzle Spray Geometry in Propeller Wake." In AIAA SCITECH 2025 Forum, p. 2578. 2025. https://doi.org/10.2514/6.2025-2578

Characterization of Rotary Atomizer Spray Geometry Under the Influence of a Propeller

Students
Citation
  • Grenwood, Brock A., Abdul Khan, Megan Bender, and Sidaard Gunasekaran. "Characterization of Rotary Atomizer Spray Geometry Under the Influence of a Propeller." In AIAA SCITECH 2026 Forum, p. 2700. 2026. https://doi.org/10.2514/6.2026-2700

Measuring Agricultural Spray Droplet Distirbutions in Propeller Wake: A Cautionary Tale

Students
Citation
  • Tierney, Ian M., Sidaard Gunasekaran, Kyle Butz, Timothy Anderson, and C. Taber Wanstall. "Measuring Agricultural Spray Droplet Distirbutions in Propeller Wake: A Cautionary Tale." In AIAA SCITECH 2023 Forum, p. 0090. 2023. https://doi.org/10.2514/6.2023-0090