Statistical Analysis and Control of Ultrasonic-based Aluminum Nano-composite Fabrication Processes

该奖项根据 2009 年美国复苏和再投资法案（公法 111-5）提供资金。该项目重点关注基于超声波空化的纳米复合材料制造工艺的工艺控制和变化减少问题，目标是将该工艺从实验室环境推广到规模化工业环境。基于超声空化的纳米粒子在铝和镁合金熔体中的分散已被证明是生产金属基纳米复合材料的非常有前途的工艺。科学的目标是通过统计方法和物理分析的结合，发现该制造过程中基本的加工/微观结构/性能关系，然后利用该关系进行过程优化和控制。本研究将重点完成以下具体任务：（i）微观结构内纳米颗粒分散的定量评估。 (ii) 原位过程传感信号处理和表征。 (iii) 现场过程监控和优化。该项目产生的知识将揭示非线性效应（空化和流化）对纳米颗粒分散、微/纳米结构和铝基纳米复合材料机械性能的影响，并将使得高性能块状铝基纳米复合材料在工业规模上的生产成为可能。该项目的成功将促进从传统过程控制技术向基于通用模型的诊断范式的转变，并为大规模纳米制造奠定新的科学基础。该项目的成功实施将为我国的制造基地提供新的、更节能的生产方法，同时使新产品（例如汽车发动机缸体）本身比现有产品更节能。该项目还可以为学生提供获得机械工程、材料科学、系统科学和统计学等各个领域跨学科培训的独特机会。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).This project focuses on process control and variation reduction issues of the ultrasonic cavitation based nanocomposite fabrication process and targets bringing this process from lab environment to a scale-up industrial environment. The ultrasonic cavitation based dispersion of nanoparticles in aluminum and magnesium alloy melts has been shown to be a very promising process of producing metal matrix nano-composites. The scientific objective is to discover the fundamental processing/microstructure/property relationship in this fabrication process through the integration of statistical methods and physical analysis, and then utilize the relationship for process optimization and control. This research will focus on the specific tasks as follows: (i) Quantitative assessment of the nano-particle dispersion within the microstructure. (ii) In-situ process sensing signal processing and characterization. (iii) In-situ process monitoring and optimization. The knowledge generated in this project will reveal the influence of non-linear effects (cavitation and streaming) on the nanoparticle dispersion, micro/nano-structures, and mechanical properties of aluminum matrix nanocomposites and will enable the production of high performance bulk Al matrix nanocomposites at the scale-up industrial level. The success of the project will catalyze a transition from traditional process control techniques to a generic model-based diagnostic paradigm and contribute to a new scientific base for scale-up nano-manufacturing. Successful implementation of this project will result in providing our nation's manufacturing base with new, more energy-efficient production methods while at the same time enabling new products (e.g., automotive engine block) that themselves are more energy efficient in comparison to products available today. This project can also provide students the unique opportunity to obtain interdisciplinary training in various fields including mechanical engineering, material science, system science, and statistics.