This work advances predictive full-$f$, global, long-wavelength gyrokinetic simulation of tokamak edge and scrape-off-layer turbulence using magnetic geometry, heating power, and total particle inventory rather than prescribed plasma profiles. An adaptive Gkeyll source controls injected energy and models recycling with zero net particle addition, allowing profiles and turbulence to relax self-consistently. For TCV discharge #65125, simulated electron density and temperature agree reasonably with Thomson-scattering and Langmuir-probe measurements, while the model reproduces scrape-off-layer blobs, a self-organized radial electric field, and consistent power accounting. Comparing positive- and negative-triangularity discharges, the simulations find higher core density, about
- Implemented an adaptive energy and recycling source for profile-predictive full-$f$ Gkeyll simulations.
- Evolved edge and scrape-off-layer turbulence without imposing density or temperature profiles.
- Validated predicted kinetic profiles and turbulence features against TCV #65125 diagnostics.
- Quantified triangularity-related changes in flow shear, fluctuation spectra, and power partition.
- Linked electron-dominated turbulent heat flux to trapped-electron-mode activity and identified missing physics.