Field Function Monitors

There are seven varieties of field function monitor. During a simulation run, they collect data samples for a selected part at a frequency that you specify.

You can control the sample count by specifying the start time and stop time, and by using a sliding sample window.

Field co-variance -- computes the co-variance of two field functions.
Field max -- obtains the highest value of a field function for the selected part.
Field mean -- obtains the average value of a field function for the selected part.
Field min -- obtains the lowest value of a field function for the selected part.
Field root mean square -- computes the root mean square of a field function for the selected part.
Field sum -- provides the total value of a field function for the selected part.
Field variance -- computes the variance of a field function.

These monitor nodes generally share common properties and a pop-up menu.

Once you set their Field Function and Parts properties, these monitors can be displayed as scalar quantities just like other field functions.

Note	Data mappers can cause inconsistent reporting if you use them with field function monitors or with update events other than iteration, time-step, or delta time.

Note

Field monitors can give less accurate results with finite element data when compared to the native finite element solution. This difference is due to finite element discretization that can provide an exact value of a solution at arbitrary location within the element.

When field monitor data is sampled, it is always sampled at region cells or boundary faces—this value will be the exact finite element solution. However, when that field monitor data is post-processed at vertices, it is interpolated from cells or faces, which cannot use the finite element evaluation process, thus introducing a numerical inconsistency compared to the exact vertex solution computed natively.

For background on Finite Element Analysis, see Finite Element Method. Regarding Finite Volume Analysis, see Finite Volume Discretization.

Note

Field monitors and field histories on moving meshes may require additional preparation. The field monitor takes a running sample of its input field function on mesh cells. In the stationary region, the mesh cells stay in one place all the time, so the sample value is at that fixed point in space. In the rotating region, the mesh cells move, so the sample is of the field value over time at a moving point that moves with the mesh. So data samples in the rotating and stationary regions should not be expected to agree with each other. If you need a value in the rotating region that is comparable to the one in the stationary region, create a non-rotating region for mapping, and use a data mapper to map the quantities of interest to that for use in a field monitor.

What Is Field Co-Variance?

The Field Co-Variance is the statistical co-variance of two field function values as the solution progresses, computed for each cell or boundary face in the selected parts.

Two separate properties exist for the Field Co-Variance monitor’s field function selections: FieldFunction 1 and FieldFunction 2.

The co-variance is based on data samples collected at a user-specified frequency for each cell of the parts being monitored. The sample co-variance, $Cov (x, y)$ , is computed for each cell as:

Cov (x, y) = \frac{1}{N - 1} [\sum_{i = 1}^{N} x_{i} y_{i} - \frac{1}{N} (\sum_{i = 1}^{N} x_{i}) (\sum_{i = 1}^{N} y_{i})]

where:

$x_{i}$ is the Field Function 1 value at collection step $i$ .
$y_{i}$ is the Field Function 2 value at collection step $i$ .
$N$ is the number of time-steps or iterations for which data has been collected.

What Is Field Max?

The Field Max is the maximum value of the specified field function which occurred within each cell or boundary face in the selected parts.

The field function is sampled at a user-specified frequency for each cell of the parts being monitored and the maximum value retained as:

{Cell}_{\max} = \max ({Cell}_{\max}, {Cell}_{c u r r e n t})

where ${Cell}_{c u r r e n t}$ indicates the field function value at the current iteration or time-step.

What Is Field Mean?

The Field Mean is the average of a field function value as the solution progresses, computed for each cell or boundary face in the selected parts.

This arithmetic mean is based on data samples collected at a user-specified frequency for each cell of the parts being monitored. The arithmetic mean, $\bar{x}$ , is computed for each cell as:

\bar{x} = \frac{1}{N} \sum_{i = 1}^{N} x_{i}

where $x_{i}$ is the field function value at collection step $i$ , and $N$ is the number of time-steps or iterations for which data has been collected.

What Is Field Min?

The Field Min is the minimum value of the specified field function which occurred within each cell or boundary face in the selected parts.

The field function is sampled at a user-specified frequency for each cell of the parts being monitored and the minimum value retained as:

{Cell}_{\min} = \min ({Cell}_{\min}, {Cell}_{c u r r e n t})

where ${Cell}_{c u r r e n t}$ indicates the field function value at the current iteration or time-step.

What Is Field Root Mean Square?

The Root Mean Square (RMS) is the square root of the average of the squares of the data.

In Simcenter STAR-CCM+, the RMS value of a field over all samples on a cell is determined from:

R_{r m s} = \sqrt{\frac{1}{n} \sum_{n} r^{2}}

(487)

where $n$ is the number of samples.

What Is Field Sum?

The Field Sum is the total of a field function value as the solution progresses, computed for each cell or boundary face in the selected parts.

This sum is composed of data samples collected at a user-specified frequency for each cell of the parts being monitored. The total, $x_{N}$ , is computed for each cell as:

x_{N} = \sum_{i = 1}^{N} x_{i}

where $x_{i}$ is the field function value at collection step $i$ , and $N$ is the number of time-steps or iterations for which data has been collected.

What Is Field Variance?

The Field Variance is the sample variance of a field function value as the solution progresses, computed for each cell or boundary face in the selected parts.

This statistical variance is based on data samples collected at a user-specified frequency for each cell of the parts being monitored. The sample variance, $s^{2} (x)$ , is computed for each cell as:

s^{2} (x) = \frac{1}{N - 1} [\sum_{i = 1}^{N} x_{i}^{2} - \frac{1}{N} {(\sum_{i = 1}^{N} x_{i})}^{2}]

where $x_{i}$ is the field function value at collection step $i$ , and $N$ is the number of time-steps or iterations for which data has been collected.