Fix the bug of calculating principal stresses. Now the fitting result is better for the criteria which expressed in principal stresses.
Thanks to Martin.
This commit is contained in:
parent
16cee5e3ee
commit
fd75772a3f
|
@ -35,7 +35,7 @@ def principalStresses(sigmas):
|
||||||
for i in xrange(np.shape(sigmas)[1]):
|
for i in xrange(np.shape(sigmas)[1]):
|
||||||
eigenvalues = np.linalg.eigvalsh(np.array(sigmas[:,i]).reshape(3,3))
|
eigenvalues = np.linalg.eigvalsh(np.array(sigmas[:,i]).reshape(3,3))
|
||||||
lambdas = np.append(lambdas,np.sort(eigenvalues)[::-1]) #append eigenvalues in descending order
|
lambdas = np.append(lambdas,np.sort(eigenvalues)[::-1]) #append eigenvalues in descending order
|
||||||
lambdas = lambdas.reshape(3,np.shape(sigmas)[1])
|
lambdas = np.transpose( lambdas.reshape(np.shape(sigmas)[1],3) )
|
||||||
return lambdas
|
return lambdas
|
||||||
|
|
||||||
def stressInvariants(lambdas):
|
def stressInvariants(lambdas):
|
||||||
|
|
Loading…
Reference in New Issue