Xinhou Wang

Modeling the air-jet flow field of a dual slot die in the melt blowing nonwoven process

An air-jet How field model of the dual slot die in the melt blowing nonwoven process is proposed and solved numerically with the finite difference method. The effects of dual slot die design parameters on velocity and temperature distributions in the melt blowing flow field are investigated. The computation results of the distributions of the x-compo nents of air velocity and air temperature coincide well with our experimental data. The results show that a smaller angle α, a larger slot width e, and a narrower head width f will all result in higher x-components of air velocity and higher air temperatures, which are beneficial to the air drawing of the polymer melt and thus to reduced fiber diameter. The results show the great potential of this research for computer-assisted design in the melt blowing nonwoven technology.

Effects of Processing Parameters on the Fiber Diameter of Melt Blown Nonwoven Fabrics

Our air drawing model of polymers in the melt blowing process is verified by the experimental results obtained with our university’s equipment. The predicted fiber diameters tally well with the experimental data. The effects of the processing parameters on the fiber diameters are further investigated in this paper. We find that a lower polymer flow rate, a higher initial polymer temperature, a higher initial air velocity, and a higher polymer melt flow index can all produce finer fibers, while the effect of the initial air temperature is insignificant. The results reveal the great potential of this research for computer assisted design of the melt blowing technology.

A Novel Approach for Evaluating the Air Permeability of Airbag Fabrics

An approach based on the shock tube experiment is proposed to evaluate the permeability of airbag fabrics. Shock tube experiments were conducted to imitate airbag inflation by fixing an airbag fabric sample near the end of an open driven section. When a plane shock wave impinges the airbag fabric, it will be reflected. Meanwhile, an increase in pressure will form at the front face of the airbag fabric and this will lead to a flow through the fabric, due to the permeable structure of the fabrics. The air permeability of airbag fabrics can therefore be determined by measuring the velocity of the reflected shock wave. It was found that at relatively high pressure the dynamic permeability results from the shock tube experiment were lower than the static results from the conventional permeability testing method. This phenomenon appears to be related to the different influences on the airbag fabric structure of the steady pressurization that occurred in the static experiments and the instantaneous pressurization that occurred in the shock tube experiments.

Effects of processing parameters on electrospun fiber morphology

This study describes the application of a hybrid neuro-fuzzy inference system to control electrospinning process and how to use this approach for developing an electrospun fiber quality prediction system. An adaptive neuro-fuzzy inference system model has been applied to the use of electrospinning process parameters to study the relationship between electrospinning processing parameters and electrospun fiber morphology. Fiber morphology has been predicted and the impact of each processing parameter has been investigated. It was found that four electrospinning process parameters including: polymer solution concentration, spinning distance, applied voltage, and volume flow rate are the most influential factors to the electrospun fiber morphology. It was observed that the relationship existing between electrospinning processing parameters and nanofiber morphology is nonlinear.

Multi-objective optimization of the coat-hanger die for melt-blowing process

In this paper, a multi-objective genetic algorithm based on the numerical simulation of the polymer flow is proposed to optimize the geometry parameters of the coat-hanger die with uniform outlet velocity and minimal residence time. The vector evaluated GA method is used to find the parameter values for obtaining the uniform outlet velocity and minimal residence time, where the manifold angle, the land height and the slot gap are chosen to be the design variables, the outlet velocity and the residence time are obtained by simulating the three-dimensional and isothermal polymer flow in the coat-hanger die. The stochastic universal sampling (SUS) is adopted to select the new population which is representative of a coat-hanger die. The optimal geometry parameters of the coat-hanger die achieved in the 30th generation among 20 individuals of each generation, which showed that the manifold angle and the gap slot were the most influencing design parameter on the coefficient of variation (CV) value of outlet velocity and residence time.

The use of hybrid algorithms to improve the performance of yarn parameters prediction models

Although gradient based Backpropagation (BP) training algorithms have been widely used in Artificial Neural Networks (ANN) models for the prediction of yarn quality properties, they still suffer from some drawbacks which include tendency to converge to local minima. One strategy of improving ANN models trained using gradient based BP algorithms is the use of hybrid training algorithms made of global based algorithms and local based BP algorithms. The aim of this paper was to improve the performance of Levenberg-Marquardt Backpropagation (LMBP) training algorithm, which is a local based BP algorithm by using a hybrid algorithm. The hybrid algorithms combined Differential Evolution (DE) and LMBP algorithms. The yarn quality prediction models trained using the hybrid algorithms performed better and exhibited better generalization when compared to the models trained using the LM algorithms.

Optimal geometry design of the melt‐blowing slot die with high stagnation temperature via the orthogonal array method and numerical simulation

In this paper, a method combining the orthogonal array design and the numerical simulation is proposed to optimize the geometry parameters of the melt‐blowing slot die. An index, the stagnation temperature, is used to evaluate the performance of the slot die. The stagnation temperature is obtained by simulating the subsonic compressible air jet from the melt‐blowing slot die, whereas the optimization is accomplished by the orthogonal array method. Three geometry parameters of the slot die: slot width, nose piece width, and slot angle are investigated. The results show that smaller slot angle and larger slot width will result in a higher stagnation temperature, which is beneficial to the air drawing of the polymer melt and thus to reducing fiber diameter, whereas the effect of nose piece width is insignificant. The optimal geometry parameters of the melt‐blowing slot die achieved in this study are: slot width of 1.5 mm, slot angle of 30°, and nose piece width of 2 mm.

Modeling melt blowing fiber with different polymer constitutive equations

The characteristics of molten polymer plays a major role in fiber formation in the melt blowing (MB) process. In this paper, the Maxwell model and two kinds of the standard linear solid (SLS) models in the bead-viscoelastic element model are proposed for melt blown fiber formation simulation. The fiber diameter, velocity and stress are studied with these different constitutive equations of polymer. The trajectory path of fiber whipping is obtained using numerical simulation and compares with the actual fiber motion which is captured with a high-speed camera. The results present that the Standard Linear Solid Model (SLS) is better than Maxwell model to predict the melt blown fiber’s characteristics under the same air drawing conditions, including fiber diameter, velocity and stress. The whipping motion of the fiber also can be well expressed by SLS constitutive model. The mathematical model with SLS model provides a clear understanding on the mechanism of the formation of microfibers during melt blowing.

Optimization of airflow field via solution blowing for chitosan/PEO nanofiber formation

In this paper, a method combining the orthogonal array design and the numerical simulation is proposed to optimize the geometry parameters of the solution blowing nozzles. The centerline velocity is used to evaluate the performance of the nozzle and the characteristics of airflow fields are calculated. Three geometry parameters of the nozzle: the protrusion length of needle, the diameter of needle and the diameter of nozzle are investigated. The results show that smaller needle diameter and larger nozzle diameter will result in a higher centerline velocity, which is beneficial to fiber attenuation, whereas the effect of needle protrusion length is insignificant. The optimal geometry parameters of the nozzle achieved in this study are that the protrusion length of needle of 5 mm, the diameter of needle of 0.8 mm, and the diameter of nozzle of 4 mm. Furthermore, chitosan/PEO nanofibers are manufactured and studied with different geometry nozzles. This work can provide a better understanding of the controllable fabrication of solution blown nanofibers.

Free surface electrospinning: investigation of the combined effects of process parameters on the morphology of electrospun fibers

In this study, three different free surface electrospinning methods: Splashing electrospinning, spiral coil electrospinning and rotary wires electrospinning methods were explored and compared in terms of fiber morphology (diameter fiber and its distribution) and process parameters. It was found that higher voltage values between 45 kV to 60 kV were necessary for Splashing electrospinning method while voltage values ranged between 50 kV to 70 kV and voltage values between 40 kV and 60 kV were enough for spiral coil and straight wires electrospinning methods, respectively. The real impact of process parameters and the evaluation of the influence of combined various processing parameters on electrospun fiber were undertaken. The results analysis demonstrates that two combined parameters based investigation can help provide insight into how to control and improve the design of the electrospinning process. The fiber diameter and its distribution can be effectively minimized either by controlling the processing parameters to a certain level. The nonlinearity relationship existing between electrospinning process parameters and nanofiber diameter and its distribution has been illustrated. It has also been observed that electric field plays a crucial role in the successful free surface electrospinning.