Reliability assessment of nuclear power plant fault-diagnostic systems using artificial neural networks

The assurance of the diagnosis obtained from a nuclear power plant (NPP) fault-diagnostic advisor based on artificial neural networks (ANNs) is essential for the practical implementation of the advisor to transient detection and identification. The objectives of this study are to develop a validation and verification technique suitable for ANNs and apply it to the fault-diagnostic advisor. The validation and verification is realized by estimating error bounds on the advisor\u27s diagnoses. The two different partition criteria are developed to create computationally effective partitions for generating the error information associated with the advisor performance. The bootstap partition criterion (BPC) and the modified bootstap partition criterion (MBPC) can alleviate the computational requirements significantly. In addition, a new error-bound prediction scheme called error estimation by series association (EESA) is constructed not only to infer error-bounds but also to alleviate the training complexity of an error predictor neural network. The EESA scheme is applied to validate the outputs of the ANNs modeled for a simple nonlinear mapping and more complicated NPP fault-diagnostic problems. Two independent sets of data simulated at San Onofre Nuclear Generating Station, a pressurized water reactor, and Duane Arnold Energy Center, a boiling water reactor, are used to design the fault-diagnostic advisor systems and to perform the reliability assessment of the advisor systems. The results of this research show that the fault-diagnostic systems developed using ANNs with EESA are effective at producing proper diagnoses with predicted error even when degraded by noise. In general, EESA can also be used to verify an ANN system by indicating that the ANN system requires training on more data in order to increase generalization. The EESA scheme developed in this study can be implemented to any ANN system regardless of ANN learning paradigm

An artificial neutral network fault-diagnostic adviser for a nuclear power plant with error prediction

Since the accidents at the Three-Mile Island (TMI) and m Chernobyl nuclear power plants (NPPs), the safety of NPPs has become an even more important concern to both the nuclear power industry and the general public. The demand for safer plants has ever since. Responding to the demand, many scientists increased have investigated augmenting NPP safety in various ways. For m example, innovative reactor designs, better safety system R designs, human factor studies, stricter safety regulations, and so on, have been developed and implemented in the years since the above-mentioned accidents

Source Mechanism of Volcanic Explosions Investigated by Seismo-Acoustic Observations

Source mechanisms of explosive, volcanic eruptions are critical for understanding magmatic plumbing systems, determining the evolution and geometry of source regions, and assessing eruptive behavior as well as hazard impact. In the last two decades, volcano seismo-infrasonic observations have become an essential part of volcano monitoring systems. Because the open vent of a volcano is a corridor connecting the solid earth to the atmosphere, explosive eruptions efficiently excite both infrasound and seismic waves. Each of these mechanical waves includes characteristic information on several stages of the eruption process, and the coupling of these processes sheds considerable light into volcano dynamics. In this dissertation, details of the explosive eruption mechanism are investigated by seismo-acoustic observations at two volcanoes: Karymsky Volcano in Kamchatka, Russia, and Tungurahua Volcano, Ecuador. First, path effects of infrasound waves near volcanic craters are investigated as they pass the rim of the vent and propagate to remote stations. Next, characteristics of infrasonic sources excited by volcanic explosion are explored. Distortion due to diffraction and reflection of infrasound at the crater vent is shown to be significant and must be accounted for when interpreting explosion source physics from wave fields. To address these problems we propose an acoustic, multipole source model in a half-space for volcanic explosions. Acoustic observations at Tungurahua Volcano appear to corroborate this model. Finally, source mechanisms of explosive eruptions at Tungurahua are investigated by jointly analyzing infrasound and seismic waves. Using this approach, the time evolution and geometric orientation of the magmatic plumbing system, during a period of volcanic crises at Tungurahua, are illuminated and explained.Doctor of Philosoph

A designed angiopoietin-2 variant, pentameric COMP-Ang2, strongly activates Tie2 receptor and stimulates angiogenesis

AbstractDespite that angiopoietin-2 (Ang2) produces more versatile and dynamic functions than angiopoietin-1 (Ang1) in angiogenesis and inflammation, the molecular mechanism that underlies this difference is still unknown. To define the role of oligomerization of Ang2 in activation of its receptor, Tie2, we designed and generated different oligomeric forms of Ang2 by replacement of the amino-terminal domains of Ang2 with dimeric, tetrameric, and pentameric short coiled-coil domains derived from GCN4, matrillin-1, and COMP. COMP-Ang2 strongly binds and activates Tie2, whereas GCN4-Ang2 and MAT-Ang2 weakly to moderately bind and activate Tie2. Although native Ang2 strongly binds to Tie2, it does not activate Tie2. Accordingly, COMP-Ang2 strongly promotes endothelial cell survival, migration, and tube formation in a Tie2-dependent manner, and the potency of COMP-Ang2 is almost identical to that of COMP-Ang1. Furthermore, the potency of COMP-Ang2-induced enhanced angiogenesis in the wound healing region is almost identical to the potency of COMP-Ang1-induced enhanced angiogenesis. Overall, there is no obvious difference between COMP-Ang2 and COMP-Ang1 in in vitro and in vivo angiogenesis. Our results provide compelling evidence that proper oligomerization of Ang2 is a critical determinant of its binding and activation of Tie2

Acoustic multipole source model for volcanic explosions and inversion for source parameters

Volcanic explosions are accompanied by strong acoustic pressure disturbances in the atmosphere. With a proper source model, these acoustic signals provide invaluable information about volcanic explosion dynamics. Far-field solutions to volcanic infrasound radiation have been derived above a rigid half-space boundary, and a simple inversion method was developed based on the half-space model. Acoustic monopole and dipole sources were estimated simultaneously from infrasound waveforms. Stability of the inversion procedure was assessed in terms of variances of source parameters, and the procedure was reliable with at least three stations around the infrasound source. Application of this method to infrasound observations recorded at Tungurahua volcano in Ecuador successfully produced a reasonable range of source parameters with acceptable variances. Observed strong directivity of infrasound radiation from explosions at Tungurahua are successfully explained by the directivity of a dipole source model. The resultant dipole axis, in turn, shows good agreement with the opening direction of the vent at Tungurahua, which is considered to be the origin of the dipole source. The method is general and can be utilized to study any monopole, dipole or combined sources generated by explosions

Nuclear power plant fault-diagnosis using artificial neural networks

Artificial neural networks (ANNs) have been applied to various fields due to their fault and noise tolerance and generalization characteristics. As an application to nuclear engineering, we apply neural networks to the early recognition of nuclear power plant operational transients. If a transient or accident occurs, the network will advise the plant operators in a timely manner. More importantly, we investigate the ability of the network to provide a measure of the confidence level in its diagnosis. In this research an ANN is trained to diagnose the status of the San Onofre Nuclear Generation Station using data obtained from the plant`s training simulator. Stacked generalization is then applied to predict the error in the ANN diagnosis. The data used consisted of 10 scenarios that include typical design basis accidents as well as less severe transients. The results show that the trained network is capable of diagnosing all 10 instabilities as well as providing a measure of the level of confidence in its diagnoses

Toll-Like Receptor 4 Decoy, TOY, Attenuates Gram-Negative Bacterial Sepsis

Lipopolysaccharide (LPS), the Gram-negative bacterial outer membrane glycolipid, induces sepsis through its interaction with myeloid differentiation protein-2 (MD-2) and Toll-like receptor 4 (TLR4). To block interaction between LPS/MD-2 complex and TLR4, we designed and generated soluble fusion proteins capable of binding MD-2, dubbed TLR4 decoy receptor (TOY) using ‘the Hybrid leucine-rich repeats (LRR) technique’. TOY contains the MD-2 binding ectodomain of TLR4, the LRR motif of hagfish variable lymphocyte receptor (VLR), and the Fc domain of IgG1 to make it soluble, productive, and functional. TOY exhibited strong binding to MD-2, but not to the extracellular matrix (ECM), resulting in a favorable pharmacokinetic profile in vivo. TOY significantly extended the lifespan, when administered in either preventive or therapeutic manners, in both the LPS- and cecal ligation/puncture-induced sepsis models in mice. TOY markedly attenuated LPS-triggered NF-κB activation, secretion of proinflammatory cytokines, and thrombus formation in multiple organs. Taken together, the targeting strategy for sequestration of LPS/MD-2 complex using the decoy receptor TOY is effective in treating LPS- and bacteria-induced sepsis; furthermore, the strategy used in TOY development can be applied to the generation of other novel decoy receptor proteins

Controllable deposition of organic metal halide perovskite films with wafer-scale uniformity by single source flash evaporation

Conventional solution-processing techniques such as the spin-coating method have been used successfully to reveal excellent properties of organic-inorganic halide perovskites (OHPs) for optoelectronic devices such as solar cell and light-emitting diode, but it is essential to explore other deposition techniques compatible with large-scale production. Single-source flash evaporation technique, in which a single source of materials of interest is rapidly heated to be deposited in a few seconds, is one of the candidate techniques for large-scale thin film deposition of OHPs. In this work, we investigated the reliability and controllability of the single-source flash evaporation technique for methylammonium lead iodide (MAPbI(3)) perovskite. In-depth statistical analysis was employed to demonstrate that the MAPbI(3) films prepared via the flash evaporation have an ultrasmooth surface and uniform thickness throughout the 4-inch wafer scale. We also show that the thickness and grain size of the MAPbI(3) film can be controlled by adjusting the amount of the source and number of deposition steps. Finally, the excellent large-area uniformity of the physical properties of the deposited thin films can be transferred to the uniformity in the device performance of MAPbI(3) photodetectors prepared by flash evaporation which exhibited the responsivity of 0.2 A/W and detectivity of 3.82x10(11) Jones.

A single gene of a commensal microbe affects host susceptibility to enteric infection

Indigenous microbes inside the host intestine maintain a complex self-regulating community. The mechanisms by which gut microbes interact with intestinal pathogens remain largely unknown. Here we identify a commensal Escherichia coli strain whose expansion predisposes mice to infection by Vibrio cholerae, a human pathogen. We refer to this strain as 'atypical' E. coli (atEc) because of its inability to ferment lactose. The atEc strain is resistant to reactive oxygen species (ROS) and proliferates extensively in antibiotic-treated adult mice. V. cholerae infection is more severe in neonatal mice transplanted with atEc compared with those transplanted with a typical E. coli strain. Intestinal ROS levels are decreased in atEc-transplanted mice, favouring proliferation of ROS-sensitive V. cholerae. An atEc mutant defective in ROS degradation fails to facilitate V. cholerae infection when transplanted, suggesting that host infection susceptibility can be regulated by a single gene product of one particular commensal species.

Field Dependence of Magnetic Ordering in Kagomé-Staircase Compound Ni\u3csub\u3e3\u3c/sub\u3eV\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e8\u3c/sub\u3e

We present powder and single-crystal neutron diffraction and bulk measurements of the Kagomé-staircase compound Ni3V2O8 (NVO) in fields up to 8.5T applied along the c direction. (The Kagomé plane is the a−c plane.) This system contains two types of Ni ions, which we call “spine” and “cross-tie.” Our neutron measurements can be described with the paramagnetic space group Cmca for T\u3c15K and each observed magnetically ordered phase is characterized by the appropriate irreducible representation(s). Our zero-field measurements show that at TPH=9.1K NVO undergoes a transition to a predominantly longitudinal incommensurate structure in which the spine spins are nearly along the a-axis. At THL=6.3K, there is a transition to an elliptically polarized incommensurate structure with both spine and cross-tie moments in the a−b plane. At TLC=4K the system undergoes a first-order phase transition to a commensurate antiferromagnetic structure with the staggered magnetization primarily along the a-axis and a weak ferromagnetic moment along the c-axis. A specific heat anomaly at TCC′=2.3K indicates an additional transition, which remarkably does not affect Bragg peaks of the commensurate C structure. Neutron, specific heat, and magnetization measurements produce a comprehensive temperature-field phase diagram. The symmetries of the incommensurate magnetic phases are consistent with the observation that only one phase is electrically polarized. The magnetic structures are explained theoretically using a simplified model Hamiltonian, that involves competing nearest- and next-nearest-neighbor exchange interactions, single-ion anisotropy, pseudodipolar interactions, and Dzyaloshinskii-Moriya interactions