Uncertainty Quantification of Drag Reduction over Superhydrophobic Surfaces by Unified Parameterizing Structure Spacing
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911132174778368 |
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| author | Kim, Byeong-Cheon Chang, Kyoungsik Lee, Sang-Wook Nguyen, Hoai-Thanh Oh, Eun Seok Ryu, Jaiyoung Kim, Minjae Yoon, Jaemoon |
| author_facet | Kim, Byeong-Cheon Chang, Kyoungsik Lee, Sang-Wook Nguyen, Hoai-Thanh Oh, Eun Seok Ryu, Jaiyoung Kim, Minjae Yoon, Jaemoon |
| contents | Superhydrophobic surfaces (SHS) have demonstrated significant potential in reducing turbulent drag by introducing slip conditions through micro-structured geometries. While previous studies have examined individual SHS configurations such as post-type, ridge-type, and transverse ridge-type surfaces, a unified analysis that connects these patterns through geometric parameterization remains limited. In this study, we propose a systematic framework to explore the drag reduction characteristics by varying the streamwise and spanwise spacing ($d_1, d_2$) of post-type patterns, effectively encompassing a range of SHS geometries. High-fidelity direct numerical simulations (DNS) were performed using NekRS, a GPU-accelerated spectral element solver, to resolve incompressible turbulent channel flows over these SHSs. To account for variability in the geometric parameters and quantify their influence, we construct a surrogate model based on polynomial chaos expansion (PCE) using Latin hypercube sampling (LHS) method. The resulting model enables efficient uncertainty quantification (UQ) and sensitivity analysis, revealing the relative importance of $d_1$ and $d_2$ in drag reduction performance. This unified UQ framework provides both predictive capability and design guidance for optimizing SHS configurations under uncertain geometric conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_01239 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Uncertainty Quantification of Drag Reduction over Superhydrophobic Surfaces by Unified Parameterizing Structure Spacing Kim, Byeong-Cheon Chang, Kyoungsik Lee, Sang-Wook Nguyen, Hoai-Thanh Oh, Eun Seok Ryu, Jaiyoung Kim, Minjae Yoon, Jaemoon Fluid Dynamics Superhydrophobic surfaces (SHS) have demonstrated significant potential in reducing turbulent drag by introducing slip conditions through micro-structured geometries. While previous studies have examined individual SHS configurations such as post-type, ridge-type, and transverse ridge-type surfaces, a unified analysis that connects these patterns through geometric parameterization remains limited. In this study, we propose a systematic framework to explore the drag reduction characteristics by varying the streamwise and spanwise spacing ($d_1, d_2$) of post-type patterns, effectively encompassing a range of SHS geometries. High-fidelity direct numerical simulations (DNS) were performed using NekRS, a GPU-accelerated spectral element solver, to resolve incompressible turbulent channel flows over these SHSs. To account for variability in the geometric parameters and quantify their influence, we construct a surrogate model based on polynomial chaos expansion (PCE) using Latin hypercube sampling (LHS) method. The resulting model enables efficient uncertainty quantification (UQ) and sensitivity analysis, revealing the relative importance of $d_1$ and $d_2$ in drag reduction performance. This unified UQ framework provides both predictive capability and design guidance for optimizing SHS configurations under uncertain geometric conditions. |
| title | Uncertainty Quantification of Drag Reduction over Superhydrophobic Surfaces by Unified Parameterizing Structure Spacing |
| topic | Fluid Dynamics |
| url | https://arxiv.org/abs/2509.01239 |