Mass Balancing (n-Product Formula): Difference between revisions

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imported>Scott.Munro
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Mineral compositions, particle size distributions and water fractions can be substituted in place of metal assays in the method.
Mineral compositions, particle size distributions and water fractions can be substituted in place of metal assays in the method.


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=== Unweighted estimates ===
=== Unweighted estimates ===
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The solids mass flow split to each product stream is found by minimising the unweighted sum of squares of the differences between the mass flows of each assayed component in the feed and product streams, i.e.
The solids mass flow split to each product stream is found by minimising the unweighted sum of squares of the differences between the mass flows of each assayed component in the feed and product streams, i.e.
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:<math>R_{ij} = \dfrac{\beta_j p_{ij}}{\hat{f}_i}</math>
:<math>R_{ij} = \dfrac{\beta_j p_{ij}}{\hat{f}_i}</math>


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=== Weighted estimates ===
=== Weighted estimates ===
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A weighted sum of squares for minimisation can be generated which takes into account measurement uncertainty.
A weighted sum of squares for minimisation can be generated which takes into account measurement uncertainty.
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and the reconstituted feed assays and component recoveries are computed as for the unweighted case.
and the reconstituted feed assays and component recoveries are computed as for the unweighted case.
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=== Monte Carlo estimates ===
=== Monte Carlo estimates ===
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The Monte Carlo method proceeds as follows:
The Monte Carlo method proceeds as follows:


# A set of randomised assays are repeatedly drawn from probability distributions representing the uncertainly of each each measurement.  
# A set of randomised assays are repeatedly drawn from probability distributions representing the uncertainly of each measurement.  
# In this implementation, the assays are assumed be normally distributed and independent.
# In this implementation, the assays are assumed be normally distributed and independent.
# Solid mass splits and recoveries are computed for each randomised assay set.  
# Solid mass splits and recoveries are computed for each randomised assay set.  
# As number of randomised draws increases, the mean values and variances of the mass splits and recoveries will approach their true values.
# As number of randomised draws increases, the mean values and variances of the mass splits and recoveries will approach their true values.
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=== Additional notes ===
=== Additional notes ===
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==== Absolute and relative standard deviations ====
==== Absolute and relative standard deviations ====
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The assay standard deviations required for the weighted estimates, (<math>\sigma_{\rm f},\sigma_{ij}</math>), are ''absolute'' standard deviations, and posses the same units as the assay measurement.  
The assay standard deviations required for the weighted estimates, (<math>\sigma_{\rm f},\sigma_{ij}</math>), are ''absolute'' standard deviations, and posses the same units as the assay measurement.  
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Care must be taken to differentiate between absolute and relative values when applying error models, e.g. the Whiten approach for particle size distributions.{{Greet (2010)}}{{Napier-Munn et al. (1996)}}
Care must be taken to differentiate between absolute and relative values when applying error models, e.g. the Whiten approach for particle size distributions.{{Greet (2010)}}{{Napier-Munn et al. (1996)}}


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==== Component assay magnitude ====
==== Component assay magnitude ====
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Component assays with larger values will tend to dominate the results of the method of mass flow errors. For example, component assays with values of thousands of parts per million will affect the solids mass split more than components with value of a fraction of a weight percent.
Component assays with larger values will tend to dominate the results of the method of mass flow errors. For example, component assays with values of thousands of parts per million will affect the solids mass split more than components with value of a fraction of a weight percent.

Latest revision as of 08:24, 1 May 2025

Description

This article describes a methodology for estimating the solids mass split and recovery of multiple assayed components from a process step with any number of product streams.

Model theory

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Unweighted estimates

Weighted estimates

Additional notes

Absolute and relative standard deviations

Component assay magnitude

Excel

The n-product formula may be invoked from the Excel formula bar with the following function call:

=mdMassBal_nProductFormula(Assays as Range, Optional AbsSD as Range, Optional Transposed as Boolean = False)

Invoking the function with no arguments will print Help text associated with the model, including a link to this page.

The input parameters and calculation results are defined below in matrix notation, along with example images showing the selection of the same cells and arrays in the Excel interface.

Default

The following default arrangement of inputs and results ranges apply when the formula argument Transposed is false or omitted:

where:

  • is total mass fraction of solids in the feed (frac), i.e.
  • the unweighted sum of squares approach is used if is omitted.
Figure 1. Example showing the selection of the Assay (blue frame), AbsSD (red frame), and Results (light blue frame) arrays in Excel.

Transposed

The following arrangement of inputs and results ranges apply when the formula argument Transposed is true:

Figure 2. Example showing the selection of the Assay (blue frame), AbsSD (red frame), and Results (light blue frame) arrays in Excel when .

See also

References