1,896 research outputs found
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
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
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
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
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