Special Section Articles

Higher-Order Linear-Time Unconditionally Stable Alternating Direction Implicit Methods for Nonlinear Convection-Diffusion Partial Differential Equation Systems

[+] Author and Article Information
Oscar P. Bruno

Computing and Mathematical Sciences,
California Institute of Technology,
Pasadena, CA 91125
e-mail: obruno@caltech.edu

Edwin Jimenez

Computing and Mathematical Sciences,
California Institute of Technology,
Pasadena, CA 91125
e-mail: jimenez@caltech.edu

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received December 2, 2013; final manuscript received January 29, 2014; published online April 28, 2014. Assoc. Editor: Ye Zhou.

J. Fluids Eng 136(6), 060904 (Apr 28, 2014) (7 pages) Paper No: FE-13-1695; doi: 10.1115/1.4026868 History: Received December 02, 2013; Revised January 29, 2014

We introduce a class of alternating direction implicit (ADI) methods, based on approximate factorizations of backward differentiation formulas (BDFs) of order p2, for the numerical solution of two-dimensional, time-dependent, nonlinear, convection-diffusion partial differential equation (PDE) systems in Cartesian domains. The proposed algorithms, which do not require the solution of nonlinear systems, additionally produce solutions of spectral accuracy in space through the use of Chebyshev approximations. In particular, these methods give rise to minimal artificial dispersion and diffusion and they therefore enable use of relatively coarse discretizations to meet a prescribed error tolerance for a given problem. A variety of numerical results presented in this text demonstrate high-order accuracy and, for the particular cases of p=2,3, unconditional stability.

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Grahic Jump Location
Fig. 3

Stability of the BDF(2)-ADI and BDF(3)-ADI temporal schemes when used in conjunction with the Chebyshev spatial approximations, as demonstrated by the display of the maximum error at a final time T=1000 with a fixed spatial resolution N=20 and various time-steps. (a) Δt=1. (b) Δt=10-1. (c) Δt=10-2.

Grahic Jump Location
Fig. 2

Temporal convergence as Δt→0, using various spatial resolutions (Nx=Ny=N), of the approximate solution to the system (3) over [0,1]2. Maximum errors versus the time step Δt are obtained by means of various methods. (a) second-order spatial finite differences with N=50,100,200 and BDF(2)-ADI. (b) Chebyshev spatial approximation with N=20 and BDF(2)-ADI. (c) Chebyshev spatial approximation with N=20 and BDF(3)-ADI.

Grahic Jump Location
Fig. 1

Burgers system solution in a Cartesian domain using BDF(3)-ADI and Chebyshev approximations




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