Abstract:In this study, a non-nucleated homopolymer (HP) and random copolymer (RACO), as well as a nucleated HP and heterophasic copolymer (HECO) were investigated regarding their crystallization kinetics. Using pvT-measurements and fast scanning chip calorimetry (FSC), the crystallization behavior was analyzed as a function of pressure, cooling rate and temperature. It is shown that pressure and cooling rate have an opposite influence on the crystallization temperature of the materials. Furthermore, the addition of nu… Show more
“…The HTC ranges are chosen in reference to the default Moldflow values ( HTC filling = 5000W/m 2• C , HTC packing = 2500W/m 2• C ). As for the pressure-dependent viscosity model parameter, the variation range goes from 0 up to 0.4 K/MPa in order to cover the actual behavior of POM and other typical semicrystalline thermoplastics such as PP [42].…”
The computational cost of high-fidelity injection molding simulations has been growing in the past years making it more and more challenging to use them for performing analyses such as optimizations or uncertainty quantification. Surrogate modeling offers a cheaper way to realize such studies and has been gaining attention in the field of injection molding simulation. In this work, we propose to compare three surrogate modeling techniques along with two design of experiment methods in their ability to predict the pressure signal at a surface node in a Moldflow simulation by varying process and modeling parameters. A Sobol sensitivity analysis is performed to study the contribution of the varied parameters on the pressure results. In addition, one of the generated models is used along with experimental pressure sensor data to improve the pressure estimation by calibrating the heat transfer coefficients during filling and packing as well as the pressure-dependency coefficient in the Cross-WLF viscosity model. This resulted in major improvements of the pressure predictions for all 27 considered cases in comparison to using the default heat transfer coefficients and viscosity model parameter.
“…The HTC ranges are chosen in reference to the default Moldflow values ( HTC filling = 5000W/m 2• C , HTC packing = 2500W/m 2• C ). As for the pressure-dependent viscosity model parameter, the variation range goes from 0 up to 0.4 K/MPa in order to cover the actual behavior of POM and other typical semicrystalline thermoplastics such as PP [42].…”
The computational cost of high-fidelity injection molding simulations has been growing in the past years making it more and more challenging to use them for performing analyses such as optimizations or uncertainty quantification. Surrogate modeling offers a cheaper way to realize such studies and has been gaining attention in the field of injection molding simulation. In this work, we propose to compare three surrogate modeling techniques along with two design of experiment methods in their ability to predict the pressure signal at a surface node in a Moldflow simulation by varying process and modeling parameters. A Sobol sensitivity analysis is performed to study the contribution of the varied parameters on the pressure results. In addition, one of the generated models is used along with experimental pressure sensor data to improve the pressure estimation by calibrating the heat transfer coefficients during filling and packing as well as the pressure-dependency coefficient in the Cross-WLF viscosity model. This resulted in major improvements of the pressure predictions for all 27 considered cases in comparison to using the default heat transfer coefficients and viscosity model parameter.
“…However, the crystallization temperature of iPP during cooling increases with the increasing pressure. Recently, a shift factor of 0.23-0.26 • C/MPa at cooling rates of 0.1-7 • C/min was determined [30,31]. Mezghani and Phillips [32] elaborated a temperature-pressure phase diagram for the αand γ-forms of iPP, and also determined the increase in the equilibrium melting temperature (T m 0 ) of both forms with the increasing pressure as well as the pressure dependence of the transition temperature between the αand γ-domains.…”
The unique nonparallel chain arrangement in the orthorhombic γ-form lamellae of isotactic polypropylene (iPP) results in the enhancement of the mechanical properties of γ-iPP. Our study aimed at the investigation of the mechanical properties of γ-iPP nanocomposites with 1–5 wt.% multiwall carbon nanotubes (MWCNT) and 5 wt.% organo-modified montmorillonite prepared by melt-mixing and high-pressure crystallization. Neat iPP and the nanocomposites were crystallized under high pressures of 200 MPa and 300 MPa, and for comparison under 1.4 MPa, in a custom-built high-pressure cell. The structure of the materials was studied using WAXS, SAXS, DSC, and SEM, whereas their mechanical properties were tested in plane-strain compression. Under a small pressure of 1.4 MPa, polymer matrix in all materials crystallized predominantly in the α-form, the most common monoclinic form of iPP, whereas under high pressure it crystallized in the γ-form. This caused a significant increase in the elastic modulus, yield stress, and stress at break. Moreover, due to the presence of MWCNT, these parameters of the nanocomposites exceeded those of the neat polymer. As a result, a 60–70% increase in the elastic modulus, yield stress, and stress at break was achieved by filling of iPP with MWCNT and high-pressure crystallization.
“…At present, in addition to the review, 14 regular articles [2][3][4][5][6][7][8][9][10][11][12][13][14][15] have been published on the special topic of "polymer crystallization". These contributions span research topics ranging from molecular mechanisms of nucleation and nucleating agents to the effect of molecular structures, chain conformations and processing parameters on the nucleation and crystallization behavior of various polymers.…”
mentioning
confidence: 99%
“…The polymorphic transition probably resulted from a gauche to trans flow-induced conformation transition. Kuehnert et al [10] analyzed the crystallization kinetics of four grades of polypropylene (with and without nucleating agents) at different temperatures and under various pressures via PVT-measurements and fast scanning chip calorimetry. It was observed that the pressure-dependent shift factor of the crystallization temperature was independent of the material.…”
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.