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)