An axisymmetric model for thread forming in polycarbonate and polypropylene screw and boss fasteners

Plastic boss and screw fasteners are an economical means of securing automotive components, such as instrument or body panels. However, new materials and/or suboptimal design present challenges to the boss/screw effectiveness. Failure of a boss/screw can result is loss of functional performance or increased squeak and rattle. Failure is often controlled by what occurs during the initial thread‐forming process. Thus, the goal of this paper is to develop an FEA model to elucidate the thread‐forming process so that we can facilitate subsequent design and/or process optimization, and understand potential failure modes. The FEA must accommodate nonlinear couplings, such as large strain and heat transfer. Heat generation is present in the forms of interfacial shear heating and plastic work associated with the large deformation of the interface between the boss and screw. Strain rate‐dependent materials are included using the Eyring theory for plastic flow of polymeric materials. Results of the model are presented and compared to experimentally determined torque curves and temperatures. Polym. Eng. Sci. 44:1498–1508, 2004. © 2004 Society of Plastics Engineers.     

Is the particle deposition in a cell exposure facility comparable to the lungs? A computer model approach

Abstract

Cell exposure experiments at the air-liquid interface (ALI) are used increasingly as indicators for health effects and for the impact of aerosols on the lung. Thereby the aerosol particles are kept airborne and can deposit on a cell surface area similar to the human respiratory tract (RT). However, geometry and air flow rates of an ALI system deviate considerably from the RT. As the tissue-delivered particle dose to the lungs (TD) can hardly be measured, computer models of particle deposition are used here to mimic both the particle deposition at ALI and in the RT. An ALI exposure setup (VitroCell GmbH) for an airflow rate of 100 cm³ min^?1 is selected, where the particle deposition model has been verified experimentally. For the RT we use the hygroscopic lung deposition model of Ferron et al. (2013 Ferron, G. A., S. Upadhyay, R. Zimmermann, and E. Karg. 2013. Model of the deposition of aerosol particles in the respiratory tract of the rat. II. Hygroscopic particle deposition. J. Aerosol Med. Pulm. Drug Deliv. 26 (2):101–19. doi:10.1089/jamp.2011.0965.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). Model runs are performed for the particle deposition and for the deposited particles per surface area in both the ALI and the RT. The results show that the ALI-deposited mass is 1-2 orders of magnitude higher than in the alveolar region, because the surface area of the lung region is substantially larger. A particle size range from 40 to 450 nm is identified, where the ratio of both the deposition in a lung region and the deposition at the ALI varies by a factor less than two. Mean values for this ratio are 31 and 101 for the tracheo-bronchial and the alveolar region, respectively. The same size range is found for the ratio of the deposited particles per surface area in a lung region and at the ALI. For this range the mean surface deposition at the ALI is 23- and 1575-times larger than in the tracheo-bronchial and the alveolar lung region, respectively. The effect is partly compensated by different flow rate and cell size.

Copyright © 2020 American Association for Aerosol Research     

Impact of processing conditions and sizing on the thermomechanical and morphological properties of polypropylene/carbon fiber composites fabricated by material extrusion additive manufacturing

For the 3D printed composites, fiber alignment is affected by the direction of melt-flow during extrusion of filaments and subsequently through the printing nozzle. The resulting fibers orientation and the fiber-matrix compatibility have a direct correlation with mechanical properties. This study investigates the impact of processing conditions on the state of the carbon fiber types and their orientation on the mechanical properties of 3D-printed composites. Short and long carbon fibers were used as starting reinforcing materials, and the state of fibers at the beginning and on the printed parts were evaluated. Strong anisotropy in terms of mechanical properties (flexural and impact properties) was observed for the samples printed with different printing orientations. Interestingly, the number of voids in the printed composites was found to be correlated with the fiber types. The present work provides a step towards the optimization of tailored composite properties by additive manufacturing.     

Smoothed Particle Hydrodynamics (SPH) simulation of a high-pressure homogenization process

High-pressure homogenization is a widely used process in the food, pharmaceutical, and cosmetic industry for producing emulsions. Because of small dimensions and high velocities, the experimental and numerical investigation of such a process is challenging. Hence, the development of products is mostly based on trial and error. In this paper, simulations of a generic high-pressure homogenization process using the Lagrangian, mesh-free smoothed particle hydrodynamics (SPH) method are presented and compared to experimental findings using Micro-Particle Image Velocimetry (μ-PIV). The SPH code has been developed and validated with the scope of simulating technical relevant multi-phase problems (Höfler et al. 2012). The present simulations cover the investigation of two different dynamic viscosities of the dispersed phase as well as different droplet trajectories. The comparison between the simulations and the experiments focusses on the velocity distribution of the continuous phase and the droplet deformation and breakup. In both cases a qualitatively good agreement is observed, demonstrating the ability of our SPH implementation for simulating technical relevant two-phase flows.     

A Python extension for the massively parallel multiphysics simulation framework waLBerla

We present a Python extension to the massively parallel HPC simulation toolkit waLBerla. waLBerla is a framework for stencil based algorithms operating on block-structured grids, with the main application field being fluid simulations in complex geometries using the lattice Boltzmann method. Careful performance engineering results in excellent node performance and good scalability to over 400,000 cores. To increase the usability and flexibility of the framework, a Python interface was developed. Python extensions are used at all stages of the simulation pipeline: they simplify and automate scenario setup, evaluation, and plotting. We show how our Python interface outperforms the existing text-file-based configuration mechanism, providing features like automatic nondimensionalization of physical quantities and handling of complex parameter dependencies. Furthermore, Python is used to process and evaluate results while the simulation is running, leading to smaller output files and the possibility to adjust parameters dependent on the current simulation state. C++ data structures are exported such that a seamless interfacing to other numerical Python libraries is possible. The expressive power of Python and the performance of C++ make development of efficient code with low time effort possible.     

Image blur and energy broadening effects in XPEEM

We report image blurring and energy broadening effects in energy-filtered XPEEM when illuminating the specimen with soft X-rays at high flux densities. With a flux of 2×10¹³ photons/s, the lateral resolution in XPEEM imaging with either core level or secondary electrons is degraded to more than 50 nm. Fermi level broadening up to several hundred meV and spectral shift to higher kinetic energies are also systematically observed. Simple considerations suggest that these artifacts result from Boersch and Loeffler effects, and that the electron-electron interactions are strongest in the initial part of the microscope optical path. Implications for aberration corrected instruments are discussed.     

Query answering under probabilistic uncertainty in Datalog+ / − ontologies

The recently introduced Datalog+?/?? family of ontology languages is especially useful for representing and reasoning over lightweight ontologies, and is set to play a central role in the context of query answering and information extraction for the Semantic Web. Recently, it has become apparent that it is necessary to develop a principled way to handle uncertainty in this domain. In addition to uncertainty as an inherent aspect of the Web, one must also deal with forms of uncertainty due to inconsistency and incompleteness, uncertainty resulting from automatically processing Web data, as well as uncertainty stemming from the integration of multiple heterogeneous data sources. In this paper, we take an important step in this direction by developing a probabilistic extension of Datalog+?/??. This extension uses Markov logic networks as the underlying probabilistic semantics. Here, we focus especially on scalable algorithms for answering threshold queries, which correspond to the question “what is the set of all ground atoms that are inferred from a given probabilistic ontology with a probability of at least p?”. These queries are especially relevant to Web information extraction, since uncertain rules lead to uncertain facts, and only information with a certain minimum confidence is desired. We present several algorithms, namely a basic approach, an anytime one, and one based on heuristics, which is guaranteed to return sound results. Furthermore, we also study inconsistency in probabilistic Datalog+?/?? ontologies. We propose two approaches for computing preferred repairs based on two different notions of distance between repairs, namely symmetric and score-based distance. We also study the complexity of the decision problems corresponding to computing such repairs, which turn out to be polynomial and NP-complete in the data complexity, respectively.