Area of research
Fluid Flow and Transfer Processes · Mechanical Engineering
Research interest
Research focused on Particle swarm optimization and Solubility, with related work in Extrusion, Artificial neural network, Die swell. Notable publications include 'Prediction of gas solubility in polymers by back propagation artificial neural network based on self-adaptive particle swarm optimization algorithm and chaos theory', 'Solubility prediction of supercritical carbon dioxide in 10 polymers using radial basis function artificial neural network based on chaotic self-adaptive particle swarm...', and 'Solubility prediction of gases in polymers using fuzzy neural network based on particle swarm optimization algorithm and clustering method'.
Comparative analysis of flow factors and crystallinity in conventional extrusion and gas-assisted extrusion
Study on the Melt Rheological Characterization of Micro-Tube Gas-Assisted Extrusion Based on the Cross-Scale Viscoelastic Model
Numerical and experimental studies on the influence of gas pressure on particle size during gas-assisted extrusion of tubes with embedded antibacterial particles
Study on the Dissolution and Diffusion of Supercritical Carbon Dioxide in Polystyrene Melts Based on Adsorption and Diffusion Mechanism
<scp>Formation</scp>mechanism of high‐pressure water penetration induced fiber orientation in overflow water‐assisted injection molded short glass fiber‐reinforced polypropylene
Improved die assembly for gas‐assisted sheet extrusion using different up and down gas layer thicknesses
The Formation Mechanism of the Double Gas Layer in Gas-Assisted Extrusion and Its Influence on Plastic Micro-Tube Formation
Research on Inner Gas Inflation Improvements in Double-layer Gas-assisted Extrusion of Micro-tubes
Solubility and diffusion coefficient of supercritical CO <sub>2</sub> in polystyrene dynamic melt
Experimental and numerical studies for the gas-assisted extrusion forming of polypropylene micro-tube
Solubility prediction of supercritical carbon dioxide in 10 polymers using radial basis function artificial neural network based on chaotic self-adaptive particle swarm optimization and K-harmonic means
Numerical and experimental studies for gas assisted extrusion forming of molten polypropylene
Predictive calculation of carbon dioxide solubility in polymers
Prediction of gas solubility in polymers by back propagation artificial neural network based on self-adaptive particle swarm optimization algorithm and chaos theory
Solubility prediction of gases in polymers using fuzzy neural network based on particle swarm optimization algorithm and clustering method
Prediction of the gas solubility in polymers by a radial basis function neural network based on chaotic self‐adaptive particle swarm optimization and a clustering method