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February 12, 2026Physics of Fluids0 citations

Flow-control-based optimization of carbon contact strip bottom profile to enhance aerodynamic performance of a high-speed panhead

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YMYamin MaSouthwest Jiaotong UniversityZPZijian PengFZFentian Zhu

Key Points

  • The research aims to optimize the bottom profile of a carbon contact strip to improve aerodynamic performance in a pantograph-catenary system.
  • Conducted computational fluid dynamics simulations at 400 km/h to analyze aerodynamic behavior.
  • Designed carbon contact strip with filleted corners and double tabs as a passive flow-control strategy.
  • Used a surrogate model to link design variables to aerodynamic outcomes.
  • Employed Non-dominated Sorting Genetic Algorithm II for optimization and validation of results.
  • Achieved over 30% drag reduction in the optimized design.
  • Lift increase was effectively controlled within 22%.
  • Standard deviation of the lift force decreased by 61%, enhancing stability.

Abstract

The combined effects of aerodynamic forces and vortex-induced vibrations can significantly degrade the current-collection quality of the pantograph–catenary system. This paper investigates the design and optimization of the bottom contour of a carbon contact strip featuring filleted corners and double tabs. Computational fluid dynamics simulations at 400 km/h are conducted to evaluate the aerodynamic behavior of the optimized structure. The proposed geometry functions as a passive flow-control strategy: the filleted corners suppress leading-edge separation and enhance surface flow attachment, while the accelerated airflow interacts with the tabs to form a stagnation region that mitigates excessive local acceleration. The tabs further break large separation vortices into smaller and weaker structures, thereby modifying the surface pressure distribution and reorganizing the wake. A surrogate model is constructed to map the design variables to the aerodynamic responses, and Non-dominated Sorting Genetic Algorithm II is employed to obtain the Pareto front, which is subsequently used to validate the predictive accuracy of the surrogate model. The resulting optimal design achieves over 30% drag reduction, with the lift increase effectively controlled within 22%, and significantly suppresses the standard deviation of the lift force by 61%.

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Cite This Study

Ma et al. (2026) studied this question.

synapsesocial.com/papers/698d6eca5be6419ac0d54962https://doi.org/10.1063/5.0316918
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