#include <LambdaEffective.h>
◆ LambdaEffective()
LambdaEffective::LambdaEffective |
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const InputParameters & |
parameters | ) |
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◆ execute()
virtual void KEigenvalue::execute |
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inlineoverridevirtualinherited |
◆ getValue()
virtual Real LambdaEffective::getValue |
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const |
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overridevirtual |
◆ initialize()
virtual void KEigenvalue::initialize |
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| ) |
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inlineoverridevirtualinherited |
◆ kMean()
Real KEigenvalue::kMean |
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const |
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protectedinherited |
A function which computes the mean value of k_{eff}.
- Returns
- the mean value of the k-eigenvalue
◆ kRelativeError()
Real KEigenvalue::kRelativeError |
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const |
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protectedinherited |
A function which computes the relative error of k_{eff}.
- Returns
- the relative error of the k-eigenvalue
◆ KStandardDeviation()
Real KEigenvalue::KStandardDeviation |
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const |
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protectedinherited |
A function which computes the standard deviation of k_{eff}.
- Returns
- the standard deviation of the k-eigenvalue
◆ stdev()
Real OpenMCBase::stdev |
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const double & |
mean, |
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const double & |
sum_sq, |
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unsigned int |
realizations |
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) |
| const |
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protectedinherited |
Compute standard deviation of a variable
- Parameters
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[in] | mean | mean |
[in] | sum_sq | sum squared |
[in] | realizations | the number of realizations of the variable |
- Returns
- standard deviation
◆ validParams()
static InputParameters LambdaEffective::validParams |
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| ) |
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static |
◆ _openmc_problem
◆ _output
The value of the kinetics parameter to output.
◆ _type
Type of k-effective value to report. Options: collision, absorption, tracklength, and combined (default).
The combined k-effective estimate is a minimum variance estimate of k-effective based on a linear combination of the collision, absorption, and tracklength estimates.
The documentation for this class was generated from the following file: