An Integrated Framework for Greener Solvent Selection and Solvent Recycling under Uncertainty

不确定性下更环保的溶剂选择和溶剂回收的综合框架

• 批准号: 0353085
• 负责人: Urmila Diwekar
• 金额: $ 24.5万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-01 至 2007-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0353085&HistoricalAwards=false
• 关键词: Integrated; Framework; Greener; Solvent; Selection

ResearchWaste solvents from the chemical process industries (CPI) are not only financially costly because funds are needed for separation, removal and disposal, but what is not removed deteriorates environmental quality. Solvent recycling is costly and determining optimal separation sequences is a complex process synthesis problem. This research project is a coupled solvent selection (which involves "product design" and chemical synthesis) and solvent recycling ("process design") approach to pollution prevention and greener processes. Integrating chemical synthesis with process synthesis to improve environmental and economic performance poses a challenging mathematical problem of multiple conflicting objectives, with a combinatorial explosion of alternatives and uncertainties. This project focuses on the development of an efficient multiobjective optimization (MOP) framework under uncertainty for this simultaneous integration around the commercially available ASPEN simulator. This framework is based on algorithms for multiobjective, discrete/continuous optimization, and for uncertainty analysis. The multiobjective optimization framework will provide a set of non-dominant designs where further improvements for one objective will be at the expense of another. This is valuable in a situation where there are a large number of desirable and important objectives, which are not easily translated into dollars: for example, human health and life, environmental impacts and plant flexibility. The framework will also be useful to solve problems where objectives are difficult to quantify, and when there is a lack of data or the data is inaccurate.Broad ImpactBesides the obvious importance to the environment, the project will also benefit underrepresented groups as the PI plans to target women for participation in the project and is collaborating with the University of Puerto Rico/Mayaguez. The PI is a faculty advisor for the Society of Women Engineers (SWE) and a mentor in the Women in Science and Engineering (WISE) program.

研究化学加工工业(CPI)产生的废溶剂不仅经济上昂贵，因为需要资金进行分离、去除和处置，而且不去除的溶剂会恶化环境质量。溶剂回收成本很高，确定最佳分离顺序是一个复杂的过程综合问题。这一研究项目是一种溶剂选择(包括“产品设计”和化学合成)和溶剂回收(“工艺设计”)相结合的方法，以防止污染和更绿色的工艺。将化学合成与过程合成相结合以改善环境和经济性能提出了一个具有挑战性的数学问题，该问题具有多个相互冲突的目标，以及备选方案和不确定性的组合爆炸。该项目致力于在不确定条件下开发一个高效的多目标优化(MOP)框架，以实现与商用Aspen模拟器的同步集成。该框架基于多目标、离散/连续优化和不确定性分析的算法。多目标优化框架将提供一套非主导设计，其中一个目标的进一步改进将以牺牲另一个目标为代价。这在有大量可取和重要目标的情况下是有价值的，这些目标不容易转化为金钱：例如，人类健康和生命、环境影响和植物灵活性。该框架还将有助于解决目标难以量化的问题，以及在缺乏数据或数据不准确的情况下。广泛影响除了对环境的明显重要性外，该项目还将使代表不足的群体受益，因为国际和平协会计划以妇女为目标参与该项目，并正在与波多黎各大学/马亚圭斯大学合作。PI是女性工程师协会(SWE)的教师顾问，也是女性科学与工程(WISE)计划的导师。