Algorithms and methodologies of controlling unsteady flows

本项目的目标是开发一个基于计算机的虚拟环境(VE)平台，以支持专家数据分析和决策。该平台是针对一个重要且普遍存在的工业挑战而设计的：控制非稳定流动(例如，液体/气体流动反应器)。该平台中嵌入了一套使能算法，可以从复杂和海量的流量数据中稳健而可靠地识别关键模式；并有效地呈现识别出的模式，用于三维可视化和多用户交互。这些算法是对当前研究挑战的非常规解决方案，例如用于流动模式识别的数据不完整、表示的主观性以及用于实时分析的模拟工具的不足。VE平台的重要性通过对化学流动反应堆的应用得到了例证，这是我们的支持组织Nova Chemals Corporation的核心业务利益。 该项目非常适合信息和通信技术的目标领域，其研究主题为“(E)从数据到知识再到行动--非结构化模式识别”。在强大的行业支持下，我们设想这样一个VE平台，以提高加拿大许多行业的生产率和竞争力；在这个平台中，跨学科的专家必须在他们的问题解决和决策活动中例行公事地一起解码复杂和海量的数据。

The objective of this project is to develop a computer-based virtual environment (VE) platform for supporting expert data-analysis and decision-making. The platform is illustrated for an important and pervasive industrial challenge: controlling unsteady flows (e.g., liquids/gas flow reactors). Embedded in the platform is a set of enabling algorithms that make robust and reliable recognition of key patterns from complex and massive flow data; and that render the recognized patterns effectively for three-dimensional visualization and multi-user interaction. Advancing the state of the art, these algorithms are unconventional solutions to current research challenges - such as incompleteness of data for flow pattern recognition, subjectivity of representations and inadequacy of simulation tools for real-time analysis. The significance of the VE platform is exemplified through applications to chemical flow reactors, a core business interest of our supporting organization NOVA Chemicals Corporation. The project fits well into the target area of Information and Communication Technologies, under the research topic of "(e) From Data to Knowledge to Action - unstructured pattern recognition." With strong industrial support, we envision such a VE platform to boost the productivity and competitiveness of many Canadian sectors; in which experts across disciplines must routinely decode complex and massive data together in their problem-solving and decision-making activities.