Particle-size distribution model wherein random samples are drawn from a given arbitrary probability density function or cumulative distribution function. Input distributions are specified as pairs of (size, probability) (i.e. (point, value) ). More...

Inheritance diagram for general:

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Collaboration diagram for general:

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Public Member Functions
	TypeName ("general")
	Runtime type information. More...

	general (const dictionary &dict, Random &rndGen)
	Construct from components. More...

	general (const UList< scalar > &sampleData, const scalar binWidth, Random &rndGen)
	Construct from components. More...

	general (const general &p)
	Copy construct. More...

virtual autoPtr< distributionModel >	clone () const
	Construct and return a clone. More...

void	operator= (const general &)=delete
	No copy assignment. More...

virtual	~general ()=default
	Destructor. More...

virtual tmp< scalarField >	x () const
	Bin boundaries. More...

virtual tmp< scalarField >	y () const
	Probabilities. More...

virtual scalar	sample () const
	Sample the distribution. More...

virtual scalar	meanValue () const
	Return the arithmetic mean of the distribution data. More...

virtual void	writeData (Ostream &os) const
	Write data to stream. More...

virtual void	readData (Istream &os)
	Read data from stream. More...

virtual dictionary	writeDict (const word &dictName) const
	Write data in dictionary format. More...

virtual void	readDict (const dictionary &dict)
	Read data from dictionary. 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	~distributionModel ()=default
	Destructor. More...

virtual scalar	minValue () const
	Return the minimum of the distribution. More...

virtual scalar	maxValue () const
	Return the maximum of the distribution. More...

Additional Inherited Members
Static Public Member Functions inherited from distributionModel
static autoPtr< distributionModel >	New (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...

Random &	rndGen_
	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 a given arbitrary probability density function or cumulative distribution function. Input distributions are specified as pairs of (size, probability) (i.e. (point, value) ).

Usage

Minimal example by using constant/<CloudProperties>:

subModels
{
    injectionModels
    {
        <name>
        {
            ...

            sizeDistribution
            {
                type        general;
                generalDistribution
                {
                    cumulative      false;

                    distribution
                    (
                        (<size1>    <probability1>)
                        (<size2>    <probability2>)
                        ...
                        (<sizeN>    <probabilityN>)
                    );
                }
            }
        }
    }
}

where the entries mean:

Property	Description	Type	Reqd	Deflt
`type`	Type name: general	word	yes	-
`generalDistribution`	Distribution settings	dict	yes	-
`distribution`	<size>-<probability> pairs	dict	yes	-
`<size>`	Particle size	scalar	yes	-
`<probability>`	Volume fraction/probability	scalar	yes	-
`cumulative`	Flag to determine if input distribution is specified as cumulative or as density	bool	no	false

Note

An example for a pair within distribution subdictionary can be given as follows: "(1e-07 1.3)" means 1.3% of particles are modelled with a particle diameter of "1e-7" [m], and so on.
Variation between input pairs is assumed to be linear.
Elements in the second column (i.e. probability) are normalised.
Elements in the second column for cumulative distribution functions must start from zero and must be non-decreasing (i.e. monotonic).
Elements in the first column (i.e. size) must be specified in an ascending order.
Input pairs cannot contain any negative element.

Source files

Definition at line 165 of file general.H.