MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641119839 A) filed by Lords Institute Of Engineering And Technology; and University Of Jeddah on October 07, 2026, for Ai Data Driven Design Optimization And Prediction Of 3d Printed Cf-Petg Aluminium Hflm Impact Specimens.
Inventors include Dr. G. M. Sayeed Ahmed; Dr. M. A. Fazal; Dr. Moksud Alam Mallik; Dr. Mohammed Tajuddin; Dr. Syed Azam Pasha Quadri; Mr. Ramavath Suman; Mr. Madhukar Samatham; Mr. Md. Abu Sufiyan; Mr. Md. Haseeb; and Mr. Mohd. Sohail Ahmed.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: AI Data Driven Design Optimization and Prediction of 3D Printed CF-PETG Aluminium HFLM Impact Specimens. The invention relates to a hybrid impact specimen (100) having a 3D-printed CF-PETG gyroid core (110) and at least one recycled aluminium sheet (120), and to a digital design workflow for its optimization. Design variables including gyroid relative density, pore size, orientation and layer thickness are evaluated using finite-element impact simulation (200) and selected physical Izod tests (300). Simulation and test data are stored in a dataset (400) used to train a machine-learning predictor (500). An optimization engine (600) identifies manufacturable parameter combinations that target increased impact strength or absorbed energy while considering mass and interface constraints. Prediction uncertainty may trigger additional simulation or testing. The invention provides a traceable workflow for sustainable hybrid composite design while reducing exhaustive trial-and-error. Figure 1 accompanies the abstract
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