Ryerson University

About: Ryerson University is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Computer science & Population. The organization has 7671 authors who have published 20164 publications receiving 394976 citations. The organization is also known as: Ryerson Polytechnical Institute & Ryerson Institute of Technology.

Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA

Abstract: Denitrification is an important net sink for NO3 − in streams, but direct measurements are limited and in situ controlling factors are not well known. We measured denitrification at multiple scales over a range of flow conditions and NO3 − concentrations in streams draining agricultural land in the upper Mississippi River basin. Comparisons of reach-scale measurements (in-stream mass transport and tracer tests) with local-scale in situ measurements (pore-water profiles, benthic chambers) and laboratory data (sediment core microcosms) gave evidence for heterogeneity in factors affecting benthic denitrification both temporally (e.g., seasonal variation in NO3 − concentrations and loads, flood-related disruption and re-growth of benthic communities and organic deposits) and spatially (e.g., local stream morphology and sediment characteristics). When expressed as vertical denitrification flux per unit area of streambed (U denit, in μmol N m−2 h−1), results of different methods for a given set of conditions commonly were in agreement within a factor of 2–3. At approximately constant temperature (~20 ± 4°C) and with minimal benthic disturbance, our aggregated data indicated an overall positive relation between U denit (~0–4,000 μmol N m−2 h−1) and stream NO3 − concentration (~20–1,100 μmol L−1) representing seasonal variation from spring high flow (high NO3 −) to late summer low flow (low NO3 −). The temporal dependence of U denit on NO3 − was less than first-order and could be described about equally well with power-law or saturation equations (e.g., for the unweighted dataset, U denit ≈26 * [NO3 −]0.44 or U denit ≈640 * [NO3 −]/[180 + NO3 −]; for a partially weighted dataset, U denit ≈14 * [NO3 −]0.54 or U denit ≈700 * [NO3 −]/[320 + NO3 −]). Similar parameters were derived from a recent spatial comparison of stream denitrification extending to lower NO3 − concentrations (LINX2), and from the combined dataset from both studies over 3 orders of magnitude in NO3 − concentration. Hypothetical models based on our results illustrate: (1) U denit was inversely related to denitrification rate constant (k1denit, in day−1) and vertical transfer velocity (v f,denit, in m day−1) at seasonal and possibly event time scales; (2) although k1denit was relatively large at low flow (low NO3 −), its impact on annual loads was relatively small because higher concentrations and loads at high flow were not fully compensated by increases in U denit; and (3) although NO3 − assimilation and denitrification were linked through production of organic reactants, rates of NO3 − loss by these processes may have been partially decoupled by changes in flow and sediment transport. Whereas k1denit and v f,denit are linked implicitly with stream depth, NO3 − concentration, and(or) NO3 − load, estimates of U denit may be related more directly to field factors (including NO3 − concentration) affecting denitrification rates in benthic sediments. Regional regressions and simulations of benthic denitrification in stream networks might be improved by including a non-linear relation between U denit and stream NO3 − concentration and accounting for temporal variation.

Online Detection of Broken Rotor Bars in Induction Motors by Wavelet Packet Decomposition and Artificial Neural Networks

Abstract: We present an algorithm for the online detection of rotor bar breakage in induction motors through the use of wavelet packet decomposition (WPD) and neural networks. The system provides a feature representation of multiple frequency resolutions for faulty modes and accurately differentiates between healthy and faulty conditions, and its main applicability is to dynamic time-variant signals experienced in induction motors during run time. The algorithm analyzes rotor bar faults by WPD of the induction motor stator current. The extracted features with different frequency resolutions, together with the slip speed, are then used by a neural network trained for the detection of faults. The experimental results show that the proposed method is able to detect the faulty conditions with high accuracy.

Bringing Translation Out of the Shadows: Translation as an Issue of Methodological Significance in Cross-Cultural Qualitative Research

Abstract: Translation is an integral component of cross-cultural research that has remained invisible. It is commonly assumed that translation is an objective and neutral process, in which the translators are “technicians” in producing texts in different languages. Drawing from the field of translation studies and the findings of a translation exercise conducted with three bilingual Cantonese-English translators, the authors highlight some of the methodological issues about translation in cross-cultural qualitative research. They argue that only by making translation visible and through open dialogue can researchers uncover the richness embedded in the research data and facilitate multiple ways of knowing.

High-Step-Up and High-Efficiency Fuel-Cell Power-Generation System With Active-Clamp Flyback–Forward Converter

Abstract: A high-efficiency fuel-cell power-generation system with an active-clamp flyback-forward converter is presented in this paper to boost a 12-V dc voltage into a 220-V 50-Hz ac voltage. The proposed system includes a high-efficiency high-step-up interleaved soft-switching flyback-forward converter and a full-bridge inverter. The front-end active-clamp flyback-forward converter has the advantages of zero-voltage-switching performance for all the primary switches, reverse-recovery-problem alleviation for the secondary output diodes, large voltage-conversion ratio, and small input-current ripple. Furthermore, there are two coupled inductors in the proposed converter. Each coupled inductor can work in the flyback mode when the corresponding main switch is in the turn-on state and in the forward mode when it is in the turnoff state, which takes full use of the magnetic core and improves the power density. In addition, the full-bridge inverter with an LC low-pass filter is adopted to provide low-total-harmonic-distortion ac voltage to the load. Therefore, high-efficiency and high-power-density conversion can be achieved in a wide input-voltage range by employing the proposed system. Finally, a 500-W prototype and another 1-kW converter are implemented and tested to verify the effectiveness of the proposed system.

A New Duty Cycle Control Strategy for Power Factor Correction and FPGA Implementation

Abstract: The bottleneck of digital control for power factor correction (PFC) implementations is mainly due to three aspects: high calculation requirements, high cost, and limited switching frequency compared with analog implementations. A new duty cycle control strategy for boost PFC implementations is proposed in this paper. The duty cycle is determined based on the input voltage, reference output voltage, inductor current, and reference current. The duty cycle determination algorithm includes two terms, the current term and the voltage term, which can be calculated in parallel and requires only one multiplication and three additions (subtractions) operations in digital implementation. A 400-kHz switching frequency boost PFC based on field programmable gate array implementation and its test results show that the proposed new duty cycle control strategy has great potential in the next generation of high switching frequency PFC implementations, due to its lower calculation requirement, lower cost, and better performance than the conventional PFC control methods