A 3D modelling approach for fluid progression during process simulation of wet compression moulding - Motivation & approach

Wet compression moulding (WCM) provides large-scale production potential for continuous fibre-reinforced structural components due to simultaneous infiltration and draping during moulding (viscous draping). Due to thickness-dominated infiltration of the laminate, comparatively low cavity pressures are sufficient – a considerable economic advantage. Experimental and numerical investigations prove strong mutual dependencies between the physical mechanisms, especially between resin flow and textile forming. Understanding and suitable modelling of these occurring physical mechanisms is crucial for process development and final part design. While existing modelling approaches are suitable for infiltration of preformed fabrics within various liquid moulding technologies, such as CRTM/RTM or VARI, WCM requires a fully coupled simulation approach for resin progression and concurrent stack deformation. Thus, the key challenge is to efficiently link these two aspects in a suitable framework. First, this work demonstrates that a three-dimensional approach for fluid progression during moulding is needed to capture WCM-process boundary conditions. In this regard, a novel test bench is used to investigate the impact of infiltration on the transversal compaction behaviour of a woven fabric. Moreover, the test setup is applied to determine the in-plane permeability values of the same material corresponding to the beforehand applied compaction states. Results are verified by comparison with an existing linear test setup. In the second part, initial steps towards a three dimensional extension of an existing 2D modelling approach are outlined. For this purpose, a macroscopic FE-based three-dimensional formulation of Darcy’s law is utilized within a User-Element in Abaqus/Explicit. Essential mechanisms within the element are presented. Additional control volumes (FE/CV) are applied to ensure mass conservation. Eventually, it is demonstrated, that the simulation model can predict the average fluid pressure beneath a punch during pre-infiltrated compaction experiments. Finally, major benefits and forthcoming steps for a fully-coupled 3D modelling approach for WCM are outlined

The outcome of protoplanetary dust growth: pebbles, boulders, or planetesimals? I. Mapping the zoo of laboratory collision experiments

The growth processes from protoplanetary dust to planetesimals are not fully understood. Laboratory experiments and theoretical models have shown that collisions among the dust aggregates can lead to sticking, bouncing, and fragmentation. However, no systematic study on the collisional outcome of protoplanetary dust has been performed so far so that a physical model of the dust evolution in protoplanetary disks is still missing. We intend to map the parameter space for the collisional interaction of arbitrarily porous dust aggregates. This parameter space encompasses the dust-aggregate masses, their porosities and the collision velocity. With such a complete mapping of the collisional outcomes of protoplanetary dust aggregates, it will be possible to follow the collisional evolution of dust in a protoplanetary disk environment. We use literature data, perform own laboratory experiments, and apply simple physical models to get a complete picture of the collisional interaction of protoplanetary dust aggregates. In our study, we found four different types of sticking, two types of bouncing, and three types of fragmentation as possible outcomes in collisions among protoplanetary dust aggregates. We distinguish between eight combinations of porosity and mass ratio. For each of these cases, we present a complete collision model for dust-aggregate masses between 10^-12 and 10^2 g and collision velocities in the range 10^-4 to 10^4 cm/s for arbitrary porosities. This model comprises the collisional outcome, the mass(es) of the resulting aggregate(s) and their porosities. We present the first complete collision model for protoplanetary dust. This collision model can be used for the determination of the dust-growth rate in protoplanetary disks.Comment: accepted by Astronomy and Astrophysic

Learning Class Regularized Features for Action Recognition

Training Deep Convolutional Neural Networks (CNNs) is based on the notion of using multiple kernels and non-linearities in their subsequent activations to extract useful features. The kernels are used as general feature extractors without specific correspondence to the target class. As a result, the extracted features do not correspond to specific classes. Subtle differences between similar classes are modeled in the same way as large differences between dissimilar classes. To overcome the class-agnostic use of kernels in CNNs, we introduce a novel method named Class Regularization that performs class-based regularization of layer activations. We demonstrate that this not only improves feature search during training, but also allows an explicit assignment of features per class during each stage of the feature extraction process. We show that using Class Regularization blocks in state-of-the-art CNN architectures for action recognition leads to systematic improvement gains of 1.8%, 1.2% and 1.4% on the Kinetics, UCF-101 and HMDB-51 datasets, respectively

FM 047-02: a collisional pair of galaxies with a ring

Aims. We investigate the nature of the galaxy pair FM 047-02, which has been proposed as an archetype of the Solitaire types of peculiar (collisional) ring galaxies. Methods. The study is based on long-slit spectrophotometric data in the range of 3500-9500 angstrons obtained with the Gemini Multi-ObjectComment: 07 pages, 06 figures, 02 tables. arXiv admin note: text overlap with arXiv:1206.071