This work discusses the modeling and optimization of a drip irrigation emitter for reducing activation pressure. Our model formulation focuses on analytically characterizing fluid-structure interactions in an existing 8 liters per hour (lph) pressure-compensating online emitter. A preliminary experimental validation of the resulting model was performed for three different emitter architectures. This model was used as a basis for a genetic algorithm-based optimization algorithm that focused on minimizing activation pressure. The design variables considered in our formulation include, geometric features of the emitter architecture, and practical constraints from manufacturing. We applied our optimization approach to four emitters (with flow rates of 4, 6, 7 and 8.2 lph) and were able to lower activation pressure by more than half in each case. The optimization results for all four emitters were experimentally validated in lab-studies. We performed a more exhaustive validation study for the 8.2 lph emitter with an emitter manufacturer. Results from these experiments (which followed ISO standards) showed that the optimized 8.2 lph emitter had a 75% lower activation pressure when compared to the original emitter design.
Implementation and experimental validation of a robust hybrid direct aperture optimization approach for mixed‐beam radiotherapy
