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Open AccessEditorial

Advanced Polymer Simulation and Processing

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Polymers 2022, 14(12), 2480; https://doi.org/10.3390/polym14122480 - 18 Jun 2022

Viewed by 1245

Abstract

Polymer processing techniques are of paramount importance in the manufacture of polymer parts [...] Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

Research

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Open AccessArticle

Predictive Methodology for Quality Assessment in Injection Molding Comparing Linear Regression and Neural Networks

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Polymers 2023, 15(19), 3915; https://doi.org/10.3390/polym15193915 - 28 Sep 2023

Viewed by 335

Abstract

The use of recycled polypropylene in industry to reduce environmental impact is increasing. Design for manufacturing and process simulation is a key stage in the development of plastic parts. Traditionally, a trial-and-error methodology is followed to eliminate uncertainties regarding geometry and process. A [...] Read more.

The use of recycled polypropylene in industry to reduce environmental impact is increasing. Design for manufacturing and process simulation is a key stage in the development of plastic parts. Traditionally, a trial-and-error methodology is followed to eliminate uncertainties regarding geometry and process. A new proposal is presented, combining simulation with the design of experiments and creating prediction models for seven different process and part quality output features. These models are used to optimize the design without developing additional time-consuming simulations. The study aims to compare the precision and correlation of these models. The methods used are linear regression and artificial neural network (ANN) fitting. A wide range of eight injection parameters and geometry variations are used as inputs. The predictability of nonlinear behavior and compensatory effects due to the complex relationships between this wide set of parameter combinations is analyzed further in the state of the art. Results show that only Back Propagation Neural Networks (BPNN) are suitable for correlating all quality features in a single formula. The use of prediction models accelerates the optimization of part design, applying multiple criteria to support decision-making. The methodology is applied to the design of a plastic support for induction hobs. Furthermore, this methodology has demonstrated that a weight reduction of 27% is feasible. However, it is necessary to combine process parameters that differ from the standard ones with a non-uniform thickness distribution so that the remaining injection parameters, material properties, and dimensions fall within tolerances. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Direct Synthesis of Gold Nanoparticles in Polymer Matrix

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Polymers 2023, 15(1), 16; https://doi.org/10.3390/polym15010016 - 20 Dec 2022

Cited by 1 | Viewed by 1120

Abstract

We report an original method for directly fabricating gold nanoparticles (Au NPs) in a polymer matrix using a thermal treatment technique and theoretically and experimentally investigate their plasmonic properties. The polymeric-metallic nanocomposite samples were first prepared by simply mixing SU-8 resist and Au [...] Read more.

We report an original method for directly fabricating gold nanoparticles (Au NPs) in a polymer matrix using a thermal treatment technique and theoretically and experimentally investigate their plasmonic properties. The polymeric-metallic nanocomposite samples were first prepared by simply mixing SU-8 resist and Au salt with different concentrations. The Au NPs growth was triggered inside the polymer through a thermal process on a hot plate and in air environment. The Au NPs creation was confirmed by the color of the nanocomposite thin films and by absorption spectra measurements. The Au NPs sizes and distributions were confirmed by transmission electron microscope measurements. It was found that the concentrations of Au salt and the annealing temperatures and durations are all crucial for tuning the Au NPs sizes and distributions, and, thus, their optical properties. We also propose a simulation model for calculations of Au NPs plasmonic properties inside a polymer medium. We realized that Au NPs having large sizes (50 to 100 nm) play an important role in absorption spectra measurements, as compared to the contribution of small NPs (<20 nm), even if the relative amount of big Au NPs is small. This simple, low-cost, and highly reproducible technique allows us to obtain plasmonic NPs within polymer thin films on a large scale, which can be potentially applied to many fields. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

A Semi-Analytical Method for Channel and Pipe Flows for the Linear Phan-Thien-Tanner Fluid Model with a Solvent Contribution

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Matheus Tozo de Araujo

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Laison Furlan

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Analice Brandi

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Leandro Souza

Polymers 2022, 14(21), 4675; https://doi.org/10.3390/polym14214675 - 02 Nov 2022

Viewed by 772

Abstract

This work presents a semi-analytical method for laminar steady-state channel and pipe flows of viscoelastic fluids using the Linear Phan-Thien-Tanner (LPTT) constitutive equation, with solvent viscosity contribution. For the semi-analytical method validation, it compares its results and two analytical solutions: the Oldroyd-B model [...] Read more.

This work presents a semi-analytical method for laminar steady-state channel and pipe flows of viscoelastic fluids using the Linear Phan-Thien-Tanner (LPTT) constitutive equation, with solvent viscosity contribution. For the semi-analytical method validation, it compares its results and two analytical solutions: the Oldroyd-B model and the simplified LPTT model (without solvent viscosity contribution). The results adopted different values of the dimensionless parameters, showing their influence on the viscoelastic fluid flow. The results include the distribution of the streamwise velocity component and the extra-stress tensor components in the wall-normal direction. In order to investigate the proposed semi-analytical method, different solutions were obtained, both for channel and pipe flows, considering different values of Reynolds number, solvent viscosity contribution in the homogeneous mixture, elongational parameter, shear parameter, and Weissenberg number. The results show that the proposed semi-analytical method can find a laminar solution using the non-Newtonian LPTT model with solvent viscosity contribution and verify the effect of the parameters in the resulting flow field. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

A Fully Implicit Log-Conformation Tensor Coupled Algorithm for the Solution of Incompressible Non-Isothermal Viscoelastic Flows

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Célio Fernandes

Polymers 2022, 14(19), 4099; https://doi.org/10.3390/polym14194099 - 30 Sep 2022

Cited by 4 | Viewed by 1101

Abstract

In this work, a block-coupled algorithm is presented, which can compute laminar, incompressible, non-isothermal, viscoelastic flow problems based on the log-conformation tensor approach. The inter-equation coupling of the incompressible Cauchy linear momentum and mass conservation equations is obtained in a procedure based on [...] Read more.

In this work, a block-coupled algorithm is presented, which can compute laminar, incompressible, non-isothermal, viscoelastic flow problems based on the log-conformation tensor approach. The inter-equation coupling of the incompressible Cauchy linear momentum and mass conservation equations is obtained in a procedure based on the Rhie–Chow interpolation. The divergence of the log-conformation tensor term in the linear momentum equations is implicitly discretized in this work. In addition, the velocity field is considered implicitly in the log-conformation tensor constitutive equations by expanding the advection, rotation and the rate of deformation terms with a Taylor series expansion truncated at the second-order error term. Finally, the advection and diffusion terms in the energy equation are also implicitly discretized. The mass, linear momentum, log-conformation tensor constitutive model and energy-discretized linear equations are joined into a block-matrix following a monolithic framework. Validation of the newly developed algorithm is performed for the non-isothermal viscoelastic matrix-based Oldroyd-B fluid flow in the axisymmetric 4:1 planar sudden contraction benchmark problem. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Effect of Bacterial Cellulose Plasma Treatment on the Biological Activity of Ag Nanoparticles Deposited Using Magnetron Deposition

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Polymers 2022, 14(18), 3907; https://doi.org/10.3390/polym14183907 - 19 Sep 2022

Cited by 5 | Viewed by 1492

Abstract

New functional medical materials with antibacterial activity based on biocompatible bacterial cellulose (BC) and Ag nanoparticles (Ag NPs) were obtained. Bacterial cellulose films were prepared by stationary liquid-phase cultivation of the Gluconacetobacter hansenii strain GH-1/2008 in Hestrin–Schramm medium with glucose as a carbon [...] Read more.

New functional medical materials with antibacterial activity based on biocompatible bacterial cellulose (BC) and Ag nanoparticles (Ag NPs) were obtained. Bacterial cellulose films were prepared by stationary liquid-phase cultivation of the Gluconacetobacter hansenii strain GH-1/2008 in Hestrin–Schramm medium with glucose as a carbon source. To functionalize the surface and immobilize Ag NPs deposited by magnetron sputtering, BC films were treated with low-pressure oxygen–nitrogen plasma. The composition and structure of the nanomaterials were studied using transmission (TEM) and scanning (SEM) electron microscopy and X-ray photoelectron spectroscopy (XPS). Using electron microscopy, it was shown that on the surface of the fibrils that make up the network of bacterial cellulose, Ag particles are stabilized in the form of aggregates 5–35 nm in size. The XPS C 1s spectra show that after the deposition of Ag NPs, the relative intensities of the C-OH and O-C-O bonds are significantly reduced. This may indicate the destruction of BC oxypyran rings and the oxidation of alcohol groups. In the Ag 3d_5/2 spectrum, two states at 368.4 and 369.7 eV with relative intensities of 0.86 and 0.14 are distinguished, which are assigned to Ag⁰ state and Ag acetate, respectively. Nanocomposites based on plasma-treated BC and Ag nanoparticles deposited by magnetron sputtering (BCP-Ag) exhibited antimicrobial activity against Aspergillus niger, S. aureus and Bacillus subtilis. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

On the Response of a Herschel–Bulkley Fluid Due to a Moving Plate

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N’dri Arthur Konan

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Eilis Rosenbaum

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Mehrdad Massoudi

Polymers 2022, 14(18), 3890; https://doi.org/10.3390/polym14183890 - 17 Sep 2022

Cited by 1 | Viewed by 1135

Abstract

In this paper, we study the boundary-layer flow of a Herschel–Bulkley fluid due to a moving plate; this problem has been experimentally investigated by others, where the fluid was assumed to be Carbopol, which has similar properties to cement. The computational fluid dynamics [...] Read more.

In this paper, we study the boundary-layer flow of a Herschel–Bulkley fluid due to a moving plate; this problem has been experimentally investigated by others, where the fluid was assumed to be Carbopol, which has similar properties to cement. The computational fluid dynamics finite volume method from the open-source toolbox/library OpenFOAM is used on structured quad grids to solve the mass and the linear momentum conservation equations using the solver “overInterDyMFoam” customized with non-Newtonian viscosity libraries. The governing equations are solved numerically by using regularization methods in the context of the overset meshing technique. The results indicate that there is a good comparison between the experimental data and the simulations. The boundary layer thicknesses are predicted within the uncertainties of the measurements. The simulations indicate strong sensitivities to the rheological properties of the fluid. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Simulation of the Particle Transport Behaviors in Nanoporous Matter

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Polymers 2022, 14(17), 3563; https://doi.org/10.3390/polym14173563 - 29 Aug 2022

Cited by 1 | Viewed by 1025

Abstract

The transport behaviors of proton into nanoporous materials were investigated using different Monte Carlo simulation codes such as GEANT4, Deeper and SRIM. The results indicated that porous structure could enhance the proton scattering effects due to a higher specific surface area and more [...] Read more.

The transport behaviors of proton into nanoporous materials were investigated using different Monte Carlo simulation codes such as GEANT4, Deeper and SRIM. The results indicated that porous structure could enhance the proton scattering effects due to a higher specific surface area and more boundaries. The existence of voids can deepen and widen the proton distribution in the targets due to relatively lower apparent density. Thus, the incident protons would transport deeper and form a wider Bragg peak in the end of the range, as the target materials are in a higher porosity state and/or have a larger pore size. The existence of voids also causes the local inhomogeneity of proton/energy distribution in micro/nano scales. As compared, the commonly used SRIM code can only be used to estimate roughly the incident proton range in nanoporous materials, based on a homogeneous apparent density equivalence rule. Moreover, the estimated errors of the proton range tend to increase with the porosity. The Deeper code (designed for evaluation of radiation effects of nuclear materials) can be used to simulate the transport behaviors of protons or heavy ions in a real porous material with porosity smaller than 52.3% due to its modeling difficulty, while the GEANT4 code has shown advantages in that it is suitable and has been proven to simulate proton transportation in nanoporous materials with porosity in its full range of 0~100%. The GEANT4 simulation results are proved consistent with the experimental data, implying compatibility to deal with ion transportation into homogeneously nanoporous materials. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Influence of Processing Glass-Fiber Filled Plastics on Different Twin-Screw Extruders and Varying Screw Designs on Fiber Length and Particle Distribution

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Annette Rüppel

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Susanne Wolff

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Jan Philipp Oldemeier

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Volker Schöppner

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Hans-Peter Heim

Polymers 2022, 14(15), 3113; https://doi.org/10.3390/polym14153113 - 30 Jul 2022

Cited by 2 | Viewed by 1805

Abstract

Due to their valuable properties (low weight, and good thermal and mechanical properties), glass fiber reinforced thermoplastics are becoming increasingly important. Fiber-reinforced thermoplastics are mainly manufactured by injection molding and extrusion, whereby the extrusion compounding process is primarily used to produce fiber-filled granulates. [...] Read more.

Due to their valuable properties (low weight, and good thermal and mechanical properties), glass fiber reinforced thermoplastics are becoming increasingly important. Fiber-reinforced thermoplastics are mainly manufactured by injection molding and extrusion, whereby the extrusion compounding process is primarily used to produce fiber-filled granulates. Reproducible production of high-quality components requires a granulate in which the fiber length is even and high. However, the extrusion process leads to the fact that fiber breakages can occur during processing. To enable a significant quality enhancement, experimentally validated modeling is required. In this study, short glass fiber reinforced thermoplastics (polypropylene) were produced on two different twin-screw extruders. Therefore, the machine-specific process behavior is of major interest regarding its influence. First, the fiber length change after processing was determined by experimental investigations and then simulated with the SIGMA simulation software. By comparing the simulation and experimental tests, important insights could be gained and the effects on fiber lengths could be determined in advance. The resulting fiber lengths and distributions were different, not only for different screw configurations (SC), but also for the same screw configurations on different twin-screw extruders. This may have been due to manufacturer-specific tolerances. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Pyrolysis Study of Mixed Polymers for Non-Isothermal TGA: Artificial Neural Networks Application

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Ibrahim Dubdub

Polymers 2022, 14(13), 2638; https://doi.org/10.3390/polym14132638 - 28 Jun 2022

Cited by 6 | Viewed by 1190

Abstract

Pure polymers of polystyrene (PS), low-density polyethylene (LDPE) and polypropylene (PP), are the main representative of plastic wastes. Thermal cracking of mixed polymers, consisting of PS, LDPE, and PP, was implemented by thermal analysis technique “thermogravimetric analyzer (TGA)” with heating rate range (5–40 [...] Read more.

Pure polymers of polystyrene (PS), low-density polyethylene (LDPE) and polypropylene (PP), are the main representative of plastic wastes. Thermal cracking of mixed polymers, consisting of PS, LDPE, and PP, was implemented by thermal analysis technique “thermogravimetric analyzer (TGA)” with heating rate range (5–40 K/min), with two groups of sets: (ratio 1:1) mixture of PS and PP, and (ratio 1:1:1) mixture of PS, LDPE, and PP. TGA data were utilized to implement one of the machine learning methods, “artificial neural network (ANN)”. A feed-forward ANN with Levenberg-Marquardt (LM) as learning algorithm in the backpropagation model was performed in both sets in order to predict the weight fraction of the mixed polymers. Temperature and the heating rate are the two input variables applied in the current ANN model. For both sets, 10-10 neurons in logsig-tansig transfer functions two hidden layers was concluded as the best architecture, with almost (R > 0.99999). Results approved a good coincidence between the actual with the predicted values. The model foresees very efficiently when it is simulated with new data. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Effect of Local Heat Pipe Cooling on Throughput Distribution and Thermal Homogeneity in a Binary Melt Pre-Distributor for Polyolefin Extrusion

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Polymers 2022, 14(11), 2271; https://doi.org/10.3390/polym14112271 - 02 Jun 2022

Cited by 1 | Viewed by 1437

Abstract

In polymer blown film extrusion, inhomogeneous die temperature distributions lead to an inhomogeneous temperature and cause film thickness variations. To avoid an inhomogeneous film thickness and to achieve good film qualities, thermal homogenisation of the melt is necessary. Therefore, a new approach for [...] Read more.

In polymer blown film extrusion, inhomogeneous die temperature distributions lead to an inhomogeneous temperature and cause film thickness variations. To avoid an inhomogeneous film thickness and to achieve good film qualities, thermal homogenisation of the melt is necessary. Therefore, a new approach for cooling hot spots with heat pipes is investigated. CFD Simulations in OpenFOAM show that heat pipes can be used to influence melt temperatures locally in the places in which a temperature reduction is required. Since the outlets interact in a pre-distribution die, one heat pipe is not sufficient to homogenise the temperature at every outlet to similar temperatures. Two heat pipes show much better results with lower average temperature deviations between the distributor outlets. In order to equalise the temperature at all outlets, at least one heat pipe per outlet will be required. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Data-Driven Modelling of Polyethylene Recycling under High-Temperature Extrusion

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Polymers 2022, 14(4), 800; https://doi.org/10.3390/polym14040800 - 18 Feb 2022

Cited by 5 | Viewed by 2439

Abstract

Two main problems are studied in this article. The first one is the use of the extrusion process for controlled thermo-mechanical degradation of polyethylene for recycling applications. The second is the data-based modelling of such reactive extrusion processes. Polyethylenes (high density polyethylene (HDPE) [...] Read more.

Two main problems are studied in this article. The first one is the use of the extrusion process for controlled thermo-mechanical degradation of polyethylene for recycling applications. The second is the data-based modelling of such reactive extrusion processes. Polyethylenes (high density polyethylene (HDPE) and ultra-high molecular weight polyethylene (UHMWPE)) were extruded in a corotating twin-screw extruder under high temperatures (350 °C < T < 420 °C) for various process conditions (flow rate and screw rotation speed). These process conditions involved a decrease in the molecular weight due to degradation reactions. A numerical method based on the Carreau-Yasuda model was developed to predict the rheological behaviour (variation of the viscosity versus shear rate) from the in-line measurement of the die pressure. The results were successfully compared to the viscosity measured from offline measurement assuming the Cox-Merz law. Weight average molecular weights were estimated from the resulting zero-shear rate viscosity. Furthermore, the linear viscoelastic behaviours (Frequency dependence of the complex shear modulus) were also used to predict the molecular weight distributions of final products by an inverse rheological method. Size exclusion chromatography (SEC) was performed on five samples, and the resulting molecular weight distributions were compared to the values obtained with the two aforementioned techniques. The values of weight average molecular weights were similar for the three techniques. The complete molecular weight distributions obtained by inverse rheology were similar to the SEC ones for extruded HDPE samples, but some inaccuracies were observed for extruded UHMWPE samples. The Ludovic^® (SC-Consultants, Saint-Etienne, France) corotating twin-screw extrusion simulation software was used as a classical process simulation. However, as the rheo-kinetic laws of this process were unknown, the software could not predict all the flow characteristics successfully. Finally, machine learning techniques, able to operate in the low-data limit, were tested to build predicting models of the process outputs and material characteristics. Support Vector Machine Regression (SVR) and sparsed Proper Generalized Decomposition (sPGD) techniques were chosen to predict the process outputs successfully. These methods were also applied to material characteristics data, and both were found to be effective in predicting molecular weights. More precisely, the sPGD gave better results than the SVR for the zero-shear viscosity prediction. Stochastic methods were also tested on some of the data and showed promising results. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Microfluidic Rheometry and Particle Settling: Characterizing the Effect of Polymer Solution Elasticity

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Salah A. Faroughi

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Francesco Del Giudice

Polymers 2022, 14(4), 657; https://doi.org/10.3390/polym14040657 - 09 Feb 2022

Cited by 1 | Viewed by 1620

Abstract

The efficient transport of solid particles using polymeric fluids is an important step in many industrial operations. Different viscoelastic fluids have been designed for this purpose, however, the effects of elasticity have not been fully integrated in examining the particle-carrying capacity of the [...] Read more.

The efficient transport of solid particles using polymeric fluids is an important step in many industrial operations. Different viscoelastic fluids have been designed for this purpose, however, the effects of elasticity have not been fully integrated in examining the particle-carrying capacity of the fluids. In this work, two elastic fluid formulations were employed to experimentally clarify the effect of elasticity on the particle drag coefficient as a proxy model for measuring carrying capacity. Fluids were designed to have a constant shear viscosity within a specific range of shear rates,

\dot{γ} < 50 (1 / s)

, while possessing distinct (longest) relaxation times to investigate the influence of elasticity. It is shown that for dilute polymeric solutions, microfluidic rheometry must be practiced to obtain a reliable relaxation time (as one of the measures of viscoelasticity), which is on the order of milliseconds. A calibrated experimental setup, furnished with two advanced particle velocity measurement techniques and spheres with different characteristics, was used to quantify the effect of elasticity on the drag coefficient. These experiments led to a unique dataset in moderate levels of Weissenberg numbers,

0 < W i < 8.5

. The data showed that there is a subtle reduction in the drag coefficient at low levels of elasticity (

W i < 1

), and a considerable enhancement at high levels of elasticity (

W i > 1

). The experimental results were then compared with direct numerical simulation predictions yielding

R^{2} = 0.982

. These evaluations endorse the numerically quantified behaviors for the drag coefficient to be used to compare the particle-carrying capacity of different polymeric fluids under different flow conditions. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Feasibility Study of the Flatness of a Plastic Injection Molded Pallet by a Newly Proposed Sequential Valve Gate System

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Hsi Hsun Tsai

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Yi Lin Liao

Polymers 2022, 14(3), 616; https://doi.org/10.3390/polym14030616 - 04 Feb 2022

Cited by 4 | Viewed by 1923

Abstract

The investigation of plastic pallet molding, assisted by a sequential valve gate system, has not yet been performed due to the limitations of the pallet scale. Furthermore, at present, the application of recycled plastics by chemical industries has become extremely popular around the [...] Read more.

The investigation of plastic pallet molding, assisted by a sequential valve gate system, has not yet been performed due to the limitations of the pallet scale. Furthermore, at present, the application of recycled plastics by chemical industries has become extremely popular around the world. This study aimed to determine pallet flatness experimentally and numerically using recycled polypropylene with a large-scale pallet. Short-shot testing on injection molding was performed to obtain short-shot samples for confirmation of the flow front during simulated filling. The real injected pallet profile, which was measured by an ATOS, was compared after confirmation to the numerical profile of the pallet. The pallet’s flatness was accurately compared to the real experimental and numerical results. By adjusting the temperature of the cooling channel within the cavity plate to 55 °C, the flatness of the pallet achieved by the newly proposed sequential valve gate-opening scheme was about 7 mm, which meets the height directional warpage standard determined by the pre-set sequential scheme. The numerical flatness is in line with existing flatness values for pallets. Furthermore, the proposed cooling temperature gives the highest yield in terms of pallet molding from the perspective of the stakeholders. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

A Meta-Model to Predict the Drag Coefficient of a Particle Translating in Viscoelastic Fluids: A Machine Learning Approach

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Salah A. Faroughi

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Ana I. Roriz

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Célio Fernandes

Polymers 2022, 14(3), 430; https://doi.org/10.3390/polym14030430 - 21 Jan 2022

Cited by 7 | Viewed by 2561

Abstract

This study presents a framework based on Machine Learning (ML) models to predict the drag coefficient of a spherical particle translating in viscoelastic fluids. For the purpose of training and testing the ML models, two datasets were generated using direct numerical simulations (DNSs) [...] Read more.

This study presents a framework based on Machine Learning (ML) models to predict the drag coefficient of a spherical particle translating in viscoelastic fluids. For the purpose of training and testing the ML models, two datasets were generated using direct numerical simulations (DNSs) for the viscoelastic unbounded flow of Oldroyd-B (OB-set containing 12,120 data points) and Giesekus (GI-set containing 4950 data points) fluids past a spherical particle. The kinematic input features were selected to be Reynolds number,

0 < R e \leq 50

, Weissenberg number,

0 \leq W i \leq 10

, polymeric retardation ratio,

0 < ζ < 1

, and shear thinning mobility parameter,

0 < α < 1

. The ML models, specifically Random Forest (RF), Deep Neural Network (DNN) and Extreme Gradient Boosting (XGBoost), were all trained, validated, and tested, and their best architecture was obtained using a 10-Fold cross-validation method. All the ML models presented remarkable accuracy on these datasets; however the XGBoost model resulted in the highest

R^{2}

and the lowest root mean square error (RMSE) and mean absolute percentage error (MAPE) measures. Additionally, a blind dataset was generated using DNSs, where the input feature coverage was outside the scope of the training set or interpolated within the training sets. The ML models were tested against this blind dataset, to further assess their generalization capability. The DNN model achieved the highest

R^{2}

and the lowest RMSE and MAPE measures when inferred on this blind dataset. Finally, we developed a meta-model using stacking technique to ensemble RF, XGBoost and DNN models and output a prediction based on the individual learner’s predictions and a DNN meta-regressor. The meta-model consistently outperformed the individual models on all datasets. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Open AccessArticle

Exact Solution for Viscoelastic Flow in Pipe and Experimental Validation

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Polymers 2022, 14(2), 334; https://doi.org/10.3390/polym14020334 - 15 Jan 2022

Cited by 3 | Viewed by 1233

Abstract

The development of analytical methods for viscoelastic fluid flows is challenging. Currently, this problem has been solved for particular cases of multimode differential rheological equations of media state (Giesekus, the exponential form of Phan-Tien-Tanner, eXtended Pom-Pom). We propose a parametric method that yields [...] Read more.

The development of analytical methods for viscoelastic fluid flows is challenging. Currently, this problem has been solved for particular cases of multimode differential rheological equations of media state (Giesekus, the exponential form of Phan-Tien-Tanner, eXtended Pom-Pom). We propose a parametric method that yields solutions without additional assumptions. The method is based on the parametric representation of the unknown velocity functions and the stress tensor components as a function of coordinate. Experimental flow visualization based on the SIV (smoke image velocimetry) method was carried out to confirm the obtained results. Compared to the Giesekus model, the experimental data are best predicted by the eXtended Pom-Pom model. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Effects of Different Mold Materials and Coolant Media on the Cooling Performance of Epoxy-Based Injection Molds

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Polymers 2022, 14(2), 280; https://doi.org/10.3390/polym14020280 - 11 Jan 2022

Cited by 18 | Viewed by 1971

Abstract

Metal additive manufacturing techniques are frequently applied to the manufacturing of injection molds with a conformal cooling channel (CCC) in order to shorten the cooling time in the injection molding process. Reducing the cooling time in the cooling stage is essential to reducing [...] Read more.

Metal additive manufacturing techniques are frequently applied to the manufacturing of injection molds with a conformal cooling channel (CCC) in order to shorten the cooling time in the injection molding process. Reducing the cooling time in the cooling stage is essential to reducing the energy consumption in mass production. However, the distinct disadvantages include higher manufacturing costs and longer processing time in the fabrication of injection mold with CCC. Rapid tooling technology (RTT) is a widely utilized technology to shorten mold development time in the mold industry. In principle, the cooling time of injection molded products is affected by both injection mold material and coolant medium. However, little work has been carried out to investigate the effects of different mold materials and coolant media on the cooling performance of epoxy-based injection molds quantitatively. In this study, the effects of four different coolant media on the cooling performance of ten sets of injection molds fabricated with different mixtures were investigated experimentally. It was found that cooling water with ultrafine bubble is the best cooling medium based on the cooling efficiency of the injection molded parts (since the cooling efficiency is increased further by about 12.4% compared to the conventional cooling water). Mold material has a greater influence on the cooling efficiency than the cooling medium, since cooling time range of different mold materials is 99 s while the cooling time range for different cooling media is 92 s. Based on the total production cost of injection mold and cooling efficiency, the epoxy resin filled with 41 vol.% aluminum powder is the optimal formula for making an injection mold since saving in the total production cost about 24% is obtained compared to injection mold made with commercially available materials. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Non-Isothermal Free-Surface Viscous Flow of Polymer Melts in Pipe Extrusion Using an Open-Source Interface Tracking Finite Volume Method

by

Célio Fernandes

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Ahmad Fakhari

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Željko Tukovic

Polymers 2021, 13(24), 4454; https://doi.org/10.3390/polym13244454 - 19 Dec 2021

Cited by 6 | Viewed by 1966

Abstract

Polymer extrudate swelling is a rheological phenomenon that occurs after polymer melt flow emerges at the die exit of extrusion equipment due to molecular stress relaxations and flow redistributions. Specifically, with the growing demand for large scale and high productivity, polymer pipes have [...] Read more.

Polymer extrudate swelling is a rheological phenomenon that occurs after polymer melt flow emerges at the die exit of extrusion equipment due to molecular stress relaxations and flow redistributions. Specifically, with the growing demand for large scale and high productivity, polymer pipes have recently been produced by extrusion. This study reports the development of a new incompressible non-isothermal finite volume method, based on the Arbitrary Lagrangian–Eulerian (ALE) formulation, to compute the viscous flow of polymer melts obeying the Herschel–Bulkley constitutive equation. The Papanastasiou-regularized version of the constitutive equation is employed. The influence of the temperature on the rheological behavior of the material is controlled by the Williams–Landel–Ferry (WLF) function. The new method is validated by comparing the extrudate swell ratio obtained for Bingham and Herschel–Bulkley flows (shear-thinning and shear-thickening) with reference data found in the scientific literature. Additionally, the essential flow characteristics including yield-stress, inertia and non-isothermal effects were investigated. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Numerical Study of the Effect of Thixotropy on Extrudate Swell

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Polymers 2021, 13(24), 4383; https://doi.org/10.3390/polym13244383 - 14 Dec 2021

Cited by 8 | Viewed by 1719

Abstract

The extrusion of highly filled elastomers is widely used in the automotive industry. In this paper, we numerically study the effect of thixotropy on 2D planar extrudate swell for constant and fluctuating flow rates, as well as the effect of thixotropy on the [...] Read more.

The extrusion of highly filled elastomers is widely used in the automotive industry. In this paper, we numerically study the effect of thixotropy on 2D planar extrudate swell for constant and fluctuating flow rates, as well as the effect of thixotropy on the swell behavior of a 3D rectangular extrudate for a constant flowrate. To this end, we used the Finite Element Method. The state of the network structure in the material is described using a kinetic equation for a structure parameter. Rate and stress-controlled models for this kinetic equation are compared. The effect of thixotropy on extrudate swell is studied by varying the damage and recovery parameters in these models. It was found that thixotropy in general decreases extrudate swell. The stress-controlled approach always predicts a larger swell ratio compared to the rate-controlled approach for the Weissenberg numbers studied in this work. When the damage parameter in the models is increased, a less viscous fluid layer appears near the die wall, which decreases the swell ratio to a value lower than the Newtonian swell ratio. Upon further increasing the damage parameter, the high viscosity core layer becomes very small, leading to an increase in the swell ratio compared to smaller damage parameters, approaching the Newtonian value. The existence of a low-viscosity outer layer and a high-viscosity core in the die have a pronounced effect on the swell ratio for thixotropic fluids. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Lime/Sodium Carbonate Treated Seawater to Improve Flocculation and Sedimentation of Clay-Based Tailings

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Polymers 2021, 13(23), 4108; https://doi.org/10.3390/polym13234108 - 25 Nov 2021

Cited by 1 | Viewed by 1522

Abstract

Seawater treated with lime and sodium carbonate in different proportions to reduce magnesium and calcium contents is used in flocculation and sedimentation tests of artificial quartz and kaolin tailings. Solid complexes were separated from water by vacuum filtration, and factors such as lime/sodium [...] Read more.

Seawater treated with lime and sodium carbonate in different proportions to reduce magnesium and calcium contents is used in flocculation and sedimentation tests of artificial quartz and kaolin tailings. Solid complexes were separated from water by vacuum filtration, and factors such as lime/sodium carbonate ratio, kaolin content, flocculation time, and flocculant dose are evaluated. The growth of the aggregates was captured in situ by a focused beam reflectance measurement (FBRM) probe. Solid magnesium and calcium complexes are formed in raw seawater at pH 11, impairing the performance of flocculant polymers based on polyacrylamides. The results show that the settling rate improved when the treatment’s lime/sodium carbonate ratio increased. That is, when a greater removal of magnesium is prioritized over calcium. The amount of magnesium required to be removed depends on the mineralogy of the system: more clay will require more significant removal of magnesium. These results respond to the structural changes of the flocs, achieving that the more magnesium is removed, the greater the size and density of the aggregates. In contrast, calcium removal does not significantly influence flocculant performance. The study suggests the necessary conditions for each type of tailing to maximize water recovery, contributing to the effective closure of the water cycle in processes that use seawater with magnesium control. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Towards the Development of a Strategy to Characterize and Model the Rheological Behavior of Filled, Uncured Rubber Compounds

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Polymers 2021, 13(23), 4068; https://doi.org/10.3390/polym13234068 - 23 Nov 2021

Cited by 3 | Viewed by 1299

Abstract

In this paper, an experimental strategy is presented to characterize the rheological behavior of filled, uncured rubber compounds. Oscillatory shear experiments on a regular plate-plate rheometer are combined with a phenomenological thixotropy model to obtain model parameters that can be used to describe [...] Read more.

In this paper, an experimental strategy is presented to characterize the rheological behavior of filled, uncured rubber compounds. Oscillatory shear experiments on a regular plate-plate rheometer are combined with a phenomenological thixotropy model to obtain model parameters that can be used to describe the steady shear behavior. We compare rate- and stress-controlled kinetic equations for a structure parameter that determines the deformation history-dependent spectrum and, thus, the dynamic thixotropic behavior of the material. We keep the models as simple as possible and the characterization straightforward to maximize applicability. The model can be implemented in a finite element framework as a tool to simulate realistic rubber processing. This will be the topic of another work, currently under preparation. In shaping processes, such as rubber- and polymer extrusion, with realistic processing conditions, the range of shear rates is far outside the range obtained during rheological characterization. Based on some motivated choices, we will present an approach to extend this range. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Viscoelastic Property of an LDPE Melt in Triangular- and Trapezoidal-Loop Shear Experiment

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Shuxin Huang

Polymers 2021, 13(22), 3997; https://doi.org/10.3390/polym13223997 - 19 Nov 2021

Cited by 1 | Viewed by 1118

Abstract

The time-dependent viscoelastic behaviors of a low-density polyethylene melt (LDPE) in a triangular- and trapezoidal-loop shear experiment reported previously are described here by an integral-type Rivlin–Sawyers (RS) constitutive equation. The linear viscoelasticity of the melt was obtained through a dynamic frequency sweep experiment [...] Read more.

The time-dependent viscoelastic behaviors of a low-density polyethylene melt (LDPE) in a triangular- and trapezoidal-loop shear experiment reported previously are described here by an integral-type Rivlin–Sawyers (RS) constitutive equation. The linear viscoelasticity of the melt was obtained through a dynamic frequency sweep experiment at a small strain and fitted by a relaxation spectrum. The nonlinear viscoelasticity was characterized by viscosity. All the experimental viscoelastic behaviors of the melt can be divided into two types in terms of the predictions of the RS model: (1) predictable time-dependent viscoelastic behaviors at low shear rates or during short-term shear, and (2) unpredictable shear weakening behavior occurring at the high shear rate of 3–5 s⁻¹ during long-term shear with the characteristic time interval of about 40–100 s. The influence of experimental error caused possibly by inhomogeneous samples on the viscoelasticity of the melt was analyzed, and the large relative error in the experiment is about 10–30%. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Transfer Learning Applied to Characteristic Prediction of Injection Molded Products

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Yan-Mao Huang

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Wen-Ren Jong

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Shia-Chung Chen

Polymers 2021, 13(22), 3874; https://doi.org/10.3390/polym13223874 - 09 Nov 2021

Cited by 3 | Viewed by 1654

Abstract

This study addresses some issues regarding the problems of applying CAE to the injection molding production process where quite complex factors inhibit its effective utilization. In this study, an artificial neural network, namely a backpropagation neural network (BPNN), is utilized to render results [...] Read more.

This study addresses some issues regarding the problems of applying CAE to the injection molding production process where quite complex factors inhibit its effective utilization. In this study, an artificial neural network, namely a backpropagation neural network (BPNN), is utilized to render results predictions for the injection molding process. By inputting the plastic temperature, mold temperature, injection speed, holding pressure, and holding time in the molding parameters, these five results are more accurately predicted: EOF pressure, maximum cooling time, warpage along the Z-axis, shrinkage along the X-axis, and shrinkage along the Y-axis. This study first uses CAE analysis data as training data and reduces the error value to less than 5% through the Taguchi method and the random shuffle method, which we introduce herein, and then successfully transfers the network, which CAE data analysis has predicted to the actual machine for verification with the use of transfer learning. This study uses a backpropagation neural network (BPNN) to train a dedicated prediction network using different, large amounts of data for training the network, which has proved fast and can predict results accurately using our optimized model. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Optimization of the Warpage of Fused Deposition Modeling Parts Using Finite Element Method

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Polymers 2021, 13(21), 3849; https://doi.org/10.3390/polym13213849 - 08 Nov 2021

Cited by 8 | Viewed by 2857

Abstract

Fused deposition modeling (FDM) is one of the most affordable and widespread additive manufacturing (AM) technologies. Despite its simplistic implementation, the physics behind this FDM process is very complex and involves rapid heating and cooling of the polymer feedstock. As a result, highly [...] Read more.

Fused deposition modeling (FDM) is one of the most affordable and widespread additive manufacturing (AM) technologies. Despite its simplistic implementation, the physics behind this FDM process is very complex and involves rapid heating and cooling of the polymer feedstock. As a result, highly non-uniform internal stresses develop within the part, which can cause warpage deformation. The severity of the warpage is highly dependent on the process parameters involved, and therefore, currently extensive experimental studies are ongoing to assess their influence on the final accuracy of the part. In this study, a thermomechanical Finite Element model of the 3D printing process was developed using ANSYS. This model was compared against experimental results and several other analytical models available in the literature. The developed Finite Element Analysis (FEA) model demonstrated a good qualitative and quantitative correlation with the experimental results. An L9 orthogonal array, from Taguchi Design of Experiments, was used for the optimization of the warpage based on experimental results and numerical simulations. The optimum process parameters were identified for each objective and parts were printed using these process parameters. Both parts showed an approximately equal warpage value of 320 μm, which was the lowest among all 10 runs of the L9 array. Additionally, this model is extended to predict the warpage of FDM printed multi-material parts. The relative percentage error between the numerical and experimental warpage results for alternating and sandwich specimens are found to be 1.4% and 9.5%, respectively. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Numerical Simulation and Experimental Validation of Hybrid Injection Molded Short and Continuous Fiber-Reinforced Thermoplastic Composites

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Polymers 2021, 13(21), 3846; https://doi.org/10.3390/polym13213846 - 07 Nov 2021

Cited by 4 | Viewed by 2664

Abstract

In-situ thermoforming and overmolding of continuous fiber-reinforced thermoplastic composites by hybrid injection molding enables the mass production of thermoplastic lightweight structures with a complex geometry. In this study, the anisotropic mechanical behavior of such hybrid injection molded short and continuous fiber-reinforced thermoplastics and [...] Read more.

In-situ thermoforming and overmolding of continuous fiber-reinforced thermoplastic composites by hybrid injection molding enables the mass production of thermoplastic lightweight structures with a complex geometry. In this study, the anisotropic mechanical behavior of such hybrid injection molded short and continuous fiber-reinforced thermoplastics and the numerical simulation of the resulting mechanical properties under flexural loading were investigated. For this, the influence of the volume flow rate between 25 and 100 cm³/s during injection molding of a PP/GF30 short fiber-reinforced overmolding material was studied and showed a strong effect on the fiber orientation but not on the fiber length, as investigated by computer tomography and fiber length analysis. Thus, the resulting anisotropies of the stiffness and strength as well as the strain hardening investigated by tensile testing were considered when the mechanical behavior of a hybrid test structure of short and continuous fiber-reinforced thermoplastic composites was predicted by numerical simulations. For this, a PP/GF60 and PP/GF30 hybrid injection molded test structure was investigated by a numerical workflow with implemented injection molding simulation data. In result, the prediction of the mechanical behavior of the hybrid test structure under flexural loading by numerical simulation was significantly improved, leading to a reduction of the deviation of the numerically predicted and experimentally measured flexural strength from 21% to 9% in comparison to the isotropic material model without the implementation of the injection molding data. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Non-Isothermal Crystallization Kinetics of Poly(ethylene glycol) and Poly(ethylene glycol)-B-Poly(ε-caprolactone) by Flash DSC Analysis

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Polymers 2021, 13(21), 3713; https://doi.org/10.3390/polym13213713 - 27 Oct 2021

Cited by 3 | Viewed by 1462

Abstract

The non-isothermal crystallization behaviors of poly (ethylene glycol) (PEG) and poly (ethylene glycol)-b-poly(ε-caprolactone) (PEG-PCL) were investigated through a commercially available chip-calorimeter Flash DSC2+. The non-isothermal crystallization data under different cooling rates were analyzed by the Ozawa model, modified Avrami model, and Mo model. [...] Read more.

The non-isothermal crystallization behaviors of poly (ethylene glycol) (PEG) and poly (ethylene glycol)-b-poly(ε-caprolactone) (PEG-PCL) were investigated through a commercially available chip-calorimeter Flash DSC2+. The non-isothermal crystallization data under different cooling rates were analyzed by the Ozawa model, modified Avrami model, and Mo model. The results of the non-isothermal crystallization showed that the PCL block crystallized first, followed by the crystallization of the PEG block when the cooling rate was 50–200 K/s. However, only the PEG block can crystallize when the cooling rate is 300–600 K/s. The crystallization of PEG-PCL is completely inhibited when the cooling rate is 1000 K/s. The modified Avrami and Ozawa models were found to describe the non-isothermal crystallization processes well. The growth methods of PEG and PEG-PCL are both three-dimensional spherulitic growth. The Mo model shows that the crystallization rate of PEG is greater than that of PEG-PCL. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Radiation Shielding of Fiber Reinforced Polymer Composites Incorporating Lead Nanoparticles—An Empirical Approach

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Polymers 2021, 13(21), 3699; https://doi.org/10.3390/polym13213699 - 27 Oct 2021

Cited by 16 | Viewed by 3090

Abstract

In the present work, an empirical approach based on a computational analysis is performed to study the shielding properties of epoxy/carbon fiber composites and epoxy/glass fiber composites incorporating lead nanoparticle (PbNPs) additives in the epoxy matrix. For this analysis, an MCNP5 model is [...] Read more.

In the present work, an empirical approach based on a computational analysis is performed to study the shielding properties of epoxy/carbon fiber composites and epoxy/glass fiber composites incorporating lead nanoparticle (PbNPs) additives in the epoxy matrix. For this analysis, an MCNP5 model is developed for calculating the mass attenuation coefficients of the two fiber reinforced polymer (FRP) composites incorporating lead nanoparticles of different weight fractions. The model is verified and validated for different materials and different particle additives. Empirical correlations of the mass attenuation coefficient as a function of PbNPs weight fraction are developed and statistically analyzed. The results show that the mass attenuation coefficient increases as the weight fraction of lead nanoparticles increases up to a certain threshold (~15 wt%) beyond which the enhancement in the mass attenuation coefficient becomes negligible. Furthermore, statistical parameters of the developed correlations indicate that the correlations can accurately capture the behavior portrayed by the simulation data with acceptable root mean square error (RMSE) values. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Flows of Linear Polymer Solutions and Other Suspensions of Rod-like Particles: Anisotropic Micropolar-Fluid Theory Approach

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Vladimir Shelukhin

Polymers 2021, 13(21), 3679; https://doi.org/10.3390/polym13213679 - 25 Oct 2021

Cited by 1 | Viewed by 1078

Abstract

We formulate equations governing flows of suspensions of rod-like particles. Such suspensions include linear polymer solutions, FD-virus, and worm-like micelles. To take into account the particles that form and their rotation, we treat the suspension as a Cosserat continuum and apply the theory [...] Read more.

We formulate equations governing flows of suspensions of rod-like particles. Such suspensions include linear polymer solutions, FD-virus, and worm-like micelles. To take into account the particles that form and their rotation, we treat the suspension as a Cosserat continuum and apply the theory of micropolar fluids. Anisotropy of suspensions is determined through the inclusion of the microinertia tensor in the rheological constitutive equations. We check that the model is consistent with the basic principles of thermodynamics. In addition to anisotropy, the theory also captures gradient banding instability, coexistence of isotropic and nematic phases, sustained temporal oscillations of macroscopic viscosity, shear thinning and hysteresis. For the flow between two planes, we also establish that the total flow rate depends not only on the pressure gradient, but on the history of its variation as well. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Solvent Effect on the Structure and Properties of RGD Peptide (1FUV) at Body Temperature (310 K) Using Ab Initio Molecular Dynamics

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Polymers 2021, 13(19), 3434; https://doi.org/10.3390/polym13193434 - 07 Oct 2021

Cited by 7 | Viewed by 1886

Abstract

The structure and properties of the arginine-glycine-aspartate (RGD) sequence of the 1FUV peptide at 0 K and body temperature (310 K) are systematically investigated in a dry and aqueous environment using more accurate ab initio molecular dynamics and density functional theory calculations. The [...] Read more.

The structure and properties of the arginine-glycine-aspartate (RGD) sequence of the 1FUV peptide at 0 K and body temperature (310 K) are systematically investigated in a dry and aqueous environment using more accurate ab initio molecular dynamics and density functional theory calculations. The fundamental properties, such as electronic structure, interatomic bonding, partial charge distribution, and dielectric response function at 0 and 310 K are analyzed, comparing them in dry and solvated models. These accurate microscopic parameters determined from highly reliable quantum mechanical calculations are useful to define the range and strength of complex molecular interactions occurring between the RGD peptide and the integrin receptor. The in-depth bonding picture analyzed using a novel quantum mechanical metric, the total bond order (TBO), quantifies the role played by hydrogen bonds in the internal cohesion of the simulated structures. The TBO at 310 K decreases in the dry model but increases in the solvated model. These differences are small but extremely important in the context of conditions prevalent in the human body and relevant for health issues. Our results provide a new level of understanding of the structure and properties of the 1FUV peptide and help in advancing the study of RGD containing other peptides. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Taguchi Optimization of Roundness and Concentricity of a Plastic Injection Molded Barrel of a Telecentric Lens

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Chao-Ming Lin

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Yun-Ju Chen

Polymers 2021, 13(19), 3419; https://doi.org/10.3390/polym13193419 - 05 Oct 2021

Cited by 1 | Viewed by 1752

Abstract

Plastic is an attractive material for the fabrication of tubular optical instruments due to its light weight, high strength, and ease of processing. However, for plastic components fabricated using the injection molding technique, roundness and concentricity remain an important concern. For example, in [...] Read more.

Plastic is an attractive material for the fabrication of tubular optical instruments due to its light weight, high strength, and ease of processing. However, for plastic components fabricated using the injection molding technique, roundness and concentricity remain an important concern. For example, in the case of a telecentric lens, concentricity errors of the lens barrel result in optical aberrations due to the deviation of the light path, while roundness errors cause radial stress due to the mismatch of the lens geometry during assembly. Accordingly, the present study applies the Taguchi design methodology to determine the optimal injection molding parameters which simultaneously minimize both the overall roundness and the overall concentricity of the optical barrel. The results show that the geometrical errors of the optical barrel are determined mainly by the melt temperature, the packing pressure, and the cooling time. The results also show that the optimal processing parameters reduce the average volume shrinkage rate (from 4.409% to 3.465%) and the average deformations from (0.592 mm to 0.469 mm) of the optical barrel, and the corresponding standard deviation values are reduced from 1.528% to 1.297% and from 0.263 mm to 0.211 mm, respectively. In addition, the overall roundness and overall concentricity of the barrel in the four planes are positively correlated. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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A Hierarchical Grid Solver for Simulation of Flows of Complex Fluids

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Antonio Castelo

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Alexandre M. Afonso

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Wesley De Souza Bezerra

Polymers 2021, 13(18), 3168; https://doi.org/10.3390/polym13183168 - 18 Sep 2021

Cited by 4 | Viewed by 1334

Abstract

Tree-based grids bring the advantage of using fast Cartesian discretizations, such as finite differences, and the flexibility and accuracy of local mesh refinement. The main challenge is how to adapt the discretization stencil near the interfaces between grid elements of different sizes, which [...] Read more.

Tree-based grids bring the advantage of using fast Cartesian discretizations, such as finite differences, and the flexibility and accuracy of local mesh refinement. The main challenge is how to adapt the discretization stencil near the interfaces between grid elements of different sizes, which is usually solved by local high-order geometrical interpolations. Most methods usually avoid this by limiting the mesh configuration (usually to graded quadtree/octree grids), reducing the number of cases to be treated locally. In this work, we employ a moving least squares meshless interpolation technique, allowing for more complex mesh configurations, still keeping the overall order of accuracy. This technique was implemented in the HiG-Flow code to simulate Newtonian, generalized Newtonian and viscoelastic fluids flows. Numerical tests and application to viscoelastic fluid flow simulations were performed to illustrate the flexibility and robustness of this new approach. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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A Hybrid Cooling Model Based on the Use of Newly Designed Fluted Conformal Cooling Channels and Fastcool Inserts for Green Molds

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Abelardo Torres-Alba

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Jorge Manuel Mercado-Colmenero

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Juan De Dios Caballero-Garcia

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Cristina Martin-Doñate

Polymers 2021, 13(18), 3115; https://doi.org/10.3390/polym13183115 - 15 Sep 2021

Cited by 20 | Viewed by 2433

Abstract

The paper presents a hybrid cooling model based on the use of newly designed fluted conformal cooling channels in combination with inserts manufactured with Fastcool material. The hybrid cooling design was applied to an industrial part with complex geometry, high rates of thickness, [...] Read more.

The paper presents a hybrid cooling model based on the use of newly designed fluted conformal cooling channels in combination with inserts manufactured with Fastcool material. The hybrid cooling design was applied to an industrial part with complex geometry, high rates of thickness, and deep internal concavities. The geometry of the industrial part, besides the ejection system requirements of the mold, makes it impossible to cool it adequately using traditional or conformal standard methods. The addition of helical flutes in the circular conformal cooling channel surfaces generates a high number of vortexes and turbulences in the coolant flow, fostering the thermal exchange between the flow and the plastic part. The use of a Fastcool insert allows an optimal transfer of the heat flow in the slender core of the plastic part. An additional conformal cooling channel layout was required, not for the cooling of the plastic part, but for cooling the Fastcool insert, improving the thermal exchange between the Fastcool insert and the coolant flow. In this way, it is possible to maintain a constant heat exchange throughout the manufacturing cycle of the plastic part. A transient numerical analysis validated the improvements of the hybrid design presented, obtaining reductions in cycle time for the analyzed part by 27.442% in comparison with traditional cooling systems. The design of the 1 mm helical fluted conformal cooling channels and the use of the Fastcool insert cooled by a conformal cooling channel improves by 4334.9% the thermal exchange between the cooling elements and the plastic part. Additionally, it improves by 51.666% the uniformity and the gradient of the temperature map in comparison with the traditional cooling solution. The results obtained in this paper are in line with the sustainability criteria of green molds, centered on reducing the cycle time and improving the quality of the complex molded parts. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System

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Polymers 2021, 13(18), 3065; https://doi.org/10.3390/polym13183065 - 10 Sep 2021

Cited by 2 | Viewed by 1539

Abstract

In this study, the assembly behavior for two injected components made by a family mold system were investigated. Specifically, a feasible method was proposed to evaluate the characteristic length of two components within a family mold system using numerical simulation and experimental validation. [...] Read more.

In this study, the assembly behavior for two injected components made by a family mold system were investigated. Specifically, a feasible method was proposed to evaluate the characteristic length of two components within a family mold system using numerical simulation and experimental validation. Results show that as the packing pressure increases, the product index (characteristic length) becomes worse. This tendency was consistent for both the simulation prediction and experimental observation. However, for the same operation condition setting through a basic test, there were some differences in the product index between the simulation prediction and experimental observation. Specifically, the product index difference of the experimental observation was 1.65 times over that of the simulation prediction. To realize that difference between simulation and experiment, a driving force index (DFI) based on the injection pressure history curve was proposed. Through the DFI investigation, the internal driving force of the experimental system was shown to be 1.59 times over that of the simulation. The DFI was further used as the basis for machine calibration. Furthermore, after finishing machine calibration, the integrated CAE and DOE (called CAE-DOE) strategy can optimize the ease of assembly up to 20%. The result was validated by experimental observation. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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Application of New Triple Hook-Shaped Conformal Cooling Channels for Cores and Sliders in Injection Molding to Reduce Residual Stress and Warping in Complex Plastic Optical Parts

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Abelardo Torres-Alba

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Jorge Manuel Mercado-Colmenero

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Juan de Dios Caballero-Garcia

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Cristina Martin-Doñate

Polymers 2021, 13(17), 2944; https://doi.org/10.3390/polym13172944 - 31 Aug 2021

Cited by 21 | Viewed by 2644

Abstract

The paper presents a new design of a triple hook-shaped conformal cooling channels for application in optical parts of great thickness, deep cores, and high dimensional and optical requirements. In these cases, the small dimensions of the core and the high requirements regarding [...] Read more.

The paper presents a new design of a triple hook-shaped conformal cooling channels for application in optical parts of great thickness, deep cores, and high dimensional and optical requirements. In these cases, the small dimensions of the core and the high requirements regarding warping and residual stresses prevent the use of traditional and standard conformal cooling channels. The research combines the use of a new triple hook-shaped conformal cooling system with the use of three independent conformal cooling sub-systems adapted to the complex geometric conditions of the sliders that completely surround the optical part under study. Finally, the new proposed conformal cooling design is complemented with a small insert manufactured with a new Fastcool material located in the internal area of the optical part beside the optical facets. A transient numerical analysis validates the set of improvements of the new proposed conformal cooling system presented. The results show an upgrade in thermal efficiency of 267.10% in comparison with the traditional solution. The increase in uniformity in the temperature gradient of the surface of the plastic part causes an enhancement in the field of displacement and in the map of residual stresses reducing the total maximum displacements by 36.343% and the Von—Mises maximum residual stress by 69.280% in comparison with the results obtained for the traditional cooling system. Additionally, the new design of cooling presented in this paper reduces the cycle time of the plastic part under study by 32.61%, compared to the traditional cooling geometry. This fact causes a very high economic and energy saving in line with the sustainability of a green mold. The improvement obtained in the technological parameters will make it possible to achieve the optical and functional requirements established for the correct operation of complex optical parts, where it is not possible to use traditional cooling channels or standard conformal cooling layouts. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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A Simulation-Data-Based Machine Learning Model for Predicting Basic Parameter Settings of the Plasticizing Process in Injection Molding

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Matthias Schmid

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Dominik Altmann

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Georg Steinbichler

Polymers 2021, 13(16), 2652; https://doi.org/10.3390/polym13162652 - 10 Aug 2021

Cited by 5 | Viewed by 2479

Abstract

The optimal machine settings in polymer processing are usually the result of time-consuming and expensive trials. We present a workflow that allows the basic machine settings for the plasticizing process in injection molding to be determined with the help of a simulation-driven machine [...] Read more.

The optimal machine settings in polymer processing are usually the result of time-consuming and expensive trials. We present a workflow that allows the basic machine settings for the plasticizing process in injection molding to be determined with the help of a simulation-driven machine learning model. Given the material, screw geometry, shot weight, and desired plasticizing time, the model is able to predict the back pressure and screw rotational speed required to achieve good melt quality. We show how data sets can be pre-processed in order to obtain a generalized model that performs well. Various supervised machine learning algorithms were compared, and the best approach was evaluated in experiments on a real machine using the predicted basic machine settings and three different materials. The neural network model that we trained generalized well with an overall absolute mean error of 0.27% and a standard deviation of 0.37% on unseen data (the test set). The experiments showed that the mean absolute errors between the real and desired plasticizing times were sufficiently small, and all predicted operating points achieved good melt quality. Our approach can provide the operators of injection molding machines with predictions of suitable initial operating points and, thus, reduce costs in the planning phase. Further, this approach gives insights into the factors that influence melt quality and can, therefore, increase our understanding of complex plasticizing processes. Full article

(This article belongs to the Special Issue Advanced Polymer Simulation and Processing)

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