scholarly journals Неравновесная кинетика начальной стадии фазового перехода

2020 ◽  
Vol 62 (1) ◽  
pp. 40
Author(s):  
Г.И. Змиевская

Kinetic partial differential equations of Kolmogorov-Feller and Einstein-Smoluchowski equation with nonlinear coefficients are solved by a new, stable numerical methods. The theory of stochastic dynamic variables establishes the connection of the solution of Ito stochastic equations in the sense of Stratonovich for the trajectories of Wiener random processes with the transition probability density of these processes, or distribution functions of kinetic equations. The classical theory of nucleation (formation of nuclei of the first order phase transition) describes a non-equilibrium stage of the condensation process by a diffusion random process in the space of the size of the nuclei of the phase transition, when fluctuations affect the clustering of the nuclei. The model of formation of vacancy-gas defects (pores, blisters) in the crystal lattice, arising as a result of its irradiation by inert gas ions xenon, is supplemented by the consideration of Brownian motion of non-point lattice defects, occurring under the action of superposition of paired long-range potentials of indirect elastic interaction of pores between themselves and with the boundaries of the layers. Pores coordinates are changing at times of the order of 10 − 100 ms, sustainable algorithms for calculating which provide a self-consistent defnition spatial - temporal structures of porosity in the sample. According to calculations of 106 trajectories, non-equilibrium kinetic functions were found. Pores distribution in size and coordinates in the layers of the irradiated materials, they characterize the fluctuation instability the initial stage of the phase transition, they are estimated local stresses and porosity in the model volume.

Author(s):  
Jun Jason Zhang ◽  
Wenfan Zhou ◽  
Narayan Kovvali ◽  
Antonia Papandreou-Suppappola ◽  
Aditi Chattopadhyay

The use of the posterior Crame´r-Rao lower bound (PCRLB) as a lower bound for the mean-squared estimation error (MSEE) of progressive damage is investigated. The estimation problem is formulated in terms of a stochastic dynamic system model that describes the random evolution of damage and provides measurement uncertainty. Based on whether the system is linear or nonlinear, sequential Monte Carlo techniques are used to approximate the posterior probability density function and thus obtain the damage state estimate. The resulting MSEE is compared to the lower bound offered by the PCRLB that is obtained from the implied state transition probability density function and the measurement likelihood function. The progressive estimation results and the PCRLB are demonstrated for fatigue crack estimation in an aluminum compact-tension (CT) sample subjected to variable-amplitude loading.


2015 ◽  
Vol 0 (0) ◽  
Author(s):  
Victoria Knopova ◽  
Alexei Kulik

AbstractIn this paper, we show that a non-local operator of certain type extends to the generator of a strong Markov process, admitting the transition probability density. For this transition probability density we construct the intrinsic upper and lower bounds, and prove some smoothness properties. Some examples are provided.


2021 ◽  
Vol 81 (9) ◽  
Author(s):  
Ziyue Wang ◽  
Xingyu Guo ◽  
Pengfei Zhuang

AbstractAs the core ingredient for spin polarization, the equilibrium spin distribution function that eliminates the collision terms is derived from the detailed balance principle. The kinetic theory for interacting fermionic systems is applied to the Nambu–Jona-Lasinio model at quark level. Under the semi-classical expansion with respect to $$\hbar $$ ħ , the kinetic equations for the vector and axial-vector distribution functions are obtained with collision terms. For an initially unpolarized system, spin polarization can be generated at the first order of $$\hbar $$ ħ from the coupling between the vector and axial-vector charges. Different from the classical transport theory, the collision terms in a quantum theory vanish only in global equilibrium with Killing condition.


2019 ◽  
Author(s):  
Richard Mandle ◽  
John W. Goodby

We compare the order parameters, orientational distribution functions (ODF) and heliconical tilt angles of the TB phase exhibited by a liquid-crystalline dimer (CB7CB) to a tetramer (O47) and hexamer (O67) by SAXS/WAXS. Following the N-TB phase transition we find that all order parameters decrease, and while 〈P2 〉 remains positive 〈P4 〉 becomes negative. For all three materials the order parameter 〈P6 〉 is near zero in both phases. The ODF is sugarloaf-like in the nematic phase and volcano-like in the TB phase, allowing us to estimate the heliconical tilt angle of each material and its thermal evolution. The heliconical tilt angle appears to be largely independent of the material studied despite the differing number of mesogenic units.


1992 ◽  
Vol 29 (2) ◽  
pp. 334-342
Author(s):  
A. Milian

We show that under some assumptions a diffusion process satisfying a one-dimensional Itô's equation has a transition probability density concentrated on a finite spatial interval. We give a formula for this density.


Author(s):  
Zhangyi He ◽  
Mark Beaumont ◽  
Feng Yu

AbstractOver the past decade there has been an increasing focus on the application of the Wright-Fisher diffusion to the inference of natural selection from genetic time series. A key ingredient for modelling the trajectory of gene frequencies through the Wright-Fisher diffusion is its transition probability density function. Recent advances in DNA sequencing techniques have made it possible to monitor genomes in great detail over time, which presents opportunities for investigating natural selection while accounting for genetic recombination and local linkage. However, most existing methods for computing the transition probability density function of the Wright-Fisher diffusion are only applicable to one-locus problems. To address two-locus problems, in this work we propose a novel numerical scheme for the Wright-Fisher stochastic differential equation of population dynamics under natural selection at two linked loci. Our key innovation is that we reformulate the stochastic differential equation in a closed form that is amenable to simulation, which enables us to avoid boundary issues and reduce computational costs. We also propose an adaptive importance sampling approach based on the proposal introduced by Fearnhead (2008) for computing the transition probability density of the Wright-Fisher diffusion between any two observed states. We show through extensive simulation studies that our approach can achieve comparable performance to the method of Fearnhead (2008) but can avoid manually tuning the parameter ρ to deliver superior performance for different observed states.


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