Roman Christopher Kerschbaumer

Selecting the optimal settings for the production of rubber goods can be a very time-consuming and resource-intensive process. A promising method for optimizing rubber processing in a short period of time is the use of simulation routines. However, process simulations have only recently enabled meaningful predictions of not only the part’s state of cure but also its mechanical characteristics. As a first approach, second-order polynomials were considered suitable for describing the properties of compression-molded parts. However, more precision is required for injection molding due to the narrower distribution of mechanical characteristics of parts produced at different vulcanization temperatures. This became evident when the approximation of mechanical data with second order models partly revealed significant failures of part behavior prediction. To tackle this issue, a combined approach for approximation is proposed in this contribution by means of logistic growth function in addition to second order polynomials. To feed the model, an experimental plan was designed for producing injection-molded parts from an SBR compound at various temperatures and to different degrees of cure. The parts obtained were then characterized mechanically, and the results were opposed to varying degrees of cure and extents of reaction to calculate the model coefficients. Once available, a simulation-based calculation of the mechanical part quality is possible. The comparison of test results from the simulation and the real process has shown a reliable prediction, as simulation results were found within the natural deviation of the real measurements.

Application of elastomers in general demands the conversion of their soluble networks into crosslinked structures. This abrupt change causes several modifications, both in the atomic/molecular level and at the macro‐scale. In this study, solid silicone rubber (high molecular weight poly(dimethylsiloxane)), was crosslinked with dicumylperoxide (DCP), a widely used crosslinking agent by the rubber industry. The changes caused by different DCP concentrations were investigated, aiming to bring attention to the molecular transformations, usually neglected when processing‐oriented studies are conducted. DCP concentration showed a limited contribution to the network's molecular dynamics, which was found to be mainly dominated by entanglements. The dominance of entanglements over other molecular constraints, like crosslink points, justifies the threshold and counter‐intuitive behavior of tensile and hardness properties. However, differences were found in the crystallization ability after crosslinking, when the more crosslink points were introduced, the lower the crystallinity was and the less stable the PDMS crystallites were. In addition to providing a deeper understanding of an industrially applied rubber system n terms of the effective concentration of DCP, and the reasoning behind such concentration, the findings of this study add to the state‐of‐the‐art comprehension of elastomeric networks, and how they behave on a molecular level.

Elastomeric materials are often used as components that undergo cyclic loading during application, such as tires, seals, and hoses. For this reason, the long-term performance, or more precisely the crack growth behavior, is of great importance. Even though several studies investigated the fatigue behavior of rubber materials during the last 80 years, this topic is still widely under discussion and remains of great interest among scientists. Mars and Fatemi reviewed the developments of the field in the beginning of 2000, however, this paper considers the overall development including new findings to serve as a guide for further investigations in the field of fatigue of elastomers. For this purpose, the usual measurement methods and their evaluation, as well as the most important factors influencing the fatigue behavior, like the formulation of the rubber compound or the application and testing conditions, are explained in detail. Furthermore, an outlook is given on parameters that still need to be scientifically investigated, such as the influence of filler orientations or the selected manufacturing method, in order to fully understand fatigue crack growth.

The perception of a surface and its haptic properties are significantly influenced by roughness and microstructure, respectively, whereby non-negligible parameters include friction, contact area, temperature, and humidity between the human finger and the examined surface. In particular, for a scientific investigation on haptic influences, the production of samples with a defined surface roughness is indispensable. The aim of this study is to analyze the impact of various mold insert roughnesses combined with the influences of particle size, filler-, and compatibilizer content on impression quality. An unfilled high density polyethylene was chosen as a reference for the impression quality investigations, while fillers with significantly different particle sizes and a compatibilizer were used to produce proprietary compounds. Injection molded parts were manufactured utilizing mold inserts with three different line roughness values. To support the obtained results, a multivariate analysis of variance, a simulation of the filling phase as well as a rheological material characterization were conducted. The results revealed that (i) the impression quality can be independent of the applied insert roughness based on the filler particle size that was studied, (ii) an increasing on both filler particle size and compatibilizer content raise the sample roughness as a function of the penetration ability of the filler into the insert valleys, and (iii) with a higher insert roughness, the thermoplastic moldings generally exhibit a significantly smoother topography. An assumed correlation between part roughness and melt viscosity could not be confirmed.

Computational fluid dynamics (CFD) simulation is an important tool as it enables engineers to study different design options without a time-consuming experimental workload. However, the prediction accuracy of any CFD simulation depends upon the set boundary conditions and upon the applied rheological constitutive equation. In the present study the viscoelastic nature of an unfilled gum acrylonitrile butadiene rubber (NBR) is considered by applying the integral and time-dependent Kaye–Bernstein–Kearsley–Zapas (K-BKZ) rheological model. First, exhaustive testing is carried out in the linear viscoelastic (LVE) and non-LVE deformation range including small amplitude oscillatory shear (SAOS) as well as high pressure capillary rheometer (HPCR) tests. Next, three abrupt capillary dies and one tapered orifice die are modeled in Ansys POLYFLOW. The pressure prediction accuracy of the K-BKZ/Wagner model was found to be excellent and insensitive to the applied normal force in SAOS testing as well as to the relation of first and second normal stress differences, provided that damping parameters are fitted to steady-state rheological data. Moreover, the crucial importance of viscoelastic modeling is proven for rubber materials, as two generalized Newtonian fluid (GNF) flow models severely underestimate measured pressure data, especially in contraction flow-dominated geometries.

Injection molding of rubber compounds is an easily conducted yet sophisticated method for rubber processing. Simulation software is used to examine the optimal process conditions, identify failure scenarios, and save resources. Due to the complexity of the entire process, various aspects have to be considered in the numerical approach. This contribution focused on a comparison of process simulations with various definitions of the material’s inlet temperature, ranging from a stepwise increase, but constant temperature, to an exact axial mass temperature profile prior to injection. The latter was obtained with a specially designed, unique test stand consisting of a plasticizing cylinder equipped with pressure sensors, a throttle valve for pressure adjustments, and a measurement bar with thermocouples for the determination of the actual state of the mass temperature. For the verification of the theoretical calculations, practical experiments were conducted on a rubber injection molding machine equipped with the mold used in the simulation. The moldings, obtained at different vulcanization time, were characterized mechanically and the results were normalized to a relative degree of cure in order to enable comparison of the real process and the simulation. Considering the actual state of the mass temperature, the simulation showed an excellent correlation of the measured and calculated mass temperatures in the cold runner. Additionally, the relative degree of cure was closer to reality when the mass temperature profile after dosing was applied in the simulation.

Highly filled rubber compounds exhibit a unique rheological behavior, which is affected by its filler–filler and filler–matrix interactions leading to pronounced nonlinear viscoelasticity. The necessity to consider these characteristics in rheological testing and modeling, adds further complexity providing universally valid numerical descriptions. In the present study, the pressure driven contraction and capillary flow of a carbon black filled hydrogenated acrylonitrile–butadiene rubber compound is studied both experimentally and numerically. Rheological testing indicates no pronounced slippage at the wall but a shear sensitive plug flow at the centerline. The viscoelastic Kaye‐Bernstein–Kearsley–Zapas/Wagner, the viscoplastic Herschel–Bulkley and the viscous power‐law models are used in computational fluid dynamic simulations aiming to predict measured pressure drops in an orifice and various capillary dies. Viscoelastic modeling is found of particular importance describing contraction flow dominated areas, whereas viscous models are able to predict pressure drops of capillary flows well. POLYM. ENG. SCI., 60:32–43, 2020. © 2019 The Authors. Polymer Engineering & Science published by Wiley Periodicals, Inc. on behalf of Society of Plastics Engineers.