1a.Objectives (from AD-416)
Develop a new method based on control systems simulation for analysis of impact of various factors on in-swath and downwind deposition for improvement of efficiency in aerial chemical application.
1b.Approach (from AD-416)
A new method is proposed to provide valuable information about the significant level of the impact from many factors influencing spray deposition. The most significant factors will be identified using statistical analysis based on the simulation results. With this method the detailed relationship between the total deposition and impact factors such as wind speed, droplet size, and spray release height will be characterized. This characterization will not require actual field testing, but will subsequently be verified under field conditions. Robust results from the simulation will allow determination of optimal droplet size and spray release height that factors in wind speed and direction, providing guidelines for the applicator to achieve the best spray result. The method will be developed based on an existing prototype developed at Texas A&M University (TAMU), for simulation and robustness analysis of dynamic systems. The prototype was originally developed for control system design and analysis. A first principle or black-box model is used to build a simulation model. Based on the simulation result, the main factors that contributed to the system performance are identified using Design of Experiment (DOE). A robust solution can be derived to reduce system variation using Response Surface Method (RSM). The robustness of the new design can be verified using the simulation model. For system test and evaluation, the results of the developed method will be compared with actual field data, and could be used as a guideline for the applicators to achieve best spray result.
A study of factors that can potentially contribute to downwind deposition from aerial spray application was performed. Major contributing factors were narrowed down, and the optimization process was further applied to reduce the negative impact from one of the main factors, wind speed. With the focus on major contributing factors such as wind speed, release height, and droplet size, the optimization process was carried out using analytical drift modeling and software packages. This process resulted in a sub-optimal offset of the flight trajectory in the direction perpendicular to the swath lines to compensate for the wind speed. The effect of the sub-optimal offset, i.e., the swath displacement, was then validated using the Monte Carlo analysis: random values for all the factors were generated; the sub-optimal swath displacement values were used in comparison to the default one half swath width offset; the difference between the default and the sub-optimal offset was analyzed. Statistical analysis of the results showed that using the sub-optimal offset values could greatly reduce downwind drift potential as compared with the default offset value. The sub-optimal offset values achieved results that were very close to the optimal ones. This project has been monitored by the ADODR with emails and phone calls.