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Stochastic uncertain lubrication in gear transmission subjected to tribodynamic loading

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Friction 2024年第8期12卷 1741-1756页

作者： Zhou CHEN Haiming SHA Sheng LI zheming tong Shuiguang tong State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China School of Mechanical Engineering Zhejiang UniversityHangzhou 310027China Wright State University 3640 Colonel Glenn HighwayDaytonOH 45435USA

A stochastic uncertain tribodynamic model is established for a spur gear pair for the first *** stochastic uncertainty of pinion rotation speed propagated to lubrication performance is *** probability density function of the minimum lubricant film thickness hmin evolves over time periodically at interval of an engagement *** between abrupt increase in meshing force and amplification of hmin uncertainty is *** and reliable lubrication performance can be achieved by suppressing the hmin uncertainty and decreasing the lubrication failure *** can be done by increasing lubricant viscosity,and decreasing input torque and uncertainty level of input rotation *** work lays a solid foundation for robust and reliability based optimization for tribodynamic gear system.

关键词： stochastic uncertainty gears elastohydrodynamic lubrication(EHL) tribodynamics

Machine learning of materials design and state prediction for lithium ion batteries

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Chinese Journal of Chemical Engineering 2021年第9期34卷 1-11页

作者： Jiale Mao Jiazhi Miao Yingying Lu zheming tong State Key Laboratory of Chemical Engineering Institute of Pharmaceutical EngineeringCollege of Chemical and Biological EngineeringZhejiang UniversityHangzhou 310027China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhou 310027China

With the widespread use of lithium ion batteries in portable electronics and electric vehicles,further improvements in the performance of lithium ion battery materials and accurate prediction of battery state are of increasing interest to battery *** learning,one of the core technologies of artificial intelligence,is rapidly changing many fields with its ability to learn from historical data and solve complex tasks,and it has emerged as a new technique for solving current research problems in the field of lithium ion *** review begins with the introduction of the conceptual framework of machine learning and the general process of its application,then reviews some of the progress made by machine learning in both improving battery materials design and accurate prediction of battery state,and finally points out the current application problems of machine learning and future research *** is believed that the use of machine learning will further promote the large-scale application and improvement of lithium-ion batteries.

关键词： Lithium ion batteries Machine learning Materials design State prediction

Fault diagnosis for gearboxes based on Fourier decomposition method and resonance demodulation

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2023年第5期24卷 404-418页

作者： Shuiguang tong Zilong FU zheming tong Junjie LI Feiyun CONG State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China School of Mechanical Engineering Zhejiang UniversityHangzhou 310027China

Condition monitoring and fault diagnosis of gearboxes play an important role in the maintenance of mechanical *** vibration signal of gearboxes is characterized by complex spectral structure and strong time variability,which brings challenges to fault feature *** address this issue,a new demodulation technique,based on the Fourier decomposition method and resonance demodulation,is proposed to extract fault-related ***,the Fourier decomposition method decomposes the vibration signal into Fourier intrinsic band functions(FIBFs)adaptively in the frequency ***,the original signal is segmented into short-time vectors to construct double-row matrices and the maximum singular value ratio method is employed to estimate the resonance ***,the resonance frequency is used as a criterion to guide the selection of the most relevant FIBF for demodulation ***,for the optimal FIBF,envelope demodulation is conducted to identify the fault characteristic *** main contributions are that the proposed method describes how to obtain the resonance frequency effectively and how to select the optimal FIBF after decomposition in order to extract the fault characteristic *** numerical and experimental studies are conducted to investigate the performance of the proposed *** is demonstrated that the proposed method can effectively demodulate the fault information from the original signal.

关键词： Fourier decomposition method Singular value ratio Resonance frequency Envelope demodulation Fault diagnosis

Ultrafast battery heat dissipation enabled by highly ordered and interconnected hexagonal boron nitride thermal conductive composites

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Green Energy & Environment 2022年第6期7卷 1401-1410页

作者： Zhuoya Wang Kaihang Zhang Bing Zhang zheming tong Shulan Mao Hao Bai Yingying Lu State Key Laboratory of Chemical Engineering Institute of Pharmaceutical EngineeringCollege of Chemical and Biological EngineeringZhejiang UniversityHangzhou310027China Brook Byers Institute of Sustainable Systems and School of Civil and Environmental Engineering Georgia Institute of TechnologyAtlantaGA30332USA ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang UniversityHangzhou311200China State Key Laboratory of Fluid Power and Mechatronic Systems College of Mechanical EngineeringZhejiang UniversityHangzhou310027China

Heat dissipation involved safety issues are crucial for industrial applications of the high-energy density battery and fast charging *** traditional air or liquid cooling methods suffering from space limitation and possible leakage of electricity during charge process,emerging phase change materials as solid cooling media are of growing *** them,paraffin wax(PW)with large latent heat capacity and low cost is desirable for heat dissipation and thermal management which mainly hindered by their relatively low thermal conductivity and susceptibility to ***,highly ordered and interconnected hexagonal boron nitride(h-BN)networks were established via ice template method and introduced into PW to enhance the thermal *** composite with 20 wt%loading amount of h-BN can guarantee a highly ordered network and exhibited high thermal conductivity(1.86 W m^(-1) K^(-1))which was 4 times larger compared with that of random dispersed h-BN involved PW and nearly 8 times larger compared with that of bare *** optimal thermal conductive composites demonstrated ultrafast heat dissipation as well as leakage resistance for lithium-ion batteries(LIBs),heat generated by LIBs can be effectively transferred under the working state and the surface temperature kept 6.9℃ lower at most under 2–5℃ continuous charge-discharge process compared with that of bare one which illustrated great potential for industrial thermal management.

关键词： Hexagonal boron nitride Paraffin wax Lithium-ion batteries Thermal conductive network Battery heat dissipation

Eco-friendly biodegradable polyurethane based coating for antibacterial and antifouling performance

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Chinese Journal of Chemical Engineering 2023年第2期54卷 80-88页

作者： Abid Ali Bilal Ul Amin Wenwu Yu Taijiang Gui Weiwei Cong Kai Zhang zheming tong Jiankun Hu Xiaoli Zhan Qinghua Zhang College of Chemical and Biological Engineering Provincial Key Laboratory of Advanced Chemical Engineering Manufacture TechnologyZhejiang UniversityHangzhou 310027China Institute of Mold Technology Changzhou Vocational Institute of Mechatronic TechnologyChangzhou 213164China State Key Laboratory of Marine Coatings Marine Chemical Research Institute Co.LtdQingdao 266072China Quzhou Research Institute Zhejiang UniversityQuzhou 324000China

Biofouling, which comprises the absorption of proteins and the adhesion of bacteria to the surface of living entities, is a severe concern for the maritime sector since it ultimately leads to hydrodynamic drag,resulting in a higher increase in fuel consumption. As a result, polymer resins are crucial in the marine sector for anti-biofouling coatings. In this work, the poly(caprolactone-ethylene glycol-caprolactone)-p olyurethane(PECL-PU) are prepared through ε-caprolactone(CL), poly(ethylene glycol)(PEG), 4,4'-methylene bis(cyclohexyl isocyanate) and 1,4 butanediol. Our study demonstrate that the PECL-PU copolymer degraded in artificial seawater(5.21%), enzymatic solution(12.63%), and seawater(13.75%)due to the presence of PEG segments in the laboratory-based test under static condition. Because the addition of PEG segments are increased the polymer's amorphous area and decreased the crystallization of the polycaprolactone(PCL) in the copolymer, as demonstrated by differential scanning calorimetry, X-ray diffraction, and water contact angle studies. Therefore, the hydrolysis rates of PECL-PU were higher than the caprolactone-co-polyurethane(CL-PU). The antifouling test showed that PECL-PU3 copolymer had about 90.29% protein resistance, 85.2% Escherichia coli(E. coli) reduction and 94.61% marine diatom Navicula incerta reduction comparison to the control. We have developed an eco-friendly and inexpensive promising degradable polyurethane for reduction of bacterial biofilm, which can preserve the formation of biofouling on marine coating under practical sea conditions.

关键词： Caprolactone PEG segments Biodegradable polyurethane Biofouling Hydrolytic degradation

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基于动态模态分解的叶道涡非定常解耦与重构

中国机械工程 2022年第7期33卷 769-776页

作者：童哲铭辛佳格童水光浙江大学流体动力与机电系统国家重点实验室杭州310063 浙江大学机械工程学院杭州310063

为进一步探索混流式水轮机偏负荷工况下叶道涡的演变机制,引入动态模态分解方法并结合数值模拟与实验对水轮机叶道涡的非定常流场进行相干结构的解耦。数值结果表明,叶道涡呈低频特性,演化的主频为0.5倍水轮机转频;涡管状叶道涡空腔起... 详细信息

为进一步探索混流式水轮机偏负荷工况下叶道涡的演变机制,引入动态模态分解方法并结合数值模拟与实验对水轮机叶道涡的非定常流场进行相干结构的解耦。数值结果表明,叶道涡呈低频特性,演化的主频为0.5倍水轮机转频;涡管状叶道涡空腔起源于叶轮上冠,并与叶片背面的片状涡连为一体。应用动态模态分解方法获得了叶道涡速度场的动态模态,并将该方法与本征正交分解方法进行了对比。结果表明,动态模态分解方法在特定频率下对叶道涡流动结构进行分解可得单倍频率特征,更便于进行相干结构的流动机理分析。两种方法都可在平均流态和主要模态的基础上对水轮机速度场流动结构进行降阶重构,但对局部复杂叶道涡区域的重构存在局限性。

关键词：叶道涡动态模态分解本征正交分解相干结构重构

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基于孪生支持向量回归的多级离心泵外特性曲线预测及设计方法

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机械工程学报 2024年第14期60卷 364-377页

作者：童哲铭马鑫航浙江大学流体动力基础件与机电系统全国重点实验室杭州310063 浙江大学机械工程学院杭州310063

准确快速地获取多级离心泵的外特性曲线,对设计过程中泵性能指标的判断具有重要的意义。现有基于计算流体力学(Computational fluid dynamics,CFD)数值模拟方法依赖设计人员经验、计算耗时以及偏工况点精度差,提出一种基于孪生支持向量... 详细信息

准确快速地获取多级离心泵的外特性曲线,对设计过程中泵性能指标的判断具有重要的意义。现有基于计算流体力学(Computational fluid dynamics,CFD)数值模拟方法依赖设计人员经验、计算耗时以及偏工况点精度差,提出一种基于孪生支持向量回归(Twin support vector regression,TSVR)的离心泵外特性曲线预测方法。针对多级离心泵流道复杂的特点,筛选出10个结构参数和流量作为模型输入。通过TSVR方法建立输入变量与外特性值之间的复杂非线性关系,对多级离心泵的外特性曲线进行预测。与试验结果相比,所提方法可以较好地预测性能指标,对扬程、效率和轴功预测的平均相对误差分别为1.71%、3.56%、3.36%。此外,与BP神经网络相比,TSVR对扬程和效率预测的方均根误差显著降低。同时,在整个工况范围内,TSVR模型对比传统采用RNG湍流模型的CFD方法有更高的精度以及计算效率。对比表明,所提方法可提高多级离心泵性能曲线预测的速度和精度,为实现多级泵的快速预测及高效性能设计提供重要的支撑。

关键词：离心泵支持向量回归数值模拟多工况性能预测

基于高速图像特征提取的滑动轴承空化特性试验研究及其数值仿真分析

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机械工程学报 2024年第13期60卷 48-55页

作者：童哲铭马廷良刘浩浙江大学流体动力基础件与机电系统全国重点实验室杭州310063 浙江大学机械工程学院杭州310063

空化现象广泛存在于各种大型旋转机械的滑动轴承中,严重影响轴承的运行稳定性和承载能力。为研究其特性,本研究设计并搭建了一套滑动轴承油膜可视化试验系统,利用高速摄像机捕捉高速旋转下的油膜空化演变图像,提出了油膜空化特征图像处... 详细信息

空化现象广泛存在于各种大型旋转机械的滑动轴承中,严重影响轴承的运行稳定性和承载能力。为研究其特性,本研究设计并搭建了一套滑动轴承油膜可视化试验系统,利用高速摄像机捕捉高速旋转下的油膜空化演变图像,提出了油膜空化特征图像处理及提取方法。结合数值模拟方法和试验手段进一步研究油膜空化特征及其影响因素。研究结果表明:径向滑动轴承空化气泡在油膜发散端呈现不规则轮廓的条状分布;油膜空化发展程度与轴颈转速和润滑油黏度成正相关,与供油压力成反相关。试验测试发现主轴转速从1 000 r/min增大至5 000 r/min,空化区域增大148%;润滑油黏度从50 mm^(2)/s增大至150 mm^(2)/s,空化区域增大170%;供油压力从0.025 MPa增大至0.150 MPa,空化区域减小77%。

关键词：滑动轴承空化现象计算流体力学图像处理高速摄影技术

基于NSGA-Ⅲ算法的低比转速离心泵多目标优化设计

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中国机械工程 2020年第18期31卷 2239-2246页

作者：童哲铭陈尧童水光余跃李进富郝国帅浙江大学机械工程学院杭州310027 杭州碱泵有限公司杭州310027 沈阳透平机械股份有限公司沈阳110869

为提高IJ125-100-400-00型低比转速离心泵的水力性能,采用基于参考点的非支配排序遗传算法(NSGA-Ⅲ)结合近似模型、数值模拟等方法对叶片进行了多目标优化。根据水力损失模型和灵敏度分析结果,选取叶轮出口宽度、叶轮出口直径以及叶轮... 详细信息

为提高IJ125-100-400-00型低比转速离心泵的水力性能,采用基于参考点的非支配排序遗传算法(NSGA-Ⅲ)结合近似模型、数值模拟等方法对叶片进行了多目标优化。根据水力损失模型和灵敏度分析结果,选取叶轮出口宽度、叶轮出口直径以及叶轮出口角度3个参数作为设计变量;使用拉丁超立方抽样随机生成了60组设计方案,针对非简化模型进行了数值模拟,得到了对应的外特性值,并建立了高效的BP神经网络近似模型;最终采用NSGA-Ⅲ算法对近似模型进行了多目标寻优,得到了最优设计变量组合。研究结果表明:初始模型的数值模拟结果与实验值具有很好的一致性,两者在额定工况下扬程的绝对误差小于2.14%;BP神经网络拟合预测效果良好;优化后的离心泵水力效率提高了6.86%,扬程满足设计需求,泵内部流场明显改善。

关键词：离心泵数值模拟神经网络多目标优化 NSGA-Ⅲ算法