def optimizationFunction(vals, args):
# Parse the constant variables
jobName = args[0]
workingDirectory = args[1]
batFileName = args[2]
experimentalResults = args[3]
# Change the material properties in the Abaqus simulation
updateSimulationVariable(vals, workingDirectory)
# Run the simulation
SimulationTools.runSimulation(jobName, workingDirectory, abaqusBatFile=batFileName)
# Get the results from the simulation, and save them using cPickle
odbFileName = '{}\\{}.odb'.format(workingDirectory, jobName) # Create the path to the odb file.
SimulationTools.getResults(workingDirectory, odbFileName, abaqusBatFile=batFileName)
# The specific results have been written to the working directory, so we can now open them as the variable that we saved.
saveResultsFileName = workingDirectory + '\\specificResults.dat' # Define the saved results file name. This needs to be the same result file name that was saved in ExtractResults.py
with open(saveResultsFileName, mode='r') as file:
simResults = cPickle.load(file) # Load the saved results. This will be the same variable that we saved in ExtractResults.py
error = (simResults - experimentalResults)**2 # Define the error
error = np.sum(error) # Sum the error to return a constant value. This may be an array, depending on the choice of optimization.
return error
def runBatch(experimentObject, batchDirectory, genericInputFile, baseJobName, rMl, springs=True):
for param in rMl:
jobName = '{}_{}'.format(baseJobName, int(param))
workingDirectory = '{}/{}'.format(batchDirectory, jobName)
experimentObject.rMl = param
if springs is True:
experimentObject.runSpringSim(jobName, workingDirectory, genericInputFile)
else:
experimentObject.runEmbedSim(jobName, workingDirectory, genericInputFile)
odbFileName = '{}/{}.odb'.format(workingDirectory, jobName)
SimulationTools.getResults(workingDirectory, odbFileName)
return
