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Ejector performance prediction at critical and subcritical operational modes
Li, Fenglei,Tian, Qi,Wu, Changzhi,Wang, Xiangyu,Lee, Jae-Myung Pergamon 2017 Applied thermal engineering Vol. No.
<P><B>Abstract</B></P> <P>Traditional ejector models are focusing on the ejector performance predictions at critical mode under design conditions. In reality, ejector systems cannot be operated under these conditions perfectly. Thus, the study of ejector performance at subcritical mode under off-design conditions is important. In this paper, novel models for ejector performance predictions at critical point and breakdown point are developed based on constant-pressure mixing and constant-pressure disturbing assumptions. Then, the two models are integrated as the model to predict ejector performance at critical and subcritical operational modes. In order to determine the ejector component efficiencies in the models, a novel concept, the effect of the change (EOC) of efficiency, is introduced to identify the efficiencies which affect ejector performance significantly. Then, the identified efficiencies are determined by sparsity-enhanced optimization method. The predicted results obtained by our model are much more accurate than those obtained by existing methods.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Novel models for ejector performance analysis at critical and breakdown points are developed. </LI> <LI> The models are integrated to predict ejector performance over entire operational range. </LI> <LI> An analysis method is developed for identifying the ejector component efficiencies. </LI> <LI> The performance prediction errors over entire operational range are within ±10%. </LI> </UL> </P>
Li, Jun,Hao, Hong,Fan, Gao,Ni, Pinghe,Wang, Xiangyu,Wu, Changzhi,Lee, Jae-Myung,Jung, Kwang-Hyo Techno-Press 2017 Smart Structures and Systems, An International Jou Vol.20 No.2
Identification of damping characteristics is of significant importance for dynamic response analysis and condition assessment of structural systems. Damping is associated with the behavior of the energy dissipation mechanism. Identification of damping ratios based on the sensitivity of dynamic responses and the model updating technique is investigated with numerical and experimental investigations. The effectiveness and performance of using the sensitivity-based model updating method and vibration monitoring data for damping ratios identification are investigated. Numerical studies on a three-dimensional truss bridge model are conducted to verify the effectiveness of the proposed approach. Measurement noise effect and the initial finite element modelling errors are considered. The results demonstrate that the damping ratio identification with the proposed approach is not sensitive to the noise effect but could be affected significantly by the modelling errors. Experimental studies on a steel planar frame structure are conducted. The robustness and performance of the proposed damping identification approach are investigated with real measured vibration data. The results demonstrate that the proposed approach has a decent and reliable performance to identify the damping ratios.
Jun Li,Hong Hao,Gao Fan,Pinghe Ni,Xiangyu Wang,Changzhi Wu,이제명,정광효 국제구조공학회 2017 Smart Structures and Systems, An International Jou Vol.20 No.2
Identification of damping characteristics is of significant importance for dynamic response analysis and condition assessment of structural systems. Damping is associated with the behavior of the energy dissipation mechanism. Identification of damping ratios based on the sensitivity of dynamic responses and the model updating technique is investigated with numerical and experimental investigations. The effectiveness and performance of using the sensitivity-based model updating method and vibration monitoring data for damping ratios identification are investigated. Numerical studies on a three-dimensional truss bridge model are conducted to verify the effectiveness of the proposed approach. Measurement noise effect and the initial finite element modelling errors are considered. The results demonstrate that the damping ratio identification with the proposed approach is not sensitive to the noise effect but could be affected significantly by the modelling errors. Experimental studies on a steel planar frame structure are conducted. The robustness and performance of the proposed damping identification approach are investigated with real measured vibration data. The results demonstrate that the proposed approach has a decent and reliable performance to identify the damping ratios.
Dynamic and static structural displacement measurement using backscattering DC coupled radar
Shanyue Guan,Jennifer A. Rice,Changzhi Li,Yiran Li,Guochao Wang 국제구조공학회 2015 Smart Structures and Systems, An International Jou Vol.16 No.3
Vibration-based monitoring is one approach used to perform structural condition assessment. By measuring structural response, such as displacement, dynamic characteristics of a structure may be estimated. Often, the primary dynamic responses in civil structures are below 5 Hz, making accurate low frequency measurement critical for successful dynamic characterization. In addition, static deflection measurements are useful for structural capacity and load rating assessments. This paper presents a DC coupled continuous wave radar to accurately detect both dynamic and static displacement. This low-cost radar sensor provides displacement measurements within a compact, wireless unit appropriate for a range of structural monitoring applications. The hardware components and operating mechanism of the radar are introduced and a series of laboratory experiments are presented to assess the performance characteristics of the radar. The laboratory and field experiments investigate the effect of factors such as target distance, motion amplitude, and motion frequency on the radar’s measurement accuracy. The results demonstrate that the radar is capable of both static and dynamic displacement measurements with sub-millimeter accuracy, making it a promising technology for structural health monitoring.