We study a continuous data assimilation (CDA) algorithm for a velocity-vorticity formulation of the 2D Navier-Stokes equations in two cases: nudging applied to the velocity and vorticity, and nudging applied to the velocity only. We prove that under a typical finite element spatial discretization and backward Euler temporal discretization, application of CDA preserves the unconditional long-time stability property of the velocity-vorticity method and provides optimal long-time accuracy. These properties hold if nudging is applied only to the velocity, and if nudging is also applied to the vorticity then the optimal long-time accuracy is achieved more rapidly in time. Numerical tests illustrate the theory, and show its effectiveness on an application problem of channel flow past a flat plate.
Citation: Matthew Gardner, Adam Larios, Leo G. Rebholz, Duygu Vargun, Camille Zerfas. Continuous data assimilation applied to a velocity-vorticity formulation of the 2D Navier-Stokes equations[J]. Electronic Research Archive, 2021, 29(3): 2223-2247. doi: 10.3934/era.2020113
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We study a continuous data assimilation (CDA) algorithm for a velocity-vorticity formulation of the 2D Navier-Stokes equations in two cases: nudging applied to the velocity and vorticity, and nudging applied to the velocity only. We prove that under a typical finite element spatial discretization and backward Euler temporal discretization, application of CDA preserves the unconditional long-time stability property of the velocity-vorticity method and provides optimal long-time accuracy. These properties hold if nudging is applied only to the velocity, and if nudging is also applied to the vorticity then the optimal long-time accuracy is achieved more rapidly in time. Numerical tests illustrate the theory, and show its effectiveness on an application problem of channel flow past a flat plate.
Riemann-Liouville fractional integral given by
Iαa+ξ(℘)=1Γ(α)∫χa(χ−℘)α−1ξ(℘)dt. |
Many different concepts of fractional derivative maybe found in [9,10,11]. In [12] studied a conformable derivative:
℘αf(℘)=limϵ→0f(℘+ϵ℘1−α)−f(℘)ϵ. |
The time scale conformable derivatives was introduced by Benkhettou et al. [17].
Further, in recent years, numerous mathematicians claimed that non-integer order derivatives and integrals are well suited to describing the properties of many actual materials, such as polymers. Fractional derivatives are a wonderful tool for describing memory and learning. a variety of materials and procedures inherited properties is one of the most significant benefits of fractional ownership. For more concepts and definition on time scales see [13,14,15,16,17,18,19,33,34,35].
Continuous version of Steffensen's inequality [7] is written as: For 0≤g(℘)≤1 on ∈[a,b]. Then
∫bb−λf(℘)dt≤∫baf(℘)g(℘)dt≤∫a+λaf(℘)dt, | (1.1) |
where λ=∫bag(℘)dt.
Supposing f is nondecreasing gets the reverse of (1.1).
Also, the discrete inequality of Steffensen [6] is: For λ2≤∑nℓ=1g(ℓ)≤λ1. Then
n∑ℓ=n−λ2+1f(ℓ)≤n∑ℓ=1f(ℓ)g(ℓ)≤λ1∑ℓ=1f(ℓ). | (1.2) |
Recently, a large number of dynamic inequalities on time scales have been studied by a small number of writers who were inspired by a few applications (see [1,2,3,4,8,28,29,30,31,32,36,37,40,41,42,44,48,49,50,51,52,53]).
In [5] Jakšetić et al. proved that, if ˆμ([c,d])=∫[a,b]g(℘)dˆμ(℘), where [c,d]⊆[a,b]. Then
∫[a,b]f(℘)g(℘)dˆμ(℘)≤∫[c,d]f(℘)g(℘)dˆμ(℘)+∫[a,c](f(℘)−f(d))g(℘)dˆμ(℘), |
and
∫[c,d]f(℘)dˆμ(℘)−∫[d,b](f(c)−f(℘))g(℘)dˆμ(℘)≤∫[a,b]f(℘)g(℘)dˆμ(℘). |
Anderson, in [3], studied the inequality:
∫bb−λϕ(℘)∇℘≤∫baϕ(℘)ψ(℘)∇℘≤∫a+λaϕ(℘)∇℘, | (1.3) |
In [47] the authors have proved, for
∫m+λ1mζ(℘)d℘=∫kmζ(℘)g(℘)d℘, |
and
∫nn−λ2ζ(℘)d℘=∫nkζ(℘)g(℘)d℘. |
If there exists a constant A such that r(℘)/ζ(℘)−At is monotonic on the intervals [m,k], [k,n], and
∫nmtq(℘)g(℘)d℘=∫m+λ1mtq(℘)d℘+∫nn−λ2tq(℘)d℘, |
then
∫nmr(℘)g(℘)d℘≤∫m+λ1mr(℘)d℘+∫nn−λ2r(℘)d℘. |
In particularly, Anderson [3] proved
∫nn−λr(℘)∇℘≤∫nmr(℘)g(℘)∇℘≤∫m+λmr(℘)∇℘. |
where m,n∈Tκ with m<n, r, g:[m,n]T→R are ∇-integrable functions such that r is of one sign and nonincreasing and 0≤g(℘)≤1 on [m,n]T and λ=∫nmg(℘)∇℘, n−λ,m+λ∈T.
We prove the next two needed results:
Theorem 1.1. Assume q>0 with 0≤g(℘)≤ζ(℘) ∀℘∈[m,n]T and λ is given from ∫nmg(℘)Δα℘=∫m+λmζ(℘)Δα℘, then
∫nmr(℘)g(℘)Δα℘≤∫m+λmr(℘)ζ(℘)Δα℘. | (1.4) |
Also, provided with 0≤g(℘)≤ζ(℘) and ∫nn−λζ(℘)Δα℘=∫nmg(℘)Δα℘, we have
∫nn−λr(℘)ζ(℘)Δα℘≤∫nmr(℘)g(℘)Δα℘. | (1.5) |
We get the reverse inequalities of (1.4) and (1.5) when assuming r/ζ is nondecreasing.
Theorem 1.2. Assume ψ is integrable on time scales interval [m,n], with ζ(℘)−ψ(℘)≥g(℘)≥ψ(℘)≥0∀℘∈[m,n]T and ∫m+λmζ(℘)Δα℘=∫nmg(℘)Δα℘=∫nn−λζ(℘)Δα℘ and g, r and ζ are Δα-integrable functions, ζ(℘)≥g(℘)≥0, we have
∫nn−λr(℘)ζ(℘)Δα℘+∫nm|(r(℘)−r(n−λ))ψ(℘)|Δα℘≤∫nmr(℘)g(℘)Δα℘≤∫m+λmr(℘)ζ(℘)Δα℘−∫nm|(r(℘)−r(m+λ))ψ(℘)|Δα℘, | (1.6) |
and
∫nn−λr(℘)ζ(℘)Δα℘≤∫nn−λ[r(℘)ζ(℘)−(r(℘)−r(n−λ))][ζ(℘)−g(℘)]Δα℘≤∫nmr(℘)g(℘)Δα℘≤∫m+λm[r(℘)ζ(℘)−(r(℘)−r(m+λ))][ζ(℘)−g(℘)]Δα℘≤∫m+λmr(℘)ζ(℘)Δα℘. | (1.7) |
Proof. The proof techniques of Theorems 1.6 and 1.7 are like to that in [4] and is removed.
Several authors proved conformable Hardy's inequality [20,21], conformable Hermite-Hadamard's inequality [22,23,24], conformable inequality of Opial's [26,27] and conformable inequality of Steffensen's [25]. In [45] Anderson proved the followong results:
Theorem 1.3. [45] Suppose α∈(0,1] and r1, r2∈R such that 0≤r1≤r2. Suppose ∏:[r1,r2]→[0,∞) and Γ:[r1,r2]→[0,1] are α-fractional integrable functions on [r1,r2] with Π is decreasing, we get
∫r2r2−ℵΠ(ζ)dαζ≤∫r2r1Π(ζ)Γ(ζ)dαζ≤∫r1+ℵr1Π(ζ)dαζ, |
where ℵ=α(r2−r1)rα2−rα1∫r2r1Γ(ζ)dαζ∈[0,r2−r1].
In [46] the authors gave an extension for Theorem 1.8:
Theorem 1.4. Assume α∈(0,1] and r1, r2∈R such that 0≤r1≤r2. Suppose ∏,Γ,Σ:[r1,r2]→[0,∞) are integrable on [r1,r2] with the decreasing function Π and 0≤Γ≤Σ, we get
∫r2r2−ℵΣ(ζ)Π(ζ)dαζ≤∫r2r1Π(ζ)Γ(ζ)dαζ≤∫r1+ℵr1Σ(ζ)Π(ζ)dαζ, |
where ℵ=(r2−r1)∫r2r1Σ(ζ)dαζ∫r2r1Γ(ζ)dαζ∈[0,r2−r1].
In this paper, we prove and explore several novel speculations of the Steffensen inequality obtained in [47] through the conformable integral containing time scale concept. We furthermore recover certain known results as special cases of our results.
Lemma 2.1. Assume ζ>0 is rd-continuous function on [m,n]∩T, g, r be rd-continuous on [m,n]∩T such that r/ζ nonincreasing function and 0≤g(℘)≤1 ∀℘∈[m,n]∩T. Then
(Λ1)
∫nmr(℘)g(℘)Δα℘≤∫m+λmr(℘)Δα℘, | (2.1) |
where λ is given by
∫nmζ(℘)g(℘)Δα℘=∫m+λmζ(℘)Δα℘. |
(Λ2)
∫nn−λr(℘)Δα℘≤∫nmr(℘)g(℘)Δα℘, | (2.2) |
such that
∫nn−λζ(℘)Δα℘=∫nmζ(℘)g(℘)Δα℘. |
(2.1) and (2.2) are reversed when r/ζ is nondecreasing.
Proof. Putting g(℘)↦ζ(℘)g(℘) and r(℘)↦r(℘)/ζ(℘) in (1.4), (1.5) to get (Λ1) and (Λ2) simultaneously.
Lemma 2.2. Under the same hypotheses of Lemma 2.1. with ψ be integrable functions on [m,n]∩T and 0≤ψ(℘)≤g(℘)≤1−ψ(℘) for all ℘∈[m,n]T. Then
∫nn−λr(℘)Δα℘+∫nm|(r(℘)ζ(℘)−r(n−λ)ζ(n−λ))ζ(℘)ψ(℘)|Δα℘≤∫nmr(℘)g(℘)Δα℘≤∫m+λmr(℘)Δα℘−∫nm|(r(℘)ζ(℘)−r(m+λ)ζ(m+λ))ζ(℘)ψ(℘)|Δα℘, |
where λ is obtained from
∫m+λmh(℘)Δα℘=∫nmζ(℘)g(℘)Δα℘=∫nn−λζ(℘)Δα℘. |
Proof. Putting g(℘)↦ζ(℘)g(℘), r(℘)↦r(℘)/h(℘) and ψ(℘)↦ζ(℘)ψ(℘) in (1.6).
Lemma 2.3. Under the same conditions of Lemma 2.1. Then
∫nn−λr(℘)Δα℘≤∫nn−λ(r(℘)−[r(℘)ζ(℘)−r(n−λ)ζ(n−λ)]ζ(℘)[1−g(℘)])Δα℘≤∫nmr(℘)g(℘)Δα℘≤∫m+λm(r(℘)−[r(℘)ζ(℘)−r(a+λ)ζ(m+λ)]ζ(℘)[1−g(℘)])Δα℘≤∫m+λmr(℘)Δα℘, |
where λ is obtained from
∫m+λmζ(℘)Δα℘=∫nmg(℘)Δα℘=∫nn−λζ(℘)Δα℘. |
Proof. Taking g(℘)↦ζ(℘)g(℘) and r(℘)↦r(℘)/ζ(℘) in (1.7).
Theorem 2.1. Under the same conditions of Lemma 2.3 such that k∈(m,n) and λ1, λ2 are given from
(Λ3)
∫m+λ1mζ(℘)Δα℘=∫kmζ(℘)g(℘)Δα℘, |
∫nn−λ2ζ(℘)Δα℘=∫nkζ(℘)g(℘)Δα℘. |
If rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫m+λ1mϕ(℘)ζ(℘)Δα℘+∫nn−λ2ϕ(℘)ζ(℘)Δα℘, | (2.3) |
then
∫nmrσ(℘)g(℘)Δα℘≤∫m+λ1mrσ(℘)Δα℘+∫nn−λ2rσ(℘)Δα℘. | (2.4) |
(2.4) is reversed if rσ/ζ∈AHk2[m,n] and (2.3).
(Λ4)
∫kk−λ1ζ(℘)Δα℘=∫kmζ(℘)g(℘)Δα℘, |
∫k+λ2kζ(℘)Δα℘=∫nkζ(℘)g(℘)Δα℘. |
If rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫k+λ2k−λ1ϕ(℘)ζ(℘)Δα℘, | (2.5) |
then
∫nmrσ(℘)g(℘)Δα℘≥∫k+λ2k−λ1rσ(℘)Δα℘. | (2.6) |
If rσ/ζ∈AHk2[m,n] and (2.5) satisfied, then we reverse (2.6).
(Λ5) If λ1, λ2 be the same as in (Λ3) and rσ/ζ∈AHk1[m,n] so that
∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫m+λ1m(ϕ(℘)ζ(℘)−[ϕ(℘)−m−λ1]ζ(℘)[1−g(℘)])Δα℘+∫nn−λ2(ϕ(℘)ζ(℘)−[ϕ(℘)−n+λ2]ζ(℘)[1−g(℘)])Δα℘, | (2.7) |
then
∫nmrσ(℘)g(℘)Δα℘≤∫m+λ1m(rσ(℘)−|rσ(℘)ζ(℘)−rσ(m+λ1)ζ(m+λ1)|ζ(℘)[1−g(℘)])Δα℘+∫nn−λ2(rσ(℘)−|rσ(℘)ζ(℘)−rσ(n−λ2)ζ(n−λ2)|ζ(℘)[1−g(℘)])Δα℘. | (2.8) |
If rσ/ζ∈AHk2[m,n] and (2.7) satisfied, the inequality in (2.8) is reversed.
(Λ6) If λ1, λ2 be defined as in (Λ4) and rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫kk−λ1(ϕ(℘)ζ(℘)−[ϕ(℘)−k+λ1]ζ(℘)[1−g(℘)])Δα℘=∫m+λ1m(ϕ(℘)ζ(℘)−[ϕ(℘)−k+λ2]ζ(℘)[1−g(℘)])Δα℘, | (2.9) |
then
∫nmrσ(℘)g(℘)Δα℘≥∫kk−λ1(rσ(℘)−[rσ(℘)ζ(℘)−rσ(k−λ1)ζ(k−λ1)]ζ(℘)[1−g(℘)])Δα℘+∫k+λ2k(rσ(℘)−[rσ(℘)ζ(℘)−rσ(k+λ2)ζ(k+λ2)]ζ(℘)[1−g(℘)])Δα℘. | (2.10) |
If rσ/ζ∈AHk2[m,n] and (2.9) satisfied, we reverse (2.10).
Proof. (Λ3) Consider rσ/ζ∈AHk1[m,n], and R1(ℓ)=rσ(ℓ)−Aϕ(ℓ)ζ(ℓ), since A is given in Definition 2.1. Since R1/ζ:[m,k]∩T→R, using Lemma 2.1(Λ1), we deduce
0≤∫m+λ1mR1(℘)Δα℘−∫kmR1(℘)g(℘)Δα℘=∫m+λ1mrσ(℘)Δα℘−∫kmrσ(℘)g(℘)Δα℘−A(∫m+λ1mϕ(℘)ζ(℘)Δα℘−∫kmϕ(℘)ζ(℘)g(℘)Δα℘). | (2.11) |
As R1/ζ:[k,n]∩T→R is nondecreasing, using Lemma 2.1(Λ2), we obtain
0≥∫nkR1(℘)g(℘)Δα℘−∫nn−λ2R1(℘)Δα℘=∫nkrσ(℘)g(℘)Δα℘−∫nn−λ2rσ(℘)Δα℘−A(∫nkϕ(℘)ζ(℘)g(℘)Δα℘−∫nn−λ2ϕ(℘)ζ(℘)Δα℘). | (2.12) |
(2.11) and (2.12) imply that
∫m+λ1mrσ(℘)Δα℘+∫nn−λ2rσ(℘)Δα℘−∫nmrσ(℘)g(℘)Δα℘≥A(∫m+λ1mϕ(℘)ζ(℘)Δα℘+∫nn−λ2ϕ(℘)ζ(℘)Δα℘−∫nmϕ(℘)ζ(℘)g(℘)Δα℘) |
Hence, if (2.3) is hold, then (2.4) holds. For rσ/ζ∈AHk2[m,n], we get the some steps.
(Λ4) Let rσ/ζ∈AHk1[m,n], also R1(x)=rσ(x)−Aϕ(x)ζ(x), where A as in Definition 2.1. R1/ζ:[m,k]∩T→R is nonincreasing, so from Lemma 2.1(Λ1) we obtain
0≤∫kmrσ(℘)g(℘)Δα℘−∫kk−λ1rσ(℘)Δα℘−A(∫kmϕ(℘)h(℘)g(℘)Δα℘−∫kc−λ1ϕ(℘)ζ(℘)Δα℘). | (2.13) |
Using Lemma 2.1(Λ1) we have
0≥∫k+λ2krσ(℘)Δα℘−∫nkrσ(℘)g(℘)Δα℘−A(∫k+λ2kϕ(℘)ζ(℘)Δα℘−∫nkϕ(℘)ζ(℘)g(℘)Δα℘). | (2.14) |
Thus, from (2.13), (2.14), we get
∫nmrσ(℘)g(℘)Δα℘−∫k+λ2k−λ1rσ(℘)Δα℘≥A(∫nmϕ(℘)ζ(℘)g(℘)Δα℘−∫k+λ2k−λ1ϕ(℘)ζ(℘)Δα℘) |
Therefore, if ∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫k+λ2k−λ1ϕ(℘)ζ(℘)Δα℘ is satisfied, then (2.8) holds. Follow the same steps for rσ/ζ∈AHk2[m,n].
Using Lemma 2.3 and repeat the steps of Theorem 2.1(Λ3) and Theorem 2.1(Λ4) in the proof of (Λ5) and (Λ6) respectively.
Corollary 2.1. The inequalities (2.4), (2.6), (2.8) and (2.10) of Theorem 2.1 letting T=R takes
(i)∫nmfσ(℘)g(℘)dα℘≤∫m+λ1mrσ(℘)dα℘+∫nn−λ2rσ(℘)dα℘. | (2.15) |
(ii)∫nmrσ(℘)g(℘)dα℘≥∫k+λ2k−λ1rσ(℘)dα℘. | (2.16) |
(iii)∫nmrσ(℘)g(℘)dα℘≤∫m+λ1m(rσ(℘)−[rσ(℘)ζ(℘)−rσ(m+λ1)ζ(m+λ1)]ζ(℘)[1−g(℘)])dα℘+∫nn−λ2(rσ(℘)−[rσ(℘)ζ(℘)−rσ(n−λ2)ζ(n−λ2)]ζ(℘)[1−g(℘)])dα℘. | (2.17) |
(iv)∫nmrσ(℘)g(℘)dα℘≥∫kk−λ1(rσ(℘)−[rσ(℘)ζ(℘)−rσ(k−λ1)ζ(k−λ1)]ζ(℘)[1−g(℘)])dα℘+∫k+λ2k(rσ(℘)−[rσ(℘)ζ(℘)−rσ(k+λ2)ζ(k+λ2)]ζ(℘)[1−g(℘)])dα℘. | (2.18) |
Corollary 2.2. We get [47,Theorems 8,10,21 and 22], if we put α=1 and ϕ(℘)=℘ in Corollary 2.1 [(i),(ii),(iii),(iv)] simultaneously.
Corollary 2.3. In Corollary 2.1 taking T=Z, the results (2.15)–(2.18) will be equivalent to
(i)n−1∑℘=mr(℘+1)g(℘)℘α−1≤m+λ1−1∑℘=mr(℘+1)+n−1∑℘=n−λ2r(℘+1)℘α−1. |
(ii)n−1∑℘=mr(℘+1)g(℘)℘α−1≥k+λ2−1∑℘=k−λ1r(℘+1)℘α−1. |
(iii)n−1∑℘=mr(℘+1)g(℘)℘α−1≤m+λ1−1∑℘=m(r(℘+1)−[r(℘+1)ζ(℘)−r(a+λ1+1)ζ(m+λ1)]ζ(℘)[1−g(℘)])℘α−1+n−1∑℘=n−λ2(r(℘+1)−[r(℘+1)ζ(℘)−r(n−λ2+1)ζ(n−λ2)]ζ(℘)[1−g(℘)])℘α−1. |
(iv)n−1∑℘=mr(℘+1)g(℘))℘α−1≥k−1∑℘=k−λ1(r(℘+1)−[r(℘+1)ζ(℘)−r(k−λ1+1)ζ(k−λ1)]ζ(℘)[1−g(℘)]))℘α−1+k+λ2−1∑℘=k(r(℘+1)−[r(℘+1)ζ(℘)−r(k+λ2+1)ζ(k+λ2)]ζ(℘)[1−g(℘)]))℘α−1. |
Theorem 2.2. Under the assumptions in Lemma 2.1 with 0≤g(℘)≤ζ(℘) and λ1, λ2 be defined as
(Λ7)
∫m+λ1mζ(℘)Δα℘=∫kmg(℘)Δα℘, |
∫nn−λ2ζ(℘)Δα℘=∫nkg(℘)Δα℘. |
If rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)g(℘)Δα℘=∫m+λ1mϕ(℘)ζ(℘)Δα℘+∫nn−λ2ϕ(℘)ζ(℘)Δα℘, | (2.19) |
then
∫nmrσ(℘)g(℘)Δα℘≤∫m+λ1mrσ(℘)ζ(℘)Δα℘+∫nn−λ2rσ(℘)ζ(℘)Δα℘. | (2.20) |
(Λ8)
∫kk−λ1ζ(℘)Δα℘=∫kmg(℘)Δα℘, |
∫k+λ2kζ(℘)Δα℘=∫nkg(℘)Δα℘. |
If rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)g(℘)Δα℘=∫k+λ2k−λ1ϕ(℘)ζ(℘)Δα℘, | (2.21) |
then
∫nmrσ(℘)g(℘)Δα℘≥∫k+λ2k−λ1rσ(℘)ζ(℘)Δα℘. | (2.22) |
If rσ/ζ∈AHk2[m,n] and (2.19), (2.21) satisfied, we get the reverse of (2.20) and (2.22).
Proof. By using Theorem 2.1 [(Λ3),(Λ4)] and by putting g↦g/h and f↦fh, we get the proof of (Λ7) and (Λ8).
Corollary 2.4. In Theorem 2.2 [(Λ7),(Λ8)], assuming T=R, the following results obtains:
(i)∫nmrσ(℘)g(℘)dα℘≤∫m+λ1mrσ(℘)ζ(℘)dα℘+∫nn−λ2rσ(℘)ζ(℘)dα℘. | (2.23) |
(ii)∫nmrσ(℘)g(℘)dα℘≥∫k+λ2k−λ1rσ(℘)ζ(℘)dα℘. | (2.24) |
Corollary 2.5. In Corollary 2.4 [(i),(ii)], when we put α=1 and ϕ(℘)=℘ then [47,Theorems 16 and 17] gotten.
Corollary 2.6. In (2.23) and (2.24) letting T=Z, gets
(i)n−1∑℘=mr(℘+1)g(℘)℘α−1≤m+λ1−1∑℘=mr(℘+1)h(℘)+n−1∑℘=n−λ2r(℘+1)h(℘)℘α−1. |
(ii)n−1∑℘=mr(℘+1)g(℘)℘α−1≥k+λ2−1∑℘=k−λ1r(℘+1)ζ(℘)℘α−1. |
Theorem 2.3. Using the same conditions in Lemma 2.3. Letting w:[m,n]∩T→R be integrable with 0≤g(℘)≤w(℘) ∀℘∈[m,n]∩T and
(Λ9)∫m+λ1mw(℘)ζ(℘)Δα℘=∫kmζ(℘)g(℘)Δα℘, |
∫nn−λ2w(℘)ζ(℘)Δα℘=∫nkζ(℘)g(℘)Δα℘. |
If rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫m+λ1mϕ(℘)w(℘)ζ(℘)Δα℘+∫nn−λ2ϕ(℘)w(℘)ζ(℘)Δα℘, | (2.25) |
then
∫nmrσ(℘)g(℘)Δα℘≤∫m+λ1mrσ(℘)w(℘)Δα℘+∫nn−λ2rσ(℘)w(℘)Δα℘. | (2.26) |
(Λ10)∫kk−λ1w(℘)ζ(℘)Δα℘=∫kmζ(℘)g(℘)Δα℘, |
∫k+λ2kw(℘)ζ(℘)Δα℘=∫nkζ(℘)g(℘)Δα℘. |
If rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫k+λ2k−λ1ϕ(℘)w(℘)ζ(℘)Δα℘, | (2.27) |
∫nmrσ(℘)g(℘)Δα℘≥∫k+λ2k−λ1rσ(℘)w(℘)Δα℘. | (2.28) |
The inequalities in (2.26) and (2.28) are reversible if rσ/ζ∈AHc2[a,b] and (2.25), (2.27) hold.
Proof. In Theorem 2.1 [(Λ3),(Λ4)], ζ changes wq, g changes g/w and r changes rw.
Corollary 2.7. In (2.26) and (2.28). Letting T=R, we have
(i)∫nmrσ(℘)g(℘)dα℘≤∫m+λ1mrσ(℘)w(℘)dα℘+∫nn−λ2rσ(℘)w(℘)dα℘. | (2.29) |
(ii)∫nmrσ(℘)g(℘)dα℘≥∫k+λ2k−λ1rσ(℘)w(℘)dα℘. | (2.30) |
Corollary 2.8. In Corollary 2.7 [(i),(ii)], letting α=1 and ϕ(℘)=℘ we get [47,Theorems 18 and 19].
Corollary 2.9. In (2.29) and (2.30), crossing T=Z, gets
(i)n−1∑℘=mr(℘+1)g(℘)℘α−1≤m+λ1−1∑℘=mr(℘+1)w(℘)+n−1∑℘=n−λ2r(℘+1)w(℘)℘α−1. |
(ii)n−1∑℘=mr(℘+1)g(℘)℘α−1≥k+λ2−1∑℘=k−λ1r(℘+1)w(℘)℘α−1. |
Theorem 2.4. Using the same conditions in Lemma 2.1, and Theorem 2.1 [(Λ3),(Λ4)] with ψ:[m,n]∩T→R be a integrable: 0≤ψ(℘)≤g(℘)≤1−ψ(℘).
(Λ11) If rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫m+λ1mϕ(℘)ζ(℘)Δα℘−∫km|ϕ(℘)−m−λ1|ζ(℘)ψ(℘)Δα℘+∫nn−λ2ϕ(℘)ζ(℘)Δα℘+∫nk|ϕ(℘)−n+λ2|ζ(℘)ψ(℘)Δα℘, | (2.31) |
then
∫nmrσ(℘)g(℘)Δα℘≤∫m+λ1mrσ(℘)Δα℘−∫km|rσ(℘)ζ(℘)−rσ(m+λ1)ζ(m+λ1)|ζ(℘)ψ(℘)Δα℘+∫nn−λ2rσ(℘)Δα℘+∫nk|rσ(℘)ζ(℘)−rσ(n−λ2)ζ(n−λ2)|ζ(℘)ψ(℘)Δα℘. | (2.32) |
(Λ12) If rσ/ζ∈AHk1[m,n] and
∫nmϕ(℘)ζ(℘)g(℘)Δα℘=∫kk−λ1ϕ(℘)ζ(℘)Δα℘−∫km|ϕ(℘)−k+λ1|ζ(℘)ψ(℘)Δα℘+∫nk|ϕ(℘)−k−λ1|ζ(℘)ψ(℘)Δα℘, | (2.33) |
then
∫nmrσ(℘)g(℘)Δα℘≥∫k+λ2k−λ1rσ(℘)Δα℘+∫km|rσ(℘)ζ(℘)−rσ(k−λ1)ζ(k−λ1)|ζ(℘)ψ(℘)Δα℘−∫nk|rσ(℘)ζ(℘)−rσ(k+λ2)ζ(k+λ2)|ζ(℘)ψ(℘)Δα℘. | (2.34) |
If rσ/ζ∈AHk2[m,n] and (2.31) and (2.33) satisfied, we get the reverse of (2.32) and (2.34).
Proof. The same steps of Theorem 2.1 [(Λ3),(Λ4)] with Lemma 2.1, R1/ζ:[m,k]∩T→R nonincreasing, R1/ζ:[k,n]∩T→R nondecreasing.
Corollary 2.10. In Theorem 2.4 [(Λ11),(Λ12)], letting T=R we get:
(i)∫nmrσ(℘)g(℘)dα℘≤∫m+λ1mrσ(℘)dα℘−∫km|rσ(℘)ζ(℘)−rσ(m+λ1)ζ(m+λ1)|ζ(℘)ψ(℘)dα℘+∫nn−λ2rσ(℘)dα℘+∫nk|rσ(℘)ζ(℘)−rσ(n−λ2)ζ(n−λ2)|ζ(℘)ψ(℘)dα℘. | (2.35) |
(ii)∫nmrσ(℘)g(℘)dα℘≥∫k+λ2k−λ1rσ(℘)dα℘+∫km|rσ(℘)ζ(℘)−rσ(k−λ1)ζ(k−λ1)|ζ(℘)ψ(℘)dα℘−∫nk|rσ(℘)ζ(℘)−rσ(k+λ2)ζ(k+λ2)|ζ(℘)ψ(℘)dα℘. | (2.36) |
Corollary 2.11. In (2.35) and (2.36), we put α=1, with ϕ(℘)=℘ we get [47,Theorems 23 and 24].
Corollary 2.12. Our results (2.35) and (2.36), by using T=Z gets
(i)n−1∑℘=mr(℘+1)g(℘)℘α−1≤m+λ1−1∑℘=mr(℘+1)℘α−1−k−1∑℘=m|r(℘+1)ζ(℘)−r(m+λ1+1)ζ(m+λ1)|ζ(℘)ψ(℘)ˆ∇℘+n−1∑℘=n−λ2r(℘+1)℘α−1+n−1∑℘=k|r(℘+1)ζ(℘)−r(n−λ2+1)ζ(n−λ2)|ζ(℘)ψ(℘)℘α−1. |
(ii)n−1∑℘=mr(℘+1)g(℘)℘α−1≥k+λ2−1∑℘=k−λ1r(℘+1)℘α−1+k−1∑℘=m|r(℘+1)ζ(℘)−r(k−λ1+1)ζ(k−λ1)|ζ(℘)ψ(℘)℘α−1−n−1∑℘=k|r(℘+1)ζ(℘)−r(k+λ2+1)ζ(k+λ2)|h(℘)ψ(℘)℘α−1. |
In this work, we explore new generalizations of the integral Steffensen inequality given in [38,39,43] by the utilization of the α-conformable derivatives and integrals, A few of these results are generalised to time scales. We also obtained the discrete and continuous case of our main results, in order to gain some fresh inequalities as specific cases.
The authors extend their appreciation to the Research Supporting Project number (RSP-2022/167), King Saud University, Riyadh, Saudi Arabia.
The authors declare no conflict of interest.
[1] |
On the stability at all times of linearly extrapolated BDF2 timestepping for multiphysics incompressible flow problems. Numer. Methods Partial Differential Equations (2017) 33: 995-1017. ![]() |
[2] |
M. Akbas, L. G. Rebholz and C. Zerfas, Optimal vorticity accuracy in an efficient velocity-vorticity method for the 2D Navier-Stokes equations, Calcolo, 55 (2018), Paper No. 3, 29 pp. 1–29. doi: 10.1007/s10092-018-0246-7
![]() |
[3] |
Continuous data assimilation for the three-dimensional Navier–Stokes-α model. Asymptotic Anal. (2016) 97: 139-164. ![]() |
[4] |
Data assimilation and initialization of hurricane prediction models. J. Atmos. Sci. (1974) 31: 702-719. ![]() |
[5] |
Continuous data assimilation using general interpolant observables. Journal of Nonlinear Science (2014) 24: 277-304. ![]() |
[6] |
Continuous data assimilation with stochastically noisy data. Nonlinearity (2015) 28: 729-753. ![]() |
[7] |
Downscaling data assimilation algorithm with applications to statistical solutions of the Navier–Stokes equations. Ann. Inst. H. Poincaré Anal. Non Linéaire (2019) 36: 295-326. ![]() |
[8] | Continuous data assimilation for the 2D magnetohydrodynamic equations using one component of the velocity and magnetic fields. Asymptot. Anal. (2018) 108: 1-43. |
[9] |
S. C. Brenner and L. R. Scott, The Mathematical Theory of Finite Element Methods, Third edition, Texts in Applied Mathematics, 15. Springer, New York, 2008. doi: 10.1007/978-0-387-75934-0
![]() |
[10] |
E. Carlson, J. Hudson and A. Larios, Parameter recovery for the 2 dimensional Navier-Stokes equations via continuous data assimilation, SIAM J. Sci. Comput., 42 (2020), A250–A270. doi: 10.1137/19M1248583
![]() |
[11] |
Spectral filtering of interpolant observables for a discrete-in-time downscaling data assimilation algorithm. SIAM J. Appl. Dyn. Syst. (2019) 18: 1118-1142. ![]() |
[12] |
On conservation laws of Navier-Stokes Galerkin discretizations. Journal of Computational Physics (2017) 337: 289-308. ![]() |
[13] | Synchronization to big-data: Nudging the Navier-Stokes equations for data assimilation of turbulent flows. Physical Review X (2020) 10: 1-15. |
[14] |
R. Daley, Atmospheric Data Analysis, Cambridge Atmospheric and Space Science Series, Cambridge University Press, 1993. doi: 10.4267/2042/51948
![]() |
[15] |
Efficient dynamical downscaling of general circulation models using continuous data assimilation. Quarterly Journal of the Royal Meteorological Society (2019) 145: 3175-3194. ![]() |
[16] |
A. Ern and J.-L. Guermond, Theory and Practice of Finite Elements, Applied Mathematical Sciences, 159. Springer-Verlag, New York, 2004. doi: 10.1007/978-1-4757-4355-5
![]() |
[17] |
Data assimilation in large Prandtl Rayleigh–Bénard convection from thermal measurements. SIAM J. Appl. Dyn. Syst. (2020) 19: 510-540. ![]() |
[18] |
Continuous data assimilation for the 2D Bénard convection through velocity measurements alone. Phys. D (2015) 303: 59-66. ![]() |
[19] | A. Farhat, E. Lunasin and E. S. Titi, A data assimilation algorithm: The paradigm of the 3D Leray-α model of turbulence, Partial Differential Equations Arising from Physics and Geometry, London Math. Soc. Lecture Note Ser., Cambridge Univ. Press, Cambridge, 450 (2019), 253-273. |
[20] |
A discrete data assimilation scheme for the solutions of the two-dimensional Navier-Stokes equations and their statistics. SIAM J. Appl. Dyn. Syst. (2016) 15: 2109-2142. ![]() |
[21] |
Uniform in time error estimates for a finite element method applied to a downscaling data assimilation algorithm for the Navier-Stokes equations. SIAM Journal on Numerical Analysis (2020) 58: 410-429. ![]() |
[22] |
A computational study of a data assimilation algorithm for the two-dimensional Navier–Stokes equations. Commun. Comput. Phys. (2016) 19: 1094-1110. ![]() |
[23] | P. Gresho and R. Sani, Incompressible Flow and the Finite Element Method, Vol. 2, Wiley, 1998. |
[24] |
The Scott-Vogelius finite elements revisited. Math. Comp. (2019) 88: 515-529. ![]() |
[25] |
Unconditional long-time stability of a velocity-vorticity method for the 2D Navier-Stokes equations. Numer. Math. (2017) 135: 143-167. ![]() |
[26] |
The initialization of numerical models by a dynamic-initialization technique. Monthly Weather Review (1976) 104: 1551-1556. ![]() |
[27] |
H. A. Ibdah, C. F. Mondaini and E. S. Titi, Fully discrete numerical schemes of a data assimilation algorithm: Uniform-in-time error estimates, IMA Journal of Numerical Analysis, Drz043, (2019). doi: 10.1093/imanum/drz043
![]() |
[28] |
A second order ensemble method based on a blended BDF time-stepping scheme for time dependent Navier-Stokes equations. Numerical Methods for Partial Differential Equations (2017) 33: 34-61. ![]() |
[29] |
A new approach to linear filtering and prediction problems. Trans. ASME Ser. D. J. Basic Engrg. (1960) 82: 35-45. ![]() |
[30] |
Global in time stability and accuracy of IMEX-FEM data assimilation schemes for Navier-Stokes equations. Computer Methods in Applied Mechanics and Engineering (2019) 345: 1077-1093. ![]() |
[31] | A. Larios and C. Victor, Continuous data assimilation with a moving cluster of data points for a reaction diffusion equation: A computational study, Commun. Comp. Phys., (accepted for publication). |
[32] |
K. Law, A. Stuart and K. Zygalakis, A Mathematical Introduction to Data Assimilation, Texts in Applied Mathematics, 62. Springer, Cham, 2015. doi: 10.1007/978-3-319-20325-6
![]() |
[33] |
On the accuracy of the rotation form in simulations of the Navier-Stokes equations. Journal of Computational Physics (2009) 228: 3433-3447. ![]() |
[34] |
On error analysis for the 3D Navier-Stokes equations in velocity-vorticity-helicity form. SIAM Journal on Numerical Analysis (2011) 49: 711-732. ![]() |
[35] |
Uniform-in-time error estimates for the postprocessing Galerkin method applied to a data assimilation algorithm. SIAM J. Numer. Anal. (2018) 56: 78-110. ![]() |
[36] |
Natural vorticity boundary conditions on solid walls. Computer Methods in Applied Mechanics and Engineering (2015) 297: 18-37. ![]() |
[37] |
Velocity-vorticity-helicity formulation and a solver for the Navier-Stokes equations. Journal of Computational Physics (2010) 229: 4291-4303. ![]() |
[38] |
On well-posedness of a velocity-vorticity formulation of the Navier-Stokes equations with no-slip boundary conditions. Discrete Contin. Dyn. Syst. (2018) 38: 3459-3477. ![]() |
[39] |
Grad-div stabilization for the Stokes equations. Math. Comp. (2004) 73: 1699-1718. ![]() |
[40] |
Continuous data assimilation for the 3D primitive equations of the ocean. Comm. Pure Appl. Math. (2019) 18: 643-661. ![]() |
[41] | L. Rebholz and C. Zerfas, Simple and efficient continuous data assimilation of evolution equations via algebraic nudging, Submitted. |
[42] |
Towards computable flows and robust estimates for inf-sup stable fem applied to the time dependent incompressible Navier-Stokes equations. SeMA J. (2018) 75: 629-653. ![]() |
[43] | C. Zerfas, Numerical Methods and Analysis for Continuous Data Assimilation in Fluid Models, PhD thesis, Clemson University, 2019,132 pp, https://tigerprints.clemson.edu/all_dissertations/2428. |
[44] |
C. Zerfas, L. G. Rebholz, M. Schneier and T. Iliescu, Continuous data assimilation reduced order models of fluid flow, Computer Methods in Applied Mechanics and Engineering, 357 (2019), 112596, 18 pp. doi: 10.1016/j.cma.2019.112596
![]() |
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