挤出吹塑过程由型坯成型、型坯吹胀与制品冷却三个阶段构成。采用不同的方法对该三阶段的机理问题进行了研究。采用神经网络方法预测了受模口温度和挤出流率影响的型坯成型阶段的膨胀。利用建立起来的神经网络模型预示的膨胀与实验结果很吻合，且可在一定范围内，预示不同工艺条件下型坯的直径膨胀和壁厚膨胀，为型坯的直径和壁厚的在线控制提供了理论依据。基于薄膜近似和neo-Hookean 本构关系，建立了描述型坯自由吹胀的数学模型，并通过实验方法获得了型坯吹胀的瞬态图象。比较发现，理论预示的型坯轮廓分布与实验观察结果较吻合。该模型还可预示型坯的自由吹胀对材料性能、型坯尺寸和工艺条件等的依赖性。基于ANSYS有限元软件，对吹塑制品的三维冷却进行了模拟，预示了制品厚度方向任一位置的瞬态温度分布，并可预示成型工艺参数、制品壁厚、塑料与模具材料的热性能以及吹塑模具冷却的强度与时间等对吹塑制品冷却的影响，这可为进一步分析吹塑制品的显微结构和性能提供温度数据。

基于薄膜近似和neo-Hookean本构关系，建立了描述塑料挤出吹塑中型坯自由吹胀的数学模型。在实验方面，采用视频图像捕获技术获得了吹塑模具型腔内型坯吹胀的瞬态图像。比较发现，理论预示的型坯轮廓分布与实验观察结果较吻合。型坯中部的胀大速率要比两端的大得多，且在很低的吹胀压力（本研究约为20kPa）下即与模具型腔接触。本文还预示了型坯中截面半径对吹胀压力、材料模量和型坯起始壁厚的依赖性。型坯的胀大速率随材料模量或型坯起始壁厚的减小而提高。本文建立的数学模型还可用于预示型坯自由吹胀过程中局部的拉伸比、轴向与周向的局部应力分布以及壁厚分布。

Studies on the melting in a single-screw extruder have mainly concentrated on the Maddock melting mechanism. The dispersive melting mechanism, named by us, is of great practical utility. A six-block physical model is first proposed for the dispersive melting mechanism in the present study. Then nonisothermal non-Newtonian mathematical models for the dispersive and Maddock melting mechanisms are developed. It has been demonstrated that the dispersive melting model has a number of advantages over the Maddock melting model: the mechanical power consumption can be decreased; the polymer temperature profile is more uniform and its average temperature is lower. Furthermore, melting can be accelerated and hence the total melting length shortened.

Self-reinforced polypropylene (PP) sheets have been prepared from melt flow-induced crystallization through a conical slit die fed by a conventional extruder. Their structure and properties, influenced by the die pressure ranging from 20 to 50 MPa and die outlet temperature, are studied by scanning electron microscopy observation, differential scanning calorimetry analyses, tensile strength, and light transmittance measurements. At a die outlet temperature of 1627C and a pressure above 30 MPa, conspicuous increases in the melting peak, tensile strength, and light transmittance (they can be used to characterize the self-reinforcement degree of sheet) are observed. The self-reinforcement degree, however, increases only slightly with increasing pressure as it exceeds 40 MPa. Raising the die outlet temperature from 162 to 1727C results in a further increase in the self-reinforcement degree (for example, a highest tensile strength of 288 MPa) while keeping the pressure at 40 MPa, so bulk PP materials with high properties can be produced from continuous melt extrusion under pressures lower than 40 MPa. Furthermore, the melt temperature plays an important role in determining the properties of self-reinforced polymeric materials. Q 1998 John Wiley & Sons, Inc. J Appl Polym Sci 67: 2111–2118, 1998

A neural network-based model approach is presented in which the effects of the die temperature and flow rate on the diameter and thickness swells of the parison in the continuous extrusion blow molding of high-density polyethylene (HDPE) are investigated. Comparison of the neural network model predictions with experimental data yields very good agreement and demonstrates that the neural network model can predict the parison swells at different processing parameters with a high degree of precision (within 0.001).  2002 Elsevier Science Ltd. All rights reserved.