def test_freq(): for model in ['plate_clt_donnell_bardell', 'plate_clt_donnell_bardell_w', 'cpanel_clt_donnell_bardell', 'kpanel_clt_donnell_bardell']: for atype in [3, 4]: print('Frequency Analysis, atype={0}, model={1}'.format( atype, model)) p = Panel() p.model = model p.bc_ssss() p.a = 1. p.b = 0.5 p.r = 1.e8 p.alphadeg = 0. p.stack = [0, 90, -45, +45] p.plyt = 1e-3*0.125 p.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9) p.mu = 1.3e3 p.m = 11 p.n = 12 p.Nxx = -60. p.Nyy = -5. p.freq(sparse_solver=True, reduced_dof=False, silent=True, atype=atype) if atype == 3: if '_w' in model: assert np.allclose(p.eigvals[0], 19.9271684726) else: assert np.allclose(p.eigvals[0], 17.8587479369) elif atype == 4: if '_w' in model: assert np.allclose(p.eigvals[0], 40.3728103572) else: assert np.allclose(p.eigvals[0], 39.3147553173)
def test_lb(): for model in ['plate_clt_donnell_bardell', 'plate_clt_donnell_bardell_w', 'cpanel_clt_donnell_bardell', 'kpanel_clt_donnell_bardell']: print('Linear buckling for model {0}'.format(model)) # ssss p = Panel() p.bc_ssss() p.m = 12 p.n = 13 p.stack = [0, 90, -45, +45] p.plyt = 0.125e-3 p.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9) p.model = model p.a = 1. p.b = 0.5 p.r = 1.e8 p.alphadeg = 0. p.Nxx = -1 p.lb(silent=True) if '_w' in model: assert np.allclose(p.eigvals[0], 88.4769618837) else: assert np.allclose(p.eigvals[0], 85.2911727144) p.Nxx = 0 p.Nyy = -1 p.lb(silent=True) if '_w' in model: assert np.allclose(p.eigvals[0], 26.4588171556) else: assert np.allclose(p.eigvals[0], 25.1756170679) # ssfs p = Panel() p.bc_ssfs() p.m = 12 p.n = 13 p.stack = [0, 90, -45, +45] p.plyt = 0.125e-3 p.laminaprop = (142.5e9, 8.7e9, 0.28, 5.1e9, 5.1e9, 5.1e9) p.model = model p.a = 1. p.b = 0.5 p.r = 1.e8 p.alphadeg = 0. p.Nxx = -1 p.lb(silent=True) if '_w' in model: assert np.allclose(p.eigvals[0], 17.1442703121) else: assert np.allclose(p.eigvals[0], 15.8423562314) p.bc_sfss() p.Nxx = 0 p.Nyy = -1 p.lb(silent=True) if '_w' in model: assert np.allclose(p.eigvals[0], 15.8099861083) else: assert np.allclose(p.eigvals[0], 13.9421987614)