scholarly journals A Study on Time-Varying Inertia Properties Estimation Using Dynamic Model Compensation

2020 ◽  
Vol 63 (4) ◽  
pp. 183-186
Author(s):  
Jisung LIM ◽  
Sungwook YANG ◽  
Cheongeon PARK ◽  
Sangchul LEE
Keyword(s):  
Dynamic Model ◽  
Time Varying ◽  
Inertia Properties

Dynamic Analysis of Mechanical Systems With Time-Varying Topologies: Part 1 — Dynamic Model and Stability Analysis

1990 ◽  
Author(s):  
Yu Wang
Keyword(s):  
Stability Analysis ◽  
Dynamic Model ◽  
Local Stability ◽  
Global Analysis ◽  
Equations Of Motion ◽  
Mechanical Systems ◽  
Time Varying ◽  
Discrete Equations ◽  
Local Stability Analysis ◽  
Multiple Collisions

Abstract A model is developed for analyzing mechanical systems with a pair of bodies with topological changes in their kinematic constraints. It is built upon the concept of Poincaré map rather than following the traditional methods of differential equations. The model provides a set of well-defined and naturally-discrete equations of motion and is capable of giving physical insights of dynamic characteristics of deadbeat convergence of multiple collisions and periodic or chaotic responses. The development of dynamic model and a local stability analysis are presented in Part 1, and the global analysis and numerical simulation are discussed in Part 2.

scholarly journals Forecasting Carbon Emissions with Dynamic Model Averaging Approach: Time-Varying Evidence from China

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Siqi Xu ◽  
Yifeng Zhang ◽  
Xiaodan Chen
Keyword(s):  
Carbon Dioxide ◽  
Dynamic Model ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Predictive Power ◽  
Carbon Dioxide Emission ◽  
Model Averaging ◽  
Predictive Ability ◽  
Time Varying ◽  
Dynamic Model Averaging

Although energy-related factors, such as energy intensity and energy consumption, are well recognized as major drivers of carbon dioxide emission in China, little is known about the time-varying impacts of other macrolevel nonenergy factors on carbon emission, especially those from macroeconomic, financial, household, and technology progress indicators in China. This paper contributes to the literature by investigating the time-varying predictive ability of 15 macrolevel indicators for China’s carbon dioxide emission from 1982 to 2017 with a dynamic model averaging (DMA) method. The empirical results show that, firstly, the explanatory power of each nonenergy predictor changes significantly with time and no predictor has a stable positive/negative impact on China’s carbon emissions throughout the whole sample period. Secondly, all these predictors present a distinct predictive ability for carbon emission in China. The proportion of industry production in GDP (IP) shows the greatest predictive power, while the proportion of FDI in GDP has the smallest forecasting ability. Interestingly, those Chinese household features, such as Engel’s coefficient and household savings rate, play very important roles in the prediction of China’s carbon emission. In addition, we find that IP are losing its predictive power in recent years, while the proportion of value-added of the service sector in GDP presents not only a leading forecasting weight, but a continuous increasing prediction power in recent years. Finally, the dynamic model averaging (DMA) method can produce the most accurate forecasts of carbon emission in China compared to other commonly used forecasting methods.

scholarly journals Structural analysis for dynamic model of time‐varying switch in bond graph – a case study of single phase switch converters

2017 ◽  
Vol 10 (7) ◽  
pp. 756-766
Author(s):  
Kuo‐Hsiung Tseng ◽  
Tuo‐Wen Chang ◽  
Ming‐Fu Hung ◽  
Kuan‐Wen Chen
Keyword(s):  
Structural Analysis ◽  
Dynamic Model ◽  
Single Phase ◽  
Bond Graph ◽  
Time Varying

scholarly journals Dynamic Model of Spur Gear Pair with Modulation Internal Excitation

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Zhong Wang ◽  
Lei Zhang ◽  
Yuan-Qing Luo ◽  
Chang-Zheng Chen
Keyword(s):  
Dynamic Model ◽  
Transmission Error ◽  
Spur Gear ◽  
Experimental Result ◽  
Time Varying ◽  
Gear Pair ◽  
Mesh Stiffness ◽  
Gear Mesh ◽  
Internal Excitation ◽  
Modulation Sideband

In the actual measurements, vibration and noise spectrum of gear pair often exhibits sidebands around the gear mesh harmonic orders. In this study, a nonlinear time-varying dynamic model of spur gear pair was established to predict the modulation sidebands caused by the AM-FM modulation internal excitation. Here, backlash, modulation time-varying mesh stiffness, and modulation transmission error are considered. Then the undamped natural mode was studied. Numerical simulation was made to reveal the dynamic characteristic of a spur gear under modulation condition. The internal excitation was shown to exhibit obvious modulation sideband because of the modulation time-varying mesh stiffness and modulation transmission error. The Runge-Kutta method was used to solve the equations for analyzing the dynamic characteristics with the effect of modulation internal excitation. The result revealed that the response under modulation excitation exhibited obvious modulation sideband. The response under nonmodulation condition was also calculated for comparison. In addition, an experiment was done to verify the prediction of the modulation sidebands. The calculated result was consistent with the experimental result.

Dynamic Model of a Sac-Type Pneumatically Driven Artificial Ventricle

1977 ◽  
Vol 99 (1) ◽  
pp. 14-19 ◽  
Author(s):  
D. B. Geselowitz ◽  
G. E. Miller ◽  
W. M. Phillips
Keyword(s):  
Dynamic Model ◽  
Circulatory System ◽  
Operating Conditions ◽  
Time Varying ◽  
Outlet Port ◽  
Mock Circulatory System ◽  
Linear Resistance ◽  
Wide Range ◽  
Artificial Ventricle ◽  
Nonlinear Resistance

Inlet and outlet pressures and flows were obtained over a wide range of operating conditions for a pneumatically driven sac-type artificial ventricle connected to a mechanical mock circulatory system. The load presented to the ventricle by the mock circulatory system was found to be characterized by a linear resistance and capacitance. A dynamic model for the ventricle which accounted for instantaneous pressures and flows was developed. The outlet port is characterized by an inertance and square law resistance; the inlet port is characterized by a nonlinear resistance dependent on the type of valve. The input to the model is the time varying sac pressure. The model predicts the fill-limited and ejection-limited modes of the artificial ventricle.

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