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Numerical prediction of the aerodynamics and aeroacoustics of a 25 kW horizontal axis wind turbine

Journal of Mechanics 2024年第40期40卷 299-312页

作者： Wang, Wen-Yu Ferng, Yuh-Ming Department of Energy and Refrigerating Air-Conditioning Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu City Taiwan

In this study, low-frequency-based numerical methods were used to predict the noise radiating from rotating horizontal axis wind turbine (HAWT) blades. The flow parameters in the vicinity of blade surfaces, which are required for the Ffowcs Williams–Hawkings (FW–H) equation, were calculated using ANSYS FLUENT. The numerical model was verified against the experimental results from the National Renewable Energy Laboratory Phase VI wind turbine blades. The coupling analysis was integrated with four Reynolds-averaged Navier–Stokes turbulence models and FW–H equation under various boundary conditions. The standard k-Ε, SST k-ω and V2f turbulence models produced results in agreement with the available experimental pressure coefficient and relative velocity distribution data in the flow fields. Under the verification of aeroacoustic results, the SST k-ω turbulence model was more consistent with the large eddy simulation data. An Institute of Nuclear Energy Research 25-kW HAWT was employed to predict noise frequency distribution at nine points on the tower on the windward and leeward sides under different operating conditions. Noise frequency distributions on the windward and leeward sides exhibited slight differences, whereas those on the left and right sides of the tower were different because of wind-shear influence. Under operating conditions, the decibels of the low-frequency noise at 0–200 Hz were ∼25–40 dB, and the noise frequency distributions on the windward and leeward sides were similar. With increasing distance, the decibel number of the monitoring point ∼25 m away dropped to 0 dB. For the noise prediction in Case 2 (wind speed = 12 m/s, pitches = 18°), the decibel number at 50 m was ∼25 dB and was ∼15 dB at 70 m. In Case 3 (wind speed = 18 m/s, pitches = 33°), the decibel number at 50 m was ∼30 dB and was ∼20 dB at 70 m. The peak amplitude of the noise was inversely proportional to the increasing distance from the tower but proportional to the wind and rotation

关键词： Horizontal axis wind turbine

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Comprehensive Overview of Gas and Bio-Sensors Enabling Artificial Intelligence in Healthcare 2

Comprehensive Overview of Gas and Bio-Sensors Enabling Artif...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Raut, Yashasvi Chaudhri, Shiv Nath Faculty of Engineering and Technology Department of Computer Science and Engineering Maharashtra India Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra India

ISBN: (纸本)9798331528713

Gas and biosensors are crucial in the modern healthcare system, enabling non-invasive monitoring and diagnosis of various medical conditions. These sensors are used in various applications, including smart home health monitoring devices and critical care units. Common non-imaging sensor types include gas or VOC sensors, diagnostic ECG sensors, blood glucose sensors, pulse oximeters, blood pressure sensors, body temperature sensors, EEG sensors, accelerometers, and imaging sensors like X-rays, MRIs, CT scans, and ultrasounds. Healthcare-related sensors offer numerous advantages, including diagnosing and treating medical conditions, monitoring vital signs, enabling remote patient monitoring, personalized healthcare, and early detection and prevention. However, issues like data accessibility, privacy, comfort, security, and accuracy must be considered when installing sensors in homes. Efficient data sharing and analysis require devices, sensors, and platforms to communicate effectively. Real-time data processing is essential for prompt diagnosis and intervention. In this article, we have put it briefly: medical sensors are transforming the way we track, identify, and manage adverse health conditions. © 2024 IEEE.

关键词： Glucose sensors

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Noise4Denoise:Leveraging noise for unsupervised point cloud denoising

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Computational Visual Media 2024年第4期10卷 659-669页

作者： Weijia Wang Xiao Liu Hailing Zhou Lei Wei Zhigang Deng Manzur Murshed Xuequan Lu Deakin University GeelongVIC 3216Australia Department of Mechanical Engineering and Product Design Engineering Swinburne University of TechnologyMelbourneVIC 3122Australia Department of Computer Science University of HoustonHoustonTX 77204-3027USA Department of Computer Science and Information Technology La Trobe UniversityMelbourneVIC 3086Australia

Existing deep learning-based point cloud denoising methods are generally trained in a supervised manner that requires clean data as ground-truth ***,in practice,it is not always feasible to obtain clean point *** this paper,we introduce a novel unsupervised point cloud denoising method that eliminates the need to use clean point clouds as groundtruth labels during *** demonstrate that it is feasible for neural networks to only take noisy point clouds as input,and learn to approximate and restore their clean *** particular,we generate two noise levels for the original point clouds,requiring the second noise level to be twice the amount of the first noise *** this,we can deduce the relationship between the displacement information that recovers the clean surfaces across the two levels of noise,and thus learn the displacement of each noisy point in order to recover the corresponding clean *** experiments demonstrate that our method achieves outstanding denoising results across various datasets with synthetic and real-world noise,obtaining better performance than previous unsupervised methods and competitive performance to current supervised methods.

关键词： point clouds denoising geometry processing deep learning

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design and Simulation of a Maintenance-friendly and Cost-effective Molten Aluminum Alloy Casting Mechanism

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Sensors and Materials 2024年第7期36卷 2955-2964页

作者： Bakhtiar, Budhi Wang, Nai-Hsien Hsu, Chao-Ming Fan, Kuo-Kuang Yang, Cheng-Fu Cai, Deng-Chuan Graduate School of Design National Yunlin University of Science & Technology Douliou Yunlin640 Taiwan Electro Engineering Department Padang State Polytechnics West-Sumetera Indonesia Department of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung807 Taiwan Department of Chemical and Materials Engineering National University of Kaohsiung Kaohsiung811 Taiwan Department of Aeronautical Engineering Chaoyang University of Technology Taichung413 Taiwan Department of Industrial Design National Yunlin University of Science and Technology Douliou Yunlin640 Taiwan

The aim of this research was to design and simulate a low-cost, easy-to-maintain molten aluminum alloy casting mechanism. This mechanism was intended to address labor shortages in harsh and high-temperature environments. The functional requirements of the mechanism were as follows: it needed to withstand temperatures exceeding 700 ℃, operate without deformation, and ensure that the ladle’s positioning error during each rotation did not exceed 1 deg. Additionally, the mechanism’s durability had to meet industry standards, with the ladle’s output shaft capable of bearing pressures exceeding 100 kg/cm2. The design should be modular, allowing for the replacement of specific components to accommodate varying specifications in the future. To begin with, a 3D model was constructed using SolidWorks CAD software to verify operational interferences and simulate assembly, ensuring that the design was practical and logically sound. During the design process, mechanical design handbooks and catalogs from major component suppliers were consulted to utilize standard sizes and specifications as much as possible. Once the model was confirmed, structural analyses were conducted using Ansys to ensure that the mechanism could withstand significant loads without failure. Furthermore, the design would focus on ensuring that the mechanism was robust and reliable under high-temperature conditions, reducing the need for frequent maintenance and downtime. The modular design approach not only enhances the flexibility of the mechanism but also simplifies future upgrades and adjustments, ensuring long-term usability and adaptability. © 2024 M Y U Scientific Publishing Division. All rights reserved.

关键词： Aluminum alloys

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive Control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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Methodology for microclimatic urban canyon design case study surrounding MUST university campus in Cairo

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HBRC Journal 2024年第1期20卷 589-603页

作者： Abd El-Razik, Mahmoud M. Hafez, Yasmine K. Hendy, Alaa H. Fawzy, Mariam M. Cairo Egypt Faculty of Engineering & Technology Architecture Engineering & Environmental Design Department Arab Academy for Science Technology & Maritime Transport Giza Egypt Nile University Giza Egypt

Climate change is a major issue all over the world which has a great impact on global warming especially in countries with hot arid climates like Egypt. With rapid urbanization, streets in Greater Cairo and new cities are mostly car-oriented, which increases the Urban Heat Island(UHI) and, hence, affects the overall outdoor thermal comfort. Looking at the urban development in recent years, almost 10 new private universities are in operation in Cairo’s new cities together with a number of large recreational projects where they lack the appropriate vegetation surrounding their borders which in turn increases the UHI effect, decreasing the walkability’s thermal comfort and in turn contributes poorly to the surrounding climate. This paper focuses on the urban canyons in streets surrounding universities as they usually have high traffic rates in terms of both vehicular and pedestrian flows. This large flow of pedestrians necessitates taking into consideration the thermal comfort of the users. MUST University in the Al-Motamayez district on the 6th of October city was chosen as a case study. This case study is considered the basis for achieving an understanding and developing a methodology approach for such studies by using Envi-Met software for the simulation of different scenarios focusing on choosing trees appropriate to the climate zone of the city. Results for the simulation of suggested scenarios of intervention show a 30% improvement toward thermal comfort, which could be considered a first step for future guidelines development toward achieving thermal comfort and decreasing UHI. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Vegetation

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Soft-GNN:towards robust graph neural networks via self-adaptive data utilization

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Frontiers of Computer science 2025年第4期19卷 1-12页

作者： Yao WU Hong HUANG Yu SONG Hai JIN National Engineering Research Center for Big Data Technology and System Service Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China College of Information and Communication National University of Defense TechnologyWuhan 430019China Department of Computer Science and Operations Research Universitéde MontréalMontreal H3C 3J7Canada

Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that has been deliberately or accidentally polluted with *** presents a challenge in learning robust GNNs under noisy *** address this issue,we propose a novel framework called Soft-GNN,which mitigates the influence of label noise by adapting the data utilized in *** approach employs a dynamic data utilization strategy that estimates adaptive weights based on prediction deviation,local deviation,and global *** better utilizing significant training samples and reducing the impact of label noise through dynamic data selection,GNNs are trained to be more *** evaluate the performance,robustness,generality,and complexity of our model on five real-world datasets,and our experimental results demonstrate the superiority of our approach over existing methods.

关键词： graph neural networks node classification label noise robustness

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In-situ TEM study of the effect of hydrogen-helium ratio on defect characteristics in Fe9Cr1.5W0.4Si F/M steel during H_(2)^(+)&He^(+)simultaneous irradiation

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Journal of Materials science & technology 2024年第6期173卷 192-201页

作者： Dewang Cui Ziqi Cao Kun He Yuanming Li Xi Qiu Guang Ran College of Energy Xiamen UniversityXiamen 361102China Fujian Provincial Nuclear Energy Engineering Technology Research Center Xiamen 361102China Science and Technology on Reactor Fuel and Materials Laboratory Chengdu 610041China Nuclear Power Institute of China Chengdu 610041China Science and Technology on Reactor System Design Technology Laboratory Chengdu 610041China

The effect of hydrogen and helium interaction,especially H-He ratio,on the irradiation behavior of nuclear materials has not yet been ***,this is an important basis for evaluating the irradiation properties of nuclear materials and developing high irradiation resistant ***,30 keV H_(2)^(+)and He^(+)dual beams with four H-He ratios of 0:10,3:10,15:10,and 30:10 were used to irradiate the newly developed Fe9Cr1.5W0.4Si F/M steel in TEM to in-situ study the interaction and ratio effect of hydrogen and *** addition of H atoms significantly promoted the nucleation of dislocation loops and *** the early stage of irradiation,the average size and density of dislocation loops increased with the increase of H-He ***,the larger the H-He ratio,the easier it was to form a complex dislocation ***,the final saturation size of bubbles increased with the increase of H-He *** was first found that the swelling was affected by H concentrations,with high H concentrations slowing down the increase in *** a certain irradiation dose,a specific H-He ratio would lead to a swelling peak of Fe9Cr1.5W0.4Si F/M *** super-sized bubbles at grain boundaries(GBs)were found after H addition,resulting in a bigger swelling of GBs than the *** the swelling of the GBs and the matrix show a dependence on the H-He *** current work is of great significance for understanding the interaction between hydrogen and helium in nuclear materials.

关键词： Dose ratio effect Ferritic-martensitic steel Hydrogen&helium synergetic irradiation In-situ TEM

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Overview of Emerging Biological Computational Framework for Olfactory Studies Utilizing Contextual Technobiomedical engineering 2

Overview of Emerging Biological Computational Framework for ...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Chaudhri, Shiv Nath Faculty of Engineering & Technology Department of Computer Science and Design Wardha India

ISBN: (纸本)9798331528713

Organoid intelligence (OI), the next paradigm of intelligence, draws inspiration from the biological learning of organs. On the other hand, artificial intelligence (AI) draws its inspiration only from the cognitive processes of the brain. While taking ethical and technological limitations into account, biological learning helps to conceptualize, accept, and apply them. Just as AI helped to make supercomputers possible, OI may help create biocomputers. Even though AI has increased the capabilities of technology to unimaginable heights, it still appears immature and is steadily moving toward cognitive computing to push the envelope even farther. In contrast to AI, OI is a new multidisciplinary computer area that attempts to be more approachable. OI has the ability to produce novel biocomputers, such as organoids, that use parts derived from live organisms to perform computational tasks. Organoids, such as human nasal organoids, are microscopic tissue cultures made from stem cells that mimic some of the functions of real organs. Although they have been used for many different purposes, including drug discovery and illness modeling, scientists are only now beginning to explore their potential for biological information processing. © 2024 IEEE.

关键词： Artificial Intelligence (AI) Biological Information Processing Biological Learning Olfactory Organoids Organoid Intelligence (OI)

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Preface to the Special Issue "Fundamentals and Application Technologies for Microstructural Control of Hot-dip Galvanized Coatings for Creating New Functionalities"

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Tetsu-To-Hagane/Journal of the Iron and Steel Institute of Japan 2025年第6期111卷 273-274页

作者： Takata, Naoki Ueda, Mitsutoshi Department of Materials Design Innovation Engineering Nagoya University Japan Division of Materials Science and Engineering Faculty of Engineering Hokkaido University Japan School of Materials and Chemical Technology Institute of Science Tokyo Japan

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