Abstract
We present a new continuous data assimilation algorithm based on ideas that have been developed for designing finite-dimensional feedback controls for dissipative dynamical systems, in particular, in the context of the incompressible two-dimensional Navier–Stokes equations. These ideas are motivated by the fact that dissipative dynamical systems possess finite numbers of determining parameters (degrees of freedom) such as modes, nodes and local spatial averages which govern their long-term behavior. Therefore, our algorithm allows the use of any type of measurement data for which a general type of approximation interpolation operator exists. Under the assumption that the observational measurements are free of noise, our main result provides conditions, on the finite-dimensional spatial resolution of the collected data, sufficient to guarantee that the approximating solution, obtained by our algorithm from the measurement data, converges to the unknown reference solution over time. Our algorithm is also applicable in the context of signal synchronization in which one can recover, asymptotically in time, the solution (signal) of the underlying dissipative system that is corresponding to a continuously transmitted partial data.
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References
Aubin, J.P.: Un théorème de compacité. C.R. Acad. Sci. Paris Sér. I Math. 256, 5042–5044 (1963)
Azouani, A., Titi, E.S.: Feedback control of nonlinear dissipative systems by finite determining parameters—a reaction-diffusion paradigm (2013). arXiv:1301.6992
Bessaih, H., Olson, E., Titi, E.S.: Continuous data assimilation of stochastically noisy data. In preparation (2013)
Blömker, D., Law, K.J.H., Stuart, A.M., Zygalakis, K.C.: Accuracy and stability of the continuous-times 3DVAR filter for the Navier–Stokes equations. Nonlinearity 26, 2193–2219 (2013)
Brenner, S.C., Scott, R.: The Mathematical Theory of Finite Element Methods. Springer, Berlin (2007)
Brézis, H., Gallouet, T.: Nonlinear Schrödinger evolution equations. Nonlinear Anal. 4(4), 677–681 (1980)
Browning, G.L., Henshaw, W.D., Kreiss, H.O.: A numerical investigation of the interaction between the large and small scales of the two-dimensional incompressible Navier–Stokes equations. Research Report LA-UR-98-1712, Los Alamos National Laboratory, (1998)
Cao, C., Titi, E.S.: Global well-posedness of the three-dimensional viscous primitive equations of large scale ocean and atmosphere dynamics. Ann. Math. 166(1), 245–267 (2007)
Cheskidov, A., Holm, D.D., Olson, E., Titi, E.S.: On a Leray-alpha model of turbulence. Proc. R. Soc. Lond., Ser. A Math. Phys. Eng. Sci. 461(2055), 629–649 (2005)
Cockburn, B., Jones, D.A., Titi, E.S.: Estimating the number of asymptotic degrees of freedom for nonlinear dissipative systems. Math. Comput. 66(219), 1073–1087 (1997)
Constantin, P., Foias, C.: Navier–Stokes Equations. University of Chicago Press, Chicago (1988)
Daley, R.: Atmospheric Data Analysis. Cambridge Atmospheric and Space Science Series. Cambridge University Press, Cambridge (1991)
Dascaliuc, R., Foias, C., Jolly, M.S.: Estimates on enstrophy, palinstrophy, and invariant measures for 2-D turbulence. J. Differ. Equ. 248, 792–819 (2010)
Foias, C., Prodi, G.: Sur le comportement global des solutions non-stationnaires des équations de Navier-Stokes en dimension 2. Rend. Semin. Mat. Univ. Padova 39, 1–34 (1967)
Foias, C., Temam, R.: Sur la détermination d’un écoulement fluide par des observations discrètes. C. R. Acad. Sci. Paris Sér. I Math. 295(3), 239–241 (1982). The continuation in 295(9), 523–525 (1982)
Foias, C., Temam, R.: Determination of the solutions of the Navier–Stokes equations by a set of nodal values. Math. Comput. 43(167), 117–133 (1984)
Foias, C., Titi, E.S.: Determining nodes, finite difference schemes and inertial manifolds. Nonlinearity 4(1), 135–153 (1991)
Foias, C., Manley, O., Rosa, R., Temam, R.: Navier–Stokes Equations and Turbulence. Encyclopedia of Mathematics and Its Applications, vol. 83. Cambridge University Press, Cambridge (2001)
Foias, C., Jolly, M., Kravchenko, R., Titi, E.S.: A determining form for the 2D Navier-Stokes equations—the Fourier modes case. J. Math. Phys. 53, 115623 (2012)
Gesho, M.: A numerical study of continuous data assimilation using nodal points in space for the two-dimensional Navier–Stokes equations. Masters Thesis, University of Nevada, Department of Mathematics and Statistics (2013)
Hayden, K., Olson, E., Titi, E.S.: Discrete data assimilation in the Lorenz and 2d Navier–Stokes equations. Physica D: Nonlinear Phenom. 240(18), 1416–1425 (2011)
Henshaw, W.D., Kreiss, H.O., Yström, J.: Numerical experiments on the interaction between the large and small-scale motions of the Navier–Stokes equations. Multiscale Model. Simul. 1(1), 119–149 (2003)
Jones, D.A., Titi, E.S.: Determining finite volume elements for the 2D Navier–Stokes equations. Physica D 60, 165–174 (1992)
Jones, D.A., Titi, E.S.: Upper bounds on the number of determining modes, nodes and volume elements for the Navier–Stokes equations. Indiana Univ. Math. J. 42(3), 875–887 (1993)
Korn, P.: Data assimilation for the Navier–Stokes-α equations. Physica D 238, 1957–1974 (2009)
Lions, J.L., Magenes, E.: Nonhomogeneous Boundary Value Problems. Springer, Berlin (1972)
Olson, E., Titi, E.S.: Determining modes for continuous data assimilation in 2D turbulence. J. Stat. Phys. 113(5–6), 799–840 (2003)
Olson, E., Titi, E.S.: Determining modes and Grashof number in 2D turbulence. Theor. Comput. Fluid Dyn. 22(5), 327–339 (2008)
Robinson, J.: In: Infinite-Dimensional Dynamical Systems. Cambridge Texts in Applied Mathematics (2001)
Temam, R.: Navier–Stokes Equations and Nonlinear Functional Analysis. CBMS Regional Conference Series, vol. 41. SIAM, Philadelphia (1983)
Temam, R.: Navier–Stokes Equations: Theory and Numerical Analysis, revised edn. AMS/Chelsea, New York (2001)
Titi, E.S.: On a criterion for locating stable stationary solutions to the Navier–Stokes equations. Nonlinear Anal. Theory Methods Appl. 11, 1085–1102 (1987)
Acknowledgements
The work of A.A. is supported in part by the DFG grants SFB-910 and SFB-947. E.S.T. is thankful to the kind hospitality of the Freie Universität Berlin, where this work was initiated. E.S.T. also acknowledges the partial support of the Alexander von Humboldt Stiftung Foundation, the Minerva Stiftung Foundation, and the National Science Foundation grants DMS-1009950, DMS-1109640 and DMS-1109645. We would also like to thank the anonymous referees for their careful reading and constructive comments.
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Communicated by P. Newton.
Appendix A: Estimates for Nodal Interpolants
Appendix A: Estimates for Nodal Interpolants
This appendix contains inequalities and estimates for interpolant operators that will be used for observables obtained from nodal measurements of the velocity field.
Consider a function \(u \in H^{2}_{\rm{per}}(\varOmega)\), where Ω=[0,L]2 is a basic domain of periodicity. Let \(\sqrt{N}\) be a positive integer and partition Ω into N squares with sides of length \(h=L/{\sqrt{N}}\). Let \(\mathcal{J}=\{1,2,\ldots, \sqrt{N}\}^{2}\) and for each \(\alpha\in \mathcal{J}\) define the semi-open square
Moreover, for φ∈L 1(Ω) we denote
Fix nodal points x α ∈Q α , and suppose we are given the nodal values u(x α ), for every \(\alpha\in \mathcal{J}\). Based on these nodal values, we define two interpolant operators, I h and \(\tilde{I}_{h}\), which we will show that they satisfy the approximation estimate (7). Specifically, define
and
where
is the L-periodic characteristic function of the semi-open square Q α . Next, we define
and
where
is a mollified version of ψ α by the mollifier ρ ϵ (x)=ϵ −2 ρ(x/ϵ). Here we take
and
The mollification parameter ϵ will be chosen \(\epsilon= \frac{h}{10}\).
Observe that \(\langle I_{h}\rangle= \langle\tilde{I}_{h}\rangle=0\), and that \(\tilde{\mathcal{I}}_{h}(x)\) and \(\tilde{I}_{h}(x)\) are C ∞ periodic functions.
We now state as Proposition 4 the estimate that was proved by Jones and Titi as inequality (6.2) in Jones and Titi (1993).
Proposition 4
Let Q be a square with sides of length ℓ>0, and φ∈H 2(Q). Then for every x,y∈Q one has
We now use Proposition 4 to obtain estimate (7) concerning the accuracy of the interpolant operators \(\mathcal{I}_{h}\) and I h . Namely, we have
Proposition 5
Suppose \(u\in H_{\rm{per}}^{2}(\varOmega)\), and let \(\mathcal{I}_{h}(u)\) and I h (u) be as in (41) and (42), respectively. Then
-
(i)
\(\|u-\mathcal{I}_{h}(u) \|_{L^{2}(\varOmega)} \le4 h \|\nabla u \|_{L^{2}(\varOmega)} +2 h^{2} \| {\partial^{2} u\over\partial x_{1}\partial x_{2}} \|_{L^{2}(\varOmega)}\).
-
(ii)
\(\|(u-\langle u \rangle) -I_{h}(u) \|_{L^{2}(\varOmega)} \le 8h \|\nabla u \|_{L^{2}(\varOmega)} + 4h^{2} \| {\partial^{2} u\over\partial x_{1}\partial x_{2}} \|_{L^{2}(\varOmega)}\).
Moreover, if 〈u〉=0, then there exists a constant c>0 such that we can replace the term \(\| {\partial^{2} u\over\partial x_{1}\partial x_{2}} \|_{L^{2}(\varOmega)}\), in the above estimates, by \(c \| \Delta u \|_{L^{2}(\varOmega)}\).
Proof
First observe that
Therefore,
Since
the above gives
Applying Proposition 4 to the square \(\overline{Q}_{\alpha}\) we obtain
Hence
which proves (i).
Next, we focus on proving (ii). By virtue of the Cauchy–Schwarz inequality we observe that
Therefore, (ii) follows from combining the triangle inequality together with the above observation, (41), (42), and part (i).
Finally, we recall the fact that for 〈u〉=0 one has \(\| u \|_{H^{2}(\varOmega)}\le c \| \Delta u \|_{L^{2}(\varOmega )}\), which concludes the proof. □
We now provide similar estimates for the C ∞ periodic interpolants \(\tilde{\mathcal{I}}_{h}\) and \(\tilde{I}_{h}\). In order to do this we make the assumptions that N≥9 and \(\epsilon=\frac{h}{10}\). Define
Since ϵ<h/2 we obtain
and
The following two propositions now follow immediately from the definition of \(\tilde{\psi}_{\alpha}\) and the fact that \(\epsilon=\frac{h}{10}\).
Proposition 6
The functions \(\tilde{\psi}_{\alpha}\), for \(\alpha\in \mathcal{J}\), form a smooth partition of unity satisfying
-
(i)
\(0 \le\tilde{\psi}_{\alpha}(x)\le1\), and \({\rm supp}(\tilde{\psi}_{\alpha})\subseteq (\mathcal{U}_{\alpha}+ (L \mathbf{ Z} )^{2} )\),
-
(ii)
\(\tilde{\psi}_{\alpha}(x)=1\), for all \(x\in (\mathcal {C}_{\alpha}+ (L \mathbf{Z} )^{2} )\), and \(\sum_{\alpha\in \mathcal{J}} \tilde{\psi}_{\alpha}(x)=1\), for all x∈R 2,
-
(iii)
\(\langle\tilde{\psi}_{\alpha}\rangle= (\frac{h}{L} )^{2}\) and \(\frac{4}{5} h \le \|\tilde{\psi}_{\alpha}\| _{L^{2}(\varOmega)} \le\frac{6}{5} h\),
-
(iv)
\({\rm supp}(\nabla\tilde{\psi}_{\alpha})\subseteq ( (\mathcal{U}_{\alpha}\setminus\mathcal{C}_{\alpha})+ L \mathbf {Z}^{2} )\),
-
(v)
\(|\nabla\tilde{\psi}_{\alpha}(x)|\le c h^{-1}\), and \(|\frac {\partial^{2}}{\partial x_{i} \partial x_{j}}\tilde{\psi}_{\alpha}(x)|\le c h^{-2}\), for all x∈R 2,
-
(vi)
\(\|\nabla\tilde{\psi}_{\alpha}\|_{L^{2}(\varOmega)} \le c \).
Proposition 7
Let \(\mathcal{K}=\{ -1,0,1\}^{2}\). The functions \(\tilde{\psi}_{\alpha}\) are nearly orthogonal in the following sense:
-
(i)
\(\int_{\varOmega} \tilde{\psi}_{\alpha}(x) \tilde{\psi}_{\beta}(x)\, \mathrm{d}x=\int_{\varOmega} (\nabla\tilde{\psi}_{\alpha}(x) ) \cdot (\nabla\tilde{\psi}_{\beta}(x) )\,\mathrm{d}x=0\) for all \(\alpha,\beta\in \mathcal{J}\) with \(\beta-\alpha\notin\mathcal{K}\).
-
(ii)
\(|\int_{\varOmega} \tilde{\psi}_{\alpha}(x) \tilde{\psi}_{\beta}(x)\,\mathrm{d}x | \le(h+2\epsilon)^{2}= \frac{36}{25}h^{2}\), for all \(\alpha,\beta\in \mathcal{J}\) with \(\beta-\alpha\in\mathcal{K}\).
-
(iii)
\(|\int_{\varOmega} (\nabla\tilde{\psi}_{\alpha}(x) ) \cdot (\nabla\tilde{\psi}_{\beta}(x) )\,\mathrm{d}x | \le c\), for all \(\alpha,\beta\in \mathcal{J}\) with \(\beta-\alpha\in\mathcal{K}\).
We are now ready to prove estimates concerning the accuracy of the interpolant operators \({\tilde{\mathcal{I}}}_{h}\) and \(\tilde{I}_{h}\) that are the analog to those of Proposition 5.
Proposition 8
Suppose \(u\in H_{\rm{per}}^{2}(\varOmega)\), and let \(\tilde{\mathcal{I}}_{h}(u)\) and \(\tilde{I}_{h}(u)\) be as in (43) and (44), respectively. Then there exists a constant c>0 such that
-
(i)
\(\|u-\tilde{\mathcal{I}}_{h}(u)\|_{L^{2}(\varOmega)} \le c (h \|\nabla u\|_{L^{2}(\varOmega)} + h^{2} \| {\partial^{2} u\over\partial x_{1}\partial x_{2}} \|_{L^{2}(\varOmega)} )\).
-
(ii)
\(\| (u-\langle u \rangle )-\tilde{I}_{h}(u)\| _{L^{2}(\varOmega)} \le c (h \|\nabla u\|_{L^{2}(\varOmega)} + h^{2} \| {\partial^{2} u\over\partial x_{1}\partial x_{2}} \|_{L^{2}(\varOmega)} )\).
-
(iii)
\(\| \nabla\tilde{I}_{h}(u)\|_{L^{2}(\varOmega)}=\| \nabla \tilde {\mathcal{I}}_{h}(u)\|_{L^{2}(\varOmega)} \le c ( \|\nabla u\|_{L^{2}(\varOmega)} + h \| {\partial^{2} u\over\partial x_{1}\partial x_{2}} \|_{L^{2}(\varOmega)} )\).
-
(iv)
\(\| \nabla(u - \tilde{I}_{h}(u))\|_{L^{2}(\varOmega)} =\| \nabla(u - \tilde{\mathcal{I}}_{h}(u))\|_{L^{2}(\varOmega)}\le c ( \|\nabla u\|_{L^{2}(\varOmega)} + h \| {\partial^{2} u\over\partial x_{1}\partial x_{2}} \|_{L^{2}(\varOmega)} )\).
Moreover, if 〈u〉=0, then there exists a constant c>0 such that we can replace the term \(\| {\partial^{2} u\over\partial x_{1}\partial x_{2}} \|_{L^{2}(\varOmega)}\), in the above estimates, by \(c \| \Delta u \|_{L^{2}(\varOmega)}\).
Proof
In what follows we will use some of the properties stated in Propositions 6 and 7.
Since \(\tilde{\psi}_{\alpha}(x)\tilde{\psi}_{\beta}(x)=0\) for \(\alpha-\beta\notin\mathcal{K}\) (see Proposition 6) we have
Applying Proposition 4 to each of the squares \(\tilde{Q}_{\alpha}\), for \(\alpha\in \mathcal{J}\), the above implies
where γ 1=11664 and γ 2=2916. By this we conclude (i).
The proof of (ii) follows from (i) by following the same lines as the proof of part (ii) of Proposition 5.
Next, we focus on the proof of (iii). To this end we implement some of the steps used in the proof of part (i), above, and the properties stated in Proposition 6.
Applying Proposition 4 to each of the squares \(\tilde{Q}_{\alpha}\), for \(\alpha\in \mathcal{J}\), in the above estimate to obtain
which concludes the proof of point (iii).
Point (iv) is an obvious consequence of (iii). The rest of the proof is similar to Proposition 5. □
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Azouani, A., Olson, E. & Titi, E.S. Continuous Data Assimilation Using General Interpolant Observables. J Nonlinear Sci 24, 277–304 (2014). https://doi.org/10.1007/s00332-013-9189-y
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DOI: https://doi.org/10.1007/s00332-013-9189-y
Keywords
- Determining modes
- Volume elements and nodes
- Continuous data assimilation
- Two-dimensional Navier–Stokes equations
- Signal synchronization