MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541123845 A) filed by Dr. J. Siva Ram Prasad; Dr. P. D. Selvi; Dr. A. Shobha; Mrs. B. Lavanya; Dr. B. Triveni; Dr. Siva M; Dr. Aswin Kumar Rauta; Dr. Animesh Kumar Sharma; Mrs. A. Megala; and Dr. D. Surjith Jiji, Vijayawada, Andhra Pradesh, on Dec. 9, 2025, for 'ai-assisted simulation models for analyzing fluid dynamics in mathematical applications.'

Inventor(s) include Dr. J. Siva Ram Prasad; Dr. P. D. Selvi; Dr. A. Shobha; Mrs. B. Lavanya; Dr. B. Triveni; Dr. Siva M; Dr. Aswin Kumar Rauta; Dr. Animesh Kumar Sharma; Mrs. A. Megala; and Dr. D. Surjith Jiji.

The application for the patent was published on Jan. 2, under issue no. 01/2026.

According to the abstract released by the Intellectual Property India: "The present invention relates to an AI-assisted simulation system for analyzing fluid dynamics in mathematical and engineering applications, integrating conventional computational fluid dynamics solvers with artificial intelligence to provide adaptive, predictive, and self-optimizing simulation capabilities. The system continuously monitors solver operations, evaluates intermediate flow states, predicts instabilities, and dynamically adjusts solver parameters, mesh resolution, time-stepping, and turbulence models to improve accuracy and efficiency. By combining physics-based numerical methods with machine-learning models trained on historical simulation data and experimental measurements, the system anticipates complex fluid phenomena, ensures numerical stability, corrects potential errors, and reduces computational cost. The invention further supports real-time and near-real-time simulation, adaptive mesh refinement, error correction, and continuous learning, enabling robust and high-fidelity modeling of laminar, turbulent, compressible, incompressible, and multi-phase flows. This hybrid framework provides a scalable, intelligent, and autonomous platform for fluid analysis across aerospace, environmental, biomedical, energy, and industrial applications, enhancing predictive accuracy, reliability, and operational efficiency."

Disclaimer: Curated by HT Syndication.