About Dynamics of Muffs from Physically Nonlinear Material

2013 ◽  
Vol 702 ◽  
pp. 291-296
Author(s):  
Lelya Khajiyeva ◽  
Almatbek Kydyrbekuly
Keyword(s):  
Experimental Data ◽  
Torsional Oscillation ◽  
Physical Nature ◽  
Nonlinear Material ◽  
Dynamic Processes ◽  
Nonlinear Characteristics ◽  
Nonlinear Properties ◽  
Physically Nonlinear Material ◽  
Rotating Shafts ◽  
Nonlinear Dynamic Processes

The paper is devoted to simulation of nonlinear dynamic processes in mechanical systems with nonlinear characteristics of the physical nature. As an example torsional oscillation of rubber-cord muff, which connects rotating shafts of a drive of machines, is investigated. Influence of nonlinear properties of a muff on amplitude-frequency characteristics of a kinematic circuit is established. The research results are in accord with experimental data of other works.

Probability Bounds Analysis Applied to the Sandia Verification and Validation Challenge Problem

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Aniruddha Choudhary ◽  
Ian T. Voyles ◽  
Christopher J. Roy ◽  
William L. Oberkampf ◽  
Mayuresh Patil
Keyword(s):  
Experimental Data ◽  
Physical Nature ◽  
Distribution Functions ◽  
Verification And Validation ◽  
Cumulative Distribution ◽  
Probability Bounds ◽  
Model Form ◽  
Interval Representation ◽  
Model Predictions ◽  
True System

Our approach to the Sandia Verification and Validation Challenge Problem is to use probability bounds analysis (PBA) based on probabilistic representation for aleatory uncertainties and interval representation for (most) epistemic uncertainties. The nondeterministic model predictions thus take the form of p-boxes, or bounding cumulative distribution functions (CDFs) that contain all possible families of CDFs that could exist within the uncertainty bounds. The scarcity of experimental data provides little support for treatment of all uncertain inputs as purely aleatory uncertainties and also precludes significant calibration of the models. We instead seek to estimate the model form uncertainty at conditions where the experimental data are available, then extrapolate this uncertainty to conditions where no data exist. The modified area validation metric (MAVM) is employed to estimate the model form uncertainty which is important because the model involves significant simplifications (both geometric and physical nature) of the true system. The results of verification and validation processes are treated as additional interval-based uncertainties applied to the nondeterministic model predictions based on which the failure prediction is made. Based on the method employed, we estimate the probability of failure to be as large as 0.0034, concluding that the tanks are unsafe.

scholarly journals Research on MRD Parametric Model Based on Magic Formula

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Wei Pan ◽  
Zhengtao Yan ◽  
Jingjun Lou ◽  
Shijian Zhu
Keyword(s):  
Experimental Data ◽  
Working Conditions ◽  
Parametric Model ◽  
Parametric Modelling ◽  
Loop Model ◽  
Magnetorheological Dampers ◽  
Nonlinear Characteristics ◽  
Magic Formula ◽  
Parameterized Model ◽  
General Method

In order to get a better description to the nonlinear characteristics of magnetorheological dampers, the magic formula is introduced into the general method of parametric modelling of magnetorheological dampers to propose a new parameterized model called magic formula-hysteresis loop model (MFM). The new model is simple in structure, the physical meaning of each parameter is clear, and the parameter identification is convenient. The fitting and experimental data of MFM and the phenomenon model under different conditions are applied for error analysis and comparison. The results show that the errors of MFM are more accurate and have better fitting and experimental data under different working conditions, which also have better adaptability and versatility.

Near-Epoch Dependence

2021 ◽  
pp. 368-398
Author(s):  
James Davidson
Keyword(s):  
Theoretical Result ◽  
Nonlinear Dynamic ◽  
Dynamic Processes ◽  
Related Concept ◽  
Mixing Processes ◽  
Special Result ◽  
Nonlinear Dynamic Processes

Near‐epoch dependence (NED) is a generalized dependence concept for functions of mixing processes. This chapter gives definitions and examples, and considers the application to nonlinear dynamic processes. The relation to mixingales is the key theoretical result. Results on the preservation of NED under various transformations and a special result for the adapted sequence case are considered next. Finally, the related concept of approximability is defined which, unlike NED, can hold in the absence of integer moments.

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