Journal of the American Ceramic Society · 1991 · 37 citations · 16 references
EngineeringMaterials EngineeringMaterials ScienceBuilding MaterialsFormation EvaluationMechanical Behavior Of MaterialsCementitious MaterialsPermeability EstimationPermeability EvaluationPorosity AnalysisPorosity CharacterizationPorous MaterialsCompound Distribution ModelsDensity Probability Distribution FunctionGraphical ModelsMercury Intrusion PorosimetryMultimodal Distribution AnalysisPermeability Of Cement PastePore-size DistributionPorosity - Permeability Relationship
The pore size distributions in cement pastes and mortars, over the range of pore sizes determined by high‐pressure mercury intrusion porosimetry (MIP), can be described in terms of a multimodal distribution by using lognormal simulation. The pore size distribution may be regarded as a mixture of lognormal distributions. Such a mixture is defined by a compound density function: p ( x ) =Σ f i p ( x , μ i , σ i ), Σ f i = 1, where x is the pore diameter, f i , is the weighting factor of the i th lognormal subdistribution of pore sizes, p ( x , μ i , σ i ), and μ i and σ i are the location parameter and the shape parameter of the i th subdistribution, respectively. It may indicate that different origins and formation mechanisms exist for pores in different size ranges in cementitious materials. A graphical method is proposed to estimate the parameters for the compound distribution. Applications of this model to prediction of permeability are discussed.
16
Applied Linear Statistical Models.
Frederick O. Lorenz, John Neter, William Wasserman et al. · Journal of the American Statistical Association · 1986 · 5.7K citations
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