30,652 research outputs found
Information Surfaces in Systems Biology and Applications to Engineering Sustainable Agriculture
Systems biology of plants offers myriad opportunities and many challenges in
modeling. A number of technical challenges stem from paucity of computational
methods for discovery of the most fundamental properties of complex dynamical
systems. In systems engineering, eigen-mode analysis have proved to be a
powerful approach. Following this philosophy, we introduce a new theory that
has the benefits of eigen-mode analysis, while it allows investigation of
complex dynamics prior to estimation of optimal scales and resolutions.
Information Surfaces organizes the many intricate relationships among
"eigen-modes" of gene networks at multiple scales and via an adaptable
multi-resolution analytic approach that permits discovery of the appropriate
scale and resolution for discovery of functions of genes in the model plant
Arabidopsis. Applications are many, and some pertain developments of crops that
sustainable agriculture requires.Comment: 24 Pages, DoCEIS 1
Multiscale computational first order homogenization of thick shells for the analysis of out-of-plane loaded masonry walls
This work presents a multiscale method based on computational homogenization for the analysis of general heterogeneous thick shell structures, with special focus on periodic brick-masonry walls. The proposed method is designed for the analysis of shells whose micro-structure is heterogeneous in the in-plane directions, but initially homogeneous in the shell-thickness direction, a structural topology that can be found in single-leaf brick masonry walls. Under this assumption, this work proposes an efficient homogenization scheme where both the macro-scale and the micro-scale are described by the same shell theory. The proposed method is then applied to the analysis of out-of-plane loaded brick-masonry walls, and compared to experimental and micro-modeling results.Peer ReviewedPostprint (author's final draft
Surface Engineering for Phase Change Heat Transfer: A Review
Among numerous challenges to meet the rising global energy demand in a
sustainable manner, improving phase change heat transfer has been at the
forefront of engineering research for decades. The high heat transfer rates
associated with phase change heat transfer are essential to energy and industry
applications; but phase change is also inherently associated with poor
thermodynamic efficiencies at low heat flux, and violent instabilities at high
heat flux. Engineers have tried since the 1930's to fabricate solid surfaces
that improve phase change heat transfer. The development of micro and
nanotechnologies has made feasible the high-resolution control of surface
texture and chemistry over length scales ranging from molecular levels to
centimeters. This paper reviews the fabrication techniques available for
metallic and silicon-based surfaces, considering sintered and polymeric
coatings. The influence of such surfaces in multiphase processes of high
practical interest, e.g., boiling, condensation, freezing, and the associated
physical phenomena are reviewed. The case is made that while engineers are in
principle able to manufacture surfaces with optimum nucleation or thermofluid
transport characteristics, more theoretical and experimental efforts are needed
to guide the design and cost-effective fabrication of surfaces that not only
satisfy the existing technological needs, but also catalyze new discoveries
Recommended from our members
Hybrid molecular-continuum methods for micro- and nanoscale liquid flows
This paper was presented at the 2nd Micro and Nano Flows Conference (MNF2009), which was held at Brunel University, West London, UK. The conference was organised by Brunel University and supported by the Institution of Mechanical Engineers, IPEM, the Italian Union of Thermofluid dynamics, the Process Intensification Network, HEXAG - the Heat Exchange Action Group and the Institute of Mathematics and its Applications.Many flows at microscale and below are characterised by an inherent multiscale nature and accurate numerical modelling of the phenomena involved is the cornerstone for enhancing the applicability of micro and nanofluidics in the industrial environment. This paper presents a hybrid molecular-continuum strategy named as point wise coupling for studying complex micro- and nanoscale flows. In this strategy one performs continuum simulations and uses a molecular solver for computing flow properties. The hybrid methodology utilises a numerical procedure to minimise the cost of the computationally expensive molecular solver. Simulations have been carried out for a slip Poiseuille flow test case. The hybrid results are in good agreement with analytical solutions and pervious molecular simulations.This study is funded by the EPSRC, MoD and AWE through the grant EP/D051940-JGS 607, as well as from the European Commission under the 6th Framework Program (Project: DINAMICS, NMP4-CT-2007-026804)
Concurrent coupling of atomistic simulation and mesoscopic hydrodynamics for flows over soft multi-functional surfaces
We develop an efficient parallel multiscale method that bridges the atomistic
and mesoscale regimes, from nanometer to micron and beyond, via concurrent
coupling of atomistic simulation and mesoscopic dynamics. In particular, we
combine an all-atom molecular dynamics (MD) description for specific atomistic
details in the vicinity of the functional surface, with a dissipative particle
dynamics (DPD) approach that captures mesoscopic hydrodynamics in the domain
away from the functional surface. In order to achieve a seamless transition in
dynamic properties we endow the MD simulation with a DPD thermostat, which is
validated against experimental results by modeling water at different
temperatures. We then validate the MD-DPD coupling method for transient Couette
and Poiseuille flows, demonstrating that the concurrent MD-DPD coupling can
resolve accurately the continuum-based analytical solutions. Subsequently, we
simulate shear flows over polydimethylsiloxane (PDMS)-grafted surfaces (polymer
brushes) for various grafting densities, and investigate the slip flow as a
function of the shear stress. We verify that a "universal" power law exists for
the sliplength, in agreement with published results. Having validated the
MD-DPD coupling method, we simulate time-dependent flows past an endothelial
glycocalyx layer (EGL) in a microchannel. Coupled simulation results elucidate
the dynamics of EGL changing from an equilibrium state to a compressed state
under shear by aligning the molecular structures along the shear direction.
MD-DPD simulation results agree well with results of a single MD simulation,
but with the former more than two orders of magnitude faster than the latter
for system sizes above one micron.Comment: 11 pages, 12 figure
Fractal Descriptors in the Fourier Domain Applied to Color Texture Analysis
The present work proposes the development of a novel method to provide
descriptors for colored texture images. The method consists in two steps. In
the first, we apply a linear transform in the color space of the image aiming
at highlighting spatial structuring relations among the color of pixels. In a
second moment, we apply a multiscale approach to the calculus of fractal
dimension based on Fourier transform. From this multiscale operation, we
extract the descriptors used to discriminate the texture represented in digital
images. The accuracy of the method is verified in the classification of two
color texture datasets, by comparing the performance of the proposed technique
to other classical and state-of-the-art methods for color texture analysis. The
results showed an advantage of almost 3% of the proposed technique over the
second best approach.Comment: Chaos, Volume 21, Issue 4, 201
Multiscale 3D Shape Analysis using Spherical Wavelets
©2005 Springer. The original publication is available at www.springerlink.com:
http://dx.doi.org/10.1007/11566489_57DOI: 10.1007/11566489_57Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data
Multiscale computational homogenization: review and proposal of a new enhanced-first-order method
This is a copy of the author 's final draft version of an article published in the Archives of computational methods in engineering. The final publication is available at Springer via http://dx.doi.org/10.1007/s11831-016-9205-0The continuous increase of computational capacity has encouraged the extensive use of multiscale techniques to simulate the material behaviour on several fields of knowledge. In solid mechanics, the multiscale approaches which consider the macro-scale deformation gradient to obtain the homogenized material behaviour from the micro-scale are called first-order computational homogenization. Following this idea, the second-order FE2 methods incorporate high-order gradients to improve the simulation accuracy. However, to capture the full advantages of these high-order framework the classical boundary value problem (BVP) at the macro-scale must be upgraded to high-order level, which complicates their numerical solution. With the purpose of obtaining the best of both methods i.e. first-order and second-order, in this work an enhanced-first-order computational homogenization is presented. The proposed approach preserves a classical BVP at the macro-scale level but taking into account the high-order gradient of the macro-scale in the micro-scale solution. The developed numerical examples show how the proposed method obtains the expected stress distribution at the micro-scale for states of structural bending loads. Nevertheless, the macro-scale results achieved are the same than the ones obtained with a first-order framework because both approaches share the same macro-scale BVP.Peer ReviewedPostprint (author's final draft
- …