Mathematical Modeling and Advanced Parameter Estimation for Polymerization Processes

在开发数学模型时，建模师对所需的复杂性和细节做出相互关联的决定，简化将做出的假设，以及将用于估计模型参数的技术。适当的决定不仅取决于正在建模的系统的物理和化学，还取决于已知的实验信息、进行进一步实验的成本以及模型的预期用途(例如，过程控制、监测、放大或优化)。我的研究计划的长期目标是：i)为特定的聚合体系建立新的基本模型，以及ii)开发模型构建工具，以解决研究人员在开发和应用机械模型时面临的关键问题。

When developing a mathematical model, modelers make interconnected decisions about the complexity and detail required, simplifying assumptions that will be made, and techniques that will be used to estimate model parameters. Appropriate decisions depend not only on the physics and chemistry of the system being modeled, but also on experimental information that is already known, costs of performing further experiments, and the  intended use of the model (e.g., process control, monitoring, scale-up or optimization). The long-term goals of my research program are: i) to build novel fundamental models for specific polymerization systems, and ii) to develop model-building tools that address key problems faced by researchers when developing and applying mechanistic models.