On-line neuro-expert monitoring system for Borssele Nuclear Power Plant

A new method for an on-line monitoring system for the nuclear power plants has been developed utilizing the neural networks and the expert system. The integration of them is expected to enhance a substantial potential of the functionality as operators support.

The recurrent neural network and the feed-forward neural network with adaptive learning are selected for the plant modeling and anomaly detection because of the high capability of modeling for dynamic behavior. The expert system is used as a decision agent, which works on the information space of both the neural networks and the human operators. The information of other sensory signals is also fed to the expert system, together with the outputs that the neural networks generate from the measured plant signals. The expert system can treat almost all known correlation between plant status patterns and operation modes as a priori set of rules.

From the off-line test at Borssele Nuclear Power Plant (PWR 480 MWe) in the Netherlands, it was shown that the neuro-expert system successfully monitored the plant status. The expert system worked satisfactorily in diagnosing the system status by using the outputs of the neural networks and a priori knowledge base from the PWR simulator. The electric power coefficient is simultaneously monitored from the measured reactive and active electric power signals.     

On Logical Foundations of Multilevel Secure Databases

It is envisaged that the application of the multilevel security (MLS) scheme will enhance flexibility and effectiveness of authorization policies in shared enterprise databases and will replace cumbersome authorization enforcement practices through complicated view definitions on a per user basis. However, the critical problem with the current model is that the belief at a higher security level is cluttered with irrelevant or inconsistent data as no mechanism for attenuation is supported. Critics also argue that it is imperative for MLS database users to theorize about the belief of others, perhaps at different security levels, an apparatus that is currently missing and the absence of which is seriously felt.The impetus for our current research is the need to provide an adequate framework for belief reasoning in MLS databases. In this paper, we show that these concepts can be captured in a F-logic style declarative query language, called MultiLog, for MLS deductive databases for which a proof theoretic, model theoretic and fixpoint semantics exist. This development is significant from a database perspective as it now enables us to compute the semantics of MultiLog databases in a bottom-up fashion. We also define a bottom-up procedure to compute unique models of stratified MultiLog databases. Finally, we establish the equivalence of MultiLog's three logical characterizations—model theory, fixpoint theory and proof theory.     

Modeling of Dispersive Materials Using Dispersion Models for FDTD Application

A nonlinear optimization algorithm based on the Nelder Mead method is used to characterize the frequency dependent permittivity of 15 materials based on Lorentz, modified Lorentz, Drude and Lorentz-Drude models. The optimized model parameters are used to calculate the complex relative permittivity of each material and compare it with experimental data. In each case, a very good match is found between the optimized and experimental data over a long wavelength range. Comparative study of the models used for each material is performed based on accuracy, wavelength range of applicability and computational efficiency. The parameters presented can be used for computer simulation of electromagnetic wave phenomena involving these materials.     

Mixed convective heat transfer enhancement in a ventilated cavity by flow modulation via rotating plate

The present study numerically explores the mixed convection phenomena in a differentially heated ventilated square cavity with active flow modulation via a rotating plate. Forced convection flow in the cavity is attained by maintaining external fluid flow through an opening at the bottom of the left cavity wall while leaving it through another opening at the right cavity wall. A counter-clockwise rotating plate at the center of the cavity acts as an active flow modulator. Moving mesh approach is used for the rotation of the plate and the numerical solution is achieved using arbitrary Lagrangian-Eulerian finite element formulation with a quadrilateral discretization scheme. Transient parametric simulations have been performed for various frequency of the rotating plate for a fixed Reynolds number (Re) of 100 based on maximum inlet flow velocity while the Richardson number (Ri) is maintained at unity. Heat transfer performance has been evaluated in terms of spatially averaged Nusselt number and time-averaged Nusselt number along the heated wall. Power spectrum analysis in the frequency domain obtained from the fast Fourier transform analysis indicates that thermal frequency and plate frequency start to deviate from each other at higher values of velocity ratio (>4).     

A comparative study of SiAlON ceramics

Two different varieties of Si₃N₄ powders were used to prepare SiAlON ceramics. 100% β-Si₃N₄ was used from refractory grade powders (B1) and another purer 98% α-Si₃N₄ (50A) powder was used to prepare the SiAlON samples. Since SiC + SiAlON composites reportedly perform better, batches were prepared with 15% SiC addition to the refractory powders (B1) and 17.5% SiC was added to the other SiAlON composition (50A). The samples were gas pressure sintered at 1840 °C and at 22 bar with 1 h dwelling time. Thereby, we could achieve 97–98% theoretical density. The hardness was recorded 14–17 GPa while fracture toughness varied from 4.3 to 5 MPa m^1/2. Fretting experiments showed initial running-in period of 300 cycles for all the tribo-couples. After which, the steady state coefficient of frictions (COF) were achieved. Steel ball of 10 mm diameter, fretting against 50A composition, showed 0.6 average steady state COF while the same composition while fretting against alumina ball of the same diameter, showed 0.57 average steady state COF. Results have been compared with SiAlON composition derived from refractory powder (B1) and found that the 50A composition performs better under identical test conditions. Moreover, cytocompatibility study also suggests that the investigated 50A composition can be used as substrate to support cell adhesion and proliferation of L929 mouse fibroblast cell lines whereas B1 composition derived from refractory powders are toxic in nature.     

Formal probabilistic analysis of a surgical robot control algorithm with different virtual fixtures

Surgical robots are increasingly being used in operation theaters involving normal or laparoscopic surgeries. The working of these surgical robots is highly dependent on their control algorithms, which require very rigorous analysis to ensure their correct functionality due to the safety-critical nature of surgeries. Traditionally, safety of control algorithms is ensured by simulations, but they provide incomplete and approximate analysis results due to their inherent sampling-based nature. We propose to use probabilistic model checking, which is a formal verification method, for quantitative analysis, to verify the control algorithms of surgical robots in this paper. As an illustrative example, the paper provides a formal analysis of a virtual fixture control algorithm, implemented in a neuro-surgical robot, using the PRISM model checker. In particular, we provide a formal discrete-time Markov chain-based model of the given control algorithm and its environment. This formal model is then analyzed for multiple virtual fixtures, like cubic, hexagonal and irregular shapes. This verification allowed us to discover new insights about the considered algorithm that allow us to design safer control algorithms.     

Improvement of Grain Size and Dome Height of Microalloyed Steels Using Taguchi Method Based on Grey Relational Grade in Controlled Rolling

An efficient approach was introduced for improving the condition of major controlled rolling process parameters of roughing, finishing and coiling temperatures and optimizing these parameters to obtain minimum grain size and maximum dome height simultaneously. Taguchi method combined with grey relational analysis was applied to achieve optimum grain size and dome height during controlled rolling process. For this purpose, four levels for the above temperatures were chosen and sixteen experiments were conducted based on orthogonal array of Taguchi method. Based on Taguchi approach, signal-to-noise (S/N) ratios were calculated and used in order to obtain the optimum levels for every input parameter. Analysis of variance revealed that finishing and coiling temperatures have the maximum effect on the grain size and dome height of microalloyed steels. The confirmation tests with the optimal levels of parameters indicated that the grain size and dome height of controlled rolled microalloyed steels can be improved effectively through this approach.