A computer simulation, a computer model, or a computational model is a computer program that
attempts to simulate an abstract model of a particular system. Simulations can be used to explore
and gain new insights into physical systems that are difficult or too complex for classical
analytical solutions or physical tests. With Discrete Element Models, we are trying to determine
(or better understand) the behavior of particulate, granular or bulk materials.
But computer modeling is only as good as the people doing the modeling. No computer program,
no matter how good it is, can be expected to produce good results without the proper inputs.
Applied DEM, as the name implies, is as concerned about the proper application of DEM technology
as it is the code behind the scenes. We are first and foremost, engineers with the goal of
solving real life problems. As such, we provide consulting services which compliment our software
If the materials we wish to simulate are consistent and uniform, the characterization of the
elements (particles) should be fairly easy. The size and properties are consistent and
therefore developing a mathematical characterization of interactions between particles
and other system boundaries is relatively straight forward.
But unfortunately for most of us, most bulk materials are not consistent in size or shape.
And mathematical characterization becomes more difficult. But difficult does not mean
impossible. Fourteen years of experience developing these models have shown us that the
characterization of particle interactions can be accurate enough to generate a huge amount
of information on bulk material behavior.
Add some fines to the mix and maybe a little water and our problem just become exponentially
more difficult to solve. Why? Our material just became much more difficult to characterize.
It might even be beyond our capabilities. But today’s research has come up with techniques
to add capillary forces due to moisture to particle interactions and the technology grows
in its goal of simulating even these most difficult real life problems.
An application such as a belt conveyor transfer involves material flowing through a physical
system of boundaries. Important variables for the boundaries may be as simple as the adhesive
coefficient of friction between the boundary material and the bulk material.
Other problems may be more difficult to setup as the boundaries may include multi-directional
movements such as an excavator digging a hole where the forces on the bucket might be determined
and compared with various bucket designs.
Model Calibration Techniques
The following three steps should be used to produce accurate simulation models: calibration,
verification, and validation. Computer simulations are good at portraying and comparing
theoretical scenarios but in order to accurately model actual problems, it has to match
what is actually happening. If a physical problem already exists and can be documented,
a base model or benchmark should be created and calibrated so that it matches the problem
being studied. Model calibration is achieved by adjusting the available parameters
(generally material characterization) in order to adjust how the model operates and
simulates the process.
If a benchmark is not possible maybe because the system being studied does not currently
exist, model verification is achieved by obtaining output data from the model and comparing
it to what is expected from the input data. Validate the model by comparing the results with
what’s expected based on historical data from similar studies. Ideally, the model should
produce similar results to what has happened historically. This might mean adjusting
material properties to reflect a probable or possible range of material properties. The
experience of the engineer is critical at this stage in order to find the parameters most
sensitive to the desired outcome. If the outputs do not reasonably match historic values
during the validation process, the model should be reviewed and updated to produce results
more in line with expectations. It is an iterative process that helps to produce more
Unless these calibration or validation techniques are employed, the simulation model
created MAY NOT produce accurate results and MAY NOT be a useful prediction tool.
Simulation models can be used as a tool to verify engineering theories but are only
valid if calibrated properly. Once satisfactory estimates of the parameters for all
models have been obtained, the models must be checked to assure that they adequately
perform the functions for which they are intended. The validation process establishes
the credibility of the model by demonstrating its ability to replicate real life. The
importance of model validation underscores the need for careful planning, thoroughness
and accuracy of the input data collection program that has this purpose. Efforts should
be made to ensure collected data is consistent with expected operation. The resulting
models and forecasts will be no better than the data used for model estimation and