Computation fluid dynamics (CFD) is a powerful measurement tool used to model many dynamic processes. Whilst single phase processes are well established, there is continual work being done to develop and improve CFD methodologies for more complex multi-phase processes.
Overall, CFD will model concentration profiles and flow velocities, mapping these on a mesh within a standardise model of the process geometry. It should be noted that whilst starting from basic physical equations, CFD requires a wide range of assumptions to develop its sophisticated outputs.
Process tomography uses volumetric measurement techniques to rapidly scan through a process space and map electrical distributions. These in turn can be converted into volumetric concentrations of process materials.
As data can be taken at frame rates up to 1,000 times per second (for a complete scan), dynamic changes can be directly measured for comparison with CFD.
The key differences between process tomography data and CFD experiments is that tomography results are derived from process conditions which have inherent experimental uncertainties arising from process conditions and measurements. Also, tomography requires the application of algorithms to translate measurements into information. However they benefit significantly from the use of actual process materials (electrical tomography rarely requires use of surrogate materials) and process conditions can be applied as they are under actual conditions.
ITS technology has contributed to CFD research across a variety of process platforms, including flow through packed beds, conveying of mineral slurries, highly gassed reactors and hydrocylones.