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This study presents an improved comprehensive atomization model for a pressure swirl atomizer. The model integrates internal flow predictions, linear instability analysis of a swirling annular liquid sheet, primary atomization sub-model, and droplet velocity sub-model. Measurement data combined with the inviscid theory model predict the internal flow, providing liquid sheet velocity and thickness at the atomizer outlet. The dispersion relation of surface disturbances is obtained through linear instability analysis. A primary breakup predictive model for particle size distribution is constructed based on the wavelength and growth rate within the full unstable wavenumber range of the dispersion relation. Assuming uniform circumferential distribution and a normal distribution of spray angles, the droplet velocity is assigned according to the liquid sheet velocity. The model is implemented into Eulerian–Lagrangian simulations as initial conditions for discrete phase droplets to simulate the spray field. Results show the model can accurately predict the Sauter mean diameter with an error of less than 6% and effectively predicts the spray structure and spray cone angle. The dependency of the model on its parameters is also studied, determining that the values of the ligament constant and dispersion angle have an obvious impact on the prediction of Sauter mean diameter and spray structure. [ABSTRACT FROM AUTHOR]

This study presents an improved comprehensive atomization model for a pressure swirl atomizer. The model integrates internal flow predictions, linear instability analysis of a swirling annular liquid sheet, primary atomization sub-model, and droplet velocity sub-model. Measurement data combined with the inviscid theory model predict the internal flow, providing liquid sheet velocity and thickness at the atomizer outlet. The dispersion relation of surface disturbances is obtained through linear instability analysis. A primary breakup predictive model for particle size distribution is constructed based on the wavelength and growth rate within the full unstable wavenumber range of the dispersion relation. Assuming uniform circumferential distribution and a normal distribution of spray angles, the droplet velocity is assigned according to the liquid sheet velocity. The model is implemented into Eulerian–Lagrangian simulations as initial conditions for discrete phase droplets to simulate the spray field. Results show the model can accurately predict the Sauter mean diameter with an error of less than 6% and effectively predicts the spray structure and spray cone angle. The dependency of the model on its parameters is also studied, determining that the values of the ligament constant and dispersion angle have an obvious impact on the prediction of Sauter mean diameter and spray structure.

ABSTRACT The shape of a spray droplet from a flat-fan nozzle in the plant protection sector is similar to a ‘U shape’, the middle particle size being small but the diameter of both sides being too large. So, flat-fan nozzles have the defects of wide droplet size and poor uniformity of droplet size. This paper simulates and tests the impingement nozzle, based on the coupling effect of the jet and impinging stream, so as to improve the droplet size uniformity and droplet spectrum. After jet impingement, it was found that the droplet size of the spray fan surface of the impingement nozzle showed the characteristics of large, uniform and smaller sides. This was beneficial in solving the uneven distribution of droplet size distribution in the field operation of the sprayer. The droplet distribution of the impingement nozzle is more concentrated, forming a narrow droplet spectrum. The experimental results are in good agreement with the results of numerical simulations and theoretical analysis. The impingement nozzle solves the shortcomings of wider fan droplets and smaller particle size uniformity, and provides feasible technical support for developing intelligent precision spray equipment.

Bioenergy grasses such as giant miscanthus ( Miscanthus × giganteus) and switchgrass ( Panicum virgatum L.) are promising alternatives to the traditional coastal bermudagrass [ Cynodon dactylon (L.) Pers.] at spray fields in Eastern North Carolina. The objective of this study was to determine the impact of different harvest practices on yield and nutrient removal of miscanthus and switchgrass in a swine ( Sus scrofa domesticus) lagoon effluent spray field environment. Field trials of grasses under six single-cut and double-cut harvest practices (May/October, June/October, July/October, Aug/October, October only, and December only) were established at three commercial swine farms in Eastern North Carolina in either 2011 or 2012. Throughout the 4-year experimental period (2012-2015), both miscanthus and switchgrass produced significantly higher biomass yield than coastal bermudagrass. Two-cut harvest systems significantly improved the yields of miscanthus and switchgrass relative to a single harvest in December at spray fields. The maximum yields were 24 Mg ha year for miscanthus and 18 Mg ha year for switchgrass. Bioenergy grasses removed more nutrients under two-cut systems than under a single harvest. The significantly greater nutrient removals under two-cut harvest systems would result in lower requirements for receiver crop acreage and are more desirable from a spray field nutrient management perspective. [ABSTRACT FROM AUTHOR]

In the field of forging the production processes are subject to extreme influences. This leads to failures in process steps or part qualities. To guarantee a high product quality and process stability it is necessary to measure and evaluate the process parameters during the manufacturing process. Online monitoring systems are especially required to avoid high scrap costs. In this paper an innovative concept for monitoring the spray field of massive forming processes is presented. So far a practical method to monitor the lubrication process for purpose of quality assurance and process fault diagnosis in forging processes does not exist. With the sensor system developed at the Institute of Forming Technology and Machines a qualitative and quantitative assessment of spray fields used for cooling and lubrication of forging die processes is possible. The sensor system operates on the basis of current flow measurements and is able to realize a local determination of the spray field. Furthermore an artificial neuronal network (ANN) was programmed to collect, evaluate and analyze the signal of the sensors automatically. Such networks have already been proven to detect and analyze process failures. Especially in the analyses of systems depending on many parameters and their interactions with each other ANN offer the advantage to deliver the desired statements on the basis of suitable test series. [ABSTRACT FROM AUTHOR]