Key words: Differential quadrature method (DQM),
pseudo-spectral method, collocation method, sampling points, centrosymmetric matrix,
structural mechanics, truncation error, orthogonal polynomials, initial value
problem, nonlinear matrix computation, Hadamard product, SJT product, Jacobian
matrix.
The pseudo-spectral
(collocation) method is so far the only method in the direct numerical simulation
(DNS) of turbulent flows and widely used in computational physics and fluid
mechanics, for instance, weather prediction, due to so-called spectral
accuracy (exponential convergence). The differential quadrature
method (DQM) can be regarded as the "direct approach"
of the normal collocation (pseudo-spectral) methods in that the governing
equations are analogized in terms of practical physical variables
instead of usually fictitious expansion (spectral) coefficients. The
advantages of the DQM over the normal pseudo-spectral method are its ease in
implementation and more flexibility in choosing the sampling points. The
direct use of the physical variables manifests the DQM in easy-to-choose starting
solutions of nonlinear iterations, while, in contrast, the fictitious
expansion variables in the collocation methods usually have not physical
meanings and are therefore difficult to do so.
The essential
difficulty in applying the DQM (pseudo-spectral, collocation)
and even finite difference method to practical engineering is complex
domain problem. Recent some studies have launched the geometry
flexibility by means of the coordinate mappings (grid generation)
and element (multidomain) techniques. Although some preliminary
successes were achieved, the flexibility of irregular geometry is still a major
deterrence in the broad application of this type methods compared with the
current dominant FEM. Now we are planning to develop a very promising meshless
technique of the DQM and pseudo-spectral method by using some new approach for
arbitrary geometry.
My contributions
in differential quadrature method and its applications to solid, structure
and fluid mechanics problems (applicable for the pseudo-spectral
and collocation methods due to the actual equivalence between them)
include:
#1: We first noticed the fact that the rank
of the DQM weighting coefficient matrix is M-i for the i-th order
derivative when the number of grid points is M. In fact, the DQM coefficient
matrix is power zero matrix. Based on this fact, we proposed a new
approach to accurately implement the multiple boundary conditions in the
DQM solution of high-order boundary value problems. The presented
methodology solves the difficulty applying the boundary conditions at corner
points especially for solid and structure mechanics problems. The
numerical experiments of linear and nonlinear plate and shell problems
show its easy use, good stability, wide applicability and high accuracy in
comparison with the other approaches.
#2: We validated the centrosymmetric
or skew-centrosymmetric structures of the DQM coefficient matrix
if symmetric gird spacing is employed. Using these matrix structure
features, the computational effort can be reduced by 75% or so for some
problems. For example, plate deflection and vibration problems.
#3: The conventional formulas of the truncation
error estimate in the DQM do not involve the grid interval and are too
imprecise for the practical applications. We presented new formulas to more
accurately estimate the truncation error at any discrete grid points. It is
noted that the formulas are also applicable for the collocation
(pseudo-spectral) method. The given formulas may validate the exponential
convergence of the DQM, while, in contrast, the traditional proof for the collocation
and pseudo-spectral methods used the norm approach and is mathematically
far more complex than mine.
#4: We gave the simplified formulas
for accurately and rapidly computing the DQM weighting coefficients for
equally spaced grid points and the zeros of the Chebyshev or Legendre
polynomials, and presented a simple transformation approach to overcome the
difficulty that the conventional application of the zeros of the orthogonal
polynomials can not encompass the boundary points. It is noted that
the formulas are different from and simpler than those for the collocation
method.
#5: Through the numerical experiments, it was
found that the sampling points using the zeros of the Chebyshev
or Legendre polynomials are often not optimal for many cases, especially
in structural and solid mechanics. A new efficient approach was
presented to choose sampling points.
#6: We presented that the DQM approximate
formulas in matrix form for multi-dimension problems. By using
these formulas, the fast algorithms in the solution of the Lyapunov matrix
equation were introduced to the DQM solution of initial and boundary value
problems with three orders of magnitude less computing effort, which was
demonstrated in the solution of the Possion equation.
#7: We presented the DQM approximate formulas
in matrix form for initial value problem and first applied this
method to approximate temporal derivative successfully. Two new
approaches were presented to apply the multiple initial conditions for
initial value problems of two order or above by analogy with the techniques
applying multiple boundary conditions. It was noted that the formulations of
initial value problems can be expressed as the Lyapunov algebraic matrix
equation. Several fast algorithms in the solution of the Lyapunov matrix
equations are applied to reduce the computing effort and storage requirements
by an order of N^3 and N^2, respectively, where N is the number of interior
grid points. Consequently, the DQM requires comparable computational effort in
the solution of linear dynamic problems as the existing multistep and single
step methods such as the Newmark and Gear methods, etc. while its
high order of computational accuracy is maintained. Numerical experiments were
done in structural dynamics and stiff dynamic systems. It should
be pointed out that the method is unconditional stability, namely, A-stable.
#8: We first used the Hadamard product,
a special matrix product, to express the DQM nonlinear numerical
discretization. By using Hadamard product power concept, we can easily
construct some very simple and efficient iteration formulas of the simple
iteration method for the solution of the Hadamard product representation of
nonlinear formulations without the use of linearization procedure. We also
presented a new special matrix product, SJT product, for easy,
efficient and accurate calculation of the Jacobian matrix of the
nonlinear analogous equations of the Hadamard product representation. The work
also leads to a general approach of uncoupling the numerical formulation
of the coupled nonlinear partial differential systems, which causes a
considerable saving of computer resources. For example, the computational
effort and storage requirements in the DQM solution of geometrically
nonlinear bending of orthotropic plates were reduced by about one
twenty-seventh and one-ninth, respectively.
Differential
Quadrature Method and Its Applications to Engineering Problems - Application
special matrix product to nonlinear computations (in English, Dec. 1996).