Systems and Methods for Enhanced Engineering Design and Optimization

An enhanced analytical system for engineering design and optimization comprising:

• one or more processors;
• and
• memory in communication with the one or more processors and storing instructions that, when executed by the one or more processors, is configured to cause the system to:
• collect desired response data;
• identify, based on the desired response data, limitation data;
• generate, based on the limitation data, simulation data comprising a design space and a response space;
• train, utilizing the response space, a first multi-layer neural network to generate a reduced response space having reduced dimensionality compared to the response space, the first multi-layer neural network comprising an encoding layer, one or more hidden layers, and a decoding layer;
• train, utilizing the design space and the response space, a second neural network to generate a reduced design space having reduced dimensionality compared to the design space;
• generate, by cascading the second neural network with the decoding layer of the first multi-layer neural network, an optimization neural network;
• invert, using the design space and the response space, the optimization neural network to generate a design generation neural network;
• determine, by applying the desired response data to the design generation neural network, optimal reduced design parameter data, wherein the reduced design space comprises the optimal reduced design parameter data;
• and
• generate, by applying the encoding layer of the first multi-layer neural network to the optimal reduced design parameter data, optimal design parameter data within the design space by:
• generating design options, each design option comprising design parameters;
• and
• determining, based on design constraints, an optimal design option from among the design options.

A method comprising:

• training, utilizing a response space, a first multi-layer neural network to generate a reduced response space having reduced dimensionality compared to the response space, the first multi-layer neural network comprising an encoding layer, one or more hidden layers, and a decoding layer;
• training, utilizing a design space and the response space, a second neural network to generate a reduced design space having reduced dimensionality compared to the design space;
• and
• generating, by cascading the second neural network with the decoding layer of the first multi-layer neural network, an optimization neural network.