Simulating nonstationary and non‐Gaussian vector ground motions with time‐ and frequency‐dependent lagged coherence

2021 ◽  
Author(s):  
X. Z. Cui ◽  
H. P. Hong
Keyword(s):  
Ground Motions ◽  
Gaussian Vector ◽  
Frequency Dependent ◽  
Non Gaussian

scholarly journals Near-surface frequency-dependent nonlinear damping ratio observation of ground motions using SMART1

2021 ◽  
Vol 147 ◽  
pp. 106798
Author(s):  
Chun-Hsiang Kuo ◽  
Jyun-Yan Huang ◽  
Che-Min Lin ◽  
Chun-Te Chen ◽  
Kuo-Liang Wen
Keyword(s):  
Ground Motions ◽  
Damping Ratio ◽  
Nonlinear Damping ◽  
Frequency Dependent ◽  
Near Surface

scholarly journals Non-Gaussian Stochastic Equivalent Linearization Method for Inelastic Nonlinear Systems with Softening Behaviour, under Seismic Ground Motions

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Francisco L. Silva-González ◽  
Sonia E. Ruiz ◽  
Alejandro Rodríguez-Castellanos
Keyword(s):  
Monte Carlo ◽  
Ground Motions ◽  
Joint Probability ◽  
Structural Response ◽  
Linearization Method ◽  
Degree Of Freedom ◽  
Structural Behavior ◽  
Equivalent Linearization ◽  
Equivalent Linearization Method ◽  
Non Gaussian

A non-Gaussian stochastic equivalent linearization (NSEL) method for estimating the non-Gaussian response of inelastic non-linear structural systems subjected to seismic ground motions represented as nonstationary random processes is presented. Based on a model that represents the time evolution of the joint probability density function (PDF) of the structural response, mathematical expressions of equivalent linearization coefficients are derived. The displacement and velocity are assumed jointly Gaussian and the marginal PDF of the hysteretic component of the displacement is modeled by a mixed PDF which is Gaussian when the structural behavior is linear and turns into a bimodal PDF when the structural behavior is hysteretic. The proposed NSEL method is applied to calculate the response of hysteretic single-degree-of-freedom systems with different vibration periods and different design displacement ductility values. The results corresponding to the proposed method are compared with those calculated by means of Monte Carlo simulation, as well as by a Gaussian equivalent linearization method. It is verified that the NSEL approach proposed herein leads to maximum structural response standard deviations similar to those obtained with Monte Carlo technique. In addition, a brief discussion about the extension of the method to muti-degree-of-freedom systems is presented.

Simulating a non-Gaussian vector process with application in hydrology

2014 ◽  
Vol 41 (6) ◽  
pp. 621-626 ◽  
Author(s):  
A. V. Frolov ◽  
T. Yu. Vyruchalkina ◽  
I. V. Solomonova
Keyword(s):  
Gaussian Vector ◽  
Vector Process ◽  
Non Gaussian

scholarly journals Deploying dengue-suppressing Wolbachia: robust models predict slow but effective spatial spread in Aedes aegypti

2016 ◽  
Author(s):  
Michael Turelli ◽  
Nicholas H. Barton
Keyword(s):  
Aedes Aegypti ◽  
Temporal Dynamics ◽  
Target Area ◽  
Long Distance ◽  
Frequency Dependent ◽  
Spatial Spread ◽  
Frequency Independent ◽  
Dispersal Distances ◽  
Novel Strategy ◽  
Non Gaussian

AbstractA novel strategy for controlling the spread of arboviral diseases such as dengue, Zika and chikungunya is to transform mosquito populations with virus-suppressing Wolbaehia. In general, Wolbachia transinfected into mosquitoes induce fitness costs through lower viability or fecundity. These maternally inherited bacteria also produce a frequency-dependent advantage for infected females by inducing cytoplasmic incompatibility (CI), which kills the embryos produced by uninfected females mated to infected males. These competing effects, a frequency-dependent advantage and frequency-independent costs, produce bistable Wolbachia frequency dynamics. Above a threshold frequency, denoted p̂, CI drives fitness-decreasing Wolbachia transinfections through local populations; but below p̂, infection frequencies tend to decline to zero. If p̂ is not too high, CI also drives spatial spread once infections become established over sufficiently large areas. We illustrate how simple models provide testable predictions concerning the spatial and temporal dynamics of Wolbachia introductions, focusing on rate of spatial spread, the shape of spreading waves, and the conditions for initiating spread from local introductions. First, we consider the robustness of diffusion-based predictions to incorporating two important features of wMel-Aedes aegypti biology that may be inconsistent with the diffusion approximations, namely fast local dynamics induced by complete CI (i.e., all embryos produced from incompatible crosses die) and long-tailed, non-Gaussian dispersal. With complete CI, our numerical analyses show that long-tailed dispersal changes wave-width predictions only slightly; but it can significantly reduce wave speed relative to the diffusion prediction; it also allows smaller local introductions to initiate spatial spread. Second, we use approximations for p̂ and dispersal distances to predict the outcome of 2013 releases of wMel-infected Aedes aegypti in Cairns, Australia, Third, we describe new data from Aedes aegypti populations near Cairns, Australia that demonstrate long-distance dispersal and provide an approximate lower bound on p̂ for wMel in northeastern Australia. Finally, we apply our analyses to produce operational guidelines for efficient transformation of vector populations over large areas. We demonstrate that even very slow spatial spread, on the order of 10-20 m/month (as predicted), can produce area-wide population transformation within a few years following initial releases covering about 20-30% of the target area.

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