PaddlePaddle/PaddleCFD
Apr 2025 – Jun 2025
3 Months active
Languages Used
MarkdownPythonXML
Technical Skills
Computational Fluid Dynamics (CFD)Deep LearningDocumentationPaddlePaddlePhysics-Informed Neural Networks (PINNs)Python
luzibo
PROFILE
Luzibo
Over a three-month period, contributed to PaddlePaddle/PaddleCFD by developing end-to-end neural network pipelines for computational fluid dynamics, focusing on physics-informed approaches. Delivered a reproducible lid-driven cavity flow simulation using Physics-Informed Neural Networks and PirateNets/SOAP, replacing legacy workflows and enhancing documentation with detailed READMEs and model diagrams. Improved onboarding and cross-team collaboration by standardizing documentation, clarifying equations, and aligning pretrained model references. Extended the repository’s capabilities to 3D Stokes flow by integrating GreenSONet and Green-ONet models, updating simulation data and VTK support. Work demonstrated expertise in Python, deep learning, scientific computing, and technical writing for CFD applications.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
12Total
Bugs
0
Commits
12
Features
4
Lines of code
422,790
Activity Months3
Your Network
123 peopleWork History
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 PaddleCFD monthly summary: Delivered end-to-end neural network modeling support for 3D Stokes flow via GreenSONet and Green-ONet, advancing PaddleCFD's physics-informed PDE capabilities. Key focus was integrating GreenSONet/Green-ONet with existing simulation workflows, including updates to simulation data/configs and VTK-related changes to support 3D lid-driven cavity tests. Established robust pipelines for inference, testing, data loading, mesh handling, and evaluation to accelerate validation and deployment of neural solvers.
2 Commits • 1 Features
Jun 1, 2025June 2025 PaddleCFD monthly summary: Delivered end-to-end neural network modeling support for 3D Stokes flow via GreenSONet and Green-ONet, advancing PaddleCFD's physics-informed PDE capabilities. Key focus was integrating GreenSONet/Green-ONet with existing simulation workflows, including updates to simulation data/configs and VTK-related changes to support 3D lid-driven cavity tests. Established robust pipelines for inference, testing, data loading, mesh handling, and evaluation to accelerate validation and deployment of neural solvers.
June 2025
May 2025
8 Commits • 2 Features
May 1, 2025May 2025 monthly summary for PaddlePaddle/PaddleCFD focusing on documentation improvements to accelerate onboarding, reduce support overhead, and align with project standards. Delivered two major README enhancements: PPDeepONet README improvements and LDC example README in PaddleCFD. Documentation updates corrected pretrained model path references, clarified mathematical equations, standardized boundary condition formatting, and improved overall README consistency. The work establishes a robust documentation baseline for future feature work and cross-team contributions, enabling faster adoption of the PPDeepONet workflow in CFD contexts.
May 2025
8 Commits • 2 Features
May 1, 2025May 2025 monthly summary for PaddlePaddle/PaddleCFD focusing on documentation improvements to accelerate onboarding, reduce support overhead, and align with project standards. Delivered two major README enhancements: PPDeepONet README improvements and LDC example README in PaddleCFD. Documentation updates corrected pretrained model path references, clarified mathematical equations, standardized boundary condition formatting, and improved overall README consistency. The work establishes a robust documentation baseline for future feature work and cross-team contributions, enabling faster adoption of the PPDeepONet workflow in CFD contexts.
April 2025
2 Commits • 1 Features
Apr 1, 2025Summary for 2025-04: Delivered end-to-end Lid-Driven Cavity (LDC) flow simulation pipeline using Physics-Informed Neural Networks (PINNs) with PirateNets/SOAP in PaddleCFD, enabling reproducible benchmarking at Re=3200. Replaced legacy MLP example with the LDC workflow and added training/evaluation/export/inference scripts and a comprehensive README detailing the problem setup and the PirateNets/SOAP approach. This work is supported by two commits: 254d3789608b67a30fe31ba282f9358f910d2f3d (add ldc code) and d07e00ce4ea4ed51873012278a9ffb0b9d4a8c14 (Add model architecture diagram).
2 Commits • 1 Features
Apr 1, 2025Summary for 2025-04: Delivered end-to-end Lid-Driven Cavity (LDC) flow simulation pipeline using Physics-Informed Neural Networks (PINNs) with PirateNets/SOAP in PaddleCFD, enabling reproducible benchmarking at Re=3200. Replaced legacy MLP example with the LDC workflow and added training/evaluation/export/inference scripts and a comprehensive README detailing the problem setup and the PirateNets/SOAP approach. This work is supported by two commits: 254d3789608b67a30fe31ba282f9358f910d2f3d (add ldc code) and d07e00ce4ea4ed51873012278a9ffb0b9d4a8c14 (Add model architecture diagram).
April 2025
Activity
Loading activity data...
Quality Metrics
Correctness94.2%
Maintainability93.4%
Architecture94.2%
Performance93.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonXML
Technical Skills
Computational Fluid Dynamics (CFD)Data ProcessingDeep LearningDocumentationNumerical MethodsPaddlePaddlePhysics-Informed Neural Networks (PINNs)PythonScientific ComputingTechnical Writing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline