微注塑成型充模流动中的对流换热行为

微注塑成型中,由于尺度效应,使聚合物熔体与微模具型腔壁面间的对流换热行为与常规注塑成型不同,其对流传热系数亦发生了明显变化。通过采用微型注塑机、温度传感器和微模具等组成的对流换热实验装置,对PP、POM和ABS聚合物熔体,以不同的注射速度填充厚度尺寸为0.510、0.420、0.325 mm,表面粗糙度分别为Ra0.062、0.393、0.695 μm微型腔时的模具温度分布进行测量,获得了模具的热通量,进而求得熔体与型腔壁面间的对流传热系数。结果表明,微尺度下实验聚合物熔体与型腔壁面间的对流传热系数,均随注射速度和型腔表面粗糙度值的增加以及型腔厚度尺寸的减小而明显增大;但聚合物材料性能不同时,其对流传热系数差别也较大。     

充模过程的Level Set两相流模拟

采用Level Set两相流方法模拟了熔体充模过程,避免了处理复杂的边界以及用Ghost方法将熔体内的速度值外推到熔体外的情况。分别对型腔水平中面与垂直中面的充模过程进行了模拟。讨论了不同注射速度、不同注射口数量以及不同Reynolds数对充模过程的影响,得出了不同时刻各种情况下熔体界面的位置与充模过程刚结束时型腔内的压力分布,分析了熔体在型腔内运动的不同阶段的特点及形成不同阶段的原因。结果表明,在注射口宽度与型腔宽度相差不大的情况下,如果采用中低速充模,则整个充模运动过程以比较平稳的扩展性运动为主,充模较完全,熔体不发生破裂,制件效果较好。充模速度越大,熔体达到平稳流动的时间越短,充模过程越短。数值模拟结果与实验结果一致,同时表明Level Set两相流方法在求解拓扑性质发生较大变化问题时具有很大的优势。     

蒸汽加热变模温注射成型数值模拟与结果分析

采用Moldflow软件对变模温注射成型过程进行数值模拟。利用蒸汽加热和冷却水冷却的变模温注塑工艺,研究不同蒸汽加热时间下注塑位置处压力以及制件冷凝层的变化规律,同时分析了制件表面和模具型腔表面的热响应规律。结果表明,相比于传统注射成型工艺过程,变模温注射成型通过提高注塑充填过程中模具温度,使得制件冷凝层出现在充填阶段之后;随着模具加热时间从10、15、25 s增加到40 s,注塑位置处最大注射压力从87.0608、84.6064、79.6863 MPa减小到74.4342 MPa,大大提高了熔体注塑充填过程中的充填能力;通过不同的蒸汽加热时间,制件表面和模具型腔表面可以获得不同的温度值,同时通过模拟获得了传热系数对制件表面温度的影响。     

气体辅助注塑在彩电外壳中的应用

研究彩电外壳注塑和气体辅助注塑充模过程的计算机模拟和实际生产。应用动态应力流变仪测试材料流变性质,得到模拟所需n、B、τ、β、T_b等5个参数。考察熔体注射温度、注射时间、入口位置、材料性质对充模过程的影响,得到优化充模结果;还考察了气体辅助注塑过程熔体预注射量、气体注射压力对充模过程的影响。结果表明,气体辅助注塑成型新工艺采用三浇口,熔体适宜预注入量为95％,注射温度230℃,注射时间5s,用幂律指数n较小的聚合物。     

注塑试样制备过程中注射速率的设定方法

注射速率表示塑料熔体在模腔内流动的快慢程度,对注塑试样的性能有很大影响。提出在注塑试样制备的注射阶段,熔体在模腔内应为流动状态,并应采用体积转换的方式确定模塑体积。在确定了正确的模塑体积基础上,通过控制螺杆的注射速度调整熔体的注射时间,当该注射时间达到根据标准公式计算的结果时,熔体在模腔内的注射速率则符合标准的要求。该方法的注射速率和注射压力为函数关系,注射压力在试样制备中不再是主要的影响因素,亦不能单独调整注射压力改变注塑试样的某项测试性能。该方法将注射过程与聚合物熔体的“流动”行为相关联,确保了注塑试样制备中的科学性和规范性,进而提高了重复性和再现性水平。     

聚合物熔体流变性能对气辅注塑工艺的影响

应用ＨｅｌｅＳｈａｗ物理模型和改进的Ｃｒｏｓ流变模型及有限元算法对５种聚丙烯的气辅注塑过程进行模拟,研究不同聚丙烯材料在充模速度相同的条件下的压力及锁模力变化规律。结果表明,气辅注塑在气体注射后与传统注塑有较大差异,所需压力、锁模力均比传统注塑有显著降低,且聚合物的熔体流动速率越小,气体注射后产生的压力降越大,表明在生产中应尽可能选用高熔体流动速率树脂以利于气辅注塑工艺。     

气体辅助注射在彩电外壳中的应用

研究彩电外壳注塑和气体辅助注塑充模过程的计算机模拟和实际生产。应用动态应力流变仪测试材料流变性质,得到模拟所需ｎ,Ｂ,τ、β,Ｔｂ等５个参数。考虑熔体注射温度,注射时间,入口位置,材料性质对充模过程的影响,得到优化充模结果：结果表明,气体辅助注射成型新工艺采用三浇口,熔体适宜预注入量为９５％,注射温度２３０℃,注射时间５ｓ,用幂律指数ｎ较小的聚合物。     

计算机模拟狭缝口模截面塑料熔体流动行为

采用有限元方法分析了狭缝口模截面内塑料熔体的流动状态，实现的过程是通过MATLAB编程．对比了矩形口模和改进口模在速度分布的差异和对流率的影响，并将计算分析结果直观地以图形、图像显示出来。     

夹芯注塑成型过程的计算机可视化模拟分析--材料粘度与工艺参数对芯层熔体穿透深度的影响

采用Moldflow公司MPI软件中的Co-injection分析模块，对夹芯注塑成型过程进行动态模拟分析；以揭示材料粘度以及工艺参数对夹芯注塑成型过程中芯层熔体穿透深度的影响规律。结果发现，芯层熔体穿透深度值随芯／壳层熔体粘度比R值的减小而增大，这主要与芯层和壳层熔体的相对流动能力有关；此外，在工艺参数中，改变熔体注射速度对芯层熔体穿透深度的影响较为突出，而模温和熔体温度对芯层熔体穿透深度的影响相对较弱。     

聚保物熔体流变性能在气辅注塑工艺的影响

应用Ｈｅｌｅ－Ｓｈａｗ物理模型和改进的Ｃｒｏｓｓ流变模型及有限元算法对５种聚丙烯的气辅注塑过程进行了模拟，研究了不同聚丙烯材料在充填速度相同的条件下的压力及锁模力变化规律。结果表明，气辅注塑在气体注射后与传统注塑有较大差异，所需压力，锁模力均比传统注塑有显著降低，且聚合物的熔体流动速率减小，气体注射后产生的压力降越大，表明在生产中应尽可能选用高熔体流动速率树脂以利于气辅注塑工艺。     

Determination of the heat transfer coefficient from short‐shots studies and precise simulation of microinjection molding

The filling process of a micro‐cavity was analyzed by modeling the compressible filling stage by using pressure‐dependent viscosity and adjusted heat transfer coefficients. Experimental filling studies were carried out at the same time on an accurately controlled microinjection molding machine. On the basis of the relationship between the injection pressure and the filling degree, essential factors for the quality of the simulation can be identified. It can be shown that the flow behavior of the melt in a micro‐cavity with a high aspect ratio is extremely dependent on the melt compressibility in the injection cylinder. This phenomenon needs to be considered in the simulation to predict an accurate flow rate. The heat transfer coefficient between the melt and the mold wall that was determined by the reverse engineering varies significantly even during the filling stage. With increasing injection speed and increasing cavity thickness, the heat transfer coefficient decreases. It is believed that the level of the cavity pressure is responsible for the resulting heat transfer between the polymer and the mold. A pressure‐dependent model for the heat transfer coefficient would be able to significantly improve the quality of the process simulation. POLYM. ENG. SCI., 2010. © 2009 Society of Plastics Engineers     

Experimental and numerical studies of injection molding with microfeatures

Injection molding with microstructures was investigated both experimentally and theoretically. A series of injection molding experiments with PP and PMMA was carried out in a long and a short rectangular mold containing microchannels with the thickness of either 50 or 100 μm and an aspect ratio of 5. The filling lengths in the microchannels were affected by injection speed, mold temperature, and channel location. A high injection speed or high mold temperature resulted in a longer filling length. The filling length in the microchannels decreased as the filling time in the main flow region increased. All filling lengths can be merged into a single curve vs. Fourier number based on the microchannel thickness. Comparison was also made between the experimental measurements and numerical simulation. The mold/melt heat transfer coefficient was found to be a critical factor in determining the filling lengths. The local heat transfer coefficient provided a much better agreement than a constant heat transfer coefficient. POLYM. ENG. SCI., 45:866–875, 2005. © 2005 Society of Plastics Engineers     

注射分析中面模型的泉涌效应的近似处理

在注射流动与传热分析的中面模型采用自适应隐式控制体积法，并在熔体前沿进行泉涌效应的近似处理。熔体前沿厚度方向的质量和能量交换依据速度分布及质量和能量的守恒进行计算，使中面的熔体向两侧进行质量和能量的传递，从而获得熔体前沿泉涌效应的近似处理。实例计算表明，通过泉涌效应的近似处理，熔体前沿的计算温度有所提高，计算的注射压力有所下降，计算结果表明这样的近似处理合理及实用。     

微注塑成型过程塑料熔体流动的偏移行为

采用集成式热电偶传感器温度测量系统和可视化全息示踪技术, 对多型腔微注塑成型过程熔体流动前沿在型腔内的偏移现象进行观察和分析。结果表明, 当注射速度为140~220 mm·s^-1时, 主流道内的塑料熔体前沿呈“U型流”状态分布, 分流道内塑料熔体前沿向上侧偏移;当注射速度为10~70 mm·s^-1时, 主流道塑料熔体前沿呈“喷泉流”状态分布, 分流道熔体前沿向下侧偏移;当注射速度为80~120 mm·s^-1时, 主流道和分流道熔体前沿均没有明显的偏移。说明微注塑时注射速度不同, 产生的剪切热也不同, 熔体前沿偏移情况也不同。为此, 引入非平衡流动系数λ, 来判断熔体前沿的流动和偏移情况。     

Gas assisted injection molding of a handle: Three‐dimensional simulation and experimental verification

Methods implemented in a three‐dimensional finite element code for the simulation of gas assisted injection molding are described, and predictions compared with the results of molding trials. The emphasis is on prediction of primary gas penetration and plastic wall thickness, including the effects of cooling during a delay before gas injection. For the latter, time dependent heat transfer coefficients at the cavity surface are used, determined in a separate analysis of transient heat conduction through the plastic and the mold tool to the circulating coolant. This shows how the initial value of 25,000 W/m²K falls by about an order of magnitude during the first few seconds of cooling, and also how values vary from cycle to cycle as steady periodic conditions are approached. For a tubular handle molded in polystyrene, with melt flow modeled by a Cross WLF model, comparisons of simulations with sectioned parts show excellent prediction of wall thickness and its variation circumferentially and in bends. The increase in wall thickness due to cooling during a gas delay is accurately modeled, as is the occurrence of a blow out. POLYM. ENG. SCI. 45:1049–1058, 2005. © 2005 Society of Plastics Engineers     

Computer simulation of the filling process in gas‐assisted injection molding based on gas‐penetration modeling

Gas‐assisted injection molding can effectively produce parts free of sink marks in thick sections and free of warpage in long plates. This article concerns the numerical simulation of melt flow and gas penetration during the filling stage in gas‐assisted injection molding. By taking the influence of gas penetration on the melt flow as boundary conditions of the melt‐filling region, a hybrid finite‐element/finite‐difference method similar to conventional‐injection molding simulation was used in the gas‐assisted injection molding‐filling simulation. For gas penetration within the gas channel, an analytical formulation of the gas‐penetration thickness ratio was deduced based on the matching asymptotic expansion method. Finally, an experiment was employed to verify this proposed simulation scheme and gas‐penetration model, by comparing the results of the experiment with the simulation. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 90: 2377–2384, 2003     

Experimental investigation and molecular dynamics simulations of the effect of processing parameters on the filling quality of injection-molded micropillars

Microinjection molding has been attracting increasing attention and application in fabricating products with functional surface microstructures. The processing parameters, packing pressure, and melt temperature have important effects on the filling quality. In order to study the mechanisms of the packing pressure and melt temperature on the filling quality of micropillars, a simulation model of injection molding of nanopillars was constructed by molecular dynamics software and a series of injection molding experiments of micropillars were carried out in this paper. Subsequently, the mechanisms were analyzed qualitatively. The results showed that the frozen layers were formed at the interface between the polymer melt and mold under the action of heat transfer, which prevented effective filling of the polymer melt. The filling quality of the micropillars could be improved significantly via increasing the melt temperature and the packing pressure, but the mechanisms were different. To be specific, the increase of the packing pressure could make more polymer melts fill into the cavity fully. Thus, the density of the micropillars was increased and the filling quality could be improved. The forming rate of frozen layers could be slowed down by increasing the melt temperature. As a result, the purpose of improving the filling quality was achieved.     

聚合物流变性能对共注射成型的影响

在共注射成型多相分层流动充模成型机理的基础上，揭示了芯壳层熔体对共注射成型的分层界面形貌和芯层熔体前沿突破的影响，并模拟了芯壳层熔体粘度比对共注射成型的影响，建立了芯壳层熔体粘度与分层界面和前沿移动界面菜貌的关系。本文的模拟研究结果与一些文献的实验结果相吻合。     

Calibration of cavity pressure simulation using autoencoder and multilayer perceptron neural networks

Numerical simulations of polymer melt flow behavior in cavities help predict and optimize injection molding process parameters. However, simulation and actual results may differ because of simplified mathematical models, inaccurate processing conditions, material property settings, and machine aging, among other factors. Therefore, simulated optimal process parameters cannot be directly applied in practice. This study applied machine learning to generate a virtual–actual correction model to improve the accuracy of simulation results, especially the cavity pressure profile, a key indicator of injection-molding quality for identifying ideal process parameter settings such as filling-to-packing switchover time and holding pressure. This method does not require big data for model training to enhance its practicality. Therefore, the correction model is only suitable for specific settings. A set of injection molding machines, molds, and processed materials were used for experimental verification. An autoencoder model was used to extract the features of simulation and actual cavity pressure curves. Then, a multilayer perceptron model was used to determine a relationship between simulation and actual features. The autoencoder was used to decode simulated features into cavity pressure curves. The proposed method was verified with dumbbell-shaped specimens; the correlation between simulated and actual cavity pressures was greatly improved from 81% to 98%.