Modelling Gas Turbine Blade Degradation in a High Fidelity Digital Twin

在高保真数字孪生中对燃气轮机叶片退化进行建模

• 批准号: 2422977
• 金额: --
• 依托单位: CRANFIELD UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2422977
• 关键词: Modelling; Gas; Turbine; Blade; Degradation

The hot blades in a gas turbine operate within an extremely hostile environment. Whilst the materials used are selected on the basis of their ability to survive in this environment the environment is such that blades degrade with time and when the operating conditions of the engine and levels of contaminants ingested change this can adversely alter the predicted life time of the blades. This leads to reduced reliability and greater costs for the equipment supplier and user. The project will therefore seek to improve understanding of gas turbine blade base material and coating corrosion and oxidation mechanisms and the models used to describe them. The models will be used in a high fidelity digital twin to replicate turbine blade degradation on gas turbines performance and service life. In particular, Siemens Industrial Turbomachinery is developing digital twins for their gas turbines to improve their performance and to tailor maintenance to a particular gas turbine's manufacture, operating history and previous repair. Such digital twins go far beyond conventional record keeping, and involve the development of a toolkit of different models (with partners including Cranfield University and the University of Cambridge).

燃气涡轮机中的热叶片在极其恶劣的环境中运行。虽然所使用的材料是基于它们在这种环境中的生存能力来选择的，但是这种环境使得叶片随着时间而退化，并且当发动机的操作条件和吸入的污染物的水平改变时，这可能不利地改变叶片的预测寿命。这导致设备供应商和用户的可靠性降低和成本增加。因此，该项目将寻求提高对燃气涡轮机叶片基础材料和涂层腐蚀和氧化机制以及用于描述它们的模型的理解。这些模型将用于高保真数字孪生，以复制涡轮机叶片退化对燃气涡轮机性能和使用寿命的影响。特别是，西门子工业涡轮机正在为其燃气轮机开发数字孪生，以提高其性能，并根据特定燃气涡轮机的制造、运行历史和以前的维修情况定制维护。这种数字双胞胎远远超出了传统的记录保存，涉及开发一个不同模型的工具包（合作伙伴包括克兰菲尔德大学和剑桥大学）。