def _getNodesandElements():
"""
This function returns the nodes and elments for an active model, in a
standardized format. The OpenSees model must be active in order for the
function to work.
Returns
-------
nodes : 2dArray
An array of all nodes in the model.
Returns nodes in the shape:
[Nodes, 3] in 2d and [Nodes, 4]
For each node the information is tored as follows:
[NodeID, x, y] or [NodeID, x, y, z]
elements : Array
An list of all elements in. Each entry in the list is it's own'
[element1, element2,...], element1 = [element#, node1, node2,...]
"""
# Get nodes and elements
nodeList = ops.getNodeTags()
eleList = ops.getEleTags()
# Check Number of dimensions and intialize variables
ndm = len(ops.nodeCoord(nodeList[0]))
Nnodes = len(nodeList)
nodes = np.zeros([Nnodes, ndm + 1])
# Get Node list
for ii, node in enumerate(nodeList):
nodes[ii, 0] = node
nodes[ii, 1:] = ops.nodeCoord(nodeList[ii])
Nele = len(eleList)
elements = [None] * Nele
# Generate the element list by looping through all emenemts
for ii, ele in enumerate(eleList):
tempNodes = ops.eleNodes(ele)
tempNnodes = len(tempNodes)
tempEle = np.zeros(tempNnodes + 1)
tempEle[0] = int(ele)
tempEle[1:] = tempNodes
elements[ii] = tempEle
return nodes, elements
def drawModel():
plt.figure()
etags = ops.getEleTags()
if etags is None:
return
if isinstance(etags, int):
etags = [etags]
for e in etags:
elenodes = ops.eleNodes(e)
for i in range(0, len(elenodes)):
[xi, yi] = ops.nodeCoord(elenodes[i - 1])
[xj, yj] = ops.nodeCoord(elenodes[i])
plt.plot([xi, xj], [yi, yj], 'k')
plt.show()
def get_multi_pile_m(
pile_layout,
cap_edge=0,
cap_thickness=2,
pile_z0=-2.5,
pile_z1=-30,
pile_d=2,
m0=7500000,
top_f=0.0,
top_h=0.0,
top_m=0.0
):
if cap_edge == 0:
if pile_d <= 1:
cap_edge = max(0.25, 0.5 * pile_d)
else:
cap_edge = max(0.5, 0.3 * pile_d)
cap_w = max(pile_layout[0]) - min(pile_layout[0]) + pile_d + cap_edge * 2
cap_l = max(pile_layout[1]) - min(pile_layout[1]) + pile_d + cap_edge * 2
top_f += cap_w * cap_l * cap_thickness * 26e3 # 承台自重
top_f += (cap_w * cap_l) * (-pile_z0 - cap_thickness) * 15e3 # 盖梁重量
pile_rows = len(pile_layout[1]) # 桩排数
top_f /= pile_rows # 桩顶力分配
top_h /= pile_rows # 桩顶水平力分配
top_m /= pile_rows # 桩顶弯矩分配
cap_i = cap_l * cap_thickness ** 3 / 12 / pile_rows # 承台横向刚度
pile_h = pile_z0 - pile_z1
pile_a = np.pi * (pile_d / 2) ** 2
pile_i = np.pi * pile_d ** 4 / 64
pile_b1 = 0.9 * (1.5 + 0.5 / pile_d) * 1 * pile_d
# 建立模型
ops.wipe()
ops.model('basic', '-ndm', 2, '-ndf', 3)
# 建立节点
cap_bot = pile_z0
# ops.node(1, 0, cap_top) # 承台竖向节点
if 0 not in pile_layout[0]:
ops.node(2, 0, cap_bot)
# 建立桩基节点
node_z = np.linspace(pile_z0, pile_z1, elem_num + 1)
for i, j in enumerate(pile_layout[0]):
node_start = 100 + i * 300
for m, n in enumerate(node_z):
ops.node(node_start + m + 1, j, n)
ops.node(node_start + m + 151, j, n)
nodes = {}
for i in ops.getNodeTags():
nodes[i] = ops.nodeCoord(i)
# 建立约束
for i, j in enumerate(pile_layout[0]):
node_start = 100 + i * 300
for m, n in enumerate(node_z):
ops.fix(node_start + m + 151, 1, 1, 1)
if n == node_z[-1]:
ops.fix(node_start + m + 1, 1, 1, 1)
# 建立材料
for i in range(len(node_z)):
pile_depth = i * (pile_h / elem_num)
pile_depth_nominal = 10 if pile_depth <= 10 else pile_depth
soil_k = m0 * pile_depth_nominal * pile_b1 * (pile_h / elem_num)
if i == 0:
ops.uniaxialMaterial('Elastic', 1 + i, soil_k / 2)
continue
ops.uniaxialMaterial('Elastic', 1 + i, soil_k)
# 装配
ops.geomTransf('Linear', 1)
# 建立单元
if len(pile_layout[0]) > 1: # 承台横向单元
cap_nodes = []
for i in nodes:
if nodes[i][1] == cap_bot:
if len(cap_nodes) == 0:
cap_nodes.append(i)
elif nodes[i][0] != nodes[cap_nodes[-1]][0]:
cap_nodes.append(i)
cap_nodes = sorted(cap_nodes, key=lambda x: nodes[x][0])
for i, j in enumerate(cap_nodes[:-1]):
ops.element('elasticBeamColumn', 10 + i, j, cap_nodes[i+1], cap_l * cap_thickness, 3e10, cap_i, 1)
pile_elem = []
for i, j in enumerate(pile_layout[0]): # 桩基单元
node_start = 100 + i * 300
pile_elem_i = []
for m, n in enumerate(node_z):
if n != pile_z1:
ops.element('elasticBeamColumn', node_start + m + 1, node_start + m + 1,
node_start + m + 2, pile_a, 3e10, pile_i, 1)
pile_elem_i.append(node_start + m + 1)
ops.element('zeroLength', node_start + m + 151, node_start + m + 151,
node_start + m + 1, '-mat', 1 + m, '-dir', 1)
pile_elem.append(pile_elem_i)
ops.timeSeries('Linear', 1)
ops.pattern('Plain', 1, 1)
for i in nodes:
if nodes[i] == [0, pile_z0]:
ops.load(i, -top_h, -top_f, top_m) # 加载
ops.system('BandGeneral')
ops.numberer('Plain')
ops.constraints('Plain')
ops.integrator('LoadControl', 0.01)
ops.test('EnergyIncr', 1e-6, 200)
ops.algorithm('Newton')
ops.analysis('Static')
ops.analyze(100)
node_disp = {}
for i in ops.getNodeTags():
node_disp[i] = [j * 1000 for j in ops.nodeDisp(i)]
elem_m = {}
for i in pile_elem:
for j in i:
elem_m[j] = [k / 1000 for k in ops.eleForce(j)]
plt.figure()
for i, j in enumerate(pile_elem):
plt.subplot(f'1{len(pile_elem)}{i+1}')
if i == 0:
plt.ylabel('Pile Depth(m)')
node_disp_x = []
for m, n in enumerate(j):
node_1 = ops.eleNodes(n)[0]
if m == 0:
plt.plot([0, node_disp[node_1][0]], [nodes[node_1][1], nodes[node_1][1]],
linewidth=1.5, color='grey')
else:
plt.plot([0, node_disp[node_1][0]], [nodes[node_1][1], nodes[node_1][1]],
linewidth=0.7, color='grey')
node_disp_x.append(node_disp[node_1][0])
for m, n in enumerate(j):
node_1 = ops.eleNodes(n)[0]
if abs(node_disp[node_1][0]) == max([abs(i) for i in node_disp_x]):
side = 1 if node_disp[node_1][0] > 0 else -1
plt.annotate(f'{node_disp[node_1][0]:.1f} mm', xy=(node_disp[node_1][0], nodes[node_1][1]),
xytext=(0.4 + 0.1 * side, 0.5), textcoords='axes fraction',
bbox=dict(boxstyle="round", fc="0.8"),
arrowprops=dict(arrowstyle='->', connectionstyle=f"arc3,rad={side * 0.3}"))
break
plt.plot([0, 0], [node_z[0], node_z[-1]], linewidth=1.5, color='dimgray')
plt.plot(node_disp_x, node_z[:-1], linewidth=1.5, color='midnightblue')
plt.xlabel(f'Displacement_{i+1} (mm)')
plt.show()
plt.figure()
for i, j in enumerate(pile_elem):
plt.subplot(f'1{len(pile_elem)}{i + 1}')
if i == 0:
plt.ylabel('Pile Depth(m)')
elem_mi = []
for m, n in enumerate(j):
node_1 = ops.eleNodes(n)[0]
if m == 0:
plt.plot([0, elem_m[n][2]], [nodes[node_1][1], nodes[node_1][1]],
linewidth=1.5, color='grey')
else:
plt.plot([0, elem_m[n][2]], [nodes[node_1][1], nodes[node_1][1]],
linewidth=0.7, color='grey')
elem_mi.append(elem_m[n][2])
for m, n in enumerate(j):
node_1 = ops.eleNodes(n)[0]
if abs(elem_m[n][2]) == max([abs(i) for i in elem_mi]):
side = 1 if elem_m[n][2] > 0 else -1
plt.annotate(f'{elem_m[n][2]:.1f} kN.m', xy=(elem_m[n][2], nodes[node_1][1]),
xytext=(0.4 + 0.1 * side, 0.5), textcoords='axes fraction',
bbox=dict(boxstyle="round", fc="0.8"),
arrowprops=dict(arrowstyle='->', connectionstyle=f"arc3,rad={side * 0.3}"))
break
plt.plot([0, 0], [node_z[0], node_z[-1]], linewidth=1.5, color='dimgray')
plt.plot(elem_mi, node_z[:-1], linewidth=1.5, color='brown')
plt.xlabel(f'Moment_{i + 1} (kN.m)')
plt.show()
return pile_elem, elem_m
def get_element_nodes():
element_nodes = dict()
ele_tags = ops.getEleTags()
for i in ele_tags:
element_nodes[i] = ops.eleNodes(i)
return element_nodes
ops.analysis('Transient')
el_tags = ops.getEleTags()
nels = len(el_tags)
Eds = np.zeros((n_steps, nels, 6))
timeV = np.zeros(n_steps)
# transient analysis loop and collecting the data
for step in range(n_steps):
ops.analyze(1, dt)
timeV[step] = ops.getTime()
# collect disp for element nodes
for el_i, ele_tag in enumerate(el_tags):
nd1, nd2 = ops.eleNodes(ele_tag)
Eds[step, el_i, :] = [ops.nodeDisp(nd1)[0],
ops.nodeDisp(nd1)[1],
ops.nodeDisp(nd1)[2],
ops.nodeDisp(nd2)[0],
ops.nodeDisp(nd2)[1],
ops.nodeDisp(nd2)[2]]
# 1. animate the deformated shape
anim = opsv.anim_defo(Eds, timeV, sfac_a, interpFlag=1, xlim=[-1, 7],
ylim=[-1, 5], fig_wi_he=(30., 22.))
plt.show()
# 2. after closing the window, animate the specified mode shape
eigVals = ops.eigen(5)