Measurements and semi-empirical model describing the onset of powder formation as a function of process parameters in an RF silane–hydrogen discharge

Magnetic field assisted powder mixed electrical discharge machining (MFAPM-EDM) process is a hybrid process machining process which improves the machining characteristics and stability of process using assistive magnetic field and dielectric admixed powder. In this article, study on overcut has been performed on MFAPM-EDM machined Aluminium 6061 alloy. Discharge current, powder concentration, pulse on duration, pulse off duration, and magnetic field strength as process parameters have been varied during experimentation. Box Behnken design approach was employed for experimental design to carry out the experiments. Suitable Semi-empirical model was formulated using dimensional analysis for predicting the overcut. The empirical model developed was also compared with RSM model and was found better in predicting the response. Optimum process parameters for minimal overcut was conducted desirability function approach of RSM. Experimental results divulged discharge current as the most important parameters for overcut as compared to other process parameters on account of higher F-value. Confirmatory experiments revealed good correlation between optimum and experimental results.

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Development of a Semi-Empirical Model for Droplet Size Determination of a Three-Channel Spray Nozzle for Pellet Coating Based on the Optical Method Concept

Processes ◽

10.3390/pr10010086 ◽

2022 ◽

Vol 10 (1) ◽

pp. 86

Author(s):

Sara Vidovič ◽

Alan Bizjak ◽

Anže Sitar ◽

Matej Horvat ◽

Biljana Janković ◽

...

Keyword(s):

Surface Tension ◽

Droplet Size ◽

Process Parameters ◽

Flow Rate ◽

Empirical Model ◽

Optical Method ◽

Spray Nozzle ◽

Production Scale ◽

Dispersion Properties ◽

Semi Empirical

The purpose of this study was to investigate the droplet size obtained with a three-channel spray nozzle typically used in fluid bed devices and to construct a semi-empirical model for prediction of droplet size. With the aid of a custom-made optical method concept, the impact of the type of polymer and solvents used through dispersion properties (viscosity, density, and surface tension), dispersion flow rate, atomization pressure, and microclimate pressure on droplet size was investigated. A semi-empirical model with adequate predictability for calculating the average droplet size (R2 = 0.90, Q2 = 0.73) and its distribution (R2 = 0.84, Q2 = 0.61) was constructed by employing dimensional analysis and design of experiments. Newtonian and non-Newtonian dispersion and process parameters on laboratory and on production scale were included, thereby enabling constant droplet size irrespective of the scale. Based on the model results, it would be possible to scale-up the atomization process (e.g., coating process) from laboratory to production scale in a systematic fashion, regardless of the type of solvent or polymer used. For the system investigated, this can be performed by understanding the dispersion properties, such as viscosity, density, and surface tension, as well as the following process parameters: dispersion flow rate, atomization, and microclimate pressure.

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A Semi-Empirical Model for Predicting Frost Properties

Processes ◽

10.3390/pr9030412 ◽

2021 ◽

Vol 9 (3) ◽

pp. 412

Author(s):

Shao-Ming Li ◽

Kai-Shing Yang ◽

Chi-Chuan Wang

Keyword(s):

Thermal Conductivity ◽

Linear Programming ◽

Numerical Model ◽

Empirical Model ◽

Quantitative Method ◽

Predictive Ability ◽

Dimensionless Temperature ◽

Crystal Shape ◽

Proposed Model ◽

Semi Empirical

In this study, a quantitative method for classifying the frost geometry is first proposed to substantiate a numerical model in predicting frost properties like density, thickness, and thermal conductivity. This method can recognize the crystal shape via linear programming of the existing map for frost morphology. By using this method, the frost conditions can be taken into account in a model to obtain the corresponding frost properties like thermal conductivity, frost thickness, and density for specific frost crystal. It is found that the developed model can predict the frost properties more accurately than the existing correlations. Specifically, the proposed model can identify the corresponding frost shape by a dimensionless temperature and the surface temperature. Moreover, by adopting the frost identification into the numerical model, the frost thickness can also be predicted satisfactorily. The proposed calculation method not only shows better predictive ability with thermal conductivities, but also gives good predictions for density and is especially accurate when the frost density is lower than 125 kg/m3. Yet, the predictive ability for frost density is improved by 24% when compared to the most accurate correlation available.

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