93,091 research outputs found
Performance measures for single-degree-of-freedom energy harvesters under stochastic excitation
We develop performance criteria for the objective comparison of different
classes of single-degree-of-freedom oscillators under stochastic excitation.
For each family of oscillators, these objective criteria take into account the
maximum possible energy harvested for a given response level, which is a
quantity that is directly connected to the size of the harvesting
configuration. We prove that the derived criteria are invariant with respect to
magnitude or temporal rescaling of the input spectrum and they depend only on
the relative distribution of energy across different harmonics of the
excitation. We then compare three different classes of linear and nonlinear
oscillators and using stochastic analysis tools we illustrate that in all cases
of excitation spectra (monochromatic, broadband, white-noise) the optimal
performance of all designs cannot exceed the performance of the linear design.
Subsequently, we study the robustness of this optimal performance to small
perturbations of the input spectrum and illustrate the advantages of nonlinear
designs relative to linear ones.Comment: 24 pages, 12 figure
A moment-equation-copula-closure method for nonlinear vibrational systems subjected to correlated noise
We develop a moment equation closure minimization method for the inexpensive
approximation of the steady state statistical structure of nonlinear systems
whose potential functions have bimodal shapes and which are subjected to
correlated excitations. Our approach relies on the derivation of moment
equations that describe the dynamics governing the two-time statistics. These
are combined with a non-Gaussian pdf representation for the joint
response-excitation statistics that has i) single time statistical structure
consistent with the analytical solutions of the Fokker-Planck equation, and ii)
two-time statistical structure with Gaussian characteristics. Through the
adopted pdf representation, we derive a closure scheme which we formulate in
terms of a consistency condition involving the second order statistics of the
response, the closure constraint. A similar condition, the dynamics constraint,
is also derived directly through the moment equations. These two constraints
are formulated as a low-dimensional minimization problem with respect to
unknown parameters of the representation, the minimization of which imposes an
interplay between the dynamics and the adopted closure. The new method allows
for the semi-analytical representation of the two-time, non-Gaussian structure
of the solution as well as the joint statistical structure of the
response-excitation over different time instants. We demonstrate its
effectiveness through the application on bistable nonlinear
single-degree-of-freedom energy harvesters with mechanical and electromagnetic
damping, and we show that the results compare favorably with direct Monte-Carlo
Simulations
A Model of Low-lying States in Strongly Interacting Electroweak Symmetry-Breaking Sector
It is proposed that, in a strongly-interacting electroweak sector, besides
the Goldstone bosons, the coexistence of a scalar state () and vector
resonances such as [)], [] and
[] is required by the proper Regge behavior of the
forward scattering amplitudes. This is a consequence of the following
well-motivated assumptions: (a). Adler-Weisberger-type sum rules and the
superconvergence relations for scattering amplitudes hold in this strongly
interacting sector; (b). the sum rules at are saturated by a minimal set
of low-lying states with appropriate quantum numbers. It therefore suggests
that a complete description should include all these resonances. These states
may lead to distinctive experimental signatures at future colliders.Comment: revised version, to appear in Modern Physics Letters A; file also
available via anonymous ftp at ftp://ucdhep.ucdavis.edu/han/sews/lowlying.p
Approximate input physics for stellar modelling
We present a simple and efficient, yet reasonably accurate, equation of
state, which at the moderately low temperatures and high densities found in the
interiors of stars less massive than the Sun is substantially more accurate
than its predecessor by Eggleton, Faulkner & Flannery. Along with the most
recently available values in tabular form of opacities, neutrino loss rates,
and nuclear reaction rates for a selection of the most important reactions,
this provides a convenient package of input physics for stellar modelling. We
briefly discuss a few results obtained with the updated stellar evolution code.Comment: uuencoded compressed postscript. The preprint are also available at
http://www.ast.cam.ac.uk/preprint/PrePrint.htm
Atrocalopteryx melli orohainani ssp. nov. on the Island of Hainan, China (Zygoptera: Calopterygidae)
The new sp. is described from the mountain core of Hainan, southern China, where it usually occurs at altitudes not lower than 300 m asl. It lives on the same type of small, shaded rivers as the nominate ssp. on the continent, and is distinguished by its larger size, slightly less enfumed wings, and a 2.6% difference in the sequence of the barcoding portion of the mitochodrial DNA-cytochrome c oxidase subunit I gene (COI). Holotype male: Diaoluoshan mountain, 6-VIII-2011; deposited in the Inst. Hydrobiol., Jinan Univ., Guanghou. It is argued that this geographically defined ssp. evolved because of persistent poor gene flow with continental populations, caused by the lowland "panhandle" between Hainan and the continent. This barrier was probably functioning equally well during interglacials (like at present) as during pleniglacials (when Hainan was connected to the mainland), because lack of suitable environments (small sized running waters), and dry and cold conditions continued to limit the contact with A. melli of the mainland
Graph Estimation From Multi-attribute Data
Many real world network problems often concern multivariate nodal attributes
such as image, textual, and multi-view feature vectors on nodes, rather than
simple univariate nodal attributes. The existing graph estimation methods built
on Gaussian graphical models and covariance selection algorithms can not handle
such data, neither can the theories developed around such methods be directly
applied. In this paper, we propose a new principled framework for estimating
graphs from multi-attribute data. Instead of estimating the partial correlation
as in current literature, our method estimates the partial canonical
correlations that naturally accommodate complex nodal features.
Computationally, we provide an efficient algorithm which utilizes the
multi-attribute structure. Theoretically, we provide sufficient conditions
which guarantee consistent graph recovery. Extensive simulation studies
demonstrate performance of our method under various conditions. Furthermore, we
provide illustrative applications to uncovering gene regulatory networks from
gene and protein profiles, and uncovering brain connectivity graph from
functional magnetic resonance imaging data.Comment: Extended simulation study. Added an application to a new data se
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