1,413 research outputs found
Dimension reduction for functionals on solenoidal vector fields
We study integral functionals constrained to divergence-free vector fields in
on a thin domain, under standard -growth and coercivity assumptions,
. We prove that as the thickness of the domain goes to zero, the
Gamma-limit with respect to weak convergence in is always given by the
associated functional with convexified energy density wherever it is finite.
Remarkably, this happens despite the fact that relaxation of nonconvex
functionals subject to the limiting constraint can give rise to a nonlocal
functional as illustrated in an example.Comment: 25 page
Heterogeneous thin films: Combining homogenization and dimension reduction with directors
We analyze the asymptotic behavior of a multiscale problem given by a
sequence of integral functionals subject to differential constraints conveyed
by a constant-rank operator with two characteristic length scales, namely the
film thickness and the period of oscillating microstructures, by means of
-convergence. On a technical level, this requires a subtile merging of
homogenization tools, such as multiscale convergence methods, with dimension
reduction techniques for functionals subject to differential constraints. One
observes that the results depend critically on the relative magnitude between
the two scales. Interestingly, this even regards the fundamental question of
locality of the limit model, and, in particular, leads to new findings also in
the gradient case.Comment: 28 page
Scan matching by cross-correlation and differential evolution
Scan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others. Methods that are accurate and adaptive and at the same time computationally efficient are required to enable location-based services in autonomous mobile devices. Such devices usually have a wide range of high-resolution sensors but only a limited processing power and constrained energy supply. This work introduces a novel high-level scan matching strategy that uses a combination of two advanced algorithms recently used in this field: cross-correlation and differential evolution. The cross-correlation between two laser range scans is used as an efficient measure of scan alignment and the differential evolution algorithm is used to search for the parameters of a transformation that aligns the scans. The proposed method was experimentally validated and showed good ability to match laser range scans taken shortly after each other and an excellent ability to match laser range scans taken with longer time intervals between them.Web of Science88art. no. 85
Scaling of the elastic energy of small balls for maps between manifolds with different curvature tensors
Motivated by experiments and formal asymptotic expansions in the physics
literature, Maor and Shachar (J. Elasticity 134 (2019), 149-173) studied the
behaviour of a model elastic energy of maps between manifolds with incompatible
metrics. For thin objects they analysed the scaling of the minimal elastic
energy as a function of the thickness. In particular they showed that for maps
from a ball of radius h in an oriented Riemannian manifold to Euclidean space,
the infimum of a model elastic energy per unit volume scales like the fourth
power of h and after rescaling one gets convergence to a quadratic expression
in the curvature tensor R(p), where p denotes the centre of the ball. In this
paper we show the same result for general compact oriented Riemannian targets
with R(p) replaced by a suitable difference of the curvature tensors in the
target and the domain, thus answering Open Question 1 in the paper by Maor and
Shachar. The result extends noncompact targets provided they satisfy a uniform
regularity condition. A key idea in the proof is to use Lipschitz
approximations to define a suitable notion of convergence.Comment: Typos corrected, exposition slightly expanded, reference [2] adde
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