GenCade:Numerical Stability: Difference between revisions
No edit summary |
mNo edit summary |
||
(One intermediate revision by one other user not shown) | |||
Line 1: | Line 1: | ||
{{DISPLAYTITLE:GenCade Numerical Stability}} | |||
The GenCade model utilizes an explicit solution scheme. The main advantages are: easy programming, simple (and sometimes the only possible) expressions of boundary conditions, and shorter computer run-time as compared to an implicit scheme (for a single time increment). A major disadvantage is, however, the stability of the solution. This means that smaller time steps are often needed, and thus a longer simulation time as compared to an implicit scheme. To minimize the computational effort, the longest time step that may be used for a specific calculation must be determined. Under certain idealized conditions, the CERC equation can be reduced to a simpler form to examine the dependence of the solution on the time and space steps. First, rewrite the CERC equation in the form: | The GenCade model utilizes an explicit solution scheme. The main advantages are: easy programming, simple (and sometimes the only possible) expressions of boundary conditions, and shorter computer run-time as compared to an implicit scheme (for a single time increment). A major disadvantage is, however, the stability of the solution. This means that smaller time steps are often needed, and thus a longer simulation time as compared to an implicit scheme. To minimize the computational effort, the longest time step that may be used for a specific calculation must be determined. Under certain idealized conditions, the CERC equation can be reduced to a simpler form to examine the dependence of the solution on the time and space steps. First, rewrite the CERC equation in the form: | ||
Line 13: | Line 14: | ||
where <math> \varepsilon_1 = \frac{2Q_O a_1}{D_B + D_C} </math> and <math> \varepsilon_2 = \frac{Q_O a_2 sin\alpha_b}{D_B + D_C} {\frac{\partial H_b}{\partial x}} </math> | where <math> \varepsilon_1 = \frac{2Q_O a_1}{D_B + D_C} </math> and <math> \varepsilon_2 = \frac{Q_O a_2 sin\alpha_b}{D_B + D_C} {\frac{\partial H_b}{\partial x}} </math> | ||
In the presence of an external current not generated by breaking waves, the second diffusion coefficient in the above partial differential will change to: | In the presence of an external current not generated by breaking waves, the second diffusion coefficient in the above partial differential equation will change to: | ||
<math> \varepsilon_2 = \frac{Q_O sin\alpha_b}{D_B + D_C} (a_2 \frac{\partial H_b}{\partial x} - a_3 \frac{\bar{v}_t}{u_m}) </math> | <math> \varepsilon_2 = \frac{Q_O sin\alpha_b}{D_B + D_C} (a_2 \frac{\partial H_b}{\partial x} - a_3 \frac{\bar{v}_t}{u_m}) </math> | ||
As the above | As the above is a diffusion-type equation, its stability properties are well known. The numerical stability of the calculation scheme is governed by: | ||
<math> R_s = \frac{\Delta t (\varepsilon_1 + \varepsilon_2)}{(\Delta x)^2} </math> | <math> R_s = \frac{\Delta t (\varepsilon_1 + \varepsilon_2)}{(\Delta x)^2} </math> |
Latest revision as of 14:57, 6 March 2023
The GenCade model utilizes an explicit solution scheme. The main advantages are: easy programming, simple (and sometimes the only possible) expressions of boundary conditions, and shorter computer run-time as compared to an implicit scheme (for a single time increment). A major disadvantage is, however, the stability of the solution. This means that smaller time steps are often needed, and thus a longer simulation time as compared to an implicit scheme. To minimize the computational effort, the longest time step that may be used for a specific calculation must be determined. Under certain idealized conditions, the CERC equation can be reduced to a simpler form to examine the dependence of the solution on the time and space steps. First, rewrite the CERC equation in the form:
where (cubic meters/second). A useful approximate stability criterion can be obtained by linearizing the governing equation with respect to y. The linearization is made by assuming small breaking wave and shoreline angles, which leads to:
and
where is the angle of breaking waves to the local shoreline orientation, is the angle of breaking waves to the x-axis, and is the local shoreline orientation. Assuming that is zero, the governing equation becomes (Kraus and Harikai 1983):
where and
In the presence of an external current not generated by breaking waves, the second diffusion coefficient in the above partial differential equation will change to:
As the above is a diffusion-type equation, its stability properties are well known. The numerical stability of the calculation scheme is governed by:
where the quantity is known as the Courant number in numerical methods; here it is called the stability parameter. The finite difference form of the above governing partial differential equation shows that which means that if is reduced by a factor of two, the time step will need to be reduced by a factor of four to maintain the same stability of the calculation scheme. If an explicit solution scheme is used to solve the diffusion equation, the following condition must be satisfied (Crank 1975):
If the value of exceeds 0.5 at any point on the grid, the calculated shoreline will start to become unstable and show unrealistic oscillations in time. The parameters and can change substantially alongshore since they depend on the local wave conditions. Assuming that the grid cell spacing is fixed by engineering requirements, a large wave height would necessitate a small value of . The GenCade model will issue a warning if the stability requirement is violated at any point in the domain. If such a warning is issued, either the time step or the spatial resolution (or both) will need to be reduced. Thus, it is necessary to increase and/or decrease .