Prediction Model for Aero-engine Combustor Temperature Field with Physical Constraints of High Temperature Deviation DOI
Xuan Wang, Chen Kong,

Yunxiao Han

и другие.

Energy, Год журнала: 2024, Номер unknown, С. 134076 - 134076

Опубликована: Дек. 1, 2024

Язык: Английский

Numerical investigation of the position effect on a hybrid wind turbine model: Integrating vertical axis wind turbines around a horizontal axis wind turbine tower DOI
K. H. M. Ali, Zhenzhou Zhao, Yige Liu

и другие.

Sustainable Energy Technologies and Assessments, Год журнала: 2025, Номер 76, С. 104304 - 104304

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Data-knowledge-driven dynamic stall modeling guided by stall patterns and semi-empirical model DOI

Zijie Shi,

Chuanqiang Gao, Weiwei Zhang

и другие.

Physics of Fluids, Год журнала: 2025, Номер 37(4)

Опубликована: Апрель 1, 2025

Dynamic stall often causes unsteady loads and negatively affects the aerodynamic performance of aircraft. Thus, accurate modeling dynamic stalls is crucial for aircraft design. With development machine learning, existing data-driven models always rely on extensive, costly training data but lack physical knowledge, which limits their generalizability interpretability. Therefore, this study proposes a data-knowledge-driven procedure. First, by exploring damping evolution moment coefficient, three distinct patterns are identified. A transitional state, significantly differs from both deep light stall, proposed to assist neural network modeling. Subsequently, with P-based degree classification force component developed, integrates Leishman–Beddoes model. This model provides unified approach predict aerodynamics across different degrees stall. Compared purely network, incorporating expert knowledge improved generalization accuracy 50%. Moreover, insights reduce reliance high-precision network.

Язык: Английский

Процитировано

0

Dynamic stall modeling of the wind turbine blade with a data-knowledge-driven method DOI

Zijie Shi,

Chuanqiang Gao, Weiwei Zhang

и другие.

Energy, Год журнала: 2025, Номер 324, С. 135987 - 135987

Опубликована: Апрель 23, 2025

Язык: Английский

Процитировано

0

Adaptive physical loss weighting model for temperature field prediction in the aero-engine combustor DOI
Xuan Wang, Chen Kong,

Yunxiao Han

и другие.

Applied Thermal Engineering, Год журнала: 2025, Номер unknown, С. 126707 - 126707

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Rapid Identification and Early Warning of Axial Compressor Stall Based on Multiscale CNN-SVM-FC Model DOI
Shimin Wang, Zhidong Chi,

Hefei Li

и другие.

Aerospace Science and Technology, Год журнала: 2024, Номер 155, С. 109604 - 109604

Опубликована: Сен. 20, 2024

Язык: Английский

Процитировано

2

Prediction Model for Aero-engine Combustor Temperature Field with Physical Constraints of High Temperature Deviation DOI
Xuan Wang, Chen Kong,

Yunxiao Han

и другие.

Energy, Год журнала: 2024, Номер unknown, С. 134076 - 134076

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2