scholarly journals Coherent resistance of a disordered one-dimensional wire:  Expressions for all moments and evidence for non-Gaussian distribution

2003 ◽  
Vol 67 (16) ◽  
Author(s):  
Pavel Vagner ◽  
Peter Markoš ◽  
Martin Moško ◽  
Thomas Schäpers
Keyword(s):  
Gaussian Distribution ◽  
One Dimensional ◽  
Non Gaussian

scholarly journals Timing of Pubertal Onset in Girls: Evidence for Non-Gaussian Distribution

2008 ◽  
Vol 93 (11) ◽  
pp. 4422-4425 ◽  
Author(s):  
Anastasios Papadimitriou ◽  
Soula Pantsiotou ◽  
Konstandinos Douros ◽  
Dimitrios T. Papadimitriou ◽  
Polyxeni Nicolaidou ◽  
...  
Keyword(s):  
Gaussian Distribution ◽  
Pubertal Onset ◽  
Non Gaussian

A simple model of a one-dimensional, randomly rough, non-Gaussian surface

2016 ◽  
Author(s):  
E. R. Méndez ◽  
G. D. Jiménez ◽  
A. A. Maradudin
Keyword(s):  
Simple Model ◽  
One Dimensional ◽  
Non Gaussian ◽  
Gaussian Surface

scholarly journals Fatigue Life Analysis of Aluminum Alloy Notched Specimens under Non-Gaussian Excitation based on Fatigue Damage Spectrum

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Kuanyu Chen ◽  
Guangwu Yang ◽  
Jianjun Zhang ◽  
Shoune Xiao ◽  
Yang Xu
Keyword(s):  
Aluminum Alloy ◽  
Fatigue Life ◽  
Fatigue Damage ◽  
Relative Error ◽  
Gaussian Distribution ◽  
Calculation Method ◽  
Shaking Table ◽  
Notched Specimens ◽  
Acceleration Method ◽  
Non Gaussian

In this study, a non-Gaussian excitation acceleration method is proposed, using aluminum alloy notched specimens as a research object and measured acceleration signal of a certain airborne bracket, during aircraft flight as input excitations, based on the fatigue damage spectrum (FDS) theory. The kurtosis and skewness of the input signal are calculated and the non-Gaussian characteristics and amplitude distribution are evaluated. Five task segments obey a non-Gaussian distribution, while one task segment obeys a Gaussian distribution. The fatigue damage spectrum calculation method of non-Gaussian excitation is derived. The appropriate FDS calculation method is selected for each task segment and the acceleration parameters are set to construct the acceleration power spectral density, which is equivalent to the pseudo-acceleration damage. A finite-element model is established, the notch stress concentration factor of the specimen is calculated, the large mass point method is used to simulate the shaking table excitation, and a random vibration analysis is carried out to calculate the accelerated fatigue life. The simulation results show that the relative error between the original cumulative damage and test original fatigue life is 15.7%. The shaking table test results show that the relative error of fatigue life before and after acceleration is less than 16.95%, and the relative error of test and simulation is 24.27%. The failure time of the specimen is accelerated from approximately 12 h to 1 h, the acceleration ratio reaches 12, and the average acceleration ideal factor is 1.125, which verifies the effectiveness of the acceleration method. It provides a reference for the compilation of the load spectrum and vibration endurance acceleration test of other airborne aircraft equipment.

scholarly journals The Spectral Power Density and Shadowing Function of a Glacial Microrelief at the Decimetre Scale

1979 ◽  
Vol 23 (89) ◽  
pp. 57-66 ◽  
Author(s):  
J.-P. Benoist
Keyword(s):  
Power Density ◽  
Gaussian Distribution ◽  
Spectral Power ◽  
Spectral Power Density ◽  
Total Length ◽  
Theoretical Function ◽  
Significant Difference ◽  
Longitudinal Profiles ◽  
Non Gaussian

Abstract Longitudinal profiles of roches moutonnées have been measured once every centimetre over a total length of more than 100 m. Only wavelengths in the range 3.6 cm < λ < 40 cm have been kept and analysed. Levels and their slopes have a symmetrical, non-Gaussian distribution. The spectral power density varies roughly as γ 0 ν–n (ν ═ wavenumber ═ 1/λ); n being the same for all the profiles (n ═ 2.36) and γ 0 being dependent on the studied area. No significant difference has been found for the shadowing function of the different studied areas. It differs consistently from Smith’s theoretical function.

Study on the mutual influence of surface roughness and texture features of rough-textured surfaces on the tribological properties

2020 ◽  
pp. 135065012094021
Author(s):  
Chunxing Gu ◽  
Xianghui Meng ◽  
Shuwen Wang ◽  
Xiaohong Ding
Keyword(s):  
Surface Roughness ◽  
Tribological Properties ◽  
Gaussian Distribution ◽  
Mutual Influence ◽  
Surface Texturing ◽  
Texture Features ◽  
Tribological Performance ◽  
Mixed Lubrication ◽  
Non Gaussian ◽  
Skewness And Kurtosis

In recent years, the efforts to better control friction and wear have focused on surface topography modification through surface texturing. To study the mutual influence of surface roughness and texture features, this paper developed one comprehensive mathematical model of mixed lubrication to study the tribological performance of the rough-textured conjunction. The typical ring-liner conjunction was chosen as the research object. In particular, the effects of skewness and kurtosis were considered based on the non-Gaussian distribution of asperity height. In this way, the influences of non-Gaussian distribution properties and surface texturing on the tribological performance were analyzed. The results show that the influences of skewness and kurtosis on the tribological performance are nontrivial and should not be neglected in the mixed lubrication. Compared to the Gaussian distribution, considering the non-Gaussian distribution can represent the physical rough surfaces more accurately. Surfaces with negative skewness were found to generally result in better tribological properties. Moreover, the tribological performance improved by surface texturing can also be improved or reduced by the effect of skewness and kurtosis. As a result, the optimization of surface texturing should take the effects of roughness parameters into account.

Parameterizations and Parameters Relations of Stable Distribution

2014 ◽  
Vol 543-547 ◽  
pp. 1721-1727 ◽  
Author(s):  
Chun Li Liu ◽  
Hai Long Chen ◽  
Lei Shao ◽  
Jun Ting Wang ◽  
Cheng Ji You
Keyword(s):  
Numerical Calculation ◽  
Gaussian Distribution ◽  
Stable Distribution ◽  
Alpha Stable Distribution ◽  
Non Gaussian

For the problem of various non-Gaussian signals and noises have distinct spiky and impulsive characteristics in practice, which cannot be solved by Gaussian distribution, we focus on the Alpha stable distribution. This paper firstly sets forth the representation of standard parameterization, and gives some properties in this parameterization. Secondly, define a representation of the parameterization for the purpose of being suitable for numerical calculation and modeling, clears the meaning of each parameter, finds relations between parameters in these representations. Finally, analyze and prove the properties equally apply in this parameterization.

ENHANCEMENT OF INTRINSIC SPIKING COHERENCE BY EXTERNAL NON-GAUSSIAN NOISE IN A STOCHASTIC HODGKIN–HUXLEY NEURON

2011 ◽  
Vol 10 (04) ◽  
pp. 359-369 ◽  
Author(s):  
LI WANG ◽  
YUBING GONG ◽  
XIU LIN
Keyword(s):  
Information Processing ◽  
Gaussian Distribution ◽  
Gaussian Noise ◽  
Correlation Time ◽  
Temporal Coherence ◽  
Channel Noise ◽  
Coherence Resonance ◽  
Non Gaussian ◽  
Proper Values ◽  
Membrane Patch

In this paper, we study the effect of external non-Gaussian noise on the temporal coherence of the intrinsic spiking induced by the channel noise in a stochastic Hodgkin–Huxley neuron. It is found that, for a sufficiently large membrane patch, the intrinsic spiking coherence can be enhanced by the proper values of non-Gaussian noise's strength, correlation time, or deviation from Gaussian distribution. And that the intrinsic spiking can exhibit coherence resonance when the noise's strength is optimal. This implies that the channel noise-induced intrinsic spiking may become more or the most ordered in time with the assistance of the external non-Gaussian noise. These results show that the external non-Gaussian noise can play a constructive role for improving the time precision of information processing in stochastic neurons.

scholarly journals A Non-Gaussian Distribution Quantifies Distances Measured with Fluorescence Localization Techniques

2006 ◽  
Vol 90 (2) ◽  
pp. 668-671 ◽  
Author(s):  
L. Stirling Churchman ◽  
Henrik Flyvbjerg ◽  
James A. Spudich
Keyword(s):  
Gaussian Distribution ◽  
Non Gaussian
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