نتایج جستجو برای: divergence instability

تعداد نتایج: 136264  

M. Abbasnejad, M. Tavakoli, N. R. Arghami,

In this paper, we introduce a goodness of fit test for expo- nentiality based on Lin-Wong divergence measure. In order to estimate the divergence, we use a method similar to Vasicek’s method for estimat- ing the Shannon entropy. The critical values and the powers of the test are computed by Monte Carlo simulation. It is shown that the proposed test are competitive with other tests of exponentia...

1996
F. Bernardeau R. van de Weygaert F. R. Bouchet

We present a series of results investigating the Ω dependence of the distribution function of the large scale local cosmic velocity divergence, ∇ · v. Analytical studies using perturbation theory techniques indicate that the shape of this distribution should be strongly dependent on Ω. This dependence is all the more interesting as it does not involve biases of the galaxy distribution with resp...

Journal: :journal of heat and mass transfer research(jhmtr) 2014
mohammad hadi hamedi estakhrsar mehdi jahromi

compressible gas flow inside a convergent-divergent nozzle and its exhaust plume atdifferent nozzle pressure ratios (npr) have been numerically studied with severalturbulence models. the numerical results reveal that, the sst k–ω model give the bestresults compared with other models in time and accuracy. the effect of changes in value ofdivergence half-angle (ε ) on the nozzle performance, thru...

Dariush Mokhtari Kajori, Reza Jamkarani

This research aims to investigate the effect of conservative reporting on the investors' opinion divergence at the time of earnings announcement in a 5 year period during 2012-2016; the required data have been collected from Tehran Securities and Stock Exchange Organization and the population is consisted of 585 corporates-years which have been selected by the systematic removal sampling. To in...

Journal: :Physics of Fluids 2022

Reynolds-averaged Navier-Stokes simulations are still the main method to study complex flows in engineering. However, traditional turbulence models cannot accurately predict flow fields with separations. In such situation, machine learning methods provide an effective way build new data-driven closure models. Nevertheless, a bottleneck that encounter is how ensure stability and convergence of R...

1992
P. Rouchon

Following some Arnol’d results relative to the geometry underlying the dynamics of a perfect incompressible fluid [3] (geodesics of left-invariant metrics on Lie groups), the linear differential equation relative to a Lagrangian stability analysis are established. This differential equation, called Jacobi equation, describes, for the same fluid element, the time evolution of the difference betw...

ژورنال: اندیشه آماری 2020
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The minimum density power divergence method provides a robust estimate in the face of a situation where the dataset includes a number of outlier data. In this study, we introduce and use a robust minimum density power divergence estimator to estimate the parameters of the linear regression model and then with some numerical examples of linear regression model, we show the robustness of this est...

Journal: :acta medica iranica 0
mm. tahmasbi aa. amis f. farahmand

the resistant* of patesa against lateral displacement (le. the stability), was studied tinder a range of conditions in vitro, at a range of knee flexion angles. muscle forces were applied in physiological directions along the separate quadriceps muscles. normal muscle actions with constant tension showed constant patellar stability up to sixty degrees knee flexion, and then a significant increa...

Journal: :Journal of Fluid Mechanics 2023

The two-dimensional stability of vertically sheared inertial oscillations at ocean fronts is explored through a linear analysis and nonlinear simulations. Baroclinic effects reduce the minimum frequency inertia-gravity waves to an extent determined by balanced Richardson number ${{Ri}}$ front. Below critical value , which depends on strength shear, become unstable parametric subharmonic instabi...

Journal: :Proceedings of the ... AAAI Conference on Artificial Intelligence 2023

Offline imitation learning (IL) promises the ability to learn performant policies from pre-collected demonstrations without interactions with environment. However, imitating behaviors fully offline typically requires numerous expert data. To tackle this issue, we study setting where have limited data and supplementary suboptimal In case, a well-known issue is distribution shift between learned ...

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