Asymmetrical Decoupling Model of Six-Phase Autotransformer and its Application

2011 ◽  
Vol 403-408 ◽  
pp. 4089-4093
Author(s):  
Lei Gao ◽  
Wei Ming Tong ◽  
Fan Gang Meng

In order to analyze the effect of asymmetry of phase-shift transformer on 12-pulse ac-dc converter, this paper sets up a decoupling model of delta-connected autotransformer. Via analyzing coupling circuit of autotransformer, the relation among branch voltage, branch current, node voltage and node current is built, and base on the relation, an admittance matrix containing the information about the connection way and electrical quantities is concluded. Utilizing the matrix, the proposed model is established. Simulation and experimental results show the validity of the model when simulating the asymmetry of delta-connected transformer

2020 ◽  
Vol 2020 (14) ◽  
pp. 305-1-305-6
Author(s):  
Tianyu Li ◽  
Camilo G. Aguilar ◽  
Ronald F. Agyei ◽  
Imad A. Hanhan ◽  
Michael D. Sangid ◽  
...  

In this paper, we extend our previous 2D connected-tube marked point process (MPP) model to a 3D connected-tube MPP model for fiber detection. In the 3D case, a tube is represented by a cylinder model with two spherical areas at its ends. The spherical area is used to define connection priors that encourage connection of tubes that belong to the same fiber. Since each long fiber can be fitted by a series of connected short tubes, the proposed model is capable of detecting curved long tubes. We present experimental results on fiber-reinforced composite material images to show the performance of our method.


2014 ◽  
Vol 04 (04) ◽  
pp. 1450035 ◽  
Author(s):  
Lin Zhang ◽  
Patrick Bass ◽  
Zhi-Min Dang ◽  
Z.-Y. Cheng

The equation ε eff ∝ (ϕc - ϕ)-s which shows the relationship between effective dielectric constant (εeff) and the filler concentration (φ), is widely used to determine the percolation behavior and obtain parameters, such as percolation threshold φc and the power constant s in conductor–dielectric composites (CDCs). Six different systems of CDCs were used to check the expression by fitting experimental results. It is found that the equation can fit the experimental results at any frequency. However, it is found that the fitting constants do not reflect the real percolation behavior of the composites. It is found that the dielectric constant is strongly dependent on the frequency, which is mainly due to the fact that the frequency dependence of the dielectric constant for the composites close to φc is almost independent of the matrix.


2011 ◽  
Vol 1 ◽  
pp. 375-380
Author(s):  
Shu Ai Wan ◽  
Kai Fang Yang ◽  
Hai Yong Zhou

In this paper the important issue of multimedia quality evaluation is concerned, given the unimodal quality of audio and video. Firstly, the quality integration model recommended in G.1070 is evaluated using experimental results. Theoretical analyses aide empirical observations suggest that the constant coefficients used in the G.1070 model should actually be piecewise adjusted for different levels of audio and visual quality. Then a piecewise function is proposed to perform multimedia quality integration under different levels of the audio and visual quality. Performance gain observed from experimental results substantiates the effectiveness of the proposed model.


The aim of this work is to introduce bacteria into the matrix of natural phosphate to catalyze the phenol oxidation in the wastewater.This electrode, designated subsequently by bacteria-NP-CPE, Showed stable response and was characterized with voltammeter methods, as cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and DRX. The experimental results revealed that the prepared electrode could be a feasible for degradation of hazardous phenol pollutants in the wastewater.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Bing Tang ◽  
Linyao Kang ◽  
Li Zhang ◽  
Feiyan Guo ◽  
Haiwu He

Nonnegative matrix factorization (NMF) has been introduced as an efficient way to reduce the complexity of data compression and its capability of extracting highly interpretable parts from data sets, and it has also been applied to various fields, such as recommendations, image analysis, and text clustering. However, as the size of the matrix increases, the processing speed of nonnegative matrix factorization is very slow. To solve this problem, this paper proposes a parallel algorithm based on GPU for NMF in Spark platform, which makes full use of the advantages of in-memory computation mode and GPU acceleration. The new GPU-accelerated NMF on Spark platform is evaluated in a 4-node Spark heterogeneous cluster using Google Compute Engine by configuring each node a NVIDIA K80 CUDA device, and experimental results indicate that it is competitive in terms of computational time against the existing solutions on a variety of matrix orders. Furthermore, a GPU-accelerated NMF-based parallel collaborative filtering (CF) algorithm is also proposed, utilizing the advantages of data dimensionality reduction and feature extraction of NMF, as well as the multicore parallel computing mode of CUDA. Using real MovieLens data sets, experimental results have shown that the parallelization of NMF-based collaborative filtering on Spark platform effectively outperforms traditional user-based and item-based CF with a higher processing speed and higher recommendation accuracy.


2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Qiang Sun ◽  
Yuebin Wu ◽  
Ying Xu ◽  
Liang Chen ◽  
Tae Uk Jang

Accurate simulation of cavitating flows in pipeline systems is important for cost-effective surge protection. However, this is still a challenge due to the complex nature of the problem. This paper presents a numerical model that combines the discrete vapor cavity model (DVCM) with the quasi-two-dimensional (quasi-2D) friction model to simulate transient cavitating flows in pipeline systems. The proposed model is solved by the method of characteristics (MOC), and the performance is investigated through a numerical case study formulated based on a laboratory pipeline reported in the literature. The results obtained by the proposed model are compared with those calculated by the classic one-dimensional (1D) friction model with the DVCM and the corresponding experimental results provided by the literature, respectively. The comparison shows that the pressure peak, waveform, and phase of pressure pulsations predicted by the proposed model are closer to the experimental results than those obtained by the classic 1D model. This demonstrates that the proposed model that combines the quasi-2D friction model with the DVCM has provided a solution to more accurately simulate transient cavitating flows in pipeline systems.


Author(s):  
G. P. Ong ◽  
T. F. Fwa ◽  
J. Guo

Hydroplaning on wet pavement occurs when a vehicle reaches a critical speed and causes a loss of contact between its tires and the pavement surface. This paper presents the development of a three-dimensional finite volume model that simulates the hydroplaning phenomenon. The theoretical considerations of the flow simulation model are described. The simulation results are in good agreement with the experimental results in the literature and with those obtained by the well-known hydroplaning equation of the National Aeronautics and Space Administration (NASA). The tire pressure–hydroplaning speed relationship predicted by the model is found to match well the one obtained with the NASA hydroplaning equation. Analyses of the results of the present study indicate that pavement microtexture in the 0.2- to 0.5-mm range can delay hydroplaning (i.e., raise the speed at which hydroplaning occurs). The paper also shows that the NASA hydroplaning equation provides a conservative estimate of the hydroplaning speed. The analyses in the present study indicate that when the microtexture of the pavement is considered, the hydroplaning speed predicted by the proposed model deviates from the speed predicted by the smooth surface relationship represented by the NASA hydroplaning equation. The discrepancies in hydroplaning speed are about 1% for a 0.1-mm microtexture depth and 22% for a 0.5-mm microtexture depth. The validity of the proposed model was verified by a check of the computed friction coefficient against the experimental results reported in the literature for pavement surfaces with known microtexture depths.


2019 ◽  
Vol 72 (1) ◽  
pp. 128-135 ◽  
Author(s):  
Hongxu Chen ◽  
Qin Yin ◽  
Guanhua Dong ◽  
Luofeng Xie ◽  
Guofu Yin

Purpose The purpose of this paper is to establish a stiffness model of fixed joint considering self-affinity and elastoplasticity of asperities. Design/methodology/approach The proposed model considers that asperities of different scales are interrelated rather than independent. For elastoplastic contact, a spring-damper model and an elastic deformation ratio function were proposed to calculate the contact stiffness of asperities. Findings A revised fractal asperity model was proposed to calculate the contact stiffness of fixed joint, the impacts of the fractal dimension, the fractal roughness parameter and the Meyer index on the contact stiffness were discussed, and the present experimental results and the Jiang’s experimental results showed that the stiffness can be well predicted by proposed model. Originality/value The contradiction between the Majumdar and Bhushan model and the Morag and Etsion model can be well explained by considering the interaction among asperities of different scales. For elastoplastic contact, elastic deformation ratio should be considered, and the stiffness of asperities increases first and then decreases with the increasing of interference.


2020 ◽  
Vol 34 (05) ◽  
pp. 7748-7755
Author(s):  
Zihao Fu ◽  
Lidong Bing ◽  
Wai Lam

Text generation tasks aim at generating human-readable text from different kinds of data. Normally, the generated text only contains the information included in the data and its application is thus restricted to some limited scenarios. In this paper, we extend the task to an open domain event text generation scenario with an entity chain as its skeleton. Specifically, given an entity chain containing several related event entities, the model should retrieve from a trustworthy repository (e.g. Wikipedia) the detailed information of these entities and generate a description text based on the retrieved sentences. We build a new dataset called WikiEvent1 that provides 34K pairs of entity chain and its corresponding description sentences. To solve the problem, we propose a wiki augmented generator framework that contains an encoder, a retriever, and a decoder. The encoder encodes the entity chain into a hidden space while the decoder decodes from the hidden space and generates description text. The retriever retrieves relevant text from a trustworthy repository which provides more information for generation. To alleviate the overfitting problem, we propose a novel random drop component that randomly deletes words from the retrieved sentences making our model more robust for handling long input sentences. We apply the proposed model on the WikiEvent dataset and compare it with a few baselines. The experimental results show that our carefully-designed architecture does help generate better event text, and extensive analysis further uncovers the characteristics of the proposed task.


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