What is Crusher Modeling?

Aggregate plant flow modeling in North America relies heavily on the use of crusher manufacturer provided gradations.  These gradation estimates may provide a useful starting point when no other data are available.  At existing plants, sporadic measurements of crusher feed and discharge gradations may be available.  These gradations may represent different plant processes or modes and therefore must be managed separately in the plant flow simulator.  Furthermore, what happens when you change a screen upstream of the crusher during “What  If” scenarios.  Did your plant flow modeling program dynamically change the crusher discharge based on the resulting change to the crusher feed using “real-world” measured data? 

Stonemont works with over 2000 plants in North America and has noticed that there is a growing trend to implement more regular sampling in aggregate plants beyond the finished products, especially at crushers.  Certainly our StonemontQC product facilitates the entry, analysis, and reporting of this data.  However, there has to be a better way to utilize this data in plant flow modeling than static discharge gradations that are no longer useful in “What If” scenarios.  One answer is to create a dynamic model of the crusher using crusher tests.

Example of Crusher Modeling in StonemontQC.

Crusher modeling uses the Whiten (1972) crusher model to simulate the classification and breakage functions of the crushing process.   The Whiten model requires that classification parameters (K1,K2,K3) and a breakage parameter (T10) be defined.  These parameters relate back to the crushing process; K1 is the size below which all particles escape breakage; K2 is the size above which all particles are crushed; K3 describes the shape of the classification function; T10 is the percent of product passing 1/10th of the original particle size, after breakage.  These parameters can be readily determined by fitting the appropriate equations to crusher feed and discharge gradations.   However, what makes the model useful is that the parameters are largely functions of flow rate, feed size and liner characteristics.  For example, the cone crushing process at a particular operation can be effectively modeled using “real-world” measured values such as closed-side setting (css), flow rate (tph), 80% passing feed (f80), liner age (lhr), and a few other optional parameters.  Crusher modeling in StonemontQC has been optimized by allowing the user to quickly evaluate which parameters (CSS, TPH, etc.) best-fit the crusher model. 

The end result is an aggregate plant flow simulation model that dynamically simulates changes to the crusher discharge gradation resulting from a changing feed distribution caused from crusher, screen, or other plant configuration changes upstream.  For more information contact Stonemont Solutions, Inc.

Adrian Field
Stonemont Solutions, Inc.