University of Groningen The Area of Contact for Non-Adhesive Rough Surfaces Solhjoo, Soheil

301 Pages·2017·1.99 MB·English

University of Groningen

The Area of Contact for Non-Adhesive Rough Surfaces
Solhjoo, Soheil; Vakis, Antonis I.
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2016
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Citation for published version (APA):
Solhjoo, S., & Vakis, A. I. (2016). The Area of Contact for Non-Adhesive Rough Surfaces: Comparison
between MD and Persson’s Model. Abstract from 8th International Conference on Multiscale Materials
Modeling, Dijon, France.
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Download date: 11-02-2018
Abstract Book
8th International Conference
on Multiscale Materials
Modeling
9–14 October 2016
Dijon, France

Contents

Plenary 2-7
Symposium A 8-25
Symposium B 26-40
Symposium C 41-69
Symposium D 70-91
Symposium E 92-116
Symposium F 117-126
Symposium G 127-156
Symposium H 157-180
Symposium I 181-196
Symposium J 197-221
Symposium K 222-232
Symposium L 233-247
Symposium M 248-271
Symposium N 272-291
Author index 292-296

MMM 2016 1
Plenary

(plenary) Model-reduction in multiscale problems for composite and polycrystalline materials
P Suquet1, R Largenton2 and J-C Michel1
1CNRS Marseille, France, 2Electricité de France (EdF), France
A common practice in multiscale problems for heterogeneous materials with well separated scales, is to look for
homogenized, or effective, constitutive relations. In linear elasticity the structure of the homogenized constitutive
relations is strictly preserved in the change of scales. The linear effective properties can be computed once for all by
solving a finite number of unit-cell problems.
Unfortunately there is no exact scale-decoupling in multiscale nonlinear problems which would allow one to solve
only a few unit-cell problems and then use them subsequently at a larger scale. Computational approaches
developed to investigate the response of representative volume elements along specific loading paths, do not
provide constitutive relations. Most of the huge body of information generated in the course of these costly
computations is often lost.
Model reduction techniques, such as the Non Uniform Transformation Field Analysis ([1]), may be used to exploit
the information generated along such computations and, at the same time, to account for the commonly observed
patterning of the local plastic strain field. A new version of the model [2] will be proposed in this talk, with the aim
of preserving the underlying variational structure of the constitutive relations (similar objective in [3]), while using
approximations which are common in nonlinear homogenization.
[1] J.C. Michel, P. Suquet, Int. J. Solids Structures 40, 6937-6955 (2003)
[2] J.C. Michel, P. Suquet, J. Mech. Phys. Solids, In press (2016)
[3] F. Fritzen, M. Leuschner, Comput. Meth. Appl. Mech. Eng. 260, 143–154 (2013)

2 MMM 2016
(plenary) The effect of dislocation junctions on the work hardening rate of face-centered cubic metals
W Cai1, R B Sills2,1, A Aghaei1 and N Bertin1
1Stanford University, USA, 2Sandia National Laboratories, USA
Understanding plasticity and strength of crystalline materials in terms of the physics of microscopic defects has
been a long-standing goal of materials research. Over the last two decades, much effort has been placed on the
prediction of stress-strain curve of single crystals through large-scale dislocation dynamics (DD) simulations. If
successful, DD can thus provide a quantitative link, which has been lacking to date, between dislocation physics at
the atomistic scale and crystal plasticity at the continuum scale. Unfortunately, the progress in this direction has
been limited by the very small strain that can be routinely reached (<1%) by existing DD simulations compared with
the typical strain (up to 30%) in experiments. Because of this limitation, a direct comparison between DD
predictions and experimental stress-strain curves has been impossible.
A series of advanced time integration algorithms have been developed to expand the strain range of DD simulations
[1]. In particular, the pairwise interaction forces between dislocation segments are separated into several groups,
and each group is integrated with a different time step size. The resulting (force-based subcycling) algorithm leads
to an increase of computational efficiency by more than 100 times. The new simulation capability enables the
prediction of stress-strain curves for shear strains in excess of 1% routinely and repeatedly. As a result, a
systematic investigation on the relation between the unit mechanisms and work hardening rate is now possible.
The strain hardening rates predicted by DD simulations in FCC metals under [001] loading are consistent with stage
II of the quasi-static stress-strain response observed in experiments, i.e. on the order of μ/200 [2]. By changing
rules on unit mechanisms in DD simulations, we determine the relative importance of different dislocation reactions
on the hardening rate. We find that glissile junctions are the most important junction type for hardening, with
collinear and Lomer junctions second most important. Interestingly, the relative importance of different junctions in
hardening is not the same as that in strength. A Boltzmann-type theory based on dislocation line length
distributions is constructed to explain the role of different junctions on the hardening rate revealed by DD
simulations.
This work was supported by Sandia National Laboratories (R.B.S.) and by the U.S. Department of Energy, Office of
Basic Energy Sciences, Division of Materials Sciences and Engineering under Award No. DE-SC0010412 (W.C. and
A.A.). Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a
wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear
Security Administration under contract DE-AC04-94AL85000.
[1] R. B. Sills, A. Aghaei, and W. Cai, Advanced Time Integration Algorithms for Dislocation Dynamics
Simulations of Work Hardening, Submitted to Modelling Simul. Mater. Sci. Eng. (2015)
[2] U. F. Kocks and H. Mecking, Physics and phenology of strain hardening: the FCC case, Prog. Materials
Science, 48, 171-273 (2003)

MMM 2016 3
(plenary) Can a simulation be reality? Does it matter?
H Van Swygenhoven-Moens
Paul Scherrer Institut & EPFL, Switzerland
Synergies between experiment and multiscale materials modelling are since many years a booming topic in
science, with both communities stimulating each other. This can be ascribed to a great extend to an increasing
availability of high performance computing resources. These resources have allowed the development of simulations
over a large span of length and time scales. One should however recognize that the increase in computational
capacities has also allowed further developments in experimental techniques and data analysis.
In science simulations can be used to mimic “experiments” on a model system with the aim to understand the
outcome of an experiment. In such cases one tries to make the model as close as possible to reality. However more
and more research is devoted to the development of computational tools allowing to turn-on or switch-off physical
mechanisms in order to distinguish between essential and incidental mechanisms among all what is possibly
occurring in real life. In these simulations the model simulated is usually further away from reality. Mechanistic
insights provided have then the potential to develop predictive computational tools and to design new experiments
with validating character.
By using illustrative examples involving different length and time scales we will elaborate how experiments stimulate
the simulation world and how simulations stimulate experimental research with an outlook to the future.

(plenary) Reaching experimental times at the atomic scale in complex materials: the kinetic activation-relaxation
technique
N Mousseau
Université de Montréal, Canada
In spite of considerable advances in computational capacities over the last decades, there remains a considerable
gap between experimentally relevant time scales and those accessible to atomistic simulations. This gap reflects the
fundamentally multi scale nature of atomistic kinetics that can only be lifted partially through approximate methods
that attempt to capture the most important aspect of specific phenomena. Among those approaches, the kinetic
activation-relaxation technique (k-ART) is an off-lattice kinetic Monte Carlo with on-the-fly cataloging capabilities
that allows fully atomistic second-long and more simulations of complex alloys and amorphous systems such as
amorphous silicon and steels, while incorporating exactly elastic effects. In this talk, I'll present the k-ART method,
recent applications to various systems and its advantages and limitations in the study of complex materials.

4 MMM 2016
(plenary) Data-driven materials research: Novel routes to new insight and predictions
C Draxl
Humboldt-Universität zu Berlin and Fritz Haber Institute of the Max Planck Society, Germany
On the steady search for advanced materials with tailored properties and novel functions, high-throughput screening
has become a new branch of materials research. For successfully exploring the chemical compound space from a
computational point of view, two aspects are crucial. These are reliable methodologies to accurately describe all
relevant properties for all materials on the same footing, and new concepts for getting insight into the materials data
that are produced since many years with an exponential growth rate.
What are our concepts for tackling big data of materials science? It is not an issue of boosting more high-throughput
calculations but it is about the question: How to exploit the wealth of information, inherently inside the materials
data which promises unprecedented insight?
I will first introduce the NoMaD Repository [1], which was established to promote the idea of open access and
sharing of materials data. As open access implies that data can be used by anyone, large collections of materials
data opens an avenue for using and developing tools that the present (computational-)materials community does
not even know. The latter is now being realized in the Novel Materials Discovery Laboratory – a European Center of
Excellene [2]. Here the main aims are the creation of a Materials Encyclopedia and the development of big-data
analytics tools for materials science. Finally, I will demonstrate some examples how statistical-learning approaches
based on domain-specific knowledge can indeed lead to new scientific insight [3].
[1] The Novel Materials Discovery (NoMaD) Repository: https://nomad-repository.eu
[2] NOMAD Center of Excellence, funded by the EU within HORIZON2020: http://nomad-CoE.eu
[3] L. Ghiringhelli, J. Vybiral, S. V. Levchenko, C. Draxl, and M. Scheffler, Big Data of Materials Science - Critical
Role of the Descriptor, Phys. Rev. Lett. 114, 105503 (2015)

MMM 2016 5
(plenary) Computational mechanics in advancing the Integrated Computational Materials Science & Engineering
(ICMSE) initiative for metals and alloys
S Ghosh
Johns Hopkins University, USA
The Integrated Computational Materials Science & Engineering or ICMSE initiative entails integration of information
across length and time scales for materials phenomena. This talk will present an integration of methods in
Computational Mechanics and Computational Materials Science to address the deformation and failure
characteristics of polycrystalline metals in various applications. Specifically it will address physics based modeling
at different scales and multi-scale spatial (scale-bridging) and temporal modeling methods for Titanium,
Magnesium and Aluminum alloys and Nickel based-superalloys. Spatial scales will range from atomistic to
component levels. Application domains will include both monotonic and cyclic loading and address properties such
as time and location-dependent strength, ductility and fatigue life. The talk will begin with methods of 3D virtual
image construction and development of statistically equivalent representative volume element at multiple scales.
Subsequently it will discuss the development of novel system of experimentally validated physics-based crystal
plasticity finite element or CPFE models to predict deformation and micro-twinning leading to crack nucleation.
These CPFE simulations will provide a platform for the implementation of physics-based crack evolution criterion
that accounts for microstructural inhomogeneity. For crack evolution, a coupled molecular dynamics-continuum
model for a crystalline material with an embedded crack will be discussed. A wavelet transformation based multi-
time scaling (WATMUS) algorithm for accelerated crystal plasticity finite element simulations will be discussed as
well. The method significantly enhances computational efficiency in comparison with conventional single time scale
integration methods. Finally, stabilized element technology for analyzing this class of complex deformation
problems will be discussed.

(plenary) Crystallography in Curved Space - the Interplay of Crystalline Order, Geometry and Topology
A Voigt
Technische Universität Dresden, Germany
The ground state configurations of two-dimensional crystals fully covering a curved surface are not defect free. Due
to topological reasons they feature crystalline defects, such as disclinations, dislocations, grain boundary scars and
pleats. What determines the type of defects? How do geometric properties influence their locations? Can these
ground states be accessed under growth? Is our understanding for crystalline defects also useful for defects in liquid
crystals on curved surfaces? We will answer these questions by phase-field-crystal simulations. The modeling
approach will be introduced and discussed in detail together with appropriate numerical schemes.

6 MMM 2016
(plenary) A new simulator for real-scale dislocation plasticity based on dynamics of dislocation-density functions
A Ngan and M H S Leung
University of Hong Kong, Hong Kong
Current strategies of computational crystal plasticity that focus on individual atoms or dislocations are impractical
for real-scale, large-strain problems even with today’s computing power. Dislocation-density based approaches are
a way forward but most schemes published to-date give a heavier weight on the consideration of geometrically
necessary dislocations (GNDs), while statistically stored dislocations (SSDs) are either ignored or treated in ad hoc
manners. In reality, however, the motions of GNDs and SSDs are intricately linked through their mutual (e.g. Taylor)
interactions. A correct scheme for dislocation dynamics should therefore be an “all-dislocation” treatment that is
equally applicable for all dislocations, with a rigorous description of the interactions between them.
In this talk, a new formulation for computational dynamics of dislocation-density functions, based on the above “all-
dislocation” principle, is discussed. The dynamic evolution laws for the dislocation densities are derived by coarse-
graining the individual density vector fields of all the discrete dislocation lines in the system, without distinguishing
between GNDs and SSDs. Elastic interactions between dislocations in 3D are treated in full in accordance with
Mura’s formulation for eigen stress. Dislocation generation is considered as a consequence of dislocations to
maintain their connectivity, and a special scheme is devised for this purpose. The model is applied to simulate a
number of intensive microstructures involving discrete dislocation events, including loop expansion and shrinkage
under applied and self stress, dipole annihilation, and Orowan looping. The scheme can also handle high densities
of dislocations present in extensive microstructures.

(plenary) Size effects in fracture and plasticity
Stefano Zapperi
University of Milan, Italy
The size dependence of strength is a well known but still unresolved issue in the fracture of materials and structures.
The difficulty in addressing this problem stems from the complex interplay between microstructual heterogeneity
and long-range elastic interactions. Furthermore, in micro and nanoscale samples, the plastic yield strength
displays size effects and strain bursts, features that are not present in macroscopic samples where plasticity is a
smooth process. Large fluctuations both in fracture processes and in microscale plasticity make the use of
conventional continuum mechanics problematic and calls instead for a statistically based approach. In this talk, I
will review recent results obtained from idelized models of disordered fracture and from more realistic simulations
of defected graphene. Finally, I will discuss the size dependence of strain burst statistics as revealed by statistical
models for crystal and amorphous plasticity.

(plenary) Programming shape
L Mahadevan
Harvard University, USA
Recent progress in understanding the shape-shifting abilities of thin sheets and slender filaments in natural
(morphogenetic) and artificial (engineered) settings naturally raises the prospect that we might be able to design
and control shape for function at multiple scales. I will describe our attempts to solve this inverse problem that
combines geometry, matter and motion in the context of controlled precipitation for functional nanoscale structures,
phytomimetic 4D printing of stimulus-responsive structures, inverse origami for programming curvature, and inverse
design of active filaments for optimal locomotion.
MMM 2016 7