Forced Convective Boiling Model of Water by Laser

Jifeng, 魏继锋 Wei; Xueyan, 高学燕 Gao; Kai, 张凯 Zhang; Shan, 周山 Zhou; Junzhang, 何均章 He; Youguang, 关有光 Guan

doi:10.3788/gzxb20103908.1438

Cited by 9 publications

(3 citation statements)

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“…Fig 2 is the topography and dimensions of the elliptical surface indentations. The depth of notch b is varied from 1 to 12μm, the ratio of width to depth of notch a/b is from 2 to 10, and the distance d between two adjacent notches on the surface fluctuates is between 2 to 10 times the width a [11].…”

Section: Fe Model With Surface Micro-notchmentioning

confidence: 99%

“…Andrews et al [10] proposed a relationship between stress concentration factor and micro-notch parameters by simplifying surface roughness into general semi-elliptical notches. Zhang et al and Liao et al [11,12] established quantitative relationship between surface roughness and surface stress concentration factor by a semi-elliptical micro-notch characterization model, and determined its effect on fatigue life. However, the stress concentration factor K t in those studies was not verified by measured surface topography.…”

Section: Introductionmentioning

confidence: 99%

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Fatigue life analysis for 6061-T6 aluminum alloy based on surface roughness

et al. 2021

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Surface condition is one of the dominant factors affecting fatigue life. Considering the complexity of surface condition, a relatively efficient and economic approach based on surface reconstruction and interpolation method was proposed. The effect of surface roughness on the fatigue life of 6061-T6 aluminum alloy is studied to analyze the fatigue life by surface roughness parameters. Surface topography was simplified into a series of elliptic micro notches, and empirical formula for stress concentration factor is established based on simulation work. Then the extraction method of surface curve is proposed to effectively represent the real surface roughness through 3D model reconstruction. Experiment of surface roughness verified the correctness of the model. The relationship between surface roughness and fatigue life is established and the calculated value of the fatigue life is compared with the test results. The maximum error is 15.65%, indicating that the formula established is reasonable and effective.

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Section: Fe Model With Surface Micro-notchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fatigue life analysis for 6061-T6 aluminum alloy based on surface roughness

et al. 2021

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“…The simulation results show that the control method can effectively reduce the impact of track disturbance and electromagnetic load disturbance on the system. Li [6] and Li [7] analyzed the characteristics of classical PID control and fuzzy control, and introduced the method that the quantitative factor of fuzzy control can make the scaling change. The genetic algorithm is used to optimize the parameters of the expansion factor, so that the parameters of the controller can be adjusted online according to the dynamic performance of the system.…”

Section: H ∞ Control Theory Proposed By Zames and Doyle Is Anmentioning

confidence: 99%

Sliding Mode Robust Adaptive Control of Maglev Vehicle’s Nonlinear Suspension System Based on Flexible Track: Design and Experiment

Chen

et al. 2019

IEEE Access

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The suspension system of Maglev vehicle needs strong robustness and anti-jamming ability in the process of operation and fluctuation control. In order to solve the open-loop instability and strong nonlinearity of the mechanical equation of the suspension system of the Maglev vehicle, the non-linear dynamic equation is established. At present, the research based on the single electromagnet and the rigid track is the most common. However, based on this method, it is impossible to study the coupled vibration caused by track factors. Therefore, based on the dynamic equation of a single span simply supported beam of flexible track and the non-linear equation of the suspended electromagnet itself, an overall control model is needed to discuss the control strategy. Based on this dynamic model, the singularities of the system are solved according to Hurwitz criterion, and the characteristic equation corresponding to the Jacobian matrix is obtained. The stability analysis shows that the system is unstable. At the same time, the necessity of using a feedback control method to control the air gap has been proved. On this basis, a sliding mode adaptive state feedback controller for the maglev system is designed based on the RBF network approximation principle. The corresponding simulation and experimental results are given. The simulation and experimental results show that the controller can ensure the vehicle's stable suspension and effectively suppress external interference. Compared with the traditional PID and fuzzy controllers, the controller can guarantee a faster dynamic response, stronger robustness, and smaller overshoot while considering the flexible track and external disturbances. INDEX TERMS Maglev system, flexible track, coupled vibration, RBF, sliding mode adaptive control.

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