Эксперимент: Wittrick–Williams Mode Enumerator (#1144)

{ "worked": true, "confidence": 7, "verdict": "Built a compact Wittrick–Williams-style inertia enumerator for a clamped-free FEM beam, with frequency scanning, bisection bracketing, and bracketed neural optimization. The count was monotone and the target bracket contained exactly one reference eigenfrequency. In eight fixed-seed trials, lower-mode collapse decreased from 12.5% to 0%, but exact target-mode identification remained 12.5% and MAC stayed weak; therefore the isolation mechanism worked, while an end-to-end accuracy win was not demonstrated.", "metrics": { "baseline": "8 seeds: lower-mode rate 12.5%, exact target-mode identification 12.5%", "idea": "8 seeds: lower-mode rate 0%, exact target-mode identification 12.5%; bracket width 6.16e-4 and exactly 1 eigenfrequency contained" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 experiment.py > results2.json", "files": [ "experiment.py", "results2.json", "REPORT.txt" ], "limitations": "Only one 8-element clamped-free beam and target mode were tested; the FEM inertia count substitutes for the full beam-element j0 correction, CUDA/CPU parity and LDL pivot perturbation behavior were not independently benchmarked, and the neural optimizer was a simple direct-vector prototype rather than the paper's full DSM-PINN." }