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March 28, 2018, 15:30 
size distribution models in OpenFOAM 4.x

#1 
Member
Min Zhang
Join Date: Mar 2017
Posts: 80
Rep Power: 7 
In distributionModel.H, it says:
Class Foam::distributionModel Description A library of runtimeselectable distribution models. Returns a sampled value given the expectation (nu) and variance (sigma^2) Current distribution models include:  exponential  fixedValue  general  multinormal  normal  RosinRammler  uniform The distributionModel is tabulated in equidistant nPoints, in an interval. These values are integrated to obtain the cumulated distribution model, which is then used to change the distribution from unifrom to the actual distributionModel. My goal: Set a volume uniform particle size distribution. my Questions: Q1. What is "general distribution", in this thread Size Distribution Models  Spray Modelling Chrisi1984 gave a general distribution example, I want to make sure whether the second column is the number fraction of the corresponding particle size in the first column. Q2. The "uniform distribution" is a uniform DISTRIBUTION between minValue and maxVaue, yes? My point is it is not a single particle size, it is a distribution. If we choose to use the uniform distribution, we only need to give "minValue" and "maxValue".Then, my question is how many particle sizes (which is nPoints in the above copied distributionModel.H description, yes?) are used? Q3. For my goal "a mass/volume uniform PSD (since the particles have the same density, volume fraction is the same as mass fraction)", which is the efficient option? Right now, I think the general distribution could be the solution. Thanks and best regards, Min 

March 30, 2018, 18:10 

#2  
Member
Min Zhang
Join Date: Mar 2017
Posts: 80
Rep Power: 7 
Quote:
My own answers: Q1: The second column is the volume fraction/probability, not number fraction. Q2: I have no answer currently. Q3: "uniform" distributionModel would be the most efficient option. This is because it is uniform mass fraction. Any comments would be very appreciated! 

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