1991
DOI: 10.1142/s0218202591000046
|View full text |Cite
|
Sign up to set email alerts
|

Stochastic Partial Differential Equations and Turbulence

Abstract: Stochastic partial differential equations are proposed in order to model some turbulence phenomena. A particular case (the stochastic Burgers equations) is studied. Global existence of solutions is proved. Their regularity is also studied in detail. It is shown that the solutions cannot possess too high regularity.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

3
67
0

Year Published

1999
1999
2017
2017

Publication Types

Select...
5
2

Relationship

0
7

Authors

Journals

citations
Cited by 79 publications
(75 citation statements)
references
References 0 publications
3
67
0
Order By: Relevance
“…(b) For every n ∈ N and u ∈ U 8) i.e., the restriction of P n to U is the (·, ·) U -projection onto the subspace span{e 1 , ..., e n }.…”
Section: Auxiliary Results From Functional Analysis -Space U and An Omentioning
confidence: 99%
See 2 more Smart Citations
“…(b) For every n ∈ N and u ∈ U 8) i.e., the restriction of P n to U is the (·, ·) U -projection onto the subspace span{e 1 , ..., e n }.…”
Section: Auxiliary Results From Functional Analysis -Space U and An Omentioning
confidence: 99%
“…In applications, the present approach allows to consider the multiplicative Gaussian noise term, represented by t 0 in the noise term is important in modelling the turbulence, see [8] and [38]. Assumptions (G.1)-(G.3) formulated in Section 2 cover the following example…”
Section: G(s U(s)) Dw(s) T ∈ (0 T ) (11)mentioning
confidence: 99%
See 1 more Smart Citation
“…The paper [8] dealt exclusively with the existence of solutions for such g. Its precursors [5,6] (see also Sec 6.3 of [9]) also gave a physical motivation for considering noise of this form.…”
Section: Preliminariesmentioning
confidence: 99%
“…Then for each v ∈ H and s ∈ R the processu(t, ω) = ψ(t, s, v, ω) is a solution to the equation (2.1) on [s, ∞) with u(s) = v. This process satisfies (1) for all t ≥ s and all ω |u(t)| 2 + c 1 t s u(r) 2 dr ≤ |u(s)| 2 exp(α(t − s)) + c 4 (exp(α(t − s)) − 1), (5.7) (2) if α < λ 1 (2ν − β), then for all t ≥ s and all ω |u(t)| 2 ≤ |u(s)| 2 exp(−c 3 (t − s)) + c5 1 − exp(−c 3 (t − s)) , (5.8) (3) for all t ≥ s, v, v ∈ H |u (t) − u(t)| 2 + t s u (r) − u(r) 2 dr ≤ |v − v| 2 c(t − s, |u|), (4) assuming F2 and G4 p , then for all T ≥ s, all v ∈ V E sup s≤t≤T u(t) p ≤ c p (T − s, v ),(5.9)(5) assuming F2 and G4 2p , then for all T ≥ s and v ∈ V c p (T − s, v ),(5.10) …”
mentioning
confidence: 99%