Methods and Systems for Fault Diagnosis in Nuclear Power Plants

This research mainly deals with fault diagnosis in nuclear power plants (NPP), based on a framework that integrates contributions from fault scope identification, optimal sensor placement, sensor validation, equipment condition monitoring, and diagnostic reasoning based on pattern analysis. The research has a particular focus on applications where data collected from the existing SCADA (supervisory, control, and data acquisition) system is not sufficient for the fault diagnosis system. Specifically, the following methods and systems are developed. A sensor placement model is developed to guide optimal placement of sensors in NPPs. The model includes 1) a method to extract a quantitative fault-sensor incidence matrix for a system; 2) a fault diagnosability criterion based on the degree of singularities of the incidence matrix; and 3) procedures to place additional sensors to meet the diagnosability criterion. Usefulness of the proposed method is demonstrated on a nuclear power plant process control test facility (NPCTF). Experimental results show that three pairs of undiagnosable faults can be effectively distinguished with three additional sensors selected by the proposed model. A wireless sensor network (WSN) is designed and a prototype is implemented on the NPCTF. WSN is an effective tool to collect data for fault diagnosis, especially for systems where additional measurements are needed. The WSN has distributed data processing and information fusion for fault diagnosis. Experimental results on the NPCTF show that the WSN system can be used to diagnose all six fault scenarios considered for the system. A fault diagnosis method based on semi-supervised pattern classification is developed which requires significantly fewer training data than is typically required in existing fault diagnosis models. It is a promising tool for applications in NPPs, where it is usually difficult to obtain training data under fault conditions for a conventional fault diagnosis model. The proposed method has successfully diagnosed nine types of faults physically simulated on the NPCTF. For equipment condition monitoring, a modified S-transform (MST) algorithm is developed by using shaping functions, particularly sigmoid functions, to modify the window width of the existing standard S-transform. The MST can achieve superior time-frequency resolution for applications that involves non-stationary multi-modal signals, where classical methods may fail. Effectiveness of the proposed algorithm is demonstrated using a vibration test system as well as applications to detect a collapsed pipe support in the NPCTF. The experimental results show that by observing changes in time-frequency characteristics of vibration signals, one can effectively detect faults occurred in components of an industrial system. To ensure that a fault diagnosis system does not suffer from erroneous data, a fault detection and isolation (FDI) method based on kernel principal component analysis (KPCA) is extended for sensor validations, where sensor faults are detected and isolated from the reconstruction errors of a KPCA model. The method is validated using measurement data from a physical NPP. The NPCTF is designed and constructed in this research for experimental validations of fault diagnosis methods and systems. Faults can be physically simulated on the NPCTF. In addition, the NPCTF is designed to support systems based on different instrumentation and control technologies such as WSN and distributed control systems. The NPCTF has been successfully utilized to validate the algorithms and WSN system developed in this research. In a real world application, it is seldom the case that one single fault diagnostic scheme can meet all the requirements of a fault diagnostic system in a nuclear power. In fact, the values and performance of the diagnosis system can potentially be enhanced if some of the methods developed in this thesis can be integrated into a suite of diagnostic tools. In such an integrated system, WSN nodes can be used to collect additional data deemed necessary by sensor placement models. These data can be integrated with those from existing SCADA systems for more comprehensive fault diagnosis. An online performance monitoring system monitors the conditions of the equipment and provides key information for the tasks of condition-based maintenance. When a fault is detected, the measured data are subsequently acquired and analyzed by pattern classification models to identify the nature of the fault. By analyzing the symptoms of the fault, root causes of the fault can eventually be identified

Features of spectral vibration diagnostics of traction power transformers in high-speed motion

This paper uses spectral analysis methods to develop a mathematical model and algorithms for evaluating the diagnosed signals corresponding to certain defects of windings and magnetic circuits of traction power transformers. A distinctive feature of the study is at certain frequencies of spectral dependences, taking into account the effects associated with defect formation that have a different cause of their manifestation, for example, wide-field fluctuations and changes in the shape and width of spectral peaks. The presence of random fluctuations caused the application of the normal Gaussian distribution law of the measured values of the spectra. To solve the problem of identifying the diagnosed spectra corresponding to certain defects of the power transformer, algorithms for identifying the vector of diagnostic features based on the method of statistical recognition theory for large amounts of information are proposed

Island hoppers : Integrative taxonomic revision of Hogna wolf spiders (Araneae, Lycosidae) endemic to the Madeira islands with description of a new species

Because of their ability for aerial dispersal using silk and preference for open habitats, many wolf spiders are formidable colonisers. Pioneering arachnologists were already aware of the large and colourful wolf spiders in the Madeira archipelago, currently included in the genus Hogna Simon, 1885. The origins were investigated and species boundaries of Madeiran Hogna examined by integrating target-gene and mor-phological information. A multi-locus phylogenetic analysis of a thorough sampling across wolf-spider diversity suggested a single origin of Madeiran endemics, albeit with low support. Divergence time estima-tion traced back their origin to the late Miocene, a time of major global cooling that drove the expansion of grasslands and the associated fauna. Morphological examination of types and newly collected material revealed a new species, hereby described as H. isambertoi Crespo, sp. nov. Additionally, H. blackwalli is revalidated and three new synonymies are proposed, namely H. biscoitoi Wunderlich, 1992, junior syno-nym of H. insularum Kulczynski, 1899, H. schmitzi Wunderlich, 1992, junior synonym of H. maderiana (Walckenaer, 1837), and Arctosa maderana Roewer, 1960 junior synonym of H. ferox (Lucas, 1838). Spe-cies delimitation analyses of mitochondrial and nuclear markers provided additional support for morpho-logical delineations. The species pair H. insularum and H. maderiana, however, constituted an exception: the lack of exclusive haplotypes in the examined markers, along with the discovery of intermediate forms, pointed to hybridisation between these two species as reported in other congeneric species on islands. Finally, the conservation status of the species is discussed and candidates for immediate conservation efforts are identified.Peer reviewe

Ecological and Evolutionary Dynamics of Complex Host-Parasite Communities

Parasites are ubiquitous in nature, and embedded in complex communities of hosts and parasites. Most parasite species infect multiple host species, and most host species are infected by multiple parasite species. However, it’s very challenging to study the complex web of host- parasite interactions in natural settings, and controlled lab experiments are often limited to small numbers of host or parasite species. Additionally, parasites can evolve rapidly, so host-parasite interactions change over time. In my dissertation, I used field surveys, network analyses, and lab experiments to understand how different host species influence parasite infections in another host species, how parasites differ in their ability to infect multiple host species, how hosts respond to the threat of multiple parasites, and how parasites evolve over the course of an epidemic. My general aims were to untangle the web of interactions in host-parasite communities and to understand the evolutionary consequences of those interactions. In Chapter 2, I estimated potential cross-species transmission of different parasite species and built networks of hosts and parasites connected by these interactions. In Chapter 3, I investigated the consequences of multiple parasites on host behavior, namely sexual reproduction. Lastly, in Chapter 4, I looked to see if parasites were evolving in response to ecological dynamics such as the growth phase of an epidemic. Overall, I found that particular host and parasite species may disproportionately contribute to cross-species transmission, hosts alter their reproductive behavior in response to biotic factors, and parasite virulence can evolve rapidly over the course of a natural epidemic.PHDEcology and Evolutionary BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163257/1/cgowler_1.pd

Genetic diversity of selected petrosiid sponges

Sponges are simple animals that mostly inhabit the marine ecosystem. The role of sponges in the marine ecosystem and the potential of their bioactive compounds for the pharmaceutical industry have already been reviewed. Because of the extensive investigations of sponges within those two disciplines, marine ecology and chemistry, sponges are among the best-studied Metazoa. Likewise, sponges have been selected as animal models for investigating the origin of the multicellularity because sponges have a simple body structure and physiology (e.g., lack of nervous and circulatory organs). Due to their diversity and abundance in the tropics, particularly in the Indo-Pacific, sponges have also attracted taxonomists, systematists and ecologists to assess their diverseness and their phylogenetic and phylogeographic relationships. Resolving those research questions is difficult, because sponges are categorised as comparatively character poor taxa. By using only conservative taxonomy or systematics, the sponge diversity might therefore be underestimated. Inevitably, sponge biologists have to employ molecular methods as additional tools. In this research, molecular tools were used in order to analyse the taxonomy, phylogeny and phylogeographic relationships of selected sponge species. Xestospongia testudinaria & Neopetrosia exigua (Family Petrosiidae, Order Haplosclerida) were selected because of their conspicuousness in the Indo-Pacific coral reef ecosystems, whereby Xestospongia testudinaria is prominently known as the Indo-Pacific giant barrel sponge. Additionally, the order Haplosclerida has been described as an example of sponge order that has been examined systematically for a number of years and displays major discrepancy between morphology and molecular phylogenies. Molecular data suggests that the order needs revision at all taxonomic levels, which is the cause for further conflicts between taxonomists and systematists. In my research I focused mostly on sponge samples that originated from South East Asia or the Indo-Australian Archipelago (IAA). This region represents one of the best-explored marine regions in the Indo-Pacific. The aim of my research is to discover to what extent molecular tools are suitable to detect a phylogenetic signal, a phylogeographical break or a genotypic difference in the two selected sponge taxa. Several markers from the mitochondrial (mtDNA), ribosomal (rRNA) and nuclear (nucDNA) have been utilised. The 3' partition of the cytochrome oxidase subunit 1 (I3-M11 of cox1) from the mtDNA could be used to detect a genetic structure in Xestospongia testudinaria in a geographical narrow scale study of < 200 km2 in Lembeh, North Sulawesi, Indonesia (Chapter 6) and throughout the Indo-Pacific despite limitations in the sample datasets (Chapter 2). In addition, the presence of a species complex in X. testudinaria was detected with the aid of phylogenetic reconstructions from a concatenation of mtDNA sequences (I3-M11 of cox1 and the Adenosine Triphosphate Synthase F0 subunit 6 / ATP6), and a nucDNA marker, the Adenosine Triphosphate Synthase β subunit intron (ATPS-β intron) (Chapter 6). At the same time, the presence of a species complex in X. testudinaria was recognised in a broader scale study of the Indo-Australian Archipleago (IAA) (Chapter 3). As a result, selected mtDNA and nucDNA markers in this thesis are useful for the investigation of the taxonomical status and phylogeographical relationships of X. testudinaria. A phylogeographical break in the IAA region due to the Pleistocene low sea level and Holocene recolonisation events (Chapter 3) could not be recovered among X. testudinaria in a phylogeographical analysis. Similarly, overlapping I3-M11 cox1 haplotypes between X. testudinaria, X. muta and X. bergquistia were recovered. This might be due to the presence of ancient polymorphisms on the barrel sponge mtDNA markers. Molecular tools are also used to help identifying my second selected sponge species (Chapter 4). The use of selected cox2 mtDNA and 28S rRNA markers contributed significantly to the identification of. Neopetrosia exigua used to be a congeneric of X. testudinaria. During my examinations of self-collected and holotype specimens I discovered that the species named N. exigua bears a wrong name. For this reason, a taxonomical revision is suggested and, more importantly, according to my findings and the principle of priority in the ICZN (International Code of Zoological Nomenclature) I use the species name ‘chaliniformis’ instead of the species name ‘exigua’. Furthermore, the use of selected nucDNA marker, the Lysidyl Aminoacyl Transfer RNA Synthetase (LTRS) intron, also contributes to the detection of phylogeographical breaks in N. chaliniformis of the IAA (Chapter 5). In a nutshell, the success of unravelling sponge taxonomies, phylogenies, and phylogeographic relationships always depends on the suitability of the utilised molecular markers and the significance of environmental influences on the sponges. Haplosclerid sponges possess limited morphological features. These hurdles create several problems, e.g. difficulties with taxa delimitation and unresolved phylogeography relationships. Even though the application of molecular techniques generated some limitations and obstacles in these studies, it has already contributed significantly to a better understanding of the phylogenies, phylogeographic relationships and taxonomical problems of X. testudinaria and N.chaliniformis, the species I selected for my research

Physical and Mental Health Interventions in a Rural, School-Based Setting: A comparative analysis of academic performance, behavioral outcomes, and attendance

Abstract The purpose of this study was to determine the differences in academic achievement, behavioral health outcomes and attendance in poor, rural children receiving physical and mental health services regularly as opposed to those children not receiving the intervention. The intervention was a school-based health and mental health clinic located on the school’s campus. This study was analyzed by providing descriptive information for several variables including the number of suspensions per year, number of times corporal punishment was used as a means of correction, educational outcomes, total number of clinic visits per year, attendance percentages per year, and number of teacher and parent referrals to the school clinic. Data for this study were presented in multiple charts and graphs and schools are compared using descriptive information. The results suggested that as the number of clinic visits increased across the three year period, the numbers of, and rates of, corporal punishment in the clinic school decreased. In contrast, the available data suggested that across the first two years the numbers of, and rates of, corporal punishment increased in the control school. Further, in the majority of subject areas, the percentage of students’ proficiency levels in the clinic school increased across time and the percentages exceeded these in the control school. These findings were consistent with the hypotheses that there will be improvements in the behavioral outcomes associated with the presence of the clinic in the school. Unfortunately there were not enough data to conduct a test of statistical significance of the differences between schools for the third year

An exploration of homeostatic plasticity in musculoskeletal pain

The brain has a remarkable capacity to reorganise itself through life. When changes occur at a cellular level between neurons, this is known as synaptic plasticity. Synaptic plasticity has been proposed to be a key mechanism underpinning the learning and memory formation that occurs following afferent input (i.e., incoming stimuli from movement and sensation). However, synaptic plasticity in the human brain follows a positive loop cycle where incoming stimuli can lead to excessive synaptic strengthening (long-term potentiation; LTP) or weakening (long-term depression; LTD). To prevent overexpression of LTP or LTD, regulatory mechanisms termed ‘homeostatic plasticity’ promote stability during synaptic plasticity. A large body of evidence suggests that short- or long-term changes to synaptic plasticity takes place following afferent input. Similarly, evidence also suggests synaptic plasticity is altered in individuals experiencing incoming stimuli that are painful. However, no study has examined homeostatic plasticity during pain. Published studies that have examined homeostatic plasticity in individuals with pathology have been conducted in neurological conditions such as writer’s cramp, and chronic migraine. These studies provide preliminary evidence that impaired homeostatic plasticity is associated with altered synaptic plasticity with patients displaying abnormally high primary motor cortex (M1) excitability, altered cortical organisation, increased pain perception, and sensorimotor dysfunction. As altered synaptic plasticity and similar clinical features have been observed in individuals with chronic musculoskeletal pain, it is possible that homeostatic plasticity is impaired during pain. Thus, the broad goal of this thesis was to explore the effect of pain, using a clinical chronic musculoskeletal pain population and an experimental pain model, on homeostatic plasticity in the M1. To address this broad goal, three primary research studies were conducted

Genetic and functional analyses point to FAN1 as the source of multiple Huntington Disease modifier effects

A recent genome-wide association study of Huntington’s disease (HD) implicated genes involved in DNA maintenance processes as modifiers of onset, including multiple genome-wide significant signals in a chr15 region containing the DNA repair gene FAN1. Here, we have carried out detailed genetic, molecular and cellular investigation of the modifiers at this locus. We find that missense changes within or near the DNA binding domain (p.Arg507His and p.Arg377Trp) reduce FAN1's DNA binding activity and its capacity to rescue mitomycin C-induced cytotoxicity, accounting for two infrequent onset-hastening modifier signals. We also identified a third onset-hastening modifier signal whose mechanism of action remains uncertain but does not involve an amino acid change in FAN1. We present additional evidence that a frequent onset-delaying modifier signal does not alter FAN1 coding sequence but is associated with increased FAN1 mRNA expression in the cerebral cortex. Consistent with these findings and other cellular overexpression/suppression studies, knock out of FAN1 increased CAG repeat expansion in HD induced pluripotent stem cells. Together, these studies support the process of somatic CAG repeat expansion as a therapeutic target in HD, and clearly indicate that multiple genetic variations act by different means through FAN1 to influence HD onset in a manner that is largely additive, except in the rare circumstance that two onset-hastening alleles are present. Thus, an individual’s particular combination of FAN1 haplotypes may influence their suitability for HD clinical trials, particularly if the therapeutic agent aims to reduce CAG repeat instability

MULTIVARIATE MODELING OF COGNITIVE PERFORMANCE AND CATEGORICAL PERCEPTION FROM NEUROIMAGING DATA

State-of-the-art cognitive-neuroscience mainly uses hypothesis-driven statistical testing to characterize and model neural disorders and diseases. While such techniques have proven to be powerful in understanding diseases and disorders, they are inadequate in explaining causal relationships as well as individuality and variations. In this study, we proposed multivariate data-driven approaches for predictive modeling of cognitive events and disorders. We developed network descriptions of both structural and functional connectivities that are critical in multivariate modeling of cognitive performance (i.e., fluency, attention, and working memory) and categorical perceptions (i.e., emotion, speech perception). We also performed dynamic network analysis on brain connectivity measures to determine the role of different functional areas in relation to categorical perceptions and cognitive events. Our empirical studies of structural connectivity were performed using Diffusion Tensor Imaging (DTI). The main objective was to discover the role of structural connectivity in selecting clinically interpretable features that are consistent over a large range of model parameters in classifying cognitive performances in relation to Acute Lymphoblastic Leukemia (ALL). The proposed approach substantially improved accuracy (13% - 26%) over existing models and also selected a relevant, small subset of features that were verified by domain experts. In summary, the proposed approach produced interpretable models with better generalization.Functional connectivity is related to similar patterns of activation in different brain regions regardless of the apparent physical connectedness of the regions. The proposed data-driven approach to the source localized electroencephalogram (EEG) data includes an array of tools such as graph mining, feature selection, and multivariate analysis to determine the functional connectivity in categorical perceptions. We used the network description to correctly classify listeners behavioral responses with an accuracy over 92% on 35 participants. State-of-the-art network description of human brain assumes static connectivities. However, brain networks in relation to perception and cognition are complex and dynamic. Analysis of transient functional networks with spatiotemporal variations to understand cognitive functions remains challenging. One of the critical missing links is the lack of sophisticated methodologies in understanding dynamics neural activity patterns. We proposed a clustering-based complex dynamic network analysis on source localized EEG data to understand the commonality and differences in gender-specific emotion processing. Besides, we also adopted Bayesian nonparametric framework for segmentation neural activity with a finite number of microstates. This approach enabled us to find the default network and transient pattern of the underlying neural mechanism in relation to categorical perception. In summary, multivariate and dynamic network analysis methods developed in this dissertation to analyze structural and functional connectivities will have a far-reaching impact on computational neuroscience to identify meaningful changes in spatiotemporal brain activities