我正在使用 Abaqus 进行抗震结构系统设计的优化。
我打算使用 Gekko 来达到这个目的。但似乎我在写下有关此任务的合适语法时犯了错误。
“Objective”是负责创建Abaqus数值模型、分析模型、处理结果和计算罚函数的子程序的名称。
“目标”返回建筑物成本与要最小化的惩罚函数的总和。
这是错误消息：
@error：数据不足
CSV 读取错误：动态问题的数据行数必须 >= 2
已识别的数据点：1
停止。 。 。
回溯（最近一次调用最后一次）：
文件“C:\temp\AK\24-Gekko\opti1.10.3.0.py”，第 721 行，位于
m.solve()
文件“C:\Users\amjad\AppData\Roaming\Python\Python38\site-packages\gekko\gekko.py”，第 2140 行，求解
引发异常（apm_error）
异常：@error：数据不足
CSV 读取错误：动态问题的数据行数必须 >= 2
已识别的数据点：1
停止。 。 。
这是优化过程的主要代码：
'''
m = GEKKO(远程=假)
Alfa1 = m.Const(1.25)
Alfa2 = m.Const(0.3)
Alfa3 = m.Const(1.25)
UCS = m.Const(1000.) # $/Ton of steel
UCC = m.Const(67.) # $/m3 of concrete
UCCF = m.Const(20.) # $/m2 of column wood framework
UCBF = m.Const(28.) # $/m2 of beam wood framework
UCWF = m.Const(20.) # $/m2 of wall wood framework
GammaS = m.Const(7850)
GammaC = m.Const(2500)
cover = m.Const(10.)
f_c = m.Const(30.)
fy = m.Const(400.)
Est = m.Const(200000.)
eu_c = m.Const(0.003)
bw = m.Const(700.)
fai = 6.
#defining material parameters
Mats = {
"CDP30.0" :("mm",GammaC.value*1.e-12,0.18,0.,[f_c.value,0.0015,0.4,100],[f_c.value/10., 0.001 , 1.0],35,0.1,1.12,0.667,0.1,1.0,0.0),
"C30.0" :("mm",GammaC.value*1.e-12,0.18,0.,f_c.value),
"S400.0":("mm",GammaS.value*1.e-12,0.3,0.,fy.value),
}
#defining section's locations within building members and lengths of members
Sections = {
"C11":[[("A0-A1","A1-A2","D0-D1","D1-D2"),750.],[],[],[]],
"C22":[[("A2-A3","A3-A4","A4-A5","D2-D3","D3-D4","D4-D5"),750.],[],[],[]],
"C33":[[("B0-B1","C0-C1","B1-B2","C1-C2","B2-B3","C2-C3","B3-B4","C3-C4","B4-B5","C4-C5",),750.],[],[],[]],
"BB1":[[("A1-B1","C1-D1","A2-B2","C2-D2","A3-B3","C3-D3","A4-B4","C4-D4","A5-B5","C5-D5",),700.],[],[]],
"WW1":[[("B0-C1","B1-C2","B2-C3","B3-C4","B4-C5",),750.],[],[]],
}
#creating materials of the model
MatText = []
for i in Mats:
if i[1:3]=="DP":CDPs(i,Mats[i][0],Mats[i][1],Mats[i][2],Mats[i][3],Mats[i][4],Mats[i][5],Mats[i][6],Mats[i][7],Mats[i][8],Mats[i][9],Mats[i][10],Mats[i][11],Mats[i][12])
elif i[0] =="C" :EPPs(i,Mats[i][0],Mats[i][1],Mats[i][2],Mats[i][3],Mats[i][4])
elif i[0] =="S" :EPPs(i,Mats[i][0],Mats[i][1],Mats[i][2],Mats[i][3],Mats[i][4])
#objective function initializing
FX = 0.
Vars = []
for i in [x for x in Sections if x[0]=="C"]:
a = m.Var(value=125,lb=100,ub=250,integer = False)
b = m.Var(value=125,lb=100,ub=250,integer = False)
Us = m.Var(value=0.02,lb=0.01,ub=0.045,integer = False)
rebarS = rectRC(a.value,b.value,Us.value,cover.value,fai,"C")
Sections[i][1] = [a.value,b.value,Us.value,rebarS]
As = np.pi*fai**2./4*(4+2*rebarS[1][0]+2*rebarS[2][0])
#calculating the cost of a Column section
Sections[i][2] = m.Intermediate(Alfa1*As/(1000**3)*GammaS*UCS+a*b/(1000*1000)*UCC+2*(a+b)/(1000)*UCCF)
Sections[i][3] = PMinteraction(eu_c.value,cover.value,a.value,b.value,f_c.value,fy.value,Est.value,(2+rebarS[1][0])*np.pi*fai**2/4,(2+rebarS[1][0])*np.pi*fai**2/4)
FX += len(Sections[i][0][0])*Sections[i][0][1]/1000*Sections[i][2]
Vars.append((i,Sections[i][1][:3]))
for i in [x for x in Sections if x[0]=="B"]:
a = m.Var(value=125,lb=100,ub=250,integer = False)
b = m.Var(value=125,lb=100,ub=250,integer = False)
Us = m.Var(value=0.02,lb=0.01,ub=0.045)
rebarS = rectRC(a.value,b.value,Us.value,cover.value,fai,"B")
Sections[i][1] = [a.value,b.value,Us.value,rebarS]
As = np.pi*fai**2./4*(4+2*rebarS[1][0]+2*rebarS[2][0])
#calculating the cost of a Beam section
Sections[i][2] = m.Intermediate((2*Alfa2*As/(1000**3)+(1-2*Alfa2)*As/(1000**3))*GammaS*UCS+a*b/(1000*1000)*UCC+(a+2*b)/(1000)*UCBF)
print (Sections[i][2])
FX += len(Sections[i][0][0])*Sections[i][0][1]/1000*Sections[i][2]
Vars.append((i,Sections[i][1][:3]))
for i in [x for x in Sections if x[0]=="W"]:
a = m.Var(value=125,lb=100,ub=250,integer = False)
b = bw.value
Us = m.Var(value=0.009,lb=0.007,ub=0.01)
rebarS = rectRC(a.value,b.value,Us.value,cover.value,fai,"W")
Sections[i][1] = [a.value,b.value,Us.value,rebarS]
As = np.pi*fai**2./4*(4+2*rebarS[1][0]+2*rebarS[2][0])
#calculating the cost of a Wall section
Sections[i][2] = m.Intermediate(Alfa3*As/(1000**3)*GammaS*UCS+a*b/(1000*1000)*UCC+2*b/(1000)*UCWF)
print (Sections[i][2])
FX += len(Sections[i][0][0])*Sections[i][0][1]/1000*Sections[i][2]
Vars.append((i,Sections[i][1][:3]))
#modifying object function by a reference value
FX = FX/ReferenceFX * 1.
m.Minimize(Objective(Vars))
m.options.SOLVER = 1
m.options.IMODE = 6
m.solve()
'''
