Open Access
Peer-Reviewed
Original Research
A Visual Analysis Method for Vector Fields Defined on Curved Surfaces
Abstract
We introduce a surface streamline generation approach for visualizing vector fields defined on curved surfaces. This approach performs the intersection calculation on curved surface s with complex topology to achieve the highly detailed underlying vector. Then, an extended Runge -Kutta streamline integration technology is applied for performing streamline tracing on an unstructured mesh, where the adaptive stepsize strategy and intersection acceleration structure are presented for sake of simplicity and efficiency. Finally, this algorithm applies the ball feature to improve its visual intuitiveness and is integrated into the general visual analysis platform. Experimental results show that our method can generate continuous and consistent geometric surface streamlines by tracing streamlines on curved surfaces.
Keywords
Surface Streamline
Extended Runge-Kutta
Adaptive Stepsize Strategy
Declarations & Ethics
Funding:
This research received academic dissemination support through ESCAP / JournalsHub publishing programs.
Conflicts of Interest:
The authors declare no competing financial or institutional interests.
Peer Review:
Double-blind peer reviewed by international subject specialists.
License:
Creative Commons Attribution 4.0 International (CC BY 4.0).
How to Cite This Article
APA / MLA / BibTeX
Wu, et al. (2023). A Visual Analysis Method for Vector Fields Defined on Curved Surfaces. IADIS International Journal on Computer Science and Information Systems, 18(2). https://doi.org/10.33965/ijcsis_2023_v18i2_12
Wu, et al. "A Visual Analysis Method for Vector Fields Defined on Curved Surfaces." IADIS International Journal on Computer Science and Information Systems, vol. 18, no. 2, 2023. https://doi.org/10.33965/ijcsis_2023_v18i2_12
Wu, et al. "A Visual Analysis Method for Vector Fields Defined on Curved Surfaces." IADIS International Journal on Computer Science and Information Systems 18, no. 2 (2023). https://doi.org/10.33965/ijcsis_2023_v18i2_12