ARJUN GOPICHANDER RAVICHANDER. Physics-Constrained Synthetic Data Generation For Industrial Machine Learning: Enforcing Conservation And Operating-Envelope Constraints, Validating Fidelity Against Sensor Records, And Measures. International Journal of Computer Information Systems and Industrial Management Applications, [S. l.], v. 18, n. 23s, p. 1707–1720, 2026. DOI: 10.70917/ijcisim-2026-5723. Disponível em: https://cspub-ijcisim.org/index.php/ijcisim/article/view/5723. Acesso em: 18 sep. 2026.