权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

A Computational Framework for Design and Optimization of Dynamic Membrane Processes

动态膜过程设计和优化的计算框架

基本信息

批准号：
2140946
负责人：
Mingheng Li
金额：
$ 30万
依托单位：
Cal Poly Pomona Foundation, Inc.
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2140946&HistoricalAwards=false
关键词：
Computational Framework Design Optimization Dynamic

项目摘要

It is estimated that over half of the world’s population is affected by fresh-water scarcity and that this figure will continue to rise because of the Earth’s changing climate, unbalanced socio-economic development, and continued population growth. The same can be said for the geographic imbalances of energy availability, which are driven by parallel factors. Desalination offers a viable solution to clean-water production from seawater and brackish groundwater. Among desalination techniques, reverse osmosis (RO) membrane separators are the most widely used due to their energy efficiency relative to those based on distillation. However, even advanced multistage RO processes suffer from inefficiencies and inherent operational challenges including membrane fouling and scaling, transient operation due to the need for periodic flushing of the membrane, the computational challenges posed in model-based optimization of RO networks, and the need for high water recovery levels in inland areas where costs are associated with disposal of brine waste. This research program will advance the fundamental understanding of dynamic (batch, semi-batch, and cyclic modes) membrane-based separation processes and will optimize their design and performance during dynamic operation. Specifically, this proposal aims to (i) investigate salt retention, fouling, scaling, and concentration polarization (a measure of solute concentration gradient at the membrane surface) under transient conditions and internal separator geometry design using computational fluid dynamics (CFD), (ii) explore system dynamics and apply optimal control theory to enhance system performance, (iii) develop novel networked process designs, and (iv) validate results using pilot-scale data from local water districts. These objectives will ultimately lead to transformative innovations in dynamic membrane processes to help address the pressing issues in water and energy availability. The project also will provide research opportunities to a diverse group of undergraduate and high school students. Educational modules on advanced RO system design and operation will be developed to benefit students, researchers, and industrial practitioners in the field.This proposal presents a vision for developing dynamic reverse osmosis (RO) processes to overcome the practical limitation of the infinite number of membrane stages and inter-stage booster pumps that would be required for (theoretically) optimal desalination system performance under steady operation, the current nominal mode of operation. The challenge to be addressed is the concurrent optimal design of the multistage networked membrane separator system together with determining the optimal time-periodic mode of operating the entire system. Dynamic 3-dimensional computational fluid dynamic (CFD) techniques are required for accurate RO module simulations – however, using these types of simulations in the task of RO network design and optimization is computationally intractable at this time. Therefore, a reduced-order 1-dimensional model with parameters fitted from the detailed CFD simulations and validated against actual desalination plant data will be developed. This reduced model can be efficiently discretized by orthogonal collocation and subsequently will be used to define a rigorous optimal control problem that seeks to minimize energy use and maximize clean water recovery. This research program will leverage current knowledge on the design of pressure-swing adsorption (PSA) processes, a mature industrial technology for gas separations, to guide initial designs for the networked RO desalination systems. Like the planned RO systems, PSA plants operate under transient conditions and feature spatial concentration gradients within the separation units. The dynamic modeling, optimization, and design tools for RO networks inspired by PSA systems will be extended to green power generation systems that effectively operate as RO in reverse: osmotic pressure generated by the permeation of water through a membrane to a saline solution increases the latter’s pressure and volumetric flowrate which is subsequently harvested for power. Overall, this research program will fundamentally advance the set of systems engineering tools available for producing reduced-order simulations from detailed, spatiotemporally distributed transport models needed for the model-based design and optimization of transient chemical processes outside of RO systems. Coupled with this research plan, a range of education and outreach plans focusing on undergraduate researcher support and a unique student exchange program with UCLA is planned.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

据估计，世界上一半以上的人口受到淡水短缺的影响，由于地球气候变化、社会经济发展不平衡和人口持续增长，这一数字将继续上升。能源可获得性的地理失衡也是如此，这些失衡是由平行因素驱动的。海水淡化为从海水和咸水地下水中生产清洁水提供了一个可行的解决方案。在海水淡化技术中，反渗透(RO)膜分离器因其相对于蒸馏的能源效率而得到最广泛的应用。然而，即使是先进的多级反渗透工艺也面临着效率低下和固有的操作挑战，包括膜污染和结垢、由于需要定期冲洗膜而导致的瞬时运行、基于模型的反渗透网络优化带来的计算挑战，以及内陆地区需要高水平的水回收，这些地区的成本与处理盐水废物有关。这项研究计划将促进对动态(间歇、半间歇和循环模式)膜分离过程的基本理解，并将在动态操作期间优化其设计和性能。具体地说，该建议旨在(I)利用计算流体力学(CFD)研究瞬变条件下的盐滞留、污染、结垢和浓差极化(膜表面溶质浓度梯度的测量)和内部分离器的几何设计，(Ii)探索系统动力学并应用最优控制理论来提高系统性能，(Iii)开发新颖的网络化过程设计，以及(Iv)使用来自当地水域的中试数据来验证结果。这些目标最终将导致动态膜工艺的变革性创新，以帮助解决水和能源供应方面的紧迫问题。该项目还将为不同的本科生和高中生群体提供研究机会。将开发先进的反渗透系统设计和操作的教学模块，以使学生、研究人员和该领域的工业从业者受益。这项建议提出了开发动态反渗透(RO)工艺的愿景，以克服在稳定运行(当前名义运行模式)下实现(理论上)最佳海水淡化系统性能所需的无限数量的膜级和级间增压泵的实际限制。需要解决的挑战是多级网络化膜分离系统的并行优化设计，以及确定整个系统运行的最佳时间周期模式。动态三维计算流体力学(CFD)技术是精确的反渗透模块模拟所必需的，然而，目前在反渗透网络设计和优化任务中使用这些类型的模拟在计算上是困难的。因此，将开发一个降阶的一维模型，其参数由详细的CFD模拟进行拟合，并与实际的海水淡化厂数据进行验证。这个简化的模型可以通过正交配置进行有效的离散化，随后将被用来定义一个严格的最优控制问题，寻求最大限度地减少能源消耗和最大限度地回收清洁水。这项研究计划将利用变压吸附(PSA)工艺设计方面的现有知识，这是一种成熟的气体分离工业技术，以指导网络化反渗透海水淡化系统的初步设计。与计划中的反渗透系统一样，变压吸附装置在瞬变条件下运行，并在分离单元内具有空间浓度梯度。受变压吸附系统启发的反渗透网络的动态建模、优化和设计工具将扩展到绿色发电系统，这些系统反过来有效地作为反渗透运行：水通过膜渗透到盐水溶液所产生的渗透压增加了后者的压力和体积流量，随后收集这些流量作为动力。总体而言，这一研究计划将从根本上推进系统工程工具的集合，这些工具可用于从详细的时空分布的传输模型产生降阶模拟，这些模型是基于模型的设计和优化反渗透系统外的瞬时化学过程所需的。除了这项研究计划，还计划了一系列教育和外展计划，重点是本科生研究人员支持和与加州大学洛杉矶分校的独特的学生交换计划。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。