US 12,229,683 B2
Systems and methods for building dynamic reduced order physical models
Mohamed Masmoudi, Toulouse (FR); Christelle Boichon-Grivot, Chozeau (FR); Valéry Morgenthaler, Villeurbanne (FR); and Michel Rochette, Lyons (FR)
Assigned to ANSYS, INC., Canonsburg, PA (US)
Filed by ANSYS, INC., Canonsburg, PA (US)
Filed on Jan. 26, 2024, as Appl. No. 18/424,678.
Application 18/424,678 is a continuation of application No. 16/527,387, filed on Jul. 31, 2019, granted, now 11,922,314.
Claims priority of provisional application 62/773,555, filed on Nov. 30, 2018.
Prior Publication US 2024/0193423 A1, Jun. 13, 2024
Int. Cl. G06N 3/084 (2023.01); G06F 30/00 (2020.01); G06N 3/048 (2023.01)
CPC G06N 3/084 (2013.01) [G06F 30/00 (2020.01); G06N 3/048 (2023.01)] 20 Claims
OG exemplary drawing
 
18. A system, comprising:
a memory storing instructions;
one or more processors coupled to the memory, the one or more processors executing the instructions from the memory, the one or more processors configured to perform operations comprising:
obtaining input data and output data of a physical system, the input data representing a dynamic input excitation to the physical system over a period of time, and the output data representing a dynamic output response of the physical system to the dynamic input excitation over the period of time,
configuring a neural network including an input layer and an output layer, the input layer including a plurality of input units to receive the input data and the output data, and the output layer including one or more output units,
training the neural network with the input data and the output data of the physical system to predict a dynamic rate of change of the input data via the one or more output units over the period of time, the input layer updated with a free input unit in additional to the plurality of input units, the output layer updated with a free output unit in addition to the one or more output units, the free output unit to predict a rate of change of data received by the free input unit over the period of time, and
generating a simulation object for the physical system, the simulation object including the trained neural network to determine future output data of the physical system in real time.