GOALI: A Multiscale Modeling Framework for Predicting Granule Property Evolution in Mixer Granulators

GOALI：用于预测混合制粒机中颗粒特性演变的多尺度建模框架

• 批准号: 1034014
• 负责人: Carl Wassgren
• 金额: $ 31.5万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1034014&HistoricalAwards=false
• 关键词: GOALI; Multiscale; Modeling; Framework; Predicting

The goal of the project is to develop fundamentally-based, multiscale modeling tools that will aid in the understanding and scaling of granulation processes, an important step in the manufacture of new products and delivery forms in detergents, consumer goods, pharmaceuticals, agricultural chemicals and specialty materials. The proposed work focuses on developing a validated and coupled discrete element method (DEM) / population balance (PB) computational model for predicting the evolution of granule size and liquid content in a dual axis paddle granulator. Specific objectives of this project are to:1. Develop a DEM model that can give predictions of particle velocity fields and residence times in the spray zone. The residence time predictions will be validated against high speed video residence time distributions and Positron Emission Particle Tracking (PEPT) data for an identical system.2. Develop a multidimensional population balance model to predict the evolution of granule size and liquid content, and validate this model with laboratory scale measurements of multidimensional granule distributions;3. Link the DEM and PB models in a serially integrated multiscale framework and use the combined model to predict performance in a lab scale granulator and the Procter and Gamble granulation pilot plant. The work proposed here primarily targets layered growth of seed granules. This work is part of a larger effort to develop a fully generalized multiscale model including nucleation, densification, coalescence, and breakage of fine powders.Intellectual Merit:This proposal is the first serious attempt to develop a multiscale model for design of granulation processes and validate the model with multidimensional distribution data at laboratory and pilot scales. This is a challenging class of problems in particulate processing because there is very strong two way coupling between the dense particulate flows and the granule growth processes.The scientific originality and significance of the research includes:-Special care in understanding the sensitivity of the DEM model predictions of macroscale phenomena to assumed mechanical properties of the granules;-Incorporating for the first time the correct physics of the spray zone into layering kinetic expressions for the population balance;-A pioneering study of DEM and PB model integration using a two way serially integrated multiscale framework; and-Unique and substantial experimental validation and application of the design models to pilot scale operation.Broader Impact:The multiscale modeling approach will be generalizable to all wet granulation systems. The models will dramatically transform the way these processes are designed. Currently, most granulation processes are designed by trial and error resulting in significant loss of materials, not to mention time, potential profits, and product effectiveness. Giving engineers the tools that allow them to more accurately design and control granulation operations will have impact over all industries that manufacture consumer and food products, pharmaceuticals, and agricultural chemicals. Successful completion of the proposed objectives will move wet granulation from an art, to a predictable and quantifiable science. This project will have a substantial educational impact at many levels: learning materials for K-12 demonstrations (developed by undergraduates in the Engineering Projects In Community Service program at Purdue), core undergraduate curricula, and industry short courses. These educational tools, as well simplified modeling tools, will be shared with the international community through the unique cyberspace community on www.pharmahub.org. The project also provides excellent training for a graduate student including an industry internship.

该项目的目标是开发基于基础的多尺度建模工具，以帮助理解和缩放造粒过程，这是制造新产品和洗涤剂，消费品，药品，农业化学品和特种材料的交付形式的重要一步。建议的工作重点是开发一个有效的和耦合的离散元方法（DEM）/人口平衡（PB）的计算模型，用于预测的颗粒尺寸和液体含量在双轴桨式搅拌机的演变。该项目的具体目标是：1。建立离散元模型，预测颗粒在喷雾区的速度场和停留时间。停留时间预测将根据高速视频停留时间分布和正电子发射粒子跟踪（PEPT）数据进行验证。建立了一个多维种群平衡模型来预测颗粒尺寸和液体含量的演变，并通过实验室尺度的多维颗粒分布测量来验证该模型;3.将DEM和PB模型连接在一个连续集成的多尺度框架中，并使用组合模型来预测实验室规模的造粒机和宝洁造粒中试装置的性能。 这里提出的工作主要针对种子颗粒的分层生长。这项工作是一个更大的努力，开发一个完全广义的多尺度模型，包括成核，致密化，聚结，和破碎的细powder.Intellectual优点：这项建议是第一次认真尝试开发一个多尺度模型的造粒工艺设计和验证模型与多维分布数据在实验室和中试规模。 这是一个具有挑战性的问题，在颗粒处理，因为有非常强的双向耦合之间的密集颗粒流和颗粒的生长过程。科学的原创性和研究的意义包括：-特别注意理解的DEM模型预测的宏观现象的敏感性，以假定的机械性能的颗粒;- 首次将喷雾区的正确物理性质转化为种群平衡的分层动力学表达式;- 一个开拓性的研究DEM和PB模型集成使用双向串联集成多尺度框架;和-独特的和大量的实验验证和应用的设计模型中试规模operation.Broader影响：多尺度建模方法将推广到所有的湿法制粒系统。这些模型将极大地改变这些流程的设计方式。目前，大多数造粒工艺都是通过试验和错误来设计的，导致材料的重大损失，更不用说时间，潜在利润和产品有效性。为工程师提供工具，使他们能够更准确地设计和控制造粒操作，这将对制造消费品和食品、药品和农用化学品的所有行业产生影响。成功完成拟议的目标将移动湿法制粒从一门艺术，一个可预测的和可量化的科学。 该项目将在许多层面产生重大的教育影响：K-12演示的学习材料（由普渡大学社区服务工程项目的本科生开发），核心本科课程和行业短期课程。这些教育工具以及简化的建模工具将通过www.pharmahub.org上独特的网络空间社区与国际社会分享。该项目还为研究生提供了出色的培训，包括行业实习。