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2月27日新西兰坎特伯雷大学赵丹教授来校讲学

来源:动力与能源学院 作者:杨秦政 摄影: 发布时间:2025-02-26 浏览次数: 【字体:

报告题目:发动机燃烧不稳定性与基于物理信息神经网络的研究与应用

报 告 人:赵丹

报告时间:2025年2月27日下午2:00

报告地点:S404

专家简介:

      赵丹教授,新西兰皇家科学院与工程院两院院士,欧洲科学院外籍院士,欧洲科学与艺术院外籍院士,博士毕业于英国剑桥大学,目前担任新西兰皇家学会院士评选委员,新西兰坎特伯雷大学机械学院教授,博士生导师,兼研究生招生办主任,国际声学与振动学会杰出会士(美国),中国侨联特聘专家委员会委员,教育部 111 计划学术大师。长期从事下一代零碳(氨、氢)排放发动机燃烧、无人机、空气动力学与噪音、燃气轮机以及航空航天推进系统热声不稳定性以及控制的研究。在国际SCI期刊发表论文300 余篇,出版英文专著4本,英文教材1本(第八版),专利 5 项,担任国际和国内多个期刊的主编或副主编,SCOPUSH-因子6。

报告内容:Self-sustained thermoacoustic oscillations as observed in low-emission combustion-involved gas turbines and aero-engines involve complicated thermal-fluid-acoustics interaction and rich nonlinear dynamics. Such pulsating oscillations are known as thermoacoustic instability. When it occurs, large-amplitude limit cycle oscillations (LCOs) of thermodynamic parameters are frequently observed. LCOs could cause overheating, flame flashback, and even engine failures. Thus, it is critical to understand and predict the generation mechanisms, nonlinear dynamics behaviors and then develop corresponding control approaches to prevent or control the onset of such instabilities. For this, we develop and extend the conventional Van der Pol (VDP) oscillators by integrating PINNs (Physics-informed neural networks) algorithm with a modeled nonlinear Rijke-type thermoacoustic combustor. The theoretical Rijke tube system (with Galerkin expansion and modified King’s Law implemented) and a CFD simulation model are applied to provide ‘training/calibration data’ for the EVDP (extended VDP)-PINNs model. The optimized EVDP oscillators are confirmed to be capable to capture the key nonlinear characteristics by comparing the transient growth behaviors of thermodynamic perturbations and LCOs’ amplitude and frequency. Further investigations are conducted to obtain Hopf bifurcation and amplitude death (AD) characteristics. Comparison is then made to the coupled EVDP systems. Quite similar Hopf bifurcation features, but differences in regions of AD, are observed In general, we demonstrate an applicable approach to intelligently ‘learn’ a nonlinear thermoacoustic system and to create reliable EVDP oscillator systems, which have great potential to contribute to the development and testing of control approaches, such as the coupling described above, which may replace costly experimental tests.

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