4.7 Article

100 years of scaling up fluidized bed and circulating fluidized bed reactors

Journal

POWDER TECHNOLOGY
Volume 409, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.powtec.2022.117813

Keywords

Fluidization; Scale -up; History; Mechanistic model; Cold -flow experimentation

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As we celebrate the 100th anniversary of the commercialization of the fluidized bed reactor, it is evident that fluidized bed technology has undergone significant advancements in the past century. With the development of sophisticated models, experimentation techniques, and statistical tools, as well as the utilization of computational platforms and AI, the application of fluidized bed technology is expected to become more cost-effective and efficient.
This year, 2022, we celebrate the 100-year anniversary of the commercialization of the fluidized bed reactor. In those years, many new processes have been developed, with many of them considered breakthrough technolo-gies, replacing technologies that were no longer considered competitive. Fluidized beds have the advantages of superior heat transfer and the ability to continuously move solids during operation, along with a list of other attributes. As a result, processes spanning coal and biomass gasification, pyrolysis, fluidized catalyst cracking, acrylonitrile, polyethylene, oxychlorination, and polycrystalline silicon have prospered with the application of fluidized bed technology. Expect that list to continue with current efforts in chemical looping, plastic pyrolysis, methane pyrolysis, and propane dehydrogenation, to name a few. In the past 100 years, the landscape of fluidized beds and circulating fluidized bed reactors has grown in numbers and applications. With those applications comes 100 years of scaling up and optimizing those fluidized beds. We have seen engineering go from an incremental approach to a more fundamental approach using so-phisticated models and relevant cold flow experimentation. That engineering work process is still changing. With the onset of better computational platforms, models, and experimental techniques, combined with better sta-tistical tools (e.g., machine learning) and control systems (e.g., artificial intelligence), the application of fluidized bed technology will require less capital, less operating costs, and allow for commercialization in less time.

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