random field
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2022 ◽  
Vol 73 ◽  
pp. 103426
Author(s):  
Sunita Samant ◽  
Pradipta Kumar Nanda ◽  
Ashish Ghosh ◽  
Adya Kinkar Panda

2022 ◽  
Vol 15 (2) ◽  
pp. 549-566
Author(s):  
Omid Karimi ◽  
Fatemeh Hosseini ◽  
◽  

2022 ◽  
pp. 1-15
Author(s):  
Pranay Seshadri ◽  
Andrew Duncan ◽  
George Thorne

Abstract This paper introduces the Bayesian mass average and details its computation. Owing to the complexity of flow in an engine and the limited instrumentation and the precision of the sensor apparatus used, it is difficult to rigorously calculate mass averages. Building upon related work, this paper views any thermodynamic quantity's spatial variation at an axial plane in an engine (or a rig) as a Gaussian random field. In cases where the mass flow rate is constant in the circumferential direction but can be expressed via a polynomial or spline radially, this paper presents an analytical calculation of the Bayesian mass average. In cases where the mass flow rate itself can be expressed as a Gaussian random field, a sampling procedure is presented to calculate the Bayesian mass average. Examples of the calculation of the Bayesian mass average for temperature are presented, including with a real engine case study where velocity profiles are inferred from stagnation pressure measurements.


Author(s):  
Adrián Hinojosa-Calleja ◽  
Marta Sanz-Solé

AbstractConsider the linear stochastic biharmonic heat equation on a d–dimen- sional torus ($$d=1,2,3$$ d = 1 , 2 , 3 ), driven by a space-time white noise and with periodic boundary conditions: $$\begin{aligned} \left( \frac{\partial }{\partial t}+(-\varDelta )^2\right) v(t,x)= \sigma \dot{W}(t,x),\ (t,x)\in (0,T]\times {\mathbb {T}}^d, \end{aligned}$$ ∂ ∂ t + ( - Δ ) 2 v ( t , x ) = σ W ˙ ( t , x ) , ( t , x ) ∈ ( 0 , T ] × T d , $$v(0,x)=v_0(x)$$ v ( 0 , x ) = v 0 ( x ) . We find the canonical pseudo-distance corresponding to the random field solution, therefore the precise description of the anisotropies of the process. We see that for $$d=2$$ d = 2 , they include a $$z(\log \tfrac{c}{z})^{1/2}$$ z ( log c z ) 1 / 2 term. Consider D independent copies of the random field solution to (0.1). Applying the criteria proved in Hinojosa-Calleja and Sanz-Solé (Stoch PDE Anal Comp 2021. 10.1007/s40072-021-00190-1), we establish upper and lower bounds for the probabilities that the path process hits bounded Borel sets.This yields results on the polarity of sets and on the Hausdorff dimension of the path process.


2022 ◽  
Vol 64 (1) ◽  
pp. 3
Author(s):  
А.А. Берзин ◽  
А.И. Морозов ◽  
А.С. Сигов

The conditions for the appearance in systems with defects of the "random local field" and "random local anisotropy" type of the Imry-Ma phases, in which the direction of the order parameter follows large-scale fluctuations of a random field or random anisotropy, are considered. It is shown that the anisotropy of the distribution of random fields of defects in the space of the order parameter can lead to the appearance of the long-range order. An attention is paid to phase diagrams arising as a result of competition between random fields of defects and anisotropy induced by defects. By the example of a system with random anisotropy (nanocrystalline ferromagnet), the dependences of the coercive field on the crystallite size are considered.


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