context: SYS_14 Neural Acceleration with dashboard integration

insight: When running neural surrogate turbo optimization, FEA validation trials MUST be logged to Optuna for dashboard visibility. Use optuna.create_study() with load_if_exists=True, then for each FEA result: trial=study.ask(), set params via suggest_float(), set objectives as user_attrs, then study.tell(trial, weighted_sum).


context: SYS_14 v2.3 update with TrialManager integration

insight: SYS_14 Neural Acceleration protocol updated to v2.3. Now uses TrialManager for consistent trial_NNNN naming instead of iter{N}. Key components: (1) TrialManager for folder+DB management, (2) DashboardDB for Optuna-compatible schema, (3) Trial numbers are monotonically increasing and NEVER reset. Reference implementation: studies/M1_Mirror/m1_mirror_cost_reduction_flat_back_V5/run_turbo_optimization.py