An efficient Neuro-Fuzzy approach to nuclear power plant transient identification

Transient identification in nuclear power plants (NPP) is often a computational very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in NPPs. The bases for the transient identification relay on the evidence that different system faults and anomalies lead to different pattern evolution in the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments that represents a specific type of event. Recently, several works have been developed for transient identification. These works frequently present a non reliable response, using the “don´t know” as the system output. In this work, we investigate the possibility of using a Neuro-Fuzzy modeling tool for efficient transient identification, aiming to helping the operator crew to take decisions relative to the procedure to be followed in situations of accidents/transients at NPPs. The proposed system uses artificial neural networks (ANN) as first level transient diagnostic. After the ANN has done the preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. A validation of this identification system was made at the three loops Pressurized Water Reactor (PWR) simulator of the Human-System Interface Laboratory (LABIHS) of the Nuclear Engineering Institute (IEN/CNEN/Brazil). The obtained results show the potential of this new transient identification system to be used in an operational NPP in order to assist the operators to take decisions during transients/accidents.     

Maximal solution to algebraic Riccati equations linked to infinite Markov jump linear systems

In this paper, we deal with a perturbed algebraic Riccati equation in an infinite dimensional Banach space. Besides the interest in its own right, this class of equations appears, for instance, in the optimal control problem for infinite Markov jump linear systems (from now on iMJLS). Here, infinite or finite has to do with the state space of the Markov chain being infinite countable or finite (see Fragoso and Baczynski in SIAM J Control Optim 40(1):270–297, 2001). By using a certain concept of stochastic stability (a sort of L ₂-stability), we prove the existence (and uniqueness) of maximal solution for this class of equation and provide a tool to compute this solution recursively, based on an initial stabilizing controller. When we recast the problem in the finite setting (finite state space of the Markov chain), we recover the result of de Souza and Fragoso (Syst Control Lett 14:233–239, 1999) set to the Markovian jump scenario, now free from an inconvenient technical hypothesis used there, originally introduced in Wonham in (SIAM J Control 6(4):681–697). Research supported by grants CNPq 520367-97-9, 300662/2003-3 and 474653/2003-0, FAPERJ 171384/2002, PRONEX and IM-AGIMB.     

The use of discrete Markov random fields in reservoir characterization

In this work, we discuss relevant aspects concerning the use of discrete Markov random fields (MRF) in the simulation of rock properties in petroleum reservoirs. The Strauss multi-color model is useful to describe complex image configurations, by handling with parameters of repulsion between the different rock facies, symbolized in this case, by the different colors. The transition between the facies and the porous medium anisotropy are imposed to the system, and it is possible to generate various types of arrangement of the facies on the image, in contrast to Gaussian stochastic process, that can only simulate diffusion-type images. Another point focused is the behavior of the spatial correlation in discrete Markov random fields, here studied by the calculus of the practical semivariogram function in the binary Markov images, generated by using the Metropolis algorithm. These images have a correspondence to Gaussian images with Gaussian-type correlation, after truncated in binary facies. This similarity is validated by analysis in the behavior of the semivariogram function of the discrete Gaussian processes.     

Thermal stability analysis of Cu-11.8 wt%Al milled samples by TEM and HT-XRD

In this work, the thermal stability of two samples of Cu-11.8 wt%Al obtained by different milling processes is analyzed. Several TEM techniques were used and HT-XRD experiments performed to determine the crystal structure and the morphological microstructure of the samples obtained during different heat treatments. The heat treatments were: quenching from 850 °C to room temperature and two consecutive calorimetric runs at 5 °C/min. After the quenching,α₂ is the major phase observed, reaching 95 mass%. The remaining 5 mass% consisted of martensitic phases: one sample had γ′, a hexagonal structure, and the other β₁′, a rhombohedral structure. During the first calorimetric run, the sample containing the γ′ phase exhibited a calorimetric event and the sample containing the β₁′ phase did not. The calorimetric event is attributed to the austenitic transformation γ′ → β₁. The lack of calorimetric event in the sample containing the β₁′ is associated with the inhibition of the transformation β₁′ → β₁ because of the precipitation of the γ₂ phase. Finally, the absence of a calorimetric event in the second run with the first sample is associated with the retransformation to β₁′ instead to γ′ phase during cooling of the first calorimetric run. These studies determined that the first sample is a better candidate than the second sample to produce a shape memory alloy after thermo-mechanical treatments of the milled powders.     

The role of dynamic recrystallization in [001] single-crystal W and W-Ta alloy ballistic rod penetration into steel targets

The microstructures of long rod [001] single-crystal penetrators of W grown by CVD and zone melt processing, and W-5% Ta grown by zone melt (ZM) processing, were examined before and after penetration into RHA steel targets, by optical metallography and transmission electron microscopy. The initial Vickers microhardness values for the CVD-W rods was 417 VHN in contrast to 485 VHN for the ZM-W and W-5% Ta rods as a consequence of an order of magnitude larger dislocation density. Both the CVD-W and ZM-W exhibited less dense head flow associated with adiabatic shear bands and dynamic recrystallization (DRX) than the ZM-W-5% Ta, but all penetrators exhibited erosion tube formation in the penetration channel. These tube and erosion debris particles exhibited dense, overlapping shear bands composed of DRX grains or areas with larger, equiaxed grains resulting from residual grain growth. These observations suggest that controlling the penetrator head flow by solute-induced DRX may control penetration.     

Protection of normal cells from irradiation bystander effects by silica-flufenamic acid nanoparticles

The development of a myriad of nanoparticles types has opened new possibilities for the diagnostics and treatment of many diseases, especially for cancer. However, most of the researches done so far do not focus on the protection of normal cells surrounding a tumor from irradiation bystander effects that might lead to cancer recurrence. Gap-junctions are known to be involved in this process, which leads to genomic instability of neighboring normal cells, and flufenamic acid (FFA) is included in a new group of gap-junction blockers recently discovered. The present work explores the use of mesoporous silica nanoparticles MCM-41 functionalized with 3-Aminopropyltriethoxysilane (APTES) for anchoring the flufenamic acid for its prolonged and controlled release and protection from radiation bystander effects. MCM-41 and functionalized samples were structurally and chemically characterized with multiple techniques. The biocompatibility of all samples was tested in a live/dead assay performed in cultured MRC-5 and HeLa cells. HeLa cells cultured were exposed to 50?Gy of gamma-rays and the media transferred to fibroblast cells cultured separately. Our results show that MCM-41 and functionalized samples have high biocompatibility with MCR-5 and HeLa cells, and most importantly, the FFA delivered by these NPs was able to halt apoptosis, one of main bystander effects.     

Node and element resequencing using the Laplacian of a finite element graph: Part I—General concepts and algorithm

A Finite Element Graph (FEG) is defined here as a nodal graph (G), a dual graph (G*), or a communication graph (G˙) associated with a generic finite element mesh. The Laplacian matrix ( L (G), L (G*) or L (G˙)), used for the study of spectral properties of an FEG, is constructed from usual vertex and edge connectivities of a graph. An automatic algorithm, based on spectral properties of an FEG (G, G* or G˙), is proposed to reorder the nodes and/or elements of the associated finite element mesh. The new algorithm is called Spectral PEG Resequencing (SFR). This algorithm uses global information in the graph, it does not depend on a pseudoperipheral vertex in the resequencing process, and it does not use any kind of level structure of the graph. Moreover, the SFR algorithm is of special advantage in computing environments with vector and parallel processing capabilities. Nodes or elements in the mesh can be reordered depending on the use of an adequate graph representation associated with the mesh. If G is used, then the nodes in the mesh are properly reordered for achieving profile and wavefront reduction of the finite element stiffness matrix. If either G* or G˙ is used, then the elements in the mesh are suitably reordered for a finite element frontai solver, A unified approach involving FEGs and finite element concepts is presented. Conclusions are inferred and possible extensions of this research are pointed out. In Part II of this work,¹ the computational implementation of the SFR algorithm is described and several numerical examples are presented. The examples emphasize important theoretical, numerical and practical aspects of the new resequencing method.     

Femtosecond-laser selective printing of graphene oxide and PPV on polymeric microstructures

Direct laser writing techniques are suitable for the high precision-patterning of 2D and 3D micro/nanostructures, featuring a variety of geometries and materials. Here, we demonstrated the use of laser-induced forward transfer with fs-pulses (fs-LIFT) to selectively transfer graphene oxide and poly(p-phenylene vinylene) patterns onto polymeric microstructures, fabricated by two-photon polymerization. The influence of different fs-LIFT experimental parameters on the width and height of the printed patterns was investigated. Upon optimum fs-LIFT parameters, we achieved homogeneous printed areas of both materials onto specific regions of the microstructures. Raman spectroscopy confirmed that fs-LIFT does not change the donor material upon transfer. Overall, this work demonstrates a promising strategy with precise printing capabilities, thus opening new opportunities for the development of photonic and optoelectronic devices.