RosinRammler Class Reference

Particle-size distribution model wherein random samples are drawn from the doubly-truncated two-parameter Rosin-Rammler (Weibull) probability density function: More...

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Public Member Functions

 TypeName ("RosinRammler")
 Runtime type information. More...
 
 RosinRammler (const dictionary &dict, Random &rndGen)
 Construct from components. More...
 
 RosinRammler (const RosinRammler &p)
 Copy construct. More...
 
virtual autoPtr< distributionModelclone () const
 Construct and return a clone. More...
 
void operator= (const RosinRammler &)=delete
 No copy assignment. More...
 
virtual ~RosinRammler ()=default
 Destructor. More...
 
virtual scalar sample () const
 Sample the distribution. More...
 
virtual scalar meanValue () const
 Return the theoretical mean of the distribution. More...
 
- Public Member Functions inherited from distributionModel
 TypeName ("distributionModel")
 Runtime type information. More...
 
 declareRunTimeSelectionTable (autoPtr, distributionModel, dictionary,(const dictionary &dict, Random &rndGen),(dict, rndGen))
 Declare runtime constructor selection table. More...
 
 distributionModel (const word &name, const dictionary &dict, Random &rndGen)
 Construct from dictionary. More...
 
 distributionModel (const distributionModel &p)
 Copy construct. More...
 
virtual autoPtr< distributionModelclone () const =0
 Construct and return a clone. More...
 
virtual ~distributionModel ()=default
 Destructor. More...
 
virtual scalar sample () const =0
 Sample the distribution. More...
 
virtual scalar minValue () const
 Return the minimum of the distribution. More...
 
virtual scalar maxValue () const
 Return the maximum of the distribution. More...
 
virtual scalar meanValue () const =0
 

Additional Inherited Members

- Static Public Member Functions inherited from distributionModel
static autoPtr< distributionModelNew (const dictionary &dict, Random &rndGen)
 Selector. More...
 
- Protected Member Functions inherited from distributionModel
virtual void check () const
 Check that the distribution model is valid. More...
 
- Protected Attributes inherited from distributionModel
const dictionary distributionModelDict_
 Coefficients dictionary. More...
 
RandomrndGen_
 Reference to the random number generator. More...
 
scalar minValue_
 Minimum of the distribution. More...
 
scalar maxValue_
 Maximum of the distribution. More...
 

Detailed Description

Particle-size distribution model wherein random samples are drawn from the doubly-truncated two-parameter Rosin-Rammler (Weibull) probability density function:

\[ f(x; \lambda, n, A, B) = \frac{ \frac{n}{\lambda} \left( \frac{x}{\lambda} \right)^{n-1} \exp\{ -(\frac{x}{\lambda})^n \} }{ \exp\{- (\frac{A}{\lambda})^n \} - \exp\{- (\frac{B}{\lambda})^n \} } \]

where

\( f(x; \lambda, n, A, B) \) = Rosin-Rammler probability density function
\( \lambda \) = Scale parameter
\( n \) = Shape parameter
\( x \) = Sample
\( A \) = Minimum of the distribution
\( B \) = Maximum of the distribution

Constraints:

  • \( \infty > B > A > 0\)
  • \( x \in [B,A] \)
  • \( \lambda > 0 \)
  • \( n > 0 \)

Random samples are generated by the inverse transform sampling technique by using the quantile function of the doubly-truncated two-parameter Rosin-Rammler (Weibull) probability density function:

\[ x = \lambda \left( q_{min} - \ln (1 - u r) \right)^{1/n} \]

with

\[ r = 1 - \exp(-q_{max} + q_{min}) \]

\[ q_{min} = \left(\frac{A}{\lambda}\right)^n \]

\[ q_{max} = \left(\frac{B}{\lambda}\right)^n \]

where \( u \) is sample drawn from the uniform probability density function on the unit interval \( (0, 1) \).

Reference:

    Doubly-truncated two-parameter Weibull distribution and its moments (tag:C):
        Crénin, F. (2015).
        Truncated Weibull Distribution Functions and Moments.
        SSRN 2690255.
        DOI:10.2139/ssrn.2690255
Usage
Minimal example by using constant/<CloudProperties>:
subModels
{
    injectionModels
    {
        <name>
        {
            ...

            sizeDistribution
            {
                type        RosinRammler;
                RosinRammlerDistribution
                {
                    lambda      <scaleParameterValue>;
                    n           <shapeParameterValue>;
                    minValue    <minValue>;
                    maxValue    <maxValue>;
                }
            }
        }
    }
}

where the entries mean:

Property Description Type Reqd Deflt
type Type name: RosinRammler word yes -
RosinRammlerDistribution Distribution settings dict yes -
lambda Scale parameter scalar yes -
n Shape parameter scalar yes -
minValue Minimum of the distribution scalar yes -
maxValue Maximum of the distribution scalar yes -
Source files

Definition at line 219 of file RosinRammler.H.

Constructor & Destructor Documentation

◆ RosinRammler() [1/2]

RosinRammler ( const dictionary dict,
Random rndGen 
)

Construct from components.

Definition at line 46 of file RosinRammler.C.

◆ RosinRammler() [2/2]

RosinRammler ( const RosinRammler p)

Copy construct.

Definition at line 80 of file RosinRammler.C.

◆ ~RosinRammler()

virtual ~RosinRammler ( )
virtualdefault

Destructor.

Member Function Documentation

◆ TypeName()

TypeName ( "RosinRammler"  )

Runtime type information.

◆ clone()

virtual autoPtr< distributionModel > clone ( ) const
inlinevirtual

Construct and return a clone.

Implements distributionModel.

Definition at line 247 of file RosinRammler.H.

◆ operator=()

void operator= ( const RosinRammler )
delete

No copy assignment.

◆ sample()

Foam::scalar sample ( ) const
virtual

Sample the distribution.

Implements distributionModel.

Definition at line 90 of file RosinRammler.C.

References Foam::exp(), Foam::log(), and Foam::pow().

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◆ meanValue()

Foam::scalar meanValue ( ) const
virtual

Return the theoretical mean of the distribution.

Implements distributionModel.

Definition at line 100 of file RosinRammler.C.

References Foam::exp(), Foam::gMax(), Foam::gMin(), Foam::Math::incGamma_P(), and Foam::pow().

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The documentation for this class was generated from the following files: