Separated-flow considerations for pressure-atomized combusting monopropellant sprays

AI AA-88-0237 Structure and Mixing Properties of Pressure-Atomized Sprays

An Artificial Neural Network Model for Predicting the Pressure Gradient in Horizontal Oil–Water Separated Flow

In this study, a three–layer artificial neural network (ANN) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. A total of 455 data points were collected from 13 data sources to develop the ANN model. Superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of ...

Continuous-phase Properties of the Near-injector Region of Non- Evaporating Pressure-atomized Sprays

Effects of Ambient Gas Density on the Structure of Pressure-atomized Sprays

A theoretical and experimental study of the dense-spray region of pressure-atomized nonevaporating sprays is described, emphasizing effects of ambient gas density in the atomization breakup regime. Mean liquid volume fraction distributions were measured for 9.5 mm diameter water jets in still air at pressures of 1-8 atm. Mixing was strongly affected by the gaslliquid density ratio and the degre...

An Artificial Neural Network Model for Predicting the Pressure Gradient in Horizontal Oil–Water Separated Flow

In this study, a three–layer artificial neural network (ANN) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. A total of 455 data points were collected from 13 data sources to develop the ANN model. Superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of ...