US 12,450,403 B2
Method and tool for modeling changes in solid materials caused by galvanic or chemical interactions
Richard J. Thompson, Huntsville, AL (US); and Kristen S. Williams, Madison, AL (US)
Assigned to The Boeing Company, Arlington, VA (US)
Filed by The Boeing Company, Chicago, IL (US)
Filed on Aug. 31, 2021, as Appl. No. 17/462,928.
Claims priority of provisional application 63/116,390, filed on Nov. 20, 2020.
Prior Publication US 2022/0164494 A1, May 26, 2022
Int. Cl. G06F 30/15 (2020.01); G01N 17/00 (2006.01); G06F 30/20 (2020.01)
CPC G06F 30/15 (2020.01) [G01N 17/006 (2013.01); G06F 30/20 (2020.01)] 25 Claims
OG exemplary drawing
 
1. A method comprising:
receiving environmental data describing a first plurality of physical parameters of an environment in which an object is located, wherein the object comprises a first material and a second material that galvanically or chemically interacts with the first material;
receiving sensor data describing a second plurality of physical parameters of the object;
receiving a multi-state model of the object, wherein the multi-state model comprises a plurality of distinct galvanic or chemical states of the object, and wherein each of the plurality of distinct galvanic or chemical states represents a corresponding different equation applicable to a corresponding specific galvanic or chemical interaction between the first material and the second material;
performing a stochastic optimization operation on the multi-state model until convergence on a plurality of candidate sets of galvanic or chemical material change rates for the plurality of distinct galvanic or chemical states of the object, wherein averaging is used to alleviate a plurality of variables from the multi-state model to thereby increase a speed of performing the stochastic optimization operation, and wherein performing the stochastic optimization operation is performed by dispatching multiple single-objective optimization runs of the plurality of distinct galvanic or chemical states of the object to concurrently minimize different determinations of error for the plurality of distinct galvanic or chemical states, and further wherein dispatching is performed according to one of: random dispatching, a lattice hypercube algorithm, or an orthogonal array algorithm;
generating a correlation model for a surrogate parameter for the second plurality of physical parameters by correlating the environmental data to the sensor data using the plurality of candidate sets of galvanic or chemical material change rates;
generating an aircraft design using the correlation model; and
building an aircraft according to the aircraft design.