黄汉雄
高分子材料加工成型(挤出、吹塑、注塑等)机械及其过程的机理和流变学,涉及多种设计理论和方法以及数学、力学等理论和计算机技术
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- 姓名:黄汉雄
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学术头衔:
博士生导师
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学科领域:
机械设计原理与方法
- 研究兴趣:高分子材料加工成型(挤出、吹塑、注塑等)机械及其过程的机理和流变学,涉及多种设计理论和方法以及数学、力学等理论和计算机技术
黄汉雄,1963年生,1984年毕业于原华南工学院。现任华南理工大学教授、博士生导师。主攻方向是高分子材料加工成型(挤出、吹塑、注塑等)机械及其过程的机理和流变学,涉及多种设计理论和方法以及数学、力学等理论和计算机技术,科研工作的特色是以机理研究为基础,促进高分子材料加工成型机械和模具的创新设计和新型高性能材料的制备。首次提出了“聚合物分散熔融理论”,引起国外同行专家相继对分散熔融开展研究;在国内最早、最系统对吹塑机理及技术开展研究,研究成果得到学术界和企业界的重视和引用,使得我国聚合物吹塑方面的理论研究得到可喜的发展。
近年来,主持国家自然科学基金(包括重大项目二级子项目和面向项目)、高校博士学科点专项科研基金、广东省自然科学基金、粤港关键领域重点突破项目、广东省重点科技攻关项目等科研项目21项。共发表论文80余篇(其中被国际三大索引收录30多篇次),出版编著和手册5部,获得中国发明专利1项。因科研和教学等工作成绩突出,入选国家人事部、科技部、教育部等七部委新世纪首届“百千万人才工程”国家级人选(2004年)、广东省高校“千百十工程”省级培养对象(2002年),获得第四届教育部“高校青年教师奖”(2002年)、中国高校科学技术二等奖(2001年,第一完成人)、广东省科学技术三等奖(2001年,第一完成人)、浙江省教学成果奖一等奖(2004年,第二完成人)、国家霍英东教育基金会“第六届高等院校青年教师奖”(1998年)等奖励。
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黄汉雄, 杨晓松
,-0001,():
-1年11月30日
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。
塑料, 吹塑, 型坯, 吹胀
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【期刊论文】HDPE/PA6 blends: parison formation behaviour in extrusion blow molding
黄汉雄, H.-X. Huang∗, C.-M. Liao
Polymer Testing 22(2003)509-513,-0001,():
-1年11月30日
The dependence of the diameter swell and sag of a parison extruded from blends of high-density polyethylene (HDPE)/polyamide-6 (PA6)/compatibilizer on the blend composition and flow rate is determined by analyzing video images of the parison. Among the blends tested, blends with a PA6 concentration of 35% or below exhibit an appreciable swell. A greater degree of sag begins to appear for the blend with a PA6 content of 45%. A neural network approach is applied to the experimental data, leading to a model for predicting the diameter swell profile from new levels of input variables, including the blend composition and flow rate.
Blends, High-density polyethylene, Polyamide-6, Extrusion blow molding, Parison formation, Neural network method
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【期刊论文】Prediction of parison swell in plastics extrusion blow molding using a neural network method
黄汉雄, H.-X. Huang*, C.-M. Liao
Polymer Testing 21(2002)745-749,-0001,():
-1年11月30日
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.
Plastics, Extrusion blow molding, Parison swell, Neural network method
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黄汉雄, HAN-XIONG HUANG
JOURNAL OF MATERIALS SCIENCE LETTERS 18(1999)225-228,-0001,():
-1年11月30日
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【期刊论文】Continuous Extrusion of Self-Reinforced High Density Polyethylene
黄汉雄, HAN-XlONG HUANG*
,-0001,():
-1年11月30日
Continuous extrusion was studied of self-reinforced high density polyethylene (HDPE) sheets from flow-induced crystallization at die pressures varying from 30 to 60 MPa. Their morphology, thermal behavior, tensile strength, and light transmit-tance were tested. Flow fields of a polymer melt through a converging wedge channel were also investigated by direct visual observations in conjunction with a theoretical analysis. The extensional strain rate increased abruptly as the melt approached the exit of the converging channel, this resulting in a higher crystallization rate. So, achieving the crystallization of molecular chains just in front of the exit of the converging channel may favor to extrude the bulk polymeric materials having high properties under lower pressures (e.g., 40 MPa or lower), this having been realized in the present work. The tensile strength of the self-reinforced HDPE sheet prepared at a 40 MPa pressure was enhanced by a factor of 8.
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黄汉雄, HAN-XIONG HUANG
,-0001,():
-1年11月30日
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
polypropylene, self-reinforcement, extrusion, structure and properties
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【期刊论文】Theoretical Modeling of Dispersive Melting Mechanism of Polymers in an Extruder
黄汉雄, HAN-XIONG HUANG* and YU-CHENG PENG
,-0001,():
-1年11月30日
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.
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黄汉雄
,-0001,():
-1年11月30日
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。
塑料, 挤出吹塑, 型坯膨胀, 型坯吹胀, 制品冷却, 神经网络方法, 有限元方法
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黄汉雄, Han-Xiong Huang, * You-Fa Huang and Shu-Lin Yang
,-0001,():
-1年11月30日
The morphology of high-density polyethylene (HDPE)/polyamide-6 (PA-6) blends with different melt-shear-viscosity ratios (VRs), prepared by combining a single-screw extruder with a convergent die was studied. Two different screw geometries, metering and mixing screws, and three screw speeds, 20, 40 and 60 rpm, were evaluated to investigate their effects on the morphology of extruded ribbons. Two mixing screws with low and high shear intensity, respectively, were used. Both the geometry and speed of screw were found to have an important role in the morphological changes of the blends. In contrast to previous studies, the results shown in this work reveal that it is possible to develop a laminar structure of PA-6 in an HDPE matrix with a VR larger than one by controlling the flow fields, through appropriately combining the type and shear intensity of the screw with its speed. A well-developed laminar PA-6 phase with an aspect ratio of about 100 was obtained under the optimum combination.
high-density polyethylene/, polyamide-6 blends, extrusion, laminar morphology, flow fields
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