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DIN ISO 9276-4:2006-02

Superseded

Superseded

A superseded Standard is one, which is fully replaced by another Standard, which is a new edition of the same Standard.

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REPRESENTATION OF RESULTS OF PARTICLE SIZE ANALYSIS - PART 4: CHARACTERIZATION OF A CLASSIFICATION PROCESS

Available format(s)

Hardcopy , PDF

Superseded date

14-03-2020

Superseded by

DIN ISO 9276-4:2019-09

Language(s)

English

Published date

01-01-2006

€91.12
Excluding VAT

Foreword
Introduction
1 Scope
2 Symbols
   2.1 Symbols for specific terms
   2.2 Subscripts
3 Characterization of a classification process based on
   error-free distribution curves and mass balances
   3.1 Density distribution curves representing a classification
       process
   3.2 Mass and number balances
   3.3 Definitions of cut size, x[e]
   3.4 Grade efficiency, T, the grade efficiency curve, T(x),
       (Tromp's curve)
   3.5 Measures of sharpness of cut
4 The influence of systematic errors on the determination of
   grade efficiency curve
   4.1 General
   4.2 Systematic error due to a splitting process in the
       classifier
   4.3 Incomplete dispersion of the feed material
   4.4 The influence of comminution of the feed in the classifier
Annex A (informative) The influence of stochastic errors on the
        evaluation of grade efficiency curves
Bibliography

Specifies the mathematical background for the characterization of a classification process.

DevelopmentNote
Supersedes DIN 66142-1. (02/2006)
DocumentType
Standard
Pages
22
PublisherName
German Institute for Standardisation (Deutsches Institut für Normung)
Status
Superseded
SupersededBy

Standards Relationship
ISO 9276-4:2001 Identical

DIN ISO 9276-6:2012-01 Representation of results of particle size analysis - Part 6: Descriptive and quantitative representation of particle shape and morphology (ISO 9276-6:2008)

ISO 9276-1:1998 Representation of results of particle size analysis — Part 1: Graphical representation
ISO 9276-2:2014 Representation of results of particle size analysis — Part 2: Calculation of average particle sizes/diameters and moments from particle size distributions

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