New CAMAC based data acquisition and beam control system for Lund nuclear microprobe

A new CAMAC based data acquisition system has been installed at the Lund Nuclear Microprobe facility. This paper reports on the development and present status of the data acquisition system. The system is a true multiparameter CAMAC based system with fast Fera bus readout and in crate memory buffer. The user interface is based on Sparrow Kmax software for a Power Macintosh platform. The system read out and tag the event data with position on-line, which make fast on-line monitoring of spectra or element maps possible.Simultaneously, all data can be saved event by event for off-line analysis. The beam scanning part is software controlled through a timed D/A converter, this allows fast scanning of the beam. With a CCD-camera and video card the area to be analysed could be defined directly from the image, and the sample position can be moved. Any kind of irregular scan patterns could be defined.     

Remarks on the mean square tracking error

The purpose of this paper is to extend recent results of Ljung and Priouret to a more general class of regressors.     

Diffusion induced grain boundary migration and recrystallization during oxidation of a Ni- 48.5 Pet Cu alloy

Diffusion induced grain boundary migration (DIGM) was observed to occur in a Ni-48.5 wt pct Cu alloy during oxidation at 450 °C, 500 °C, 600 °C, and 707 °C in air. The DIGM zones are Cu enriched. A Ni depleted zone, consisting of small recrystallized grains, formed in the matrix beneath the metal-oxide interface during oxidation at 600 °C and 707 °C. This process is referred to as oxidation-induced recrystallization (OIR). Growth of the small OIR grains was observed to be associated with Cu-rich DIGM. No Cu-rich DIGM was found in the same alloy when annealed in Ar at 707 °C. Oxidation of this alloy in air resulted in the formation of a duplex oxide: an inner NiO layer and an outer CuO layer. The NiO layer was observed to grow at a faster rate than the CuO layer. The occurrence of Cu-rich DIGM is interpreted in terms of this preferential oxidation of Ni.     

Performance analysis of general tracking algorithms

A general family of tracking algorithms for linear regression models is studied. It includes the familiar least mean square gradient approach, recursive least squares, and Kalman filter based estimators. The exact expressions for the quality of the obtained estimates are complicated. Approximate, and easy-to-use, expressions for the covariance matrix of the parameter tracking error are developed. These are applicable over the whole time interval, including the transient, and the approximation error can be explicitly calculated     

Nonlinear black-box modeling in system identification: a unified overview

A nonlinear black-box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area, with structures based on neural networks, radial basis networks, wavelet networks and hinging hyperplanes, as well as wavelet-transform-based methods and models based on fuzzy sets and fuzzy rules. This paper describes all these approaches in a common framework, from a user's perspective. It focuses on what are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques. It is pointed out that the nonlinear structures can be seen as a concatenation of a mapping form observed data to a regression vector and a nonlinear mapping from the regressor space to the output space. These mappings are discussed separately. The latter mapping is usually formed as a basis function expansion. The basis functions are typically formed from one simple scalar function, which is modified in terms of scale and location. The expansion from the scalar argument to the regressor space is achieved by a radial- or a ridge-type approach. Basic techniques for estimating the parameters in the structures are criterion minimization, as well as two-step procedures, where first the relevant basis functions are determined, using data, and then a linear least-squares step to determine the coordinates of the function approximation. A particular problem is to deal with the large number of potentially necessary parameters. This is handled by making the number of ‘used’ parameters considerably less than the number of ‘offered’ parameters, by regularization, shrinking, pruning or regressor selection.     

Simulation of small break LOCA effects on BWR-pressure suppression systems

The GKSS-Forschungszentrum has simulated within an extensive PSS (Pressure Suppression System) program small break LOCA situations in a large scale multivent PSS test arrangement. The gained experimental information indicates that the simulated small break LOCA in a BWR-PSS which initiates steam condensation in the wetwell pool at the vent pipe outlets, gives strong cyclic pressure pulses from chugging events over a long time period.     

An Extended Replication of an Experiment for Assessing Methods for Software Requirements Inspections

We have performed an extended replication of the Porter-Votta-Basili experiment comparing the Scenario method and the Checklist method for inspecting requirements specifications using identical instruments. The experiment has been conducted in our educational context represented by a more general definition of a defect compared to the original defect list. Our study involving 24 undergraduate students manipulated three independent variables: detection method, requirements specification, and the order of the inspections. The dependent variable measured is the defect detection rate. We found the requirements specification inspected and not the detection method to be the most probable explanation for the variance in defect detection rate. This suggests that it is important to gather knowledge of how a requirements specification can convey an understandable view of the product and to adapt inspection methods accordingly. Contrary to the original experiment, we can not significantly support the superiority of the Scenario method. This is in accordance with a replication conducted by Fusaro, Lanubile and Visaggio, and might be explained by the lack of individual defect detection skill of our less experienced subjects.     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.