2017
DOI: 10.1007/978-3-319-63082-3_100
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Semi-Discretized Stochastic Fiber Dynamics: Non-Linear Drag Force

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Cited by 2 publications
(4 citation statements)
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“…Hence, γ(r, ṽ, h) = κ(r, ṽ, h) for all (r, ṽ, h) ∈ V 1 . We obtain that the Lagrange multiplier κ(r, v, h) 24), and the definition of A(r, v, h, γ) ∈ R m×m in (3.23). Thus, replacing the Lagrange remainder terms appearing due to Taylor expansions on the right hand side of (3.34) by their corresponding integral representations, it follows that λre (r, v, h) ∈ R m and Λre (r, v, h) ∈ R m×ℓ depend continuously on (r, v, h) ∈ D as well.…”
Section: Solvability Of the Scheme And Lagrange Multiplier Estimatesmentioning
confidence: 99%
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“…Hence, γ(r, ṽ, h) = κ(r, ṽ, h) for all (r, ṽ, h) ∈ V 1 . We obtain that the Lagrange multiplier κ(r, v, h) 24), and the definition of A(r, v, h, γ) ∈ R m×m in (3.23). Thus, replacing the Lagrange remainder terms appearing due to Taylor expansions on the right hand side of (3.34) by their corresponding integral representations, it follows that λre (r, v, h) ∈ R m and Λre (r, v, h) ∈ R m×ℓ depend continuously on (r, v, h) ∈ D as well.…”
Section: Solvability Of the Scheme And Lagrange Multiplier Estimatesmentioning
confidence: 99%
“…. , N , in three-dimensional Euclidean space, described by an SDAE of the form dr(t) = v(t) dt dv(t) = f int (r(t)) + f grav + f air r(t), v(t) dt + L air r(t), r(t) D turb r(t), v(t) dw(t) + ∇g(r(t)) dµ(t) g(r(t)) = 0, see [23,24]. Here r(t) = (r i (t)) i∈{1,...,N } is the 3N -dimensional position vector, v(t) = (v i (t)) i∈{1,...,N } is the corresponding 3N -dimensional velocity vector and w is a N -dimensional Brownian motion.…”
Section: Examplesmentioning
confidence: 99%
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