A framework for economically optimal operation of explosive waste incineration process to reduce nox emission concentration

Sunghyun Cho, Dongwoo Kang, Joseph Sang Il Kwon, Minsu Kim, Hyungtae Cho, Il Moon, Junghwan Kim

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Explosives, especially those used for military weapons, have a short lifespan and their performance noticeably deteriorates over time. These old explosives need to be disposed of safely. Fluidized bed incinerators (FBIs) are safe for disposal of explosive waste (such as TNT) and produce fewer gas emissions compared to conventional methods, such as the rotary kiln. However, previous studies on this FBI process have only focused on minimizing the amount of NOx emissions without considering the operating and unitality costs (i.e., total cost) associated with the process. It is important to note that, in general, a number of different operating conditions are available to achieve a target NOx emission concentration and, thus, it requires a significant computational requirement to compare the total costs among those candidate operating conditions using a computational fluid dynamics simulation. To this end, a novel framework is proposed to quickly determine the most economically viable FBI process operating condition for a target NOx concentration. First, a surrogate model was developed to replace the high-fidelity model of an FBI process, and utilized to determine a set of possible operating conditions that may lead to a target NOx emission concentration. Second, the candidate operating conditions were fed to the Aspen Plus™ process simulation program to determine the most economically competitive option with respect to its total cost. The developed framework can provide operational guidelines for a clean and economical incineration process of explosive waste.

Original languageEnglish
Article number2174
JournalMathematics
Volume9
Issue number17
DOIs
Publication statusPublished - 2021 Sept

Bibliographical note

Funding Information:
Funding: This work was supported by the Korean Institute of Industrial Technology within the framework of the following projects: “Development of Global Optimization System for Energy Process [grant number EM-21-0022, IR-21-0029, IZ-21-0052]” and “Development of AI Platform Technology for Smart Chemical Process [grant number JH-21-0005]”.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Mathematics(all)
  • Engineering (miscellaneous)

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