1,167 research outputs found
Confluence Detection for Transformations of Labelled Transition Systems
The development of complex component software systems can be made more
manageable by first creating an abstract model and then incrementally adding
details. Model transformation is an approach to add such details in a
controlled way. In order for model transformation systems to be useful, it is
crucial that they are confluent, i.e. that when applied on a given model, they
will always produce a unique output model, independent of the order in which
rules of the system are applied on the input. In this work, we consider
Labelled Transition Systems (LTSs) to reason about the semantics of models, and
LTS transformation systems to reason about model transformations. In related
work, the problem of confluence detection has been investigated for general
graph structures. We observe, however, that confluence can be detected more
efficiently in special cases where the graphs have particular structural
properties. In this paper, we present a number of observations to detect
confluence of LTS transformation systems, and propose both a new confluence
detection algorithm and a conflict resolution algorithm based on them.Comment: In Proceedings GaM 2015, arXiv:1504.0244
Analysing the Performance of GPU Hash Tables for State Space Exploration
In the past few years, General Purpose Graphics Processors (GPUs) have been
used to significantly speed up numerous applications. One of the areas in which
GPUs have recently led to a significant speed-up is model checking. In model
checking, state spaces, i.e., large directed graphs, are explored to verify
whether models satisfy desirable properties. GPUexplore is a GPU-based model
checker that uses a hash table to efficiently keep track of already explored
states. As a large number of states is discovered and stored during such an
exploration, the hash table should be able to quickly handle many inserts and
queries concurrently. In this paper, we experimentally compare two different
hash tables optimised for the GPU, one being the GPUexplore hash table, and the
other using Cuckoo hashing. We compare the performance of both hash tables
using random and non-random data obtained from model checking experiments, to
analyse the applicability of the two hash tables for state space exploration.
We conclude that Cuckoo hashing is three times faster than GPUexplore hashing
for random data, and that Cuckoo hashing is five to nine times faster for
non-random data. This suggests great potential to further speed up GPUexplore
in the near future.Comment: In Proceedings GaM 2017, arXiv:1712.0834
First-principles calculations of the crystal structure, electronic structure, and thermodynamic stability of Be(BH4)2
Alanates and boranates are intensively studied because of their potential use as hydrogen storage materials. In this paper, we present a first-principles study of the electronic structure and the energetics of beryllium boranate BeBH42. From total energy calculations, we show that—in contrast to the other boranates and alanates—hydrogen desorption directly to the elements is likely and is at least competitive with desorption to the elemental hydride BeH2. The formation enthalpy of BeBH42 is only −0.14 eV/H2 at T=0 K. This low value can be rationalized by the participation of all atoms in the covalent bonding, which is in contrast to the ionic bonding observed in other boranates. From calculations of thermodynamic properties at finite temperature, we estimate a decomposition temperature of 162 K at a pressure of 1 bar
Ab initio study on the effects of transition metal doping of Mg2NiH4
Mg2NiH4 is a promising hydrogen storage material with fast (de)hydrogenation
kinetics. Its hydrogen desorption enthalpy, however, is too large for practical
applications. In this paper we study the effects of transition metal doping by
first-principles density functional theory calculations. We show that the
hydrogen desorption enthalpy can be reduced by ~0.1 eV/H2 if one in eight Ni
atoms is replaced by Cu or Fe. Replacing Ni by Co atoms, however, increases the
hydrogen desorption enthalpy. We study the thermodynamic stability of the
dopants in the hydrogenated and dehydrogenated phases. Doping with Co or Cu
leads to marginally stable compounds, whereas doping with Fe leads to an
unstable compound. The optical response of Mg2NiH4 is also substantially
affected by doping. The optical gap in Mg2NiH4 is ~1.7 eV. Doping with Co, Fe
or Cu leads to impurity bands that reduce the optical gap by up to 0.5 eV.Comment: 8 pages, 4 figure
Interactions of adsorbed CO on water ice at low temperatures
We present a computational study into the adsorption properties of CO on
amorphous and crystalline water surfaces under astrophysically relevant
conditions. Water and carbon dioxide are two of the most dominant species in
the icy mantles of interstellar dust grains and a thorough understanding of
their solid phase interactions at low temperatures is crucial for understanding
the structural evolution of the ices due to thermal segregation. In this paper,
a new HO-CO interaction potential is proposed and used to model the
ballistic deposition of CO layers on water ice surfaces, and to study the
individual binding sites at low coverages. Contrary to recent experimental
results, we do not observe CO island formation on any type of water
substrate. Additionally, density functional theory calculations are performed
to assess the importance of induced electrostatic interactions.Comment: Accepted for publication in Physical Chemistry Chemical Physic
Atomistic models of hydrogenated amorphous silicon nitride from first principles
We present a theoretical study of hydrogenated amorphous silicon nitride (a-SiNx:H), with equal concentrations of Si and N atoms (x=1), for two considerably different densities (2.0 and 3.0 g/cm3). Densities and hydrogen concentration were chosen according to experimental data. Using first-principles molecular-dynamics within density-functional theory the models were generated by cooling from the liquid. Where both models have a short-range order resembling that of crystalline Si3N4 because of their different densities and hydrogen concentrations they show marked differences at longer length scales. The low-density nitride forms a percolating network of voids with the internal surfaces passivated by hydrogen. Although some voids are still present for the high-density nitride, this material has a much denser and uniform space filling. The structure factors reveal some tendency for the nonstoichiometric high-density nitride to phase separate into nitrogen rich and poor areas. For our slowest cooling rate (0.023 K/fs) we obtain models with a modest number of defect states, where the low (high) density nitride favors undercoordinated (overcoordinated) defects. Analysis of the structural defects and electronic density of states shows that there is no direct one-to-one correspondence between the structural defects and states in the gap. There are several structural defects that do not contribute to in-gap states and there are in-gap states that do only have little to no contributions from (atoms in) structural defects. Finally an estimation of the size and cooling rate effects on the amorphous network is reported.
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