Recently, the 2024 Academic Annual Conference of the Global Power and Propulsion Society (GPPS) was held in Greece. During the conference, Dr. Vladimir Navrotsky, Chairman of the GPPS Awards Committee, presented the 2023 GPPS Best Paper Award. The paper titled "An Efficient Multi-Fidelity Simulation Approach for Performance Prediction of Adaptive Cycle Engines" by Professor Zheng Xinqian's team was awarded the prize. Out of 158 academic papers submitted by scholars from around the world, four papers were honored with this award.

The chairman of the GPPS Awards Committee presented the award

To address the issue of inaccurate overall performance prediction caused by various variable geometry components and complex adjustment rules in the next-generation adaptive cycle engines for aviation propulsion systems, Professor Zheng Xinqian's team proposed a new, universal, and efficient multi-dimensional coupled performance prediction method for variable cycle engines. The award-winning paper established physics-based one-dimensional mean flow models for multi-spool adaptive fans and variable geometry turbines, respectively. An iterative coupling method was used to couple these components into a zero-dimensional model of the entire engine. This method allows researchers to study the impact of component design parameters and variable geometry parameters on both the components and the overall engine performance in an integrated engine environment. It significantly improves the accuracy of performance predictions during the conceptual and preliminary design stages of complex configuration variable cycle engines.

The authors of the award-winning paper are Zou Wangzhi, Song Zhaoyun, Wang Baotong, Wen Mengyang, and Zheng Xinqian. In addition to Professor Zheng Xinqian, the other authors are doctoral students of Professor Zheng's team: Zou Wangzhi (2020 graduate), postdoctoral researcher Song Zhaoyun (2020 graduate), doctoral student Wen Mengyang (2020 graduate), and Associate Researcher Wang Baotong, a young faculty member from the School of Aerospace Engineering at Tsinghua University.

Citation Information：Zou, W., Song, Z., Wang, B., Wen, M., and Zheng, X. "An efficient multi-fidelity simulation approach for performance prediction of adaptive cycle engines." Journal of the Global Power and Propulsion Society, vol. 8, 2024, pp. 310-322. doi:10.33737/jgpps/191167.

Full paper link：https://journal.gpps.global/An-efficient-multi-fidelity-simulation-approach-for-performance-prediction-of-adaptive,191167,0,2.html

Award Certificate