20,037 research outputs found
Multiscale Bone Remodelling with Spatial P Systems
Many biological phenomena are inherently multiscale, i.e. they are
characterized by interactions involving different spatial and temporal scales
simultaneously. Though several approaches have been proposed to provide
"multilayer" models, only Complex Automata, derived from Cellular Automata,
naturally embed spatial information and realize multiscaling with
well-established inter-scale integration schemas. Spatial P systems, a variant
of P systems in which a more geometric concept of space has been added, have
several characteristics in common with Cellular Automata. We propose such a
formalism as a basis to rephrase the Complex Automata multiscaling approach
and, in this perspective, provide a 2-scale Spatial P system describing bone
remodelling. The proposed model not only results to be highly faithful and
expressive in a multiscale scenario, but also highlights the need of a deep and
formal expressiveness study involving Complex Automata, Spatial P systems and
other promising multiscale approaches, such as our shape-based one already
resulted to be highly faithful.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005
Multiscale approach including microfibril scale to assess elastic constants of cortical bone based on neural network computation and homogenization method
The complexity and heterogeneity of bone tissue require a multiscale
modelling to understand its mechanical behaviour and its remodelling
mechanisms. In this paper, a novel multiscale hierarchical approach including
microfibril scale based on hybrid neural network computation and homogenisation
equations was developed to link nanoscopic and macroscopic scales to estimate
the elastic properties of human cortical bone. The multiscale model is divided
into three main phases: (i) in step 0, the elastic constants of collagen-water
and mineral-water composites are calculated by averaging the upper and lower
Hill bounds; (ii) in step 1, the elastic properties of the collagen microfibril
are computed using a trained neural network simulation. Finite element (FE)
calculation is performed at nanoscopic levels to provide a database to train an
in-house neural network program; (iii) in steps 2 to 10 from fibril to
continuum cortical bone tissue, homogenisation equations are used to perform
the computation at the higher scales. The neural network outputs (elastic
properties of the microfibril) are used as inputs for the homogenisation
computation to determine the properties of mineralised collagen fibril. The
mechanical and geometrical properties of bone constituents (mineral, collagen
and cross-links) as well as the porosity were taken in consideration. This
paper aims to predict analytically the effective elastic constants of cortical
bone by modelling its elastic response at these different scales, ranging from
the nanostructural to mesostructural levels. Our findings of the lowest scale's
output were well integrated with the other higher levels and serve as inputs
for the next higher scale modelling. Good agreement was obtained between our
predicted results and literature data.Comment: 2
Multiscale Modeling of Binary Polymer Mixtures: Scale Bridging in the Athermal and Thermal Regime
Obtaining a rigorous and reliable method for linking computer simulations of
polymer blends and composites at different length scales of interest is a
highly desirable goal in soft matter physics. In this paper a multiscale
modeling procedure is presented for the efficient calculation of the static
structural properties of binary homopolymer blends. The procedure combines
computer simulations of polymer chains on two different length scales, using a
united atom representation for the finer structure and a highly coarse-grained
approach on the meso-scale, where chains are represented as soft colloidal
particles interacting through an effective potential. A method for combining
the structural information by inverse mapping is discussed, allowing for the
efficient calculation of partial correlation functions, which are compared with
results from full united atom simulations. The structure of several polymer
mixtures is obtained in an efficient manner for several mixtures in the
homogeneous region of the phase diagram. The method is then extended to
incorporate thermal fluctuations through an effective chi parameter. Since the
approach is analytical, it is fully transferable to numerous systems.Comment: in press, 13 pages, 7 figures, 6 table
Computational studies of biomembrane systems: Theoretical considerations, simulation models, and applications
This chapter summarizes several approaches combining theory, simulation and
experiment that aim for a better understanding of phenomena in lipid bilayers
and membrane protein systems, covering topics such as lipid rafts, membrane
mediated interactions, attraction between transmembrane proteins, and
aggregation in biomembranes leading to large superstructures such as the light
harvesting complex of green plants. After a general overview of theoretical
considerations and continuum theory of lipid membranes we introduce different
options for simulations of biomembrane systems, addressing questions such as:
What can be learned from generic models? When is it expedient to go beyond
them? And what are the merits and challenges for systematic coarse graining and
quasi-atomistic coarse grained models that ensure a certain chemical
specificity
Review of the Synergies Between Computational Modeling and Experimental Characterization of Materials Across Length Scales
With the increasing interplay between experimental and computational
approaches at multiple length scales, new research directions are emerging in
materials science and computational mechanics. Such cooperative interactions
find many applications in the development, characterization and design of
complex material systems. This manuscript provides a broad and comprehensive
overview of recent trends where predictive modeling capabilities are developed
in conjunction with experiments and advanced characterization to gain a greater
insight into structure-properties relationships and study various physical
phenomena and mechanisms. The focus of this review is on the intersections of
multiscale materials experiments and modeling relevant to the materials
mechanics community. After a general discussion on the perspective from various
communities, the article focuses on the latest experimental and theoretical
opportunities. Emphasis is given to the role of experiments in multiscale
models, including insights into how computations can be used as discovery tools
for materials engineering, rather than to "simply" support experimental work.
This is illustrated by examples from several application areas on structural
materials. This manuscript ends with a discussion on some problems and open
scientific questions that are being explored in order to advance this
relatively new field of research.Comment: 25 pages, 11 figures, review article accepted for publication in J.
Mater. Sc
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