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检索条件"丛书名=Mechanisms and Machine Science"

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Dynamic Analysis of a Radial Bearing Using the FEM Model 12th

Dynamic Analysis of a Radial Bearing Using the FEM Model

引用

12th International Conference of machine and Industrial Design in Mechanical Engineering

作者： Sejat, Mirjana Bojanic Knezev, Milos Zivkovic, Aleksandar Rackov, Milan Knezevic, Ivan Zlatanovic, Danka Labus Univ Novi Sad Fac Tech Sci Novi Sad Serbia Tech Univ Ilmenau Prod Technol Dept Ilmenau Germany

ISBN: (纸本)9783031805141;9783031805127;9783031805110

Comprehensive analysis of ball bearings involves a complex examination of parameters that affect the behavior of the bearing during operation. In particular, the influence of the rotational speed, clearance, load, and changes in elastic deformations on the dynamic characteristics of the bearing should be taken into account. In this paper, a model was developed in a general purpose software system based on the finite element method (FEM), which consists of a static and a dynamic model. Only part of the dynamic model related to explicit dynamic analysis will be presented in the paper. Explicit dynamic analysis provides changes in acceleration, velocity, displacement, and stress on bearing components over time, depending on external loads, clearance, and the bearing's rotational speed. In this work, the results for bearing 6006 will be presented.

关键词： Ball Bearing FEM Explicit Dynamic Analysis

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A Fracturing Model Coupled with THM Based on Three Dimensional Discrete Element Method: Case Study of a Hot Dry Rock Reservoir 30th

A Fracturing Model Coupled with THM Based on Three Dimension...

引用

30th International Conference on Computational and Experimental Engineering and sciences

作者： Wu, Zhiying He, Yuting Guo, Wuhao Bi, Zhenhui Chang, Xin Wang, Lei Guo, Yintong Sinopec Res Inst Petr Engn Co Ltd Beijing Peoples R China Chinese Acad Sci Inst Rock & Soil Mech State Key Lab Geomechan & Geotechn Engn Wuhan Peoples R China

ISBN: (纸本)9783031816758;9783031816734;9783031816727

In order to study the problem of fracture propagation at field scale of hydraulic fracturing and carbon dioxide fracturing in hot dry rock reservoir. In this study, a numerical model of fracture dynamic propagation coupled with thermo-hydraulic-mechanical (THM) processes is established based on the three-dimensional discrete element method. In this model, discrete fracture network (DFN) modeling is also considered. In the case study, the effects of different fracturing parameters and geological parameters are analyzed. The study found that the total fracture area is negatively correlated with the injection rate. But compared with hydraulic fracturing, the fracture area of carbon dioxide fracturing is less affected by the injection rate. The fracture area of carbon dioxide fracturing is 1.67 similar to 1.81 times of the total fracture area of hydraulic fracturing. The proportion of natural fractures activated by carbon dioxide fracturing is 1.38 similar to 1.54 times that of hydraulic fracturing.

关键词： Hot dry rock Fracturing Hydraulic Carbon dioxide Numerical simulation

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Sources of Noise and Vibration on Car Gearboxes 12th

Sources of Noise and Vibration on Car Gearboxes

引用

12th International Conference of machine and Industrial Design in Mechanical Engineering

作者： Tomeh, Elias Sann, Samnang Tech Univ Liberec Liberec Czech Republic

ISBN: (纸本)9783031805141;9783031805127;9783031805110

It is necessary to have a deep understanding of mechanical systems and motor vehicle construction when designing and developing new equipment and solving noise and vibration problems of gearboxes. Gearboxes are one of the main causes of noise and vibration in cars. In car gearboxes, noise and vibration are mostly caused by shafts, gears, and bearings. Moreover, noise and vibrations in the transfer path of the drivetrain might be brought on by imbalances, misalignments, and other issues. Frequency analysis and order analysis are often used to analyze noise and vibration in automobile gearboxes. Bearing fault analysis involves the use of envelope analysis. The current equipment of the Department of Vehicles and Engines makes it possible to significantly strengthen the experimental part of the vibration and noise of passenger car gearboxes. This paper aims to identify the noise and vibration sources on car gearboxes by frequency analysis and to improve the reliability and maintainability of gearboxes in passenger cars. The effect of eccentricity, the clearance of the input shaft bearings, and the clearance of the bearing near the clutch were found in traction for all speed degrees. In backward, the effect of eccentricity was found for all speed degrees.

关键词： Noise Vibration Car Gearbox Method Diagnostic

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Research on Jet Head Velocity Based on Back Propagation Neural Network 30th

Research on Jet Head Velocity Based on Back Propagation Neur...

引用

30th International Conference on Computational and Experimental Engineering and sciences

作者： Yuan, Jiaxin Cui, Hao Guo, Rui Nanjing Univ Sci & Technol Sch Mech Engn Nanjing 210094 Peoples R China

ISBN: (纸本)9783031774911;9783031774898;9783031774881

Extensive theoretical research has been conducted on jet head velocity in previous studies. However, due to the influence of numerous nonlinear factors, these theories cannot accurately calculate the jet head velocity under different warhead structures. To address this issue, neural networks have inherent advantages. In this paper, the charge radius r, the charge height h, the liner angle a and the liner thickness t are employed as the input for the BP neural network, while the jet head velocity serves as the output. A dataset comprising 168 sets of data is prepared for training the BP neural network, with a split ratio of 80% for training and 20% for validation. The training results demonstrate that the back propagation (BP) neural network is capable of accurately predicting the jet head velocity. The jet head velocity v increases with the increase of the charge radius r, increases with the increase of the charge height h, decreases with the increase of the liner angle a, and decreases with the increase of the liner thickness t. Compared to BP Neural Networks, RNN performs very well on datasets average error can be up to 11.63 m/s but performs poorly when dealing with new time series data. These conclusions can provide guidance for further jet design and optimization, and help to understand the relationship between jet head velocity and warhead structure.

关键词： BP neural network Shaped charge jet Jet head velocity RNN

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Collapse Failure of Tubular Elements in Ultra-Deep Wells Under Complex Conditions 30th

Collapse Failure of Tubular Elements in Ultra-Deep Wells Und...

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30th International Conference on Computational and Experimental Engineering and sciences

作者： Wang, Long Wang, Zijian Huang, Liang Dong, Xuelin Wang, Jieli CNPC Key Lab Enhanced Oil Recovery Carbonate Fractured Urumqi Peoples R China SINOPEC Northwest Co China Petr & Chem Corp Urumqi Peoples R China China Univ Petr Lab Petr Engn Beijing Peoples R China

ISBN: (纸本)9783031816758;9783031816734;9783031816727

China has gradually increased efforts to explore and develop ultra-deep oil and gas reservoirs in recent years, leading to a growing number of ultra-deep wells. The geological structures of ultra-deep oil and gas reservoirs are complex, with high pressures, high temperatures, and abundant acidic gases, posing a severe threat to the integrity of the tubular elements. Among them, tubing or casing collapse failure caused by high pressure and high temperature is a typical damage mode exacerbated by the corrosive environment of ultra-deep wells. The industry mainly designs pipe collapse pressure according to the American Petroleum Institute (API) standards and the Det Norske Veritas (DNV). This study compares the collapse pressures based on these two standards. Additionally, combining both standards and the finite element method (FEM), an analysis of tubing collapse failure caused by the blockage in ultra-deep wells is conducted. The results indicate that the collapse pressure calculated according to the DNV standard for the same steel grade is higher than that of the API standard. Internal pressure reduction due to tubing plug, degradation of mechanical properties in high-temperature environments, and wall thinning caused by corrosion all contribute to collapse failure.

关键词： Ultra-deep wells High pressure and high temperature Wellbore integrity Collapse Tubing plug

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Seismic Attribute-Constrained Stratigraphic Drill Ability Modeling Method 30th

Seismic Attribute-Constrained Stratigraphic Drill Ability Mo...

引用

30th International Conference on Computational and Experimental Engineering and sciences

作者： Yan, Ding Meng, Cui Yi, Cui Gao Reyu Ge, Wang Fei, Zhao CNPC Engn Technol R&D Co Ltd Beijing 102206 Peoples R China Leibniz Univ Hannover Inst Kontinuumsmech Hannover Germany

ISBN: (纸本)9783031774911;9783031774898;9783031774881

In deep and ultra-deep complex formations, strong heterogeneity poses challenges to predictability. The acquisition, transmission, and integration of formation-engineering data are complex, influenced by intricate subsurface conditions. Additionally, the accuracy of physical modeling for drill ability of formations is constrained, and the uncertainty in rock-breaking mechanics further complicates matters. Traditional spatial interpolation methods struggle to ensure modeling accuracy, especially in cases of abrupt changes in formations. To address these challenges, this paper proposes an attribute-constrained method for modeling formation drill ability based on seismic and borehole data. Under the constraint of seismic attributes, the limited drill ability information from wells is interpolated and extrapolated according to the geological "facies" characteristics represented by attribute descriptions. A three-dimensional formation drill ability model is established, providing a better simulation of variations and uncertainties in deep formations.

关键词： Seismic attributes attribute-constrained interpolation formation drill ability spatial modeling

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Adaptive Traffic Signal Control for Urban Corridor Based on Reinforcement Learning 30th

Adaptive Traffic Signal Control for Urban Corridor Based on ...

引用

30th International Conference on Computational and Experimental Engineering and sciences

作者： Liu, Lishan Zhuang, Xiya Li, Qiang Shenzhen Technol Univ Coll Urban Transportat & Logist 3002 Lantian Rd Shenzhen 518118 Guangdong Peoples R China

ISBN: (纸本)9783031774911;9783031774898;9783031774881

More recently, the advancement of reinforcement learning brings increasing attention in transport areas. Several studies have utilized them to address the challenge of adaptive traffic signal control (TSC) and have obtained encouraging outcomes. In this paper, a new adaptive traffic signal control algorithm is proposed based on reinforcement learning (RL) to alleviate congestion in urban corridors. To associate with congestion and signal control plans, first, the method employs the negative value of queue lengths for links in the urban corridor as the reward and takes the queue lengths at several time points as the state features. Compared to traditional traffic flow indicator, queue length is able to identify the deteriorating trend of traffic conditions after intersections become saturated, which helps in early detection of traffic congestion trends. Then, adjusting the green split at each intersection is chosen as the action to control congestion levels by adjusting the traffic flow at the upstream and downstream intersections. Through the SUMO simulation platform, the proposed signal control method is comprehensively evaluated at different levels of traffic demand and several RL algorithms have been compared. It has been proved that the proposed signal control approach not only can be trained efficiently on a single low-performance GPU but also can reduce congestion significantly.

关键词： Traffic signal controller reinforcement learning Automatic Vehicle Identification (AVI) congestion management

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Lift-Drag Ratio of Arc-Shaped Wing During Water Entry Based on Nonlinear Boundary Element Method 30th

Lift-Drag Ratio of Arc-Shaped Wing During Water Entry Based ...

引用

30th International Conference on Computational and Experimental Engineering and sciences

作者： Sun, Shiyan Lu, Junhao Duah, Gideon Addai Bao, Chaoming Jiangsu Univ Sci & Technol Sch Naval Architecture & Ocean Engn Zhenjiang 212003 Jiangsu Peoples R China

ISBN: (纸本)9783031774911;9783031774898;9783031774881

The study delves into the lift-to-drag ratio characteristics of arc-shaped wing during water entry, employing a time-domain boundary element method under fully nonlinear boundary conditions. The wing's entry commences from a single contact point, followed by a rapid expansion of the wet surface, and this would pose a notable challenge for numerical simulation. To address this, a stretched coordinate system technique is deployed to extend the physical domain, effectively managing numerical difficulties at the initial stage. Additionally, the auxiliary function method is utilized to derive pressure distribution. The investigation encompasses varying deadrise angles, attack angles, and body curvatures to discern their effects on the lift-to-drag ratio. Notably, the study finds that the lift-to-drag ratio is predominantly influenced by the effective attack angle. Moreover, the effective deadrise angle and surface curvature of the body also play significant roles in shaping the lift-to-drag ratio. These findings underscore the multifaceted nature of factors contributing to the hydrodynamic performance of curved foils during water entry.

关键词： Potential flow Boundary element method Water entry Nonlinear

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Numerical Analysis on the Cooling Performance of the Battery Thermal Management System Using U-Shaped Flat Heat Pipe 30th

Numerical Analysis on the Cooling Performance of the Battery...

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30th International Conference on Computational and Experimental Engineering and sciences

作者： Dong, Xinyi Dai, Yijia Shao, Zhixiong Fu, Zaiguo Zhu, Qunzhi Shanghai Univ Elect Power Coll Energy & Mech Engn Shanghai 201306 Peoples R China Sunshore Solar Energy Co Engn Technol Ctr Nantong 226300 Peoples R China

ISBN: (纸本)9783031774911;9783031774898;9783031774881

Battery Thermal Management System (BTMS) is designed for energy storage batteries to ensure optimal performance during high-power operation. It regulates the battery temperature, reduces the risk of thermal runaway and improves safety, thus safeguarding the operation of the battery. A BTMS using U-shaped flat heat pipe (UFHP) combined with a submerged liquid channel is established in this paper, and the temperature control behavior of the UFHP BTMS is investigated by numerical simulation with a number of influencing factors including working fluid, water flow rate and inlet water temperature. The results indicate that when the water flow rate is 0.2 L/min and the inlet water temperature is 25 degrees C, the maximum temperature of the battery at 0.5 C, 1 C, and 1.5 C rates with UFHP BTMS decreases by 37.77%, 51.91%, and 58.17%, respectively, versus the battery without UFHP BTMS. In battery heating conditions, the minimum temperature of the battery with UFHP BTMS increases from 0 degrees C to 15 degrees C at 320 s of discharge, 93.44% earlier than the battery without UFHP BTMS.

关键词： Battery thermal management Heat pipe Cooling and heating Lithium-ion battery

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Security Analysis of the Combination of Smart Contract and Artificial Intelligence 30th

Security Analysis of the Combination of Smart Contract and A...

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30th International Conference on Computational and Experimental Engineering and sciences

作者： Chen, Yan Wei, Zunbo Ma, Jue Kuang, Haiyan Zhang, Yijian Zhang, Qing Sun, Shuning Chen, Jianghao Chen, Xiaofeng Minist Publ Secur Res Inst 3 Shanghai Engn Res Ctr Cyber & Informat Secur Eval Shanghai Peoples R China Hangzhou Qulian Technol Co Ltd Hangzhou Peoples R China Hangzhou High Tech Zone Binjiang Inst Blockchain Hangzhou Peoples R China Zhejiang Univ Hangzhou Peoples R China Zhejiang Soc Measurement & Stand Hangzhou Zhejiang Peoples R China Beyondsoft Technol Hangzhou Co Ltd Dept Ant One Hangzhou Peoples R China Zhejiang Univ State Key Lab Blockchain & Data Secur Hangzhou Peoples R China Univ Chinese Acad Sci Hangzhou Inst Adv Study Hangzhou Peoples R China

ISBN: (纸本)9783031774911;9783031774898;9783031774881

Although blockchain technology uses encryption to protect data, there are still challenges in security, especially in the application of smart contracts based on blockchain. In terms of security, artificial intelligence technology represented by machine learning can help the development of blockchain applications. This paper discusses the security status of smart contract in blockchain technology, and the solutions brought by artificial intelligence technology to better understand the potential of combining artificial intelligence and blockchain to enhance the security of smart contracts.

关键词： blockchain smart contracts artificial intelligence machine learning security risk

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