Zhiqiang Duan , Jialin Tian , Yu He , Lanhui Mao , Qianrui Xiao , Jianhua Deng
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引用次数: 0
Abstract
The dual-vortex fluid oscillator (DVFO) generates periodic axial forces without relying on moving components, effectively reducing friction between the drill bit and the wellbore. However, minimizing the total pressure drop to conserve energy while maintaining optimal axial force for improved drilling safety poses a significant challenge. This study proposes a multi-objective optimization strategy that integrates adaptive sampling, two surrogate modeling methods, and genetic algorithms. Furthermore, enhanced evaluation metrics are employed to assess the fitting and predictive performance of these surrogate models. The results demonstrate that, based on the sample data obtained through adaptive sampling, the deep infinite mixture Gaussian process achieves exceptional accuracy, with all evaluation metrics exceeding 0.94. The optimized DVFO, with a 12.62 % increase in the average flow rate, achieves a 2.47 % reduction in the time-averaged total pressure drop and a 7.09 % reduction in the time-averaged axial force. Sensitivity analysis identifies channel thickness, shunt channel width, offset, and feedback channel width as the most influential parameters. A wider shunt channel, increased channel thickness, and smaller offset collectively reduce the vortex number and strength, thereby minimizing pressure loss. Additionally, the significant reduction in pressure and wall shear stress acting on the leading surface is the primary reason for the decrease in axial force. This research presents an efficient and adaptable strategy for optimizing transient DVFOs, underscoring the importance of geometric design in enhancing flow performance and providing valuable insights for similar fluidic systems.
期刊介绍:
The International Journal of Mechanical Sciences (IJMS) serves as a global platform for the publication and dissemination of original research that contributes to a deeper scientific understanding of the fundamental disciplines within mechanical, civil, and material engineering.
The primary focus of IJMS is to showcase innovative and ground-breaking work that utilizes analytical and computational modeling techniques, such as Finite Element Method (FEM), Boundary Element Method (BEM), and mesh-free methods, among others. These modeling methods are applied to diverse fields including rigid-body mechanics (e.g., dynamics, vibration, stability), structural mechanics, metal forming, advanced materials (e.g., metals, composites, cellular, smart) behavior and applications, impact mechanics, strain localization, and other nonlinear effects (e.g., large deflections, plasticity, fracture).
Additionally, IJMS covers the realms of fluid mechanics (both external and internal flows), tribology, thermodynamics, and materials processing. These subjects collectively form the core of the journal's content.
In summary, IJMS provides a prestigious platform for researchers to present their original contributions, shedding light on analytical and computational modeling methods in various areas of mechanical engineering, as well as exploring the behavior and application of advanced materials, fluid mechanics, thermodynamics, and materials processing.