Tracerco will be highlighting our latest technology and improved analysis, PackView™ for packed towers, at this year's AIChE 2017 Spring Meeting in San Antonio, Texas.
Mark your schedule to sit in on the paper "Packed Bed Performance Analytics Based on Gamma Scans" presented by Lowell Pless - Business Development Manager - Distillation Applications for Johnson Matthey - Tracerco. The presentation will provide actual case studies illustrating how this advanced analysis provides a new method of extracting quantitative information from gamma scan data to diagnose and characterize operation of distillation and separation towers. Read more about the the presentation in the following abstract that will provide an overview of what will be presented.
Join Lowell Pless for his presentation on Tracerco's PackView™ technology. A brief description of the presentation is shown below.
Refinery and chemical plant operations depend heavily on distillation and separation towers. Tower gamma scanning is well established in the process industries as a qualitative tool to help troubleshoot towers. Advancements in data analysis have led to a quantitative approach in expressing gamma scan data in numerical terms easily understood by process and operations engineers.
For packed towers, a grid-scan of 3 or 4 equal-distant scans crossing through the beds of packing would typically be used to investigate the quality of liquid distribution. The conventional approach to “analyzing” a gamma scan has been to visualize how well the scan data from the individual scans matched each other or how well they “overlaid” with each other. This is a totally subjective analysis lacking consistency, open to varying interpretation and does not translate well from tower-to-tower. Therefore the resulting conclusions from this approach can be very ambiguous regarding magnitude of any detected liquid mal-distribution.
An alternative analytical approach, termed PackView™, has been developed whereby data from a grid-scan provides a relative density scale. The density scale begins at the density of the dry or non-operating packing. To derive this value it is necessary to know the packing type to reference its dry bulk density. The density scale displays the calculated density of liquid retained in the bed of packing based on the scan results. As with typical gamma scan analysis, if the four scanlines have matching liquid retention densities then the implication is that the liquid distribution is good. However, if there is a difference between the scanlines, the retention density gives a numerical comparison from which to gauge the extent or severity of any liquid mal-distribution.
Another calculation by which to put the liquid distribution into perspective and to get a measure on the useful capacity of the packing is to calculate the liquid holdup fraction or liquid volume fraction. If the measured liquid retention density is divided by the process liquid density at bed conditions (the liquid density at the actual operating temperature and pressure), liquid holdup or liquid volume fraction can be established. A comparison to packing operating capacity curves allows this fraction to provide an objective appraisal of current operating capacity.
It is always easier to understand and discuss technical issues when quantitative information can be used to compare operational parameters with engineering design. Over the past 40 years gamma scanning has become more and more popular as a useful diagnostic tool to understand the hydraulic operation of fractionation equipment. This advanced analysis provides a new method of extracting quantitative information from gamma scan data to diagnose and characterize operation of distillation and separation towers. It is our goal that using the advanced analysis presented will improve the value of gamma scan data and facilitate improvements in the operation of mass transfer equipment.
If you want to learn more about how Tracerco's PackView™ technology please complete the form on our contact us page at http://www.tracerco.com/contact-us and request additional PackView™ case studies.