对于过程合成的高级建模和优化策略
Efstratios N Pistikopoulos1, Yuhe Tian2
1Texas A&M Energy Institute and Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas, USA;
Annual review of chemical and biomolecular engineering
|April 10, 2024
概括
本综述涵盖了基于优化的过程合成方面的进展,包括多尺度建模和可持续性等扩展目标. 它探索新的算法和工具,如机器学习和量子计算,用于未来的战略.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 工艺系统工程 工艺系统工程
背景情况:
- 基于优化的过程合成对于开发高效和可持续的化学过程至关重要.
- 传统的方法正在发展,以应对动态市场和环境问题中的复杂挑战.
研究的目的:
- 系统地审查基于优化的过程合成的最新进展.
- 突出建模,目标和计算工具方面的进步.
主要方法:
- 对多尺度建模框架的审查 (定向,基于现象,基于单元操作,混合).
- 对扩展过程合成目标 (可持续性,可操作性) 的分析.
- 对优化算法和工具 (机器学习,量子计算) 的调查.
主要成果:
- 多尺度建模为流程设计提供了多样化的框架.
- 整合可持续性和可操作性提高了过程竞争力和环境调整.
- 新的优化方法,包括人工智能和量子计算,正在出现.
结论:
- 在基于优化的过程合成方面取得了重大进展.
- 未来的战略可能将集成先进的建模,更广泛的目标和尖端的计算工具.
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