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computational fluid dynamics Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical analysis and data structures to analyze and solve problems that involve fluid flows. Computers are used to perform the calculations required to simulate t ...
QUICK, which stands for Quadratic Upstream Interpolation for Convective Kinematics, is a higher-
order Order, ORDER or Orders may refer to: * Categorization, the process in which ideas and objects are recognized, differentiated, and understood * Heterarchy, a system of organization wherein the elements have the potential to be ranked a number of d ...
differencing scheme that considers a three-point upstream weighted
quadratic interpolation In the mathematical field of numerical analysis, interpolation is a type of estimation, a method of constructing (finding) new data points based on the range of a discrete set of known data points. In engineering and science, one often h ...
for the cell face values. In computational fluid dynamics there are many solution methods for solving the steady
convection–diffusion equation The convection–diffusion equation is a combination of the diffusion and convection (advection) equations, and describes physical phenomena where particles, energy, or other physical quantities are transferred inside a physical system due to two ...
. Some of the used methods are the central differencing scheme, upwind scheme, hybrid scheme, power law scheme and QUICK scheme. The QUICK scheme was presented by Brian P. Leonard – together with the QUICKEST (QUICK with Estimated Streaming Terms) scheme – in a 1979 paper. In order to find the cell face value a
quadratic function In mathematics, a quadratic polynomial is a polynomial of degree two in one or more variables. A quadratic function is the polynomial function defined by a quadratic polynomial. Before 20th century, the distinction was unclear between a polynomi ...
passing through two bracketing or surrounding nodes and one
node In general, a node is a localized swelling (a "knot") or a point of intersection (a vertex). Node may refer to: In mathematics * Vertex (graph theory), a vertex in a mathematical graph * Vertex (geometry), a point where two or more curves, line ...
on the upstream side must be used. In central differencing scheme and second order upwind scheme the first order derivative is included and the second order derivative is ignored. These schemes are therefore considered second order accurate where as QUICK does take the second order derivative into account, but ignores the third order derivative hence this is considered third order accurate. This scheme is used to solve
convection–diffusion equation The convection–diffusion equation is a combination of the diffusion and convection (advection) equations, and describes physical phenomena where particles, energy, or other physical quantities are transferred inside a physical system due to two ...
s using second order central difference for the diffusion term and for the
convection Convection is single or multiphase fluid flow that occurs spontaneously due to the combined effects of material property heterogeneity and body forces on a fluid, most commonly density and gravity (see buoyancy). When the cause of the c ...
term the scheme is third order accurate in space and first order accurate in time. QUICK is most appropriate for steady flow or quasi-steady highly convective
elliptic flow Relativistic heavy-ion collisions produce very large numbers of subatomic particles in all directions. In such collisions, ''flow'' refers to how energy, momentum, and number of these particles varies with direction, and elliptic flow is a measure ...
.


Quadratic interpolation for QUICK scheme

For the one-dimensional domain shown in the figure the Φ value at a
control volume In continuum mechanics and thermodynamics, a control volume (CV) is a mathematical abstraction employed in the process of creating mathematical models of physical processes. In an inertial frame of reference, it is a fictitious region of a given v ...
face is approximated using three-point quadratic function passing through the two bracketing or surrounding nodes and one other node on upstream side. In the figure, in order to calculate the value of the property at the face, we should have three nodes i.e. two bracketing or surrounding nodes and one upstream node. # Φw when ''u''w > 0 and ''u''e > 0 a quadratic fit through WW, W and P is used, # Φe when ''u''w > 0 and ''u''e > 0 a quadratic fit through W, P and E is used, # Φw when ''u''w < 0 and ''u''e < 0 values of W, P and E are used, # Φe when ''u''w < 0 and ''u''e < 0 values of P, E and EE are used. Let the two bracketing nodes be ''i'' and ''i'' − 1 and upstream node ''i'' – 2 then for a uniform grid the value of φ at the cell face between the three nodes is given by: : \phi_ = \frac\phi_ + \frac\phi_ - \frac\phi_


Interpretation of the property when the flow is in different directions

The steady convection and diffusion of a property 'Ƥ' in a given one-dimensional flow field with velocity 'u' and in the absence of sources is given : = \frac\left(r \frac\right) . For the continuity of the flow it must also satisfy : = 0. Discretizing the above equation to a control volume around a particular node we get :(\rho u A \phi)_e - (\rho u A \phi)_w = \left(rA\frac\right)_e - \left(rA\frac\right)_w Integrating this continuity equation over the control volume we get : \left(\rho u A \right)_e - \left( \rho u A \right)_w = 0 now assuming F = \rho u and D = r/\sigma x The corresponding cell face values of the above variables are given by : F_w = \left(\rho u\right)_w : F_e = \left(\rho u \right)_e : D_w = / : D_e = / Assuming constant area over the entire control volume we get : F_e\phi_e - F_w\phi_w = D_e\left(\phi_E - \phi_P\right) - D_w \left(\phi_P - \phi_W \right)


Positive direction

When the flow is in positive direction the values of the velocities will be u_w > 0 and u_e > 0 , For "w (west face)" bracketing nodes are W and P, the upstream node is WW then, : \phi_w = \frac\phi_W + \frac\phi_P - \frac\phi_ For "e (east face)" bracketing nodes are P and E, the upstream node is W then : \phi_e = \frac\phi_P + \frac\phi_E - \frac\phi_W
Gradient In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gr ...
of
parabola In mathematics, a parabola is a plane curve which is mirror-symmetrical and is approximately U-shaped. It fits several superficially different mathematical descriptions, which can all be proved to define exactly the same curves. One descri ...
is used to evaluate
diffusion Diffusion is the net movement of anything (for example, atoms, ions, molecules, energy) generally from a region of higher concentration to a region of lower concentration. Diffusion is driven by a gradient in Gibbs free energy or chemical p ...
terms. If ''F''w > 0 and ''F''e > 0 and if we use above equations for the convective terms and central differencing for the diffusion terms, the
discretized In applied mathematics, discretization is the process of transferring continuous functions, models, variables, and equations into discrete counterparts. This process is usually carried out as a first step toward making them suitable for numerical ...
form of the one-dimensional convection–diffusion transport equation will be written as: : F_e \phi_e - F_w \phi_w = D_e\left(\phi_E-\phi_P\right) - D_w \left(\phi_P - \phi_W\right) : F_e \left(\frac \phi_p + \frac\phi_E - \frac\phi_w \right) - F_W\left(\frac\phi_w + \frac\phi_p - \frac\phi_ \right) = D_e \left(\phi_E - \phi_P \right) - D_W\left(\phi_p - \phi_w\right) On re-arranging we get : \left(D_w - \frac F_w + D_e + \frac F_e\right)\phi_P = \left(D_w + \fracF_w + \fracF_e\right)\phi_W + \left(D_e - \fracF_e\right)\phi_E - \fracF_w \phi_ now it can be written in the standard form: : a_P \phi_P = a_W \phi_W + a_E \phi_E + a_ \phi_ where:


Negative direction

When the flow is in negative direction the value of the velocities will be ''u''w < 0 and ''u''e < 0, For west face w the bracketing nodes are W and P, upstream node is E and for the east face E the bracketing nodes are P and E, upstream node is EE For F_w < 0 and F_e < 0 the flux across the west and east boundaries is given by the expressions : : \phi_w = \frac\phi_P + \frac\phi_W - \frac\phi_ : \phi_e = \frac\phi_E + \frac\phi_P - \frac\phi_ Substitution of these two formulae for the convective terms in the discretized convection-diffusion equation together with central differencing for the
diffusion Diffusion is the net movement of anything (for example, atoms, ions, molecules, energy) generally from a region of higher concentration to a region of lower concentration. Diffusion is driven by a gradient in Gibbs free energy or chemical p ...
terms leads, after re-arrangement similar to positive direction as above, to the following coefficients.


QUICK scheme for 1-D convection–diffusion problems

:aPΦP = aWΦW + aEΦE + aWWΦWW + aEEΦEE Here, aP = aW + aE + aWW + aEE + (Fe - Fw) other coefficients where :αw=1 for Fw > 0 and αe=1 for Fe > 0 :αw=0 for Fw < 0 and αe=0 for Fe < 0.


Comparing the solutions of QUICK and upwind schemes

From the below graph we can see that the QUICK scheme is more accurate than the upwind scheme. In the QUICK scheme we face the problems of undershoot and overshoot due to which some errors occur. These overshoots and undershoots should be considered while interpreting solutions. False diffusion errors will be minimized with the QUICK scheme when compared with other schemes.


See also

* Upwind scheme * Power law scheme *
Finite-volume method The finite volume method (FVM) is a method for representing and evaluating partial differential equations in the form of algebraic equations. In the finite volume method, volume integrals in a partial differential equation that contain a divergenc ...
* Finite difference method


References


Further reading

* * *{{Citation , publisher = Cambridge University Press , isbn = 978-0-521-85326-2 , last = Date , first = Anil W. , title = Introduction to Computational Fluid Dynamics , year = 2005 Computational fluid dynamics