Scalable Nanomanufacturing of High Performance Polymer Foams

高性能聚合物泡沫的可扩展纳米制造

• 批准号: 0620911
• 负责人: David Tomasko
• 金额: $ 40万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-15 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0620911&HistoricalAwards=false
• 关键词: Scalable; Nanomanufacturing; Performance; Polymer; Foams

This grant provides funding for the development of a numerical tool for determining optimal process parameters in bulk forming processes, such as rolling, extrusion, and forging. The developed numerical tool will determine the optimal process geometry, temperature and speed that satisfy specified design criteria for a given two-dimensional forming process. An optimization algorithm based on an adaptive arbitrary Lagrangian-Eulerian finite element formulation for modeling large deformation thermo-elasto-viscoplastic contact problems will be used. The algorithm will be implemented in the context of an existing advanced computational framework that has tools for mesh generation, adaptivity, and parallel computing. Experiments involving the extrusion process will also be performed to validate the algorithms developed. Experimental dies will be manufactured according to the optimal die shapes predicted in this work and tested at the predicted optimal die speeds. A model press, which can extrude plasticine material marked with a grid, will be used in these experiments to observe the material flow behavior.If successful, the results of this research will lead to improvements in the design of bulk forming processes and new developments in optimization methods for handling complex non-linear problems. The primary goal of this work is to determine optimal process geometry, thermal conditions, and process speed in bulk forming processes that will satisfy typically prescribed design criteria. These design criteria may include generating a uniform flow of the material, generating a specified material property distribution in the formed product, minimizing the production time, or minimizing the energy required for the process. Determining the process parameters to achieve these objectives will help to reduce the cost and improve the quality of the final product in processes such as extrusion and forging. The proposed work will also contribute to the computational tools and methodologies available for nonlinear optimization problems.

这笔赠款提供资金用于开发一种数值工具，用于确定体积成形过程中的最佳工艺参数，如轧制，挤压和锻造。 开发的数值工具将确定满足给定二维成形工艺指定设计标准的最佳工艺几何形状、温度和速度。 将使用基于自适应任意拉格朗日-欧拉有限元公式的优化算法来模拟大变形热弹粘塑性接触问题。 该算法将在现有的先进的计算框架，具有网格生成，自适应和并行计算的工具的背景下实施。 还将进行涉及挤出过程的实验以验证所开发的算法。实验模具将根据本工作中预测的最佳模具形状制造，并在预测的最佳模具速度下进行测试。 实验中将使用一台可挤压带有网格的橡皮泥材料的模型压机来观察材料的流动行为，如果成功的话，这项研究的结果将导致体积成形工艺设计的改进和处理复杂非线性问题的优化方法的新发展。 这项工作的主要目标是确定最佳的工艺几何形状，热条件，并在散装成型过程中，将满足通常规定的设计标准的过程速度。 这些设计标准可以包括产生材料的均匀流动、在成形产品中产生指定的材料性质分布、最小化生产时间或最小化工艺所需的能量。 确定工艺参数以实现这些目标将有助于降低成本并提高挤压和锻造等工艺中最终产品的质量。 拟议的工作也将有助于非线性优化问题的计算工具和方法。