An Online Non-Invasive Condition Monitoring Method for Stepping Motor CRDM in HTGR

Control Rod Drive Mechanism (CRDM) based on stepping motor is one of the components applied in High Temperature Gas Coold Reactor (HTGR) to control the reactivity as well as to maintain the safety of reactor. The stepping motor requires a unique condition monitoring to avoid any failures especially due to the specific environments of CRDM in HTGR such as the allowable of high temperature, high radiation and the location of stepper motor inside a pressure shell. This research aims to demonstrate an online non-invasive condition monitoring method without direct access to the CRDM of HTGR based on voltage and stator current measurements. A simple stepping motor CRDM simulator is employed. The online condition monitoring is carried out by direct pattern matching of the output signals of logic generator block and the output signals of motor driver. The online method utilizes signature patterns of voltage and stator current signals of the healthy motor as a baseline for healthy motor. In addition, the method is applied to detect high-resistance problem on the connector between the motor driver block and the stepper motor to show the effectiveness and the applicability of this method. The online condition monitoring system demonstrates a capability to identify a minimum detectable simulated high-resistance for about 2.9% which decreases the measured stator current and motor’s torque for around 5.1% and 3.3%, respectively. The paper also points out signatures of healthy motor, including mutual inductions of the motor’s winding in voltage and current measurement which can be used as the fault symptom indicators for online monitoring purposes.Received: 19 November 2014; Revised: 13 April 2016; Accepted: 22 June 201

Reducing iron loss in interior PM machines under field-weakening conditions

Field-weakening in interior PM machines is performed by using negative rf-axis current to oppose the magnet flux and hence reduce the total fundamental rf-axis flux at high speeds. Due to the rotor saliency, the rf-axis current produces large amplitude harmonic airgap flux density components which can cause large harmonic stator iron losses. Reducing the magnet flux density reduces the required rf-axis stator mmf to oppose it and hence reduces the field-weakening iron losses. However reducing the magnet flux density also reduces the magnet torque and hence increases the stator current requirement, particularly at lower speeds. This paper examines this trade-off for an automotive integrated starter/alternator using a graphical interior PM machine parameter plane approach.W.L. Soong, S.H. Han, T.M. Jahns and N. Ertugru

Nonlinear Time-History Analysis of Soil-Structure Systems Incorporating Frequency-Dependent Impedance Functions

To accurately analyze structures, soil-structure interaction effects must be taken into account. One approach is to create a complete finite element model of the full system wherein the soil is represented as a semi-infinite domain. This direct method is frequently adopted in research studies, but it is typically avoided in engineering practice due to the labor-intensive model development, and the high computational cost. In practice, soil-structure interaction analysis is mostly carried out through a substructure approach where the superstructure is modeled through a detailed model and is placed on a soil-foundation substructure which is represented by a system called impedance function. Then, the entire system is analyzed under foundation input motions. While the method is theoretically designed for linear-elastic behavior, it can be partially applied to nonlinear systems too. Although impedance functions for various soil and foundation configurations can be obtained from analytical, numerical, or experimental analyses, their implementation in the time-domain is not trivial because they are frequency-dependent. A simple solution for this problem has been to convert them to some physical models with frequency-independent components, but there is no straightforward way to connect these components. More importantly, the coefficients of these components could be non-physical parameters that cannot be modeled in software like OpenSEES. To resolve these problems, various alternative approaches have been proposed in the literature. In this project, we review some of the existing solutions and verify them through numerical examples. After extensive review and evaluation, the Hybrid Time Frequency Domain method seems a more practical solution with fewer stability issues. This method is implemented in Opensees to be used by researchers and practitioners

Pyrolysis Mass Spectrometric Analysis of styrene butadiene block and random copolymers

Cataloged from PDF version of article.Direct pyrolysis mass spectrometric analysis of a styrene-butadiene-styrene block copolymer indicated that thermal decomposition of each block shows a resemblance to the related homopolymer, giving a possibility of differentiation of blocks. However, the random analog, the styrene butadiene rubber, degraded in a manner that is somewhat in between in nature of the thermal characteristics of both homopolymers. This technique shows promise to differentiate thermal behaviors of each sequence in block polymers if any exist. Indirect pyrolysis mass spectrometric analysis gave no clear evidence for differentiation of the nature and the composition of the copolymers. © 1997 Elsevier Science Ltd. All rights reserved

Estimation of PM Machine Efficiency Maps from Limited Data

This article investigates the accuracy of the estimation of efficiency maps for permanent magnet (PM) machines using the stator resistance, d- and q-axis flux-linkages versus the corresponding axis current and the iron loss versus the speed characteristic. The ultimate goal is to apply this approach to the experimental measurements, but this article performs initial investigation using only the finite-element (FE) data. Detailed FE data for 50-kW surface PM (SPM) and interior PM (IPM) machines are used to determine the 'actual' or exact efficiency map and, hence, the accuracy of using approximations. This article examines the effect on the torque-speed capability curve when ignoring cross-saturation effects. It also examines the modeling of the variation of iron losses as a function of load in the constant torque and power regions. A novel approach based on scaling the no-load (NL) losses as a function of load is proposed and shown to give promising results. FE results from two other machines are also provided, which show good correspondence

CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting

Opioid overdose is a growing public health crisis in the United States. This crisis, recognized as "opioid epidemic," has widespread societal consequences including the degradation of health, and the increase in crime rates and family problems. To improve the overdose surveillance and to identify the areas in need of prevention effort, in this work, we focus on forecasting opioid overdose using real-time crime dynamics. Previous work identified various types of links between opioid use and criminal activities, such as financial motives and common causes. Motivated by these observations, we propose a novel spatio-temporal predictive model for opioid overdose forecasting by leveraging the spatio-temporal patterns of crime incidents. Our proposed model incorporates multi-head attentional networks to learn different representation subspaces of features. Such deep learning architecture, called "community-attentive" networks, allows the prediction of a given location to be optimized by a mixture of groups (i.e., communities) of regions. In addition, our proposed model allows for interpreting what features, from what communities, have more contributions to predicting local incidents as well as how these communities are captured through forecasting. Our results on two real-world overdose datasets indicate that our model achieves superior forecasting performance and provides meaningful interpretations in terms of spatio-temporal relationships between the dynamics of crime and that of opioid overdose.Comment: Accepted as conference paper at ECML-PKDD 201

Arteries get confused: an arch variation

We present a case of an arch anomaly in a 54-year-old female who was admitted to our hospital for magnetic resonance angiography (MRA) to evaluate her right-sided numbness. MRA revealed a truncus bicaroticus, right common carotid artery (CCA) originating right vertebral artery, right subclavian artery arising as the final branch of the descending aortic arch and arch originating left vertebral artery. The possible embryologic mechanism and clinical importance of this previously unreported variant are reviewed