Executive Summary : | Precise droplet size and velocity distribution in the agricultural spray are very much desirable. High precision spraying results extensive economic and environmental benefits. Research in use of agriculture robots having controlled nozzle performance is a need of the present time. Due to droplet drift for cross flow of wind droplet size and velocity plays an essential role in pesticide spray. The nonlinear analysis of primary as well as secondary breakup of the droplets in the presence of cross-flowing gas medium came across in various agricultural sprays especially, in the Drone-sprays. The use of AI to cater to uncertainties in predicting probabilistic droplet size and velocity distribution is also rare in literature which is also considered in the present analysis. The objective of the present proposal is to develop a mathematical model to perform a nonlinear instability analysis of droplets to predict primary as well as secondary breakup of the droplets to assess the final size and velocity distribution of the droplets generated in any agricultural spray. Moreover, the model will be able to track the trajectory of droplet clouds to predict the flight time as well as the distance travelled by the droplets. AI module will be integrated with this numerical model to generate a total predictive module to assess an efficient and effective spray in agriculture. The proposed study consists of four modules. The first part deals with the formation of primary droplets and their velocity distribution using Maximum entropy formulation. The second part deals with the instability of the primary droplets resulting secondary breakup of the droplets. Third part deals with the calculation of the flight time and probable estimation of the spray area depending upon the final droplet size and velocity distribution. The final part develops an AI module using programming language for the precise prediction of the droplet characteristics and suggestion of the nozzle exit condition for an efficient spray. The primary contribution of the present proposal is to develop a theoretical model to predict the droplet size and velocity distribution in various sprays applicable to the agricultural sector. The model will use parameters describing the atomizer exit conditions, i.e. Weber number (We), gas-to-liquid density ratio (ρ), gas-to-liquid velocity ratio (U), and rheological property of the fluid as input. The droplet distribution model is also assisted by AI to cater to various uncertainties related to drone sprays in agriculture. Therefore, it is hoped that the findings will have a broad scientific and technological relevance. |