gdtk-uq/gdtk
Aug 2025 – Oct 2025
3 Months active
Languages Used
DLuaPythonC++MakefileYAML
Technical Skills
CI/CDCode RefactoringConfiguration ManagementFluid DynamicsNumerical MethodsNumerical Simulation
Kyle Damm
PROFILE
Kyle Damm
Kyle Damm contributed to the gdtk-uq/gdtk repository by developing and refining advanced features for computational fluid dynamics simulations. He implemented a differentiable smooth maximum in the AUSMDV flux calculator to improve numerical stability and addressed check-jacobian errors, using Python and C++ for both algorithmic changes and test alignment. Kyle introduced a dual time stepping solver with implicit Newton-Krylov methods and BDF schemes, enhancing time-accurate simulation capabilities. He also improved turbulence modeling and boundary condition handling, applying complex-step differentiation and robust initialization strategies. His work demonstrated depth in numerical methods, solver development, and cross-platform testing, resulting in more reliable simulations.
Overall Statistics
Feature vs Bugs
63%Features
Repository Contributions
11Total
Bugs
3
Commits
11
Features
5
Lines of code
10,222
Activity Months3
Your Network
21 people
Work History
October 2025
2 Commits • 1 Features
Oct 1, 2025Monthly summary for 2025-10 focused on gdtk-uq/gdtk. Delivered two targeted changes that enhance boundary accuracy and turbulence robustness, with clear commits enabling traceability. Key achievements: - Boundary gradient correction feature implemented: added a configuration option to apply interface-average spatial derivative correction at boundaries; extends gradient computation to boundary faces to improve accuracy on boundary-layer meshes (commit 1c9bdb9fcc8b05db993aff2738e692a1a9750fb4). - Turbulence model robustness improvements: enforce non-negative turbulence quantities by throwing on negative values in decode_conserved and reduce minimum small_tke to prevent non-physical clipping in boundary layers (commit 9c06ddd27e2ea1e7fddae75b8eac1c68a2703a7c).
2 Commits • 1 Features
Oct 1, 2025Monthly summary for 2025-10 focused on gdtk-uq/gdtk. Delivered two targeted changes that enhance boundary accuracy and turbulence robustness, with clear commits enabling traceability. Key achievements: - Boundary gradient correction feature implemented: added a configuration option to apply interface-average spatial derivative correction at boundaries; extends gradient computation to boundary faces to improve accuracy on boundary-layer meshes (commit 1c9bdb9fcc8b05db993aff2738e692a1a9750fb4). - Turbulence model robustness improvements: enforce non-negative turbulence quantities by throwing on negative values in decode_conserved and reduce minimum small_tke to prevent non-physical clipping in boundary layers (commit 9c06ddd27e2ea1e7fddae75b8eac1c68a2703a7c).
October 2025
September 2025
5 Commits • 4 Features
Sep 1, 2025September 2025 focused on strengthening the LMR module in gdtk with numerical robustness, time-accurate capabilities, initialization improvements, and turbulence model validation. Key features delivered include complex-step based boundary condition linearisation for the flow Jacobian, a new Dual Time Stepping (DTS) solver mode with BDF1/BDF2 and implicit Newton-Krylov solver, initialization diffusion for wall boundary conditions, and a k-log-omega turbulence model with validation cases. A bug fix corrected initialization parameters for Jacobi and diagonal preconditioners in Newton-Krylov. Impact: improved accuracy and stability, larger time steps, faster convergence, expanded validation suite, and cross-OS consistency. Technologies demonstrated: complex-step differentiation, Newton-Krylov solvers, BDF schemes, DiffuseWallBCsOnInit, turbulence modeling, preconditioner tuning; cross-OS test updates.
September 2025
5 Commits • 4 Features
Sep 1, 2025September 2025 focused on strengthening the LMR module in gdtk with numerical robustness, time-accurate capabilities, initialization improvements, and turbulence model validation. Key features delivered include complex-step based boundary condition linearisation for the flow Jacobian, a new Dual Time Stepping (DTS) solver mode with BDF1/BDF2 and implicit Newton-Krylov solver, initialization diffusion for wall boundary conditions, and a k-log-omega turbulence model with validation cases. A bug fix corrected initialization parameters for Jacobi and diagonal preconditioners in Newton-Krylov. Impact: improved accuracy and stability, larger time steps, faster convergence, expanded validation suite, and cross-OS consistency. Technologies demonstrated: complex-step differentiation, Newton-Krylov solvers, BDF schemes, DiffuseWallBCsOnInit, turbulence modeling, preconditioner tuning; cross-OS test updates.
August 2025
4 Commits
Aug 1, 2025Concise monthly summary for 2025-08 focusing on dev work for AUSMDV Flux Calculator in gdtk. Delivered a differentiable, differentiable smooth maximum implementation and aligned tests to improve numerical stability and check-jacobian robustness across configurations and platforms.
4 Commits
Aug 1, 2025Concise monthly summary for 2025-08 focusing on dev work for AUSMDV Flux Calculator in gdtk. Delivered a differentiable, differentiable smooth maximum implementation and aligned tests to improve numerical stability and check-jacobian robustness across configurations and platforms.
August 2025
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Quality Metrics
Correctness83.6%
Maintainability81.8%
Architecture79.0%
Performance71.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++DLuaMakefilePythonYAML
Technical Skills
C++ DevelopmentCI/CDCode RefactoringComputational Fluid DynamicsConfiguration ManagementFinite Volume MethodFluid DynamicsLinear AlgebraLinear Algebra SolversLua ScriptingNewton-Krylov MethodsNumerical MethodsNumerical SimulationPythonPython Scripting
Repositories Contributed To
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