Solving large sparse linear systems in a grid environment: the GREMLINS code versus the PETSc library

Solving large sparse linear systems is essential in numerous scientific domains. Several algorithms, based on direct or iterative methods, have been developed for parallel architectures. On distributed grids consisting of processors located in distant geographical sites, their performance may be unsatisfactory because they suffer from too many synchronizations and communications. The GREMLINS code has been developed for solving large sparse linear systems on distributed grids. It implements the multisplitting method that consists in splitting the original linear system into several subsystems that can be solved independently. In this paper, the performance of the GREMLINS code obtained with several libraries for solving the linear subsystems is analyzed. Its performance is also compared with that of the widely used PETSc library that enables one to develop portable parallel applications. Numerical experiments have been carried out both on local clusters and on distributed grids.     

Design and development of a fuzzy agent-based model to measure interest rate expectations

The financial system, which has been investigated by various researchers, is a rather complicated environment. Most research has only been concerned with quantitative factors (technical indexes), though qualitative factors (e.g., political situation, social conditions, international events, government policies, among others) play a critical role in the financial system environment, determining the regulatory policies within an economy. This paper presents a fuzzy knowledge-based model to measure the qualitative aspects related to one of the most important financial instruments used to regulate an economy, the base interest rate. The development and assessment of the proposed model was based on the Brazilian economy. Evaluation of the results obtained indicates that our approach gives good results when compared with real data and statistical-based forecasting tools. The main advantage of our approach is its capability to forecast long term interest rate expectations when combined with a powerful econometric model.     

The use of energy windowing to discriminate SNM from NORM in radiation portal monitors

Energy windowing is an algorithmic alarm method that can be applied to plastic scintillator-based radiation portal monitor (RPM) systems to improve operational sensitivity to certain threat sources while reducing the alarm rates from naturally occurring radioactive material. Various implementations of energy windowing have been tested and documented by industry and at Pacific Northwest National Laboratory, and are available in commercial RPMs built by several manufacturers. Moreover, energy windowing is being used in many deployed RPMs to reduce nuisance alarms and improve operational sensitivity during the screening of cargo. This paper describes energy windowing algorithms and demonstrates how these algorithms succeed when applied to “controlled” experimental measurements and “real world” vehicle traffic data.     

Percolation and the resistive transition of the critical temperature Tc of Nb3Sn

The relationship between the distribution of the critical temperature, the percolation function, and the resistive transition of the critical temperature is explored for polycrystalline Nb₃Sn. In the neighborhood of the critical temperature, Nb₃Sn is assumed to be a random mixture of superconducting and normal grains. Percolation concepts are applied to a study of the resistivity. A general analysis is made showing that the onset and shape of the resistive transition for composite conductors are determined by the percolation function and the distribution of the critical temperature. An approximate form of the percolation function is determined based on a linear FEM analysis. Example resistive transitions are calculated for an assumed normal distribution of the critical temperature. An argument is presented that relates grain orientation and strain dependence in Nb₃Sn. It is noted that a dependence of the distribution of T_c with strain, in addition to the usual shift in T_c with strain, would be the result of a strain dependence that is a function of grain orientation. The analysis shows the extent to which the slope of the resistive transition is a measure of the distribution of the critical temperature, and therefore a measure of the grain orientation strain sensitivity. Finally, a method is described to determine the percolation function experimentally.     

Simulation of pellet-cladding thermomechanical interaction and fission gas release

This paper summarizes the present status of a computer code that describes some of the main phenomena occurring in a nuclear fuel rod throughout its life. Temperature distribution, thermal expansion, elastic and plastic strains, creep, mechanical interaction between pellet and cladding, fission gas release, gas mixing, swelling, and densification are modeled. The modular structure of the code allows for the incorporation of models to simulate different phenomena and material properties. Collapsible rods can be also simulated.The code is bidimensional, assumes cylindrical symmetry for the rod and uses the finite element method to integrate the differential equations. The stress–strain and heat conduction problems are nonlinear due to plasticity and to the temperature dependence of the thermal conductivity. The fission gas inventory is calculated with a diffusion model, assuming spherical grains and using a one-dimensional finite element scheme. Pressure increase, swelling and densification are coupled with the stress field.Good results are obtained for the simulation of the irradiation tests of the first argentine prototypes of MOX fuels, where the bamboo effect is clearly observed, and of the FUMEX series for the fuel centerline temperature, the inside rod pressure and the fractional gas release.     

An algebraic approach to data languages and timed languages

Algebra offers an elegant and powerful approach to understand regular languages and finite automata. Such framework has been notoriously lacking for timed languages and timed automata. We introduce the notion of monoid recognizability for data languages, which includes timed languages as special case, in a way that respects the spirit of the classical situation. We study closure properties and hierarchies in this model and prove that emptiness is decidable under natural hypotheses. Our class of recognizable languages properly includes many families of deterministic timed languages that have been proposed until now, and the same holds for non-deterministic versions.     

Conquering Uncertainty in Multiple-Valued Logic Design

In modern science, significant advances are typically made atcross-roads of disciplines. Thus, many optimization problems inMultiple-valued Logic Design have been successfullyapproached using ideas and techniques from ArtificialIntelligence. In particular, improvements in multiple-valuedlogic design have been made by exploiting information/uncertaintymeasures. In this paper, we review well-known information measuresin the multiple-valued domain and consider some methods of findinginformation measures for completely or incompletely specifiedfunctions with multiple-valued and continuous attributes. In thisrespect, the paper addresses the problem known as discretizationand introduces a method of finding an optimal representation ofcontinuous data in the multiple-valued domain. We also propose atechnique for efficient calculation of different informationmeasures using Multiple-valued Decision Diagrams. As oneapplication of our technique, we outline an approach tosynthesizing digital circuits derived from decision diagrams thatcan yield to reduction in power dissipation. The paper also showsthe impact in several important areas of multiple-valued systemdesign including (i) fuzzy logic, (ii) quantum computing systems,and (iii) data mining.     

A Hadamard transform electron ionization time-of-flight mass spectrometer

We describe the first Hadamard transform time-of-flight mass spectrometer (HT-TOFMS) that incorporates an electron (impact) ionization source. This implementation was realized in an existent TOF instrument using commercially available components and simple modifications to the ion source. In the present apparatus, a Hadamard mask is expressed by modulating the ion generation process within the ion source; thus, the present approach differs from previous designs that use external electrostatic devices to modulate a continuous ion stream. The present implementation may be operated in conventional TOF mode at 12.5 kHz and in HT-TOF mode at 20-40 MHz. In Hadamard mode the design can operate using any circulant simplex code, allowing the operator much flexibility for optimizing resolution and mass range and for eliminating nonstochastic fluctuations, e.g., encoding errors and signal hum. We demonstrate typical performance of the HT-TOFMS in standard and reflectron geometries using sequences of three constructions and of varied length, generating HT-TOF mass spectra of molecules that match conventional reference spectra. The auxiliary material includes an electrical schematic for the floating high-speed encoding amplifier, which is also of use in other high-speed electrostatic optics applications, and a list of 537 validated vectors comprising the first row of each circulant simplex sequence (S(n)=3-8219) derived using maximal shift register (n=2(m)-1), quadratic residue (n=4m-3), and twin prime constructions [n=p(p+2)].