基于神经网络的挤出吹塑中型坯尺寸预测

延续了本课题组在挤出吹塑中利用人工神经网络(ANN)预测型坯尺寸的工作,建立一个新的ANN模型。经过样本训练和检验后,模型能在一定范围内预测型坯任意位置上的尺寸(直径和厚度);与以往工作相比,相同的实验量能提供更丰富的训练样本。     

Noncontact measurement of parison thickness profiles affected by swell and sag in continuous extrusion blow molding

Optimization of final part thickness distributions is crucial in the extrusion blow molding process in order to minimize resin usage. Prediction of part thickness distributions from basic process and material parameters would be ideal. However, attempts to do so have been unsuccessful, largely because of the inability to predict parison thickness profiles. One must therefore resort to measurement of the parison thickness profile and estimation of the final part thickness distribution by computational methods. This paper describes a new technique for the noncontact estimation of parison thickness profiles in continuous extrusion blow molding. The method accounts for sag and requires no previous knowledge of rheological data. It can be employed on-line for the purposes of process monitoring and control. The approach is based on the measurement of the parison length evolution with time during extrusion, the parison diameter profile, the flow rate, and the melt temperature gradient along the length of the parison. These parameters are utilized in conjunction with a theoretical approach that describes the extrusion of a parison under the effects of swell, sag, and extrusion into ambient conditions. Results are presented for three resins of various molecular weight distributions. The degree of sag is minimal at the top and bottom of the parison, and reaches a maximum near the center of the parison. Results are also presented to demonstrate the versatility of the method under other process conditions, such as varying flow rate, die temperature, and die gap.     

Effect of die gap width on annular extrudates by the annular extrudate swell simulation in steady-states

We calculated the steady-state annular extrudate swell of polymer melts through flow geometries encountered in processes used to control parison thickness. A streamline-upwinding finite element method with an under-relaxation for the rate of deformation tensor was used. The Giesekus model was employed as the constitutive equation. An operation that widens the die gap is appropriate for the control of parison thickness corresponding to the change of die gap width. However, a control process that decreases the die gap width is not useful, because the parison thickness does not correspond to the die gap width. Furthermore, thickness swells change strikingly with the Weissenberg number. It is difficult to control the parison outer diameter in the case of a converging die, because the change of the outer diameter swell becomes large with increasing Weissenberg number. In the case of a diverging die, the changing value of the outer diameter swell is smaller than that in the case of a converging die.     

Modeling parison formation in extrusion blow molding by neural networks

A series of experiments were carried out on the parison formation stage in extrusion blow molding of high‐density polyethylene (HDPE) under different die temperature, extrusion flow rate, and parison length. The drop time of parison when it reached a given length and its swells, including the diameter, thickness, and area swells, were determined by analyzing its video images. Two back‐propagation (BP) artificial neural network models, one for predicting the length evolution of parison with its drop time, the other predicting the swells along the parison, were constructed based on the experimental data. Some modifications to the original BP algorithm were carried out to speed it up. The comparison of the predicted parison swells using the trained BP network models with the experimentally determined ones showed quite a good agreement between the two. The sum of squared error for the predictions is within 0.001. The prediction of the parison diameter and thickness distributions can be made online at any parison length or any parison drop time within a given range using the trained models. The predicted parison swells were analyzed. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 2230–2239, 2005     

Numerical simulation of blow molding—prediction of parison diameter and thickness distributions in the parison formation process

In our previous study, we calculated the time course of parison length in the parison formation stage, but it could predict only the parison area swell. The next target in our study is to calculate the parison diameter and thickness swell. Annular extrudate swell simulation is necessary for the understanding of various kinds of swelling ratios in blow molding. We have examined three kinds of swells (outer diameter, thickness, and area swells) obtained from simulation results of annular extrudate swell, using the Giesekus model, and have developed a method of predicting parison outer diameter and thickness swell values. The predicted values of parison outer diameters are discussed in comparison with experimental data, and reasonable results are obtained by the proposed method. This prediction method could also be applied to the parison formation process using a parison controller. As a result, it is possible to predict approximately the whole process of parison formation by numerical simulation.     

Fast online acquisition and analysis for parison swell and sag in blow molding

It is critical to quantitatively and reliably characterize the effects of swell and sag phenomena on the final parison dimensions in extrusion blow molding. To achieve this goal, an online image acquisition and analysis technique was developed. The successive images of parison were automatically taken using the online acquisition apparatus. These images were then analyzed by the combined use of the conventional digital image processing method and the new one developed by the authors. So the development of parison diameter and thickness swells with the extrusion time could be determined online. On the basis of the online obtained actual swell values, the pure swell and sag components were quantitatively determined. The developed technique was tested through a series of experiments using several resins under different processing parameters and die types. Shown in the present article were the results for a converging die under three different die gaps and a high‐density polyethylene. Some new phenomena were observed using the proposed technique. The results showed that the technique yields fast and accurate determination of the evolution of diameter, thickness, and length of parison during its extrusion. The technique can be employed as a part of the closed loop control for blow molded part thickness. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2399–2406, 2006     

Experimental and theoretical investigation of the inflation of variable thickness parisons

In today's blow molding of complex parts, an optimal resin distribution is critical to a successful operation. These goals are mostly attained through a technique known as parison programming. The process involves varying the die gap during extrusion and therefore results in a parison having a variable thickness along its length. The subsequent inflation of a variable thickness parison is a complex phenomenon involving the interaction of many process variables. The final thickness distribution and inflation patterns were obtained for various programmed parisons. Constant, one step, two step, and sinusoidal thickness parisons were studied. The inflation patterns were monitored by employing a transparent mold in conjunction with a video camera. The experimental data indicated the presence of an oscillatory inflation pattern for some of the variable thickness parisons. The experimental final part thickness distribution for these cases was highly nonlinear. Theoretical predictions of the final thickness distribution were also obtained for some of the cases. The simulation is based on the inflation of a Mooney-Rivlin hyperelastic material. A wide range of deformation is accounted for by introducing an evolutionary Mooney constant, dependent on the level of deformation.     

聚丙烯/聚乙烯共混物环状型坯挤出膨胀和垂伸的研究

利用双螺杆挤出机将聚丙烯分别与不同熔体流动速率的聚乙烯进行共混,通过环状型坯挤出,研究了共混物的型坯膨胀和垂伸情况。结果表明,聚丙烯与较高熔体流动速率的聚乙烯共混后,其型坯直径膨胀的变化范围较宽,垂伸较明显。     

Numerical simulation of suction blow molding process for producing curved ducts

During suction blow molding process, the extruded parison undergoes twisting deformation within the mold cavity, as the air drawing flow around the deforming parison exerts non‐uniform shear stresses on its surface. Such twisting deformation can compromise the specific radial and circumferential variations in parison thickness that are intentionally generated during extrusion. This research is devoted in developing a fluid–structure interaction model for predicting parison deformation during suction blow molding process, with a specific emphasis on the suction stage. A fluid flow model, based on Hele‐Shaw approximations, is formulated to simulate the air drag force exerted on the parison surface. The rheology of the material of the parison is assumed to obey the viscoelastic K‐BKZ model. As the suction process also involves the sliding of the parison within the mold cavity, a modified Coulomb's law of dry friction is used to simulate the frictional contact between parison and mold. The numerical results of this study allowed identifying a clear correlation between the twisting deformation undergone by the parison during the suction stage, also observed experimentally and the design parameters, namely, the air drawing speed, the geometry of the duct mold cavity, and the parison/mold eccentricity. POLYM. ENG. SCI., 59:418–434, 2019. © 2018 Her Majesty the Queen in Right of Canada     

On-Line measurement of parison geometry during blow molding: Parison swelling for three high-density polyethylenes with different molecular weights and molecular weight distributions

An image analysis technique has been developed to measure diameter and thickness distribution of a parison during the extrusion stage in blow molding. The system operates on-line during extrusion on any commercial blow-molding machine. The system has been developed to help development of new blow-molding resins by increasing our understanding of the connection between polymer structure and parison shape. The system can also be used for die design during optimization of a production process. The combined use of experimental design and multivariate projection techniques makes this an efficient tool for the practical processing engineer. Experiments done on three high-density polyethylene blow-molding resins show the importance of measuring the time dependence of the diameter and thickness distribution under different extrusion conditions for a given polymer. Our results show that many of the swell and sag related properties we see cannot be directly inferred from standard laboratory swell-experiments.     

Measurement and calculation of parison dimensions and bottle thickness distribution during blow molding

Experimental data are reported regarding the dynamics of the blow molding process, including parison formation, growth, and inflation. These data have been obtained with the aid of high speed cinematography and pinch mold experiments, in conjunction with two commercial blow molding polyethylene resins. It is shown that pinch mold experiments alone do not yield accurate data regarding thickness and diameter swell. Furthermore, the inflation process involves decreasing rates of inflation with time, as a result of the rise in viscosity due to the cooling of the parison during inflation. Mathematical procedures are proposed for a first-order estimation of parison length and swell as a function of time and the inflation behavior after clamping. In the absence of more dependable basic procedures, the proposed treatment is employed to estimate the effective transient swell functions for the parison using experimental data obtained under the specified conditions. The mathematical treatment is extended to determine the thickness distribution of the bottle. Good agreement is obtained between experimental and calculated results.     

变径毛细管流量关联式开发

变径毛细管是一种用于家用热泵的低成本节流装置,其非对称结构可以实现正反两个流向的流量不同,从而可以满足热泵系统制冷和制热所需的流量。为了实现变径毛细管工程设计,开发了变径毛细管流量的关联式。通过构建变径毛细管等效管径和等效管长计算公式并代入等径毛细管关联式,得到了变径毛细管流量的关联式的公式形式;通过数值计算模型产生用于拟合关联式系数的数据源。开发的变径毛细管流量关联式可计算变径毛细管正向和反向的制冷剂流量以及传统的等径毛细管的流量。开发关联式能很好地预测变径毛细管在不同工况下制冷剂流量的变化趋势,预测93%实验数据点的精度在10%以内。     

Extrusion blow molding of long fiber reinforced polyolefins

A 58% (by weight) long glass fiber reinforced (LGF)‐HDPE master batch was blended with a typical blow molding HDPE grade. HDPE composites having between 5% and 20% (by weight) long fiber content were extruded at different processing conditions (extrusion speed, die gap, hang time). The parison swell (diameter and thickness) decreased with increasing fiber content. Although the HDPE exhibited significant shear rate dependence, the LGF/HDPE composites were shear rate insensitive. Both the diameter and weight swell results also indicated very different sagging behavior. The LGF/HDPE parisons did sag as a solid‐body (equal speed at different axial locations) governed by the orientation caused by the flow in the die. Samples taken from blown bottles showed that fiber lengths decreased to 1‐3 mm, from the original 11 mm fiber length fed to the extruder. No significant difference in fiber length distribution was found when samples for different regions of the bottle were analyzed. SEM micrographs corroborate the absence of fiber segregation and clustering or the occurrence of fiber bundles (homogeneous spatial fiber distribution) as well as a preferential fiber orientation with the direction of flow. The blowing step did not change the orientation of the fibers. Five‐percent (5%) and 10% LGF/HDPE composites could be blown with very slight variations to the neat HDPE inflation conditions. However, 20% LGF/HDPE composites could not be consistently inflated. Problems related to blowouts and incomplete weldlines were the major source of problems.     

Overall numerical simulation of extrusion blow molding process

This paper focuses on the overall numerical simulation of the parison formation and inflation process of extrusion blow molding. The competing effects due to swell and drawdown in the parison formation process were analyzed by a Lagrangian Eulerian (LE) finite element method (FEM) using an automatic remeshing technique. The parison extruded through an annular die was modeled as an axisymmetric unsteady nonisothermal flow with free surfaces and its viscoelastic properties were described by a K‐BKZ integral constitutive equation. An unsteady die‐swell simulation was performed to predict the time course of the extrudate parison shape under the influence of gravity and the parison controller. In addition, an unsteady large deformation analysis of the parison inflation process was also carried out using a three‐dimensional membrane FEM for viscoelastic material. The inflation sequence for the parison molded into a complex‐shaped mold cavity was analyzed. The numerical results were verified using experimental data from each of the sub‐processes. The greatest advantage of the overall simulation is that the variation in the parison dimension caused by the swell and drawdown effect can be incorporated into the inflation analysis, and consequently, the accuracy of the numerical prediction can be enhanced. The overall simulation technique provides a rational means to assist the mold design and the determination of the optimal process conditions.     

基于自适应神经网络的芳烃异构化过程建模

针对芳烃异构化过程(AHIP)中影响对二甲苯(PX)产率的因素众多且复杂等特点,提出一种自适应神经网络(Adaptive ANN)以建立AHIP的各因素与PX产率的关联模型.Adaptive ANN将样本分成训练样本和校验样本,并设计过拟合判据参数.通过训练样本对网络进行训练,训练过程中以模型对校验样本的预测性能为指标,通过过拟合判据参数的计算自适应地在获得具有最佳预测性能模型时终止网络训练,克服了传统的神经网络以模型的拟合精度为指标,造成训练时间过长和过拟合等缺点.     

Numerical simulation of blow molding—Viscoelastic flow analysis of parison formation

The simulation of the parison formation process in blow molding has been studied. The flow field was divided into two regions, namely, the extrudate swell region near the die lip and the parison formation region after the exit swell. In the swell region, we predicted the swelling ratio and residual stress distribution for high Weissenberg numbers for steady planar well using the 1-mode Giesekus model. In the parison formation region, the flow is assumed to be an unsteady unaxial elongational flow including drawdown and recoverable swell and is modeled using the 10-mode Giesekus model. We calculated the time course of parison length and thickness distribution, and compare the calculation results of parison length with experimental data. It was found that the predicted values agreed rather well with the experimental values. The calculation results could especially predict the shrink-back, which is the phenomenon where the parison length becomes shorter after the cessation of extrusion, and it was found tat this was caused by the recoverable swell of the parison, which depends on the tensile stress generation in the die. Various flow rates and die geometries were studied and confirmed the reliability and usefulness of the method.     

Improved die assembly for gas-assisted sheet extrusion using different up and down gas layer thicknesses

Gas-assisted sheet extrusion is a promising and environment-friendly method used in polymer processing. Insufficient gas intake due to the adherence of the polymer melt to the inlet gap is a disadvantage of the method. Therefore, in this study an improved die assembly with parallel gas intake was designed. As the melt is prone to falling at the die exit during the horizontal extrusion process, different thickness settings are used for the up and down gas layers (0.25 and 0.75 mm, respectively) to avoid this. For the improved die assembly, the gas inlet pressure may be varied systematically to study the mechanism of stable sheet extrusion. When the gas inlet pressure is 0.1 MPa, the melt can be extruded smoothly, and the extruded sheet surface is transparent and flat. However, when the optimum pressure is exceeded, the extruded sheet becomes twisted or even broken.     

A comprehensive experimental study and numerical modeling of parison formation in extrusion blow molding

Parison dimensions in extrusion blow molding are affected by two phenomena, swell due to stress relaxation and sag drawdown due to gravity. It is well established that the parison swell and sag are strongly dependent on the die geometry and the operating conditions. The availability of a modeling technique ensures a more accurate prediction of the entire blow molding process, as the proper prediction of the parison formation is the input for the remaining process phases. This study considers both the simulated and the experimental effects of the die geometry, the operating conditions, and the resin properties on the parison dimensions using high density polyethylene. Parison programming with a moving mandrel and the flow rate evolution in intermittent extrusion are also considered. The parison dimensions are measured experimentally by using the pinch-off mold technique on two industrial scale machines. The finite element software BlowParison® developed at IMI is used to predict the parison formation, taking into account the swell, sag, and nonisothermal effects. The comparison between the predicted parison/part dimensions and the corresponding experimental data demonstrates the efficiency of numerical tools in the prediction of the final part thickness and weight distributions. POLYM. ENG. SCI., 47:1–13, 2007. © 2006 Society of Plastics Engineers     

Variables affecting parison diameter swell and their correlation with rheological parameters

An important factor in the selection of blow molding resins for producing handled bottles is the effective diameter swell of the parison. Ideally, the diameter swell is directly related to the weight swell and would require no separate consideration. In actual practice, the existence of gravity, the finite parison drop time and the anisotropic aspects of the blow molding operation prevent reliable prediction of the parison diameter swell directly from the weight swell. The parison diameter swell is a complex function of the weight swell, the rate of swell and the melt strength. Elements of this function are presented which show the effect of extrusion rate, parison drop time and parison weight. A technique is presented which allows the estimation of local weight and diameter swell ratios. Their direct relationship is confirmed by data obtained on several blow molding resins. The relationship between weight swell and diameter swell is definitely anisotropic. A mathematical model for swell is proposed which incorporates experimentally determined rate constants and swell coefficients. Correlations are given which suggest fundamental relationships between these derived coefficients and basic variables such as resin properties or process conditions. The model's predictive capability is demonstrated by using it to back calculate parison dimensions.     

Modeling of complex parison formation in extrusion blow molding: Effect of medium to large die heads and fuel tank geometry

This work presents the effect of die geometry and die gap opening on the extrudate swell phenomenon, in complex parison formation using the vertical wall distribution system (VWDS) and partial wall distribution system (PWDS). The BlowParison^© software from IMI is used to predict the parison formation for a combined VWDS/PWDS system, accounting for swell, sag, and nonisothermal effects. This software couples a fluid mechanics approach to represent the die flow, with a solid mechanics approach to represent the parison behavior outside the die, and a mathematical swell model to account for the pronounced elongational and shear stresses at high Weissenberg numbers. The emphasis is placed on experimental validation of the predicted parison dimensions using four diverging die geometries and different sets of VWDS/PWDS profiles. The experimental and predicted weight profiles for a dissected fuel tank are also presented. Both experimental and simulation results suggest a strong dependence of extrudate swell to the die geometry in the die land zone. The results also demonstrate the validity of the numerical predictions for part design purposes given the multitude of experimental validations presented in this work. POLYM. ENG. SCI., 2009. Published by the Society of Plastics Engineers