Computational Study of the Structure and Thermodynamic Properties of Ammonium Chloride Clusters Using a Parallel J-Walking Approach

The thermodynamic and structural properties of (NH$_4$Cl)$_n$ clusters, n=3-10 are studied. Using the method of simulated annealing, the geometries of several isomers for each cluster size are examined. Jump-walking Monte Carlo simulations are then used to compute the constant-volume heat capacity for each cluster size over a wide temperature range. To carry out these simulations a new parallel algorithm is developed using the Parallel Virtual Machine (PVM) software package. Features of the cluster potential energy surfaces, such as energy differences among isomers and rotational barriers of the ammonium ions, are found to play important roles in determining the shape of the heat capacity curves.Comment: Journal of Chemical Physics, accepted for publicatio

State-of-the-Art in Parallel Computing with R

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly useful for general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems four different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix

State of the Art in Parallel Computing with R

R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly suited to general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems five different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix.

Beyond XSPEC: Towards Highly Configurable Analysis

We present a quantitative comparison between software features of the defacto standard X-ray spectral analysis tool, XSPEC, and ISIS, the Interactive Spectral Interpretation System. Our emphasis is on customized analysis, with ISIS offered as a strong example of configurable software. While noting that XSPEC has been of immense value to astronomers, and that its scientific core is moderately extensible--most commonly via the inclusion of user contributed "local models"--we identify a series of limitations with its use beyond conventional spectral modeling. We argue that from the viewpoint of the astronomical user, the XSPEC internal structure presents a Black Box Problem, with many of its important features hidden from the top-level interface, thus discouraging user customization. Drawing from examples in custom modeling, numerical analysis, parallel computation, visualization, data management, and automated code generation, we show how a numerically scriptable, modular, and extensible analysis platform such as ISIS facilitates many forms of advanced astrophysical inquiry.Comment: Accepted by PASP, for July 2008 (15 pages

The thermodynamic and kinetic properties of hydrogen dimers on graphene

The thermodynamic and kinetic properties of hydrogen adatoms on graphene are important to the materials and devices based on hydrogenated graphene. Hydrogen dimers on graphene with coverages varying from 0.040 to 0.111 ML (1.0 ML $= 3.8\times10^{15}$cm$^{-2}$) were considered in this report. The thermodynamic and kinetic properties of H, D and T dimers were studied by ab initio simulations. The vibrational zero-point energy corrections were found to be not negligible in kinetics, varying from 0.038 (0.028, 0.017) to 0.257 (0.187, 0.157) eV for H (D, T) dimers. The isotope effect exhibits as that the kinetic mobility of a hydrogen dimer decreases with increasing the hydrogen mass. The simulated thermal desorption spectra with the heating rate $\alpha = 1.0$ K/s were quite close to experimental measurements. The effect of the interaction between hydrogen dimers on their thermodynamic and kinetic properties were analyzed in detail.Comment: submitted to Surface Scienc

The triangulated Hopf category n_+SL(2)

We discuss an example of a triangulated Hopf category related to SL(2). It is an equivariant derived category equipped with multiplication and comultiplication functors and structure isomorphisms. We prove some coherence equations for structure isomorphisms. In particular, the Hopf category is monoidal.Comment: 38 pages, AmsLaTeX 1.2 + diagrams.tex; the published versio

Genetic algorithm design of neural network and fuzzy logic controllers

Genetic algorithm design of neural network and fuzzy logic controller

MELCOR-To-MELCOR Coupling Method in Severe Accident Analysis Involving Core and Spent Fuel Pool

A lot of effort has been spent to prevent the occurrence of SA in nuclear plant and to develop Severe Accidents (SA) Management to mitigate the consequences of a SA. Those consequences are mainly related to limit the release of fission product to the environment. The core in the vessel is not the only source of fission products as the Spent Fuel Pool (SFP) hosting the fuel removed by the core is, in some NPP, inside the containment and SA conditions can also occur. This is especially important in reactors having proximity between the RPV and SFP such as the VVER-1200. This close proximity implies that any SA occurring in the SFP potentially affects the RPV and vice-versa. This potential combination might cause unexpected evolution in the SA progression to whom the safety systems are not able to contain. MELCOR code is a widely used, flexible powerful SA code but it is incapable (due to the uniqueness of the COR package use inside the same input) to reproduce a situation in which both the fuel in vessel core and the fuel in the SFP, inside the same containment, are going to experience a severe accident scenario. The current study presents a MELCOR-to-MELCOR coupling method to simulate simultaneously scenarios with both, core and SFP, as sources capable of H2 generation, fuel damage and FP release in a VVER-1200 NPP. The coupling is performed by running two simulations in parallel and with the data exchange supervised and managed by a dedicated Python coupling supervising script developed at NINE