Multi-modal deep learning based surrogate model for high-fidelity simulation

A computer program product for using multiple artificial intelligence models for generating a high fidelity simulation, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

• generate, by the processor, multiple artificial intelligence models, each artificial intelligence model simulating an industry design process;
• fuse, by the processor, the multiple artificial intelligence models to generate a best-fit proposed industry design process;
• utilize, by the processor, a physics constraint model to determine whether the best-fit proposed industry design process is feasible;
• and
• display, by the processor, a representation of the best-fit proposed industry design process in response to determining that the best-fit proposed industry design process is feasible.

An apparatus comprising:

• a memory configured to store instructions;
• and
• a processor configured to execute the instructions to:
• generate multiple artificial intelligence models, each artificial intelligence model simulating an industry design process;
• fuse the multiple artificial intelligence models to generate a best-fit proposed industry design process;
• utilize a physics constraint model to determine whether the best-fit proposed industry design process is feasible;
• and
• display a representation of the best-fit proposed industry design process in response to determining that the best-fit proposed industry design process is feasible.