The effect of non-Newtonian behavior on contact formation in an external gear pump

In an extrusion process, an external gear pump can be used to control the flow rate of the system. When extruding polymers, the viscosity is quite high, resulting in negligible inertia and thus laminar flow. The external gear pump contains two gears, one driven by a motor and one driven by means of contact with the other gear. In our previous work, the flow of a viscous fluid through an external gear pump was studied using the finite element method. Local mesh refinement was applied based on the respective distance between boundaries. Furthermore, the rotation of both gears was imposed. In this work, the rotation of one gear is imposed, whereas the other gear is freely rotating. However, the minimum distance between the gears is limited to a minimum value. When this value is reached, contact is assumed and also the rotation of second gear is imposed. A reversion of the torque on this gear results in a release of contact. In this manner, a quasi driver/driven situation is created in the numerical simulations. It is observed that contact is released periodically, and thus cannot be assumed present continuously, as is often prescribed. Non-Newtonian material properties, such as shear thinning and the pressure dependence of the density or the viscosity, alter how long contact is released during a tooth rotation

Modelling and optimization of the Cavity Transfer Mixer

The blending of different materials is an important process in polymer industry, where a good mixing is essential to guarantee adequate performances of the finished product. In the 80s a new device called the Cavity Transfer Mixer (CTM) was invented and patented by Gale at Rapra Technology Limited, as an add-on to be mounted downstream of existing extruders, in order to improve distributive mixing. The CTM consists of two concentric cylinders, the rotor and the stator, both provided with staggered rows of hemispherical cavities. The inner cylinder (rotor) rotates, while the outer (stator) remains still. At the same time, the pressure load imposed upstream, pushes the fluid through the mixer. The result of the interaction between the moving geometry, the imposed pressure load and the rheology of the fluid is the complex flow field driving the mixing mechanisms inside the device. Because of the variety of the phenomena involved, a clear understanding of the CTM mixing processes is still missing and the system development and optimization encounter noticeable difficulties. In this context, the present work proposes a full three dimensional model of the CTM, able to accurately simulate the device operations. A finite element solver provides the transient velocity field, which is used in the mapping method implementation in order to compute the concentration field evolution. A broad range of simulations is run assessing the impact on mixing of several geometrical and functioning parameters, such as the number of cavities per row, the number of rows, the size of the mixer, the rheology of the fluid and the ratio between the rotation speed and the fluid throughput. Results are used to develop some design and operation guidelines for the CTM

Modeling and simulation of viscoelastic film retraction

In this paper, we investigate the retraction of a circular viscoelastic liquid film with a hole initially present in its center by means of finite element numerical simulations. We study the whole retraction process, aiming at understanding the hole opening dynamics both when the hole does not feel any confinement and when it interacts with the solid wall bounding the film. The retraction behavior is also interpreted through a simple toy model, that highlights the physical mechanism underlying the process.We consider three different viscoelastic constitutive equations, namely, Oldroyd-B, Giesekus (Gsk), and Phan Thien-Tanner (PTT) models, and several system geometries, in terms of the film initial radius and thickness. For each given geometry, we investigate the effects of liquid inertia, elasticity, and flow-dependent viscosity on the dynamics of the hole opening. Depending on the relative strength of such parameters, qualitatively different features can appear in the retracting film shape and dynamics.When inertia is relevant, as far as the opening hole does not interact withthe wall bounding the film, the influence of liquid elasticity is very moderate,and the retraction dynamics tends to the one of Newtonian sheets; whenthe hole starts to interact with the solid wall, hole radius/opening velocityoscillations are detected. Such oscillations enhance at increasing elasticity.From the morphological point of view, the formation of a rim at the edge ofthe retracting film is observed. If inertial forces become less relevant withrespect to viscous forces, R-oscillations disappear, the hole opening velocitygoes through a maximum and then monotonically decays to zero, and norim forms during the film retraction. Geometrical changes have the effect ofenlarging or reducing the portion of the retraction dynamics not influencedby the presence of the solid wall with respect to the one governed by thehole-wall interactions

InParanoid 6: eukaryotic ortholog clusters with inparalogs

The InParanoid eukaryotic ortholog database (http://InParanoid.sbc.su.se/) has been updated to version 6 and is now based on 35 species. We collected all available ‘complete’ eukaryotic proteomes and Escherichia coli, and calculated ortholog groups for all 595 species pairs using the InParanoid program. This resulted in 2 642 187 pairwise ortholog groups in total. The orthology-based species relations are presented in an orthophylogram. InParanoid clusters contain one or more orthologs from each of the two species. Multiple orthologs in the same species, i.e. inparalogs, result from gene duplications after the species divergence. A new InParanoid website has been developed which is optimized for speed both for users and for updating the system. The XML output format has been improved for efficient processing of the InParanoid ortholog clusters

The ReIMAGINE Multimodal Warehouse: Using Artificial Intelligence for Accurate Risk Stratification of Prostate Cancer

Introduction. Prostate cancer (PCa) is the most frequent cancer diagnosis in men worldwide. Our ability to identify those men whose cancer will decrease their lifespan and/or quality of life remains poor. The ReIMAGINE Consortium has been established to improve PCa diagnosis. / Materials and methods. MRI will likely become the future cornerstone of the risk-stratification process for men at risk of early prostate cancer. We will, for the first time, be able to combine the underlying molecular changes in PCa with the state-of-the-art imaging. ReIMAGINE Screening invites men for MRI and PSA evaluation. ReIMAGINE Risk includes men at risk of prostate cancer based on MRI, and includes biomarker testing. / Results. Baseline clinical information, genomics, blood, urine, fresh prostate tissue samples, digital pathology and radiomics data will be analysed. Data will be de-identified, stored with correlated mpMRI disease endotypes and linked with long term follow-up outcomes in an instance of the Philips Clinical Data Lake, consisting of cloud-based software. The ReIMAGINE platform includes application programming interfaces and a user interface that allows users to browse data, select cohorts, manage users and access rights, query data, and more. Connection to analytics tools such as Python allows statistical and stratification method pipelines to run profiling regression analyses. / Discussion. The ReIMAGINE Multimodal Warehouse comprises a unique data source for PCa research, to improve risk stratification for PCa and inform clinical practice. The de-identified dataset characterized by clinical, imaging, genomics and digital pathology PCa patient phenotypes will be a valuable resource for the scientific and medical community

Analyzing circadian expression data by harmonic regression based on autoregressive spectral estimation

Motivation: Circadian rhythms are prevalent in most organisms. Identification of circadian-regulated genes is a crucial step in discovering underlying pathways and processes that are clock-controlled. Such genes are largely detected by searching periodic patterns in microarray data. However, temporal gene expression profiles usually have a short time-series with low sampling frequency and high levels of noise. This makes circadian rhythmic analysis of temporal microarray data very challenging