Domain-specific discrete event modelling and simulation using graph transformation

Graph transformation is being increasingly used to express the semantics of domain-specific visual languages since its graphical nature makes rules intuitive. However, many application domains require an explicit handling of time to accurately represent the behaviour of a real system and to obtain useful simulation metrics to measure throughputs, utilization times and average delays. Inspired by the vast knowledge and experience accumulated by the discrete event simulation community, we propose a novel way of adding explicit time to graph transformation rules. In particular, we take the event scheduling discrete simulation world view and provide rules with the ability to schedule the occurrence of other rules in the future. Hence, our work combines standard, efficient techniques for discrete event simulation (based on the handling of a future event set) and the intuitive, visual nature of graph transformation. Moreover, we show how our formalism can be used to give semantics to other timed approaches and provide an implementation on top of the rewriting logic system Maude.     

Phase Diagrams of 4He on Flat and Curved Environments

By means of diffusion Monte Carlo calculations, we obtained the phase diagrams of a first and second layer of ⁴He on graphene and on the outside of different isolated armchair carbon nanotubes with radii in the range 3.42 to 10.85 Å. That corresponds to tubes between the (5, 5) and (16, 16) in standard nomenclature. In both cases, the ground state is either a liquid (second layer on graphene and on nanotubes whose radii is greater than ～7 Å) or an incommensurate solid (for thinner tubes). In the former case, upon a density increase, the system undergoes a first-order phase transition to another incommensurate solid. A study of the influence of the C–He potential (isotropic or anisotropic) on the phase diagrams is also presented.     

Influence of the Interaction Potential on the D↓1 Equation of State

The ground-state properties of spin-polarized deuterium with only one occupied nuclear spin state (D↓₁) at zero temperature are studied by means of the variational Monte Carlo (VMC) method. Influence of the backflow correlations on the ground-state energy of this Fermi system under investigation is also explored. The calculations have been performed using several interatomic potentials and the quantum phase of the D↓₁ system is discussed. Our results are compared with other previously reported variational results.     

A Quantum Monte Carlo Study of 4He in Carbon Nanotube Bundles

We present the results of a diffusion Monte Carlo calculation on the groundstate energy of ⁴ He adsorbed in the interstitial channels of a bundle of (10, 10) nanotubes. The one-dimensionality of that system is analyzed by comparing the bundle results with the equation of state of purely 1D ⁴ He. In spite of the narrowness of the intersites, significant differences in both the binding energy and the equilibrium density of the two systems appear. Moreover, additional attraction provided by neighboring interchannels filled with helium modifies in a sizeable amount the equation of state of a single intersite.     

Momentum Distribution of Quantum Liquids at Finite Temperature

We present results of a path integral Monte Carlo (PIMC) calculation of the momentum distribution of Ne and normal ⁴ He at low temperatures. In the range of temperatures analyzed, consequently exchanges can be disregarded and both systems are considered Boltzmann quantum liquids. Their quantum character is well reflected in their momentum distributions which show clear departures from the classical limit. The PIMC momentum distributions are sampled using a new and more efficient method that generalises the standard McMillan approach. Kinetic energies of both systems as a function of temperature and at a fixed density are also reported.     

Incremental execution of rule-based model transformation

When model transformations are used to implement consistency relations between very large models, incrementality plays a cornerstone role in detecting and resolving inconsistencies efficiently when models are updated. Given a directed consistency relation between two models, the problem studied in this work consists in propagating model changes from a source model to a target model in order to ensure consistency while minimizing computational costs. The mechanism that enforces such consistency is called consistency maintainer and, in this context, its scalability is a required non-functional requirement. State-of-the-art model transformation engines with support for incrementality normally rely on an observer pattern for linking model changes, also known as deltas, to the application of model transformation rules, in so-called dependencies, at run time. These model changes can then be propagated along an already executed model transformation. Only a few approaches to model transformation provide domain-specific languages for representing and storing model changes in order to enable their use in asynchronous, event-based execution environments. The principal contribution of this work is the design of a forward change propagation mechanism for incremental execution of model transformations, which decouples dependency tracking from change propagation using two innovations. First, the observer pattern-based model is replaced with dependency injection, decoupling domain models from consistency maintainers. Second, a standardized representation of model changes is reused, enabling interoperability with EMF-compliant tools, both for defining model changes and for processing them asynchronously. This procedure has been implemented in a model transformation engine, whose performance has been evaluated experimentally using the VIATRA CPS benchmark. In the experiments performed, the new transformation engine shows gains in the form of several orders of magnitude in the initial phase of the incremental execution of the benchmark model transformation and change propagation is performed in real time for those model sizes that are processable by other tools and, in addition, is able to process much larger models.

     

H2 Physisorbed on Graphane

We study the zero-temperature phase diagrams of H₂ adsorbed on the three structures predicted for graphane (chair, boat and washboard graphane), using a diffusion Monte Carlo technique. Graphane is the hydrogenated version of graphene, in which each carbon atom changes its hybridization to sp ³ and forms a covalent bond with a hydrogen atom. Our results show that the ground state of H₂ adsorbed on all three types of graphane is a $\sqrt{3}\times\sqrt{3}$ solid, similar to the structures found both for H₂ and D₂ on graphene. When the H₂ density increases, the system undergoes a first order phase transition to a triangular incommensurate solid. This change is direct in the case of washboard graphane, but indirect via different commensurate structures in the other cases. The total hydrogen weight percentage on the three graphane types in their ground states is in the range 10 % to 12 %, depending on if one or both graphane surfaces are covered with H₂.     

Comparative study of the rheological behavior of multiwalled carbon nanotubes and nanofiber composites prepared by the dilution of a masterbatch of polypropylene

In this investigation, the characteristics and the rheological properties of two different nanocomposite systems were investigated. These systems consisted of a dispersion of carbon nanotubes (CNTs) and carbon nanofibers (CNFs) in a polypropylene (PP) matrix. The mixing process was carried out by melt compounding with a twin‐screw corotating extruder with different reinforcement amounts (0.2–20 wt %) from concentrated masterbatches (20 wt %) of PP/CNT and PP/CNF. The results show a remarkable increase in the viscosity for both blends as the reinforcement amount was increased. It was important to evaluate the rheological behavior to understand the effect of the nanocarbon particles on the internal structures and their processing properties of the obtained composites. CNFs were a more viable reinforcement from a processability point of view because the obtained viscosities of the PP/CNF blends were more manageable. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Tuning the Behavior of Au and Pt Catalysts for the Chemoselective Hydrogenation of Nitroaromatic Compounds

Efficient catalysts for the synthesis of functionalized anilines from the corresponding substituted nitroaromatics should combine an excellent chemoselectivity with a high hydrogenation activity. Attempts to increase the activity of the Au/TiO₂ catalyst and to improve the selectivity of traditional Pt catalysts, based on a previous understanding of the mode of action of supported gold and platinum nanoparticles, are reviewed and discussed.