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Research on temperature field and finite element modeling of high-speed gear shaft under parallel misalignment on wind turbine 6

Research on temperature field and finite element modeling of...

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6th international conference on Intelligent computing, Communication, and Devices, ICCD 2023

作者： Zhang, Guangjian Xiao, Yancai Tianjin University of Technology and Education Tute Tianjin China Beijing Jiaotong University Bjtu Beijing China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

High-speed (1761r/min∼2077r/min) gear shaft is an important transmission component of wind turbines. Its thermal characteristics have an important influence on the transmission power. therefore, in order to reduce the chance of wind turbines' failure, study on high-speed axle's temperature field is proposed at this paper based on transmission principle using heat transfer as well as method of finite element. this assembly model for wind turbines is firstly established in SolidWorks. then, analysis of high-speed shaft's temperature field is conducted with ADAMS simulation data that is input into Ansys workbench. the finite element model is established. Finally, the stress caused by temperature is superimposed to the mechanical stress. Simulation results show that with the increase of misalignment in high-speed shaft, the circumferential force on the gear shaft is also increasing. thus, the temperature is going up by inches. Deformation also increases. Analysis of gear shaft's temperature field has laid a foundation for the study of tooth surface bonding, gear bearing capacity, tooth modification and so on, it can also provide a basis for the future temperature prediction and fatigue life analysis. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Wind turbines

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Analysis of the photoelectric pluse spectra polarity effect of typical defects in SF6 gas 6

Analysis of the photoelectric pluse spectra polarity effect ...

引用

6th international conference on Intelligent computing, Communication, and Devices, ICCD 2023

作者： He, Nan Liu, Hongjing Liu, Hongliang Liu, Kewen State Grid Beijing Electric Power Research Institute 30 Nansanhuan Middle Road Fengtai District Beijing100075 China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

the polarity effect caused by the asymmetry and non-uniformity of electric field is one of the important basic characteristics of gas discharge, and the previous knowledge of polarity effect is mainly the differences of discharge initial voltage and electrical pulse statistical characteristics, while the lack of knowledge of the light emission characteristics and the "polarity effect"of photoelectric pulse accompanying the discharge. To better apply the optical detection and arc light monitoring in the SF6 gas insulated system and further improve the understanding of the photoelectric pulse polarity effect, this paper builds a set of SF6 partial discharge photoelectric simulation experimental system, and analyzes the multi-spectral photoelectric polarity effect by collecting the multi-spectral signals of insulator creepage and corona discharge with multi-spectral sensor. the research shows that there are significant differences of the amplitude and proportion of two type of discharges, among which the multispectral polarity effect of corona discharge is more obvious, with the rise of the applied voltage, the amplitude of multi-spectral signal along the surface discharge increases and the rate accelerates, while the rate of corona discharge slows down, and the proportion of UV band decreases for both discharge types, the proportion of visible band increases, and the infrared band remains low. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Sulfur hexafluoride

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Pomelo: Alternative Mechanism of threads Communication for Accelerating Convolution on SIMT Based Processor

Pomelo: Alternative Mechanism of Threads Communication for A...

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6th international conference on Intelligent computing and Signal Processing (ICSP)

作者： Zhenfu Feng Lele Yang Yaying Zhang Xi'an University of Posts and Telecommunications School of Engineering Xi'an China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Single Instruction Multiple thread (SIMT) based processor and parallel model are effective ways to solve computation problems exist in big data era. Commonly, work load is organized into mass parallel computing threads according the specific application. However, interaction and communication between parallel individual threads is inevitable during the whole computing process. In this work, 1) a SIMT based processor named Pomelo is developed, 2) a fundamental thread communication method based on shard memory is implemented, 3) communication avoiding mechanism for reducing the time cost of thread communication is studied, 4) and convolution based test set is adapted on Pomelo to verify the effectiveness of the proposed mechanism. Experimental result illustrates that Pomelo processor equipped with proposed mechanism achieves 2X performance augmentation on test sets based on convolution.

关键词： Costs Convolution Instruction sets Computational modeling parallel processing Big Data Data models Convolutional neural networks Load modeling

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An improvement of SAX representation for time series by using wavelet packet decomposition and FastDTW 23

An improvement of SAX representation for time series by usin...

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6th international conference on Big Data Technologies, ICBDT 2023

作者： Guo, Yonghua Zhu, Kai Cheng, Xu School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China School of Computing Xi'an Shiyou University Xi'an710065 China

ISBN: (纸本)9798400707667

Aiming at the shortcomings of conventional SAX that using the mean value as the eigenvalue may lead to misclassification, this paper comprehensively considers the numerical distribution difference and morphological fluctuation characteristics of time series data. Firstly, wavelet packet decomposition (WPD) can decompose various types of non-smooth random signals into wavelet components at different scales. Firstly, the WPD is used to extract the features of the time series, and then the Fast Dynamic Time Warping (FastDTW) is used to take advantage of the metrics, and the FastDTW metrics are applied to the features to define the global trend indicators. then, the SAX distance is combined with the trend distance, and an improved distance measure is proposed. Finally, the experimental results on different time series datasets show that the proposed method has the highest classification accuracy in 11 of the 20 datasets, which proves that the representation method proposed in the paper is significantly better than the original SAX representation and the improved SAX representation. © 2023 ACM.

关键词： Time series

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Fault Tolerance for Ensemble-based Molecular-Continuum Flow Simulations 23

Fault Tolerance for Ensemble-based Molecular-Continuum Flow ...

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6th international conference on High Performance computing in Asia-Pacific Region, HPC Asia 2023

作者： Jafari, Vahid Neumann, Philipp Helmut Schmidt University Chair for High Performance Computing Germany

ISBN: (纸本)9781450398060

Molecular dynamics (MD) simulations exhibit big computational efforts, which makes them very time-consuming. this particularly holds for molecular-continuum simulations in fluid dynamics, which rely on the simulation of MD ensembles that are coupled to computational fluid dynamics (CFD) solvers. Massively parallel implementations for MD simulations and the respective ensembles are therefore of utmost importance. However, the more processors are used for the molecular-continuum simulation, the higher the probability of software-and hardware-induced failures or malfunctions of one processor becomes, which may lead to the issue that the entire simulation crashes. To avoid long re-calculation times for the simulation, a fault tolerance mechanism is required, especially considering respective simulations carried out at the exascale. In this paper, we introduce a fault tolerance method for molecular-continuum simulations implemented in the macro-micro-coupling tool (MaMiCo), an open-source coupling tool for such multiscale simulations which allows the re-use of one's favorite MD and CFD solvers. the method makes use of a dynamic ensemble handling approach that has been used previously to estimate statistical errors due to thermal fluctuations in the MD ensemble. the dynamic ensemble is always homogeneously distributed and, thus, balanced on the computational resources to minimize the overall induced overhead overhead. the method further relies on an MPI implementation with fault tolerance support. We report scalability results with and without modeled system failures on three TOP500 supercomputers-Fugaku/RIKEN with ARM technology, Hawk/HLRS with AMD EPYC technology and HSUper/Helmut Schmidt University with Intel Icelake processors-to demonstrate the feasibility of our approach. © 2023 ACM.

关键词： Fault tolerance

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Large-scale parallel exact diagonalization algorithm of the Hubbard model on Tianhe-2 supercomputer 22

Large-scale parallel exact diagonalization algorithm of the ...

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6th international conference on High Performance Compilation, computing and Communications, HP3C 2022

作者： Li, Biao Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Hunan Changsha China

ISBN: (纸本)9781450396295

We propose a parallel exact diagonalization method for solving the large-scale Hubbard model. the core of this algorithm is the parallelization of the Lanczos algorithm, for which we propose a hierarchical communication model and a fast strategy for finding nonzero elements of large-scale matrix, starting only from the symmetry of Hamiltonian matrix. the effect of our parallel algorithm was tested on the Tianhe-2 supercomputer, where the strong scaling efficiency could reach 53% for 30,000 cores in a 140-billion dimensional matrix, and the weak scaling efficiency remained above 40% for 60,000 cores in a 730-billion dimensional matrix. © 2022 ACM.

关键词： parallel algorithms

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Automated Radiology Report Generation from Chest X-ray Scans Using Deep Learning 6th

Automated Radiology Report Generation from Chest X-ray Scans...

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6th international conference on Recent Innovations in computing, ICRIC 2023

作者： Veer, V. Druva Priya, S. Baghavathi Tamilselvi, M. Department of Computer Science and Engineering Amrita School of Computing AmritaVishwaVidyapeetham Chennai India Information Technology Department University of Technology and Applied Sciences Nizwa Oman

ISBN: (纸本)9789819778614

A chest X-ray is a common diagnostic tool for many thoracic illnesses. Interpreting these images and coming up with accurate diagnostic results is a difficult and time-consuming task for radiologists. Recent results using deep learning approaches to automate the analysis of chest X-rays are promising. this paper provides a comprehensive description of deep learning techniques used to chest X-ray processing for the diagnosis of several diseases, including TB, pneumonia, and COVID-19. this paper provide a summary of the primary deep learning architectures, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and attention models, that are used for disease classification, localization, segmentation, and report generation from chest X-rays. this paper also discuss explainability techniques that are used to offer transparency and increase trust in model predictions. Along with existing issues, future directions are taken into consideration, such as multimodal learning, few-shot learning, and model evaluation. this paper explains the model which takes less time and give the optimal results. In order to facilitate future research into developing AI systems that are more accurate, understandable, and advantageous from a medical standpoint, this article provides an overview of the most current developments in deep learning techniques for automated chest X-ray diagnosis. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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parallel Acceleration of Transportation Problem Solving Using SpMV in the Industrial Chain Context 25th

Parallel Acceleration of Transportation Problem Solving Usi...

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25th international conference on parallel and Distributed computing, Applications and Technologies, PDCAT 2024

作者： Dong, De Lin, Guanyu Xu, Yicheng Ma, Ruikang Xia, Chenliang Fan, Jianping Li, Fuchong Southern University of Science and Technology Guangdong Shenzhen China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China University of Chinese Academy of Sciences Beijing China Jinan Industrial Development Park Technology Development Co. Ltd. Shandong Jinan China

ISBN: (纸本)9789819642069

As modern industrial chains grow increasingly complex and time-sensitive, traditional transportation planning methods face efficiency bottlenecks. To address this, we propose a parallelization method based on Sparse Matrix-Vector Multiplication (SpMV) to accelerate the Transportation Simplex Algorithm (TSA) for large-scale transportation problems. Existing approaches primarily leverage data parallelism but underutilize GPU computational potential. this study transforms sequential algorithms into matrix-based representations, combining SpMV and parallel graph algorithms to enhance TSA performance. Key contributions include mapping performance bottlenecks—potential vector calculation and closed-loop search—onto SpMV operations, and converting branch logic into matrix operations to reduce divergence. Experiments on a 10000×10000 dataset demonstrate a 20.8x speedup for the parallelized MODI algorithm and a 28x overall speedup for solving the Transportation Problem, significantly improving efficiency. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph algorithms

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Using Deep Learning and Adaptive Window Adjustment to Facilitate the Detection of Pulmonary Edema Detection in Chest X-Rays 6

Using Deep Learning and Adaptive Window Adjustment to Facili...

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6th international conference on Digital Medicine and Image Processing, DMIP 2023

作者： Chiu, Yen-Jung Chuang, Chao-Chun Tang, Shih-Tsang Department of Biomedical Engineering Ming Chuan University Taiwan National Center for High-Performance Computing Taiwan

ISBN: (纸本)9798400709425

Cardiogenic pulmonary edema encompasses a diversity of subtypes, each of which requires specific treatment strategies. Physicians must have the ability to rapidly identify edema subtypes in medical images to achieve timely intervention and mitigate lung impairment. this study compared six supervised classification models pre-trained and tested using the MIMIC-CXR dataset in the identification of cardiogenic pulmonary edema subtypes. Note that the same analytic methods were consistently applied across the six parameter sets. Fine-tuning the windowing to L: 2500 and W: 3000 resulted in five AUC values that surpassed 0.8, despite the fact that this did not result in peak accuracy across all test data categories. the predictive accuracy for vascular congestion reached 90%, while that of interstitial and alveolar edema reached 96%. this research holds significant potential for the early diagnosis and targeted treatment of cardiogenic pulmonary edema to enhance the standard of patient care. © 2023 ACM.

关键词： Deep learning

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Configuring the parallel Committees Database Architecture through Bayesian Optimization

Configuring the Parallel Committees Database Architecture th...

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Blockchain computing and Applications (BCCA), international conference on

作者： Siamak Solat Ahmed Mabrouk Université Paris Cité (Formerly Known as Université de Paris) Paris France CSAI Lab CRIGEN ENGIE Group Stains France

ISBN: (数字)9798350351538

ISBN: (纸本)9798350351545

Distributed databases are often used when scalability, fault tolerance, and high availability are crucial. they excel in scenarios where traditional, centralized databases may struggle to handle the increasing volume of data or traffic. Common use cases include large-scale web applications, cloud computing environments, and systems requiring geographic distribution for improved performance and resilience. the "parallel Committees" architecture was recently proposed, designed, and published in [1] as an innovative and novel approach for distributed databases. the configuration of the parallel Committees architecture must be precisely tailored based on a set of input parameters. In this paper, we propose an approach to configure the parallel Committees database architecture through Bayesian optimization, aiming to identify the optimal parameter configuration for each specific use case.

关键词： Fault tolerance Cloud computing Scalability Fault tolerant systems Computer architecture Bayes methods Blockchains Optimization Resilience

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