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Analysis of generalized compressor characteristics on surge phenomena in axial compressors

Journal of Computational and Applied Research in Mechanical engineering 2021年第2期10卷 337-344页

作者： Maqsood, Adnan Tareen, Muhammad Kamran Khan Riaz, Rizwan Dala, Laurent Research Center for Modeling and Simulation National University of Sciences and Technology H–12 Campus Islamabad44000 Pakistan Department of Mechanical & Construction Engineering Northumbria University Newcastle United Kingdom

The paper discusses the effect of compressor characteristic on surge phenomena in axial flow compressors. Specifically, the effect of nonlinearities on the compressor dynamics is analyzed. For this purpose, generalized multiple time scales method is used to parameterize equations in amplitude and frequency explicitly. The pure surge case of the famous Moore-Greitzer model is used as the basis of the study. The compressor characteristic used in the Moore-Greitzer model is generalized to evaluate the effect of the parameters involved. Subsequently, bifurcation theory is used to study the effect of nonlinear dynamics on surge behavior. It has been found that the system exhibits supercritical Hopf bifurcation under specific conditions in which surge manifests as limit cycle oscillations. Key parameters have been identified in the analytical solution which govern the nonlinear dynamic behavior and are responsible for the existence of limit cycle oscillations. Numerical simulations of the Moore-Greitzer model are carried out and found to be in good agreement with the analytical solution. © 2021 The author(s).

关键词： Hopf bifurcation

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Lagrangian eddies in the Northwestern Pacifi c Ocean

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Journal of Oceanology and Limnology 2022年第1期40卷 66-77页

作者： Qiu HE Fenglin TIAN Xiaokun YANG Ge CHEN Department of Marine Technology College of Information Science and EngineeringOcean University of ChinaQingdao 266100China Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao 266237China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034China

The Lagrangian eddies in the western Pacifi c Ocean are identifi ed and analysed based on Maps of Sea Level Anomaly(MSLA)data from 1998 to *** calculating the Lagrangian eddy advected by the AVISO velocity fi eld,we analyzed the variations in Lagrangian eddies and the average transport eff ects on diff erent time *** introducing the Niño coeffi cient,the lag response of the Lagrangian eddy to El Niño is *** data are helpful to further explore the role of mesoscale eddies in ocean energy *** normalized chlorophyll data,we observed chlorophyll aggregation and hole eff ects caused by Lagrangian *** fi ndings demonstrate the important role of Lagrangian eddies in material *** transportation volume of the Lagrangian eddy is calculated quantitatively,and several major transport routes have been identifi ed,which helps us to more accurately and objectively estimate the transport capacity of Lagrangian eddies in the western Pacifi c Ocean.

关键词： Lagrangian coherent structure(LCS) mesoscale eddy distribution character material transport

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Efference information flow during skill acquisition mediates its interaction with medical simulation technology

Efference information flow during skill acquisition mediates...

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Clinical and Translational Biophotonics, Translational 2022

作者： Kamat, Anil Intes, Xavier De, Suvranu Dutta, Anirban Center for Modeling Simulation and Imaging in Medicine Rensselaer Polytechnic Institute TroyNY United States Neuroengineering and Informatics for Rehabilitation Laboratory Department of Biomedical Engineering University at Buffalo BuffaloNY United States

We employed portable optical neuroimaging technology and the Granger causality approach to uncover the impact of the two medical simulation technologies on the directed functional brain network of the subjects with tw... 详细信息

ISBN: (纸本)9781557528209

关键词： Neuroimaging

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Probabilistic Multi-Objective Optimal Power Flow: A Grey Wolf Optimizer Approach Considering Load and Wind Turbine Uncertainties

Probabilistic Multi-Objective Optimal Power Flow: A Grey Wol...

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Canadian Conference on Electrical and Computer engineering (CCECE)

作者： Shiva Amini Innocent Kamwa Shabbo Nahvi Hêmin Golpîra Department of Electrical and Computer Science Engineering Laval University Quebec Canada Department of Electrical and Computer Engineering University of Kurdistan Sanandaj Iran Department of Electrical and Computer Engineering Power Systems Modeling & Simulation Lab University of Kurdistan Sanandaj Iran

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

This article presents a novel approach to tackle the challenge of Probabilistic Multi-Objective Optimal Power Flow (PMOOPF) by utilizing the Grey Wolf Optimizer (GWO). The methodology incorporates uncertainties related to both load and wind turbine generation, modeling load uncertainty with a normal distribution and wind speed uncertainty with a Weibull distribution and employs Monte Carlo simulation (MCS) to establish the probability distribution function (PDF) for both the load and power generated by the hybrid sources. The PMOOPF problem aims to concurrently minimize thermal generation costs, real power losses, and maximize voltage stability. The proposed approach is tested on the IEEE 26-bus system, and the outcomes are compared with the Gravitational Search Algorithm (GSA). The contribution of this paper lies in effectively addressing uncertainties in load and wind turbine generation, incorporating diverse PMOOPF objectives, and employing the GWO optimization technique. The simulation results demonstrate the method's efficacy and efficiency in achieving economic and technical benefits.

关键词： Uncertainty Costs Wind speed Voltage Probabilistic logic Stability analysis Wind turbines

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Real-Time Vehicle Detection And Urban Traffic Behavior Analysis Based On Uav Traffic Videos On Mobile Devices

arXiv

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arXiv 2024年

作者： Zhu, Yuan Wang, Yanqiang An, Yadong Yang, Hong Pan, Yiming Inner Mongolia Center for Transportation Research Inner Mongolia University Hohhot China Department of Computational Modeling and Simulation Engineering Old Dominion University Norfolk United States

This paper focuses on a real-time vehicle detection and urban traffic behavior analysis system based on Unmanned Aerial Vehicle (UAV) traffic video. By using UAV to collect traffic data and combining the YOLOv8 model and SORT tracking algorithm, the object detection and tracking functions are implemented on the iOS mobile platform. For the problem of traffic data acquisition and analysis, the dynamic computing method is used to process the performance in real time and calculate the micro and macro traffic parameters of the vehicles, and real-time traffic behavior analysis is conducted and visualized. The experiment results reveals that the vehicle object detection can reach 98.27% precision rate and 87.93% recall rate, and the real-time processing capacity is stable at 30 frames per seconds. This work integrates drone technology, iOS development, and deep learning techniques to integrate traffic video acquisition, object detection, object tracking, and traffic behavior analysis functions on mobile devices. It provides new possibilities for lightweight traffic information collection and data analysis, and offers innovative solutions to improve the efficiency of analyzing road traffic conditions and addressing transportation issues for transportation authorities. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Exergy cost assessment of Very High Gravity (VHG) Fermentation in the sugarcane industry 36

Exergy cost assessment of Very High Gravity (VHG) Fermentati...

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36th International Conference on Efficiency, Cost, Optimization, simulation and Environmental Impact of Energy Systems, ECOS 2023

作者： Palacios-Bereche, Milagros Cecilia Palacios-Bereche, Reynaldo Gallego, Antonio Garrido Serra, Luis M. Lozano, Miguel A. Nebra, Silvia Azucena Energy Engineering Modeling and Simulation Laboratory Federal University of ABC S.P. Santo André Brazil Federal University of ABC SP Santo André Brazil GITSE-I3A Department of Mechanical Engineering Universidad de Zaragoza Spain University of Campinas S. P. Campinas Brazil

ISBN: (纸本)9781713874928

The vinasse, produced as the bottom product of the distillation column of the ethanol production process, is the main liquid residue of this industry, whose disposition represents a problem for the industry because of its high production rate, which ranges from 10 to 15 litres of vinasse per litre of ethanol produced. In this way, the evaluation of technologies that could reduce the vinasse volume-either reducing its production during ethanol production process or its volume once already produced-is advantageous to the process and its sustainability, seeing as a lower amount of vinasse would allow a better and appropriate disposal of this effluent. This way, this work addresses the vinasse problem by a preliminary exergy cost analysis of two different technologies for vinasse volume reduction and a Base Case for comparison purposes;being the analysed cases: i) a Base Case (conventional production process), ii) the introduction of the VHG (Very High Gravity) fermentation with the use of ejectors as complementary refrigeration system, aiming at utilising a more concentrated most during fermentation to produce a wine with a higher ethanol content, thus reducing the amount of vinasse produced in the distillation step. The analysis aims at comparing the unitary exergy costs of the main products and by-products of the different alternatives, and identifying the processes with the highest irreversibilities associated, which resulted in the fermentation with distillation volume control, with values of 37.1% and 41%, for the conventional and VHG cases, respectively. © (2023) by ECOS 2023 All rights reserved.

关键词： Fermentation

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Multi-modal Speech Emotion Recognition: Improving Accuracy Through Fusion of VGGish and BERT Features with Multi-head Attention 1

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9th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2023

作者： Tran, Phuong-Nam Vu, Thuy-Duong Thi Dang, Duc Ngoc Minh Pham, Nhat Truong Tran, Anh-Khoa Computing Fundamental Department FPT University Ho Chi Minh City Viet Nam Department of Integrative Biotechnology Sungkyunkwan University Suwon Korea Republic of Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam

ISBN: (数字)9783031473593

ISBN: (纸本)9783031473586

Recent research has shown that multi-modal learning is a successful method for enhancing classification performance by mixing several forms of input, notably in speech-emotion recognition (SER) tasks. However, the difference between the modalities may affect SER performance. To overcome this problem, a novel approach for multi-modal SER called 3M-SER is proposed in this paper. The 3M-SER leverages multi-head attention to fuse information from multiple feature embeddings, including audio and text features. The 3M-SER approach is based on the SERVER approach but includes an additional fusion module that improves the integration of text and audio features, leading to improved classification performance. To further enhance the correlation between the modalities, a LayerNorm is applied to audio features prior to fusion. Our approach achieved an unweighted accuracy (UA) and weighted accuracy (WA) of 79.96% and 80.66%, respectively, on the IEMOCAP benchmark dataset. This indicates that the proposed approach is better than SERVER and recent methods with similar approaches. In addition, it highlights the effectiveness of incorporating an extra fusion module in multi-modal learning. © 2023, © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Modal analysis

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Multi-Objective Model-Predictive Control for Dielectric Elastomer Wave Harvesters

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IFAC-PapersOnLine 2023年第2期56卷 7802-7807页

作者： Matthias K. Hoffmann Lennart Heib Gianluca Rizzello Giacomo Moretti Kathrin Flaßkamp Systems Modeling and Simulation Saarland University Saarbrücken Germany Adaptive Polymer Systems Saarland University Saarbrücken Germany Department of Industrial Engineering Università di Trento Italy

This contribution deals with multi-objective model-predictive control (MPC) of a wave energy converter (WEC) device concept, which can harvest energy from sea waves using a dielectric elastomer generator (DEG) power take-off system. We aim to maximise the extracted energy through control while minimising the accumulated damage to the DEG. With reference to system operation in stochastic waves, we first generate ground truth solutions by solving an optimal control problem, comparing it to the performance of MPC to determine a prediction horizon that trades off accuracy and efficiency for computation. Fixed weights in the MPC scheme can produce unpredictable costs for variable sea conditions, meaning the average rate of cost accumulation can vary vastly. To steer this cost growth, we propose a heuristic to adapt the algorithm by changing the weighting of the cost functions for fulfilling the long-time goal of accumulating a small enough damage in a fixed time. A simulated case-study is presented in order to evaluate the performance of the proposed MPC framework and the weight-adaptation algorithm. The proposed heuristic proves to be able to limit the amount of accumulated damage while improving the energy yield obtained with a comparable fixed-weight MPC.

关键词： Optimal Control Multi-objective Model-predictive Control Energy Harvesting Non-Linear Optimization Dielectric Elastomer Generators

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Adisutjipto Institute of Aerospace Technology Virtual Tour with Artificial Intelligence (AI) Agent 1

Adisutjipto Institute of Aerospace Technology Virtual Tour w...

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1st International Conference of Adisutjipto on Aerospace Electrical engineering and Informatics, ICAAEEI 2024

作者： Ayuningtyas, Astika Wahyudi Sumari, Arwin Datumaya Aryanto, Salam Nuryatno, Edi Triono Mulyani, Sri Kusumaningrum, Anggraini Adisutjipto Institute of Aerospace Technology Aerospace Intelligent Systems and Data Engineering Research Group Faculty of Industrial Technology Yogyakarta Indonesia Department of Electrical Engineering Malang Indonesia Adisutjipto Institute of Aerospace Technology Aerospace Modeling and Simulation Research Group Faculty of Industrial Technology Yogyakarta Indonesia The University of Western Australia Uwa Centre for Medical Research Perth Australia Adisutjipto Institute of Aerospace Technology Faculty of Aerospace Engineering Technology Yogyakarta Indonesia

ISBN: (纸本)9798331507930

This study aims to develop an interactive virtual tour based on Android with a first-person shooter approach to introduce the Adisutjipto Institute of Aerospace Technology (ITD Adisutjipto) virtually. This virtual tour utilizes an Artificial Intelligence (AI) agent as an intelligent guide who can answer questions and provide relevant information related to facilities and locations inside the ITD Adisutjipto building. The test results show that this virtual tour is effective and feasible to use, with a user satisfaction rate reaching 87.72%. This study contributes to the field of educational virtual technology by offering a more immersive and interactive experience. Users can easily explore the ITD Adisutjipto building virtually and obtain the information they need efficiently. This research is expected to be an innovative solution to introduce the ITD Adisutjipto to wider community, as well as support learning and research activities in the aerospace technology field. © 2024 IEEE.

关键词： Virtual environments

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Enhancing Sentiment Analysis with Attention Mechanism and Bayesian-Lipschitz Recurrent Neural Networks

Enhancing Sentiment Analysis with Attention Mechanism and Ba...

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International Symposium on Networks, Computers and Communications (ISNCC)

作者： Mahmudul Hasan Sachin Shetty Peter B. Foytik Department of Electrical and Computer Engineering Old Dominion University Norfolk Virginia USA Virginia Modeling Analysis and Simulation Center (VMASC) Old Dominion University Suffolk Virginia USA

ISBN: (数字)9798350364910

ISBN: (纸本)9798350364927

In medical chatbots and other healthcare domains, government agencies and other essential industries use sentiment analysis for public safety, improving the service quality of products, and other necessary purposes. Sometimes, the data is noisy, ambiguous, and contains mixed sentiments, where different parts of the text may convey different emotions, creating a problem in adequately detecting the sentiment. We proposed a novel recurrent neural network called the Bayesian-Lipschitz RNN with an attention mechanism to address these challenges. The Bayesian approach manages noisy and ambiguous data by representing uncertainty and avoiding overfitting. At the same time, the attention mechanism focuses on the most relevant parts of the text, effectively capturing context and mixed sentiments. Then, the Lipschitz Recurrent Neural Networks (LRNN), based on hidden-to-hidden matrices, are employed and constructed using a symmetric-skew decomposition scheme. The hidden-to-hidden matrices are used to update the hidden state and this hidden state is used to predict the sentiment, mitigate the vanishing gradient and stability issues, and got accuracy with 92.45 %.

关键词： Sentiment analysis Recurrent neural networks Attention mechanisms Symmetric matrices Uncertainty Stability analysis Public security Bayes methods Noise measurement Matrix decomposition

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