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MDOF_CN.py
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MDOF_CN.py
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########################################################
# Generate structural parameters according to basic building information based on CN standards.
#
# Dependancy:
# - numpy, pandas
########################################################
from pathlib import Path
import numpy as np
import pandas as pd
import re
import Alpha_CNcode as ACN
class MDOF_CN:
# private
__FloorUnitMass = 1200 # 1200 kg/m2
# input parameters
NumOfStories = 0
FloorArea = 0 # m2
StructuralType = 'UNKNOWN' # Hazus table 5.1
SeismicDesignLevel = '7' # 6, 7, 7.5, 8, 8.5, 9 (g)
EQGroup = '2' # 1, 2, 3
SiteClass = '3' # 1_0, 1_1, 2, 3, 4
longitude = None
latitude = None
# output parameters
# basic
mass = 0 # kg
K0 = 0 # N/m
T1 = 0 # s
N = 0
DampingRatio = 0.05 # damping ratio
TypicalStoryHeight = 0 # (m)
# backbone curve
Vdi = [] # design strength (N) (475-year return period)
Vyi = [] # N
betai = [] # overstrength ratio. Utlmate strength divided by yield strength
etai = [] # hardening ratio
DeltaCi = [] # ultimate drift, meter
# hysteretic parameters
tao = []
# ['Modified-Clough','Kinematic hardening','Pinching']
HystereticCurveType = 'Modified-Clough'
# If the seismic design level or EQgroup is not provided, they will be set according to the city.
# If the site class is not provided, it will be set according to the location.
def __init__(self, NumOfStories, FloorArea, StructuralType,
SeismicDesignLevel = 'UNKNOWN', EQGroup = 'UNKNOWN', City='UNKNOWN',
SiteClass='UNKNOWN', longitude = None, latitude = None):
self.N = NumOfStories
self.NumOfStories = NumOfStories
self.FloorArea = FloorArea
self.__Read_StructuralType(StructuralType)
# design level
if not (SeismicDesignLevel == 'UNKNOWN'):
self.SeismicDesignLevel = SeismicDesignLevel
if not (EQGroup == 'UNKNOWN'):
self.EQGroup = EQGroup
if (not (City == 'UNKNOWN')) and \
((SeismicDesignLevel == 'UNKNOWN') or (EQGroup == 'UNKNOWN')):
self.__Set_DesignLevelbyCity(City)
# site class
self.longitude = longitude
self.latitude = latitude
if not (SiteClass == 'UNKNOWN'):
self.SiteClass = SiteClass
else:
if (longitude and latitude):
self.__Set_SiteClassbyLoc(longitude,latitude)
# story mass
self.mass = self.__FloorUnitMass * self.FloorArea
# read hazus data
current_path = Path(__file__).resolve().parent
HazusDataTable5_5 = pd.read_csv(current_path/"./Resources/HazusData Table 5.5.csv",
index_col='building type')
HazusDataTable5_1 = pd.read_csv(current_path/"./Resources/HazusData Table 5.1.csv",
index_col='building type')
HazusDataTable5_6 = pd.read_csv(current_path/"./Resources/HazusData Table 5.6.csv",
index_col='building type')
HazusDataTable5_9 = pd.read_csv(current_path/"./Resources/HazusData Table 5.9.csv",
index_col=0, header=[0,1,2,3])
HazusDataTable5_18 = pd.read_csv(current_path/"./Resources/HazusData Table 5.18.csv",
index_col=0, header=[0,1])
# Concert_CN2Hazus_SeismicDesignLevel
SDL_Hazus = ACN.Concert_CN2Hazus_SeismicDesignLevel(self.SeismicDesignLevel)
# periods. According to Hazus Table 5.5
T0 = HazusDataTable5_5['typical periods, Te (seconds)'][self.StructuralType]
N0 = HazusDataTable5_1['typical stories'][self.StructuralType]
self.T1 = self.N / N0 * T0
# According to CN code, if the building has more than 10 stories, the period is calculated as follows:
# [1] 中国建筑科学研究院, 同济大学, 中国建筑设计研究院, 等. 建筑结构荷载规范(GB 50009-2012) [S]. 2012.
if self.N >= 10:
if self.StructuralType[0] == 'C': # concrete
self.T1 = 0.075*self.N
elif self.StructuralType[0] == 'S': # steel
self.T1 = 0.125*self.N
# elastic stiffness
UnitMassMat = np.zeros([self.N,self.N])
if self.N == 1:
lambda1 = 1
elif self.N > 1:
for i in range(0,self.N-1):
UnitMassMat[i,i] = 2
UnitMassMat[i,i+1] = -1
for i in range(1,self.N):
UnitMassMat[i,i-1] = -1
UnitMassMat[-1,-1] = 1
lambda_list, featurevector = np.linalg.eig(UnitMassMat)
lambda1 = lambda_list.min()
else:
pass
self.K0 = 4.0*3.14**2*self.mass/self.T1**2/lambda1
# damping ratio
if self.StructuralType[0] == 'C': # concrete
self.DampingRatio = 0.07
elif self.StructuralType[0] == 'S': # steel
self.DampingRatio = 0.05
elif self.StructuralType[0] == 'W': # wood
self.DampingRatio = 0.10
elif self.StructuralType[0:2] == 'RM' or self.StructuralType[0:3] == 'URM':
# reinforced mansory or unreinforced mansory
self.DampingRatio = 0.10
else:
pass
# Tg
Tg = ACN.Tg_CNcode(self.EQGroup,self.SiteClass)
# alphaMax_medium
alphaMax_medium = ACN.alphaMax_CNcode('medium',self.SeismicDesignLevel)
alpha1_medium = ACN.Alpha_CNcode(self.T1,Tg,alphaMax_medium,self.DampingRatio)
alphaMax_major = ACN.alphaMax_CNcode('major',self.SeismicDesignLevel)
alpha1_major = ACN.Alpha_CNcode(self.T1,Tg,alphaMax_major,self.DampingRatio)
# Vyi, betai, etai
# Per GB 50011-2010
kesi_y = 0.4 # Table 5.5.4, GB 50011-2010
SAy = 0.85*alpha1_major*kesi_y
SDy = self.mass * SAy / self.K0
gamma = (alpha1_major*kesi_y)/alpha1_medium # 'overstrength ratio, yield, gamma'
lambda_ = HazusDataTable5_5['overstrength ratio, ultimate, lambda'][self.StructuralType]
SAu = lambda_ * SAy
miu = HazusDataTable5_6[SDL_Hazus][self.StructuralType]
SDu = SDy * lambda_ * miu
ISDR_threshold = HazusDataTable5_9.loc[self.StructuralType,
(SDL_Hazus,'Interstory Drift at Threshold of Damage State','Median','Complete')]
kappa = HazusDataTable5_18.loc[self.StructuralType,(SDL_Hazus,'Moderate')]
# typical story height
Height_feet = HazusDataTable5_1['typical height to roof (feet)'][self.StructuralType]
StoryHeight = Height_feet/N0*0.3048
self.TypicalStoryHeight = StoryHeight
# Vyi, Vdi, betai, etai of other stories
self.Vyi = [0] * self.N
self.Vdi = [0] * self.N
self.betai = [0] * self.N
self.etai = [0] * self.N
self.DeltaCi = [0] * self.N
for i in range(self.N):
Gammai = 1.0 - i*(i+1.0)/(self.N+1.0)/self.N
self.Vyi[i] = SAy*self.mass*9.8*self.N*Gammai
self.Vdi[i] = self.Vyi[i]/gamma
self.betai[i] = SAu / SAy
self.etai[i] = (SAu - SAy) / (SDu - SDy) * SDy / SAy
self.DeltaCi[i] = StoryHeight*ISDR_threshold
# hysteretic parameters
if self.StructuralType[0:2] == 'C1': # concrete
self.HystereticCurveType = 'Modified-Clough'
elif self.StructuralType[0:2] in ['S1','S3']: # steel
self.HystereticCurveType = 'Kinematic hardening'
else:
self.HystereticCurveType = 'Pinching'
self.tao = kappa
def set_DesignLevel(self, DesignLevel: str):
self.SeismicDesignLevel = DesignLevel
self.__init__(self.NumOfStories,self.FloorArea,self.StructuralType)
def OutputStructuralParameters(self, filename):
data = {
'damping ratio': [self.DampingRatio],
'Hysteretic curve type': [self.HystereticCurveType],
'Hysteretic parameter, tao': [self.tao],
'Typical story height (m)': [self.TypicalStoryHeight]
}
pd.DataFrame(data).to_csv(filename +'.csv',index=0,sep=',')
yileddisp = np.array(self.Vyi)/self.K0
designforce = np.array(self.Vdi)
designdisp = designforce/self.K0
ultforce = np.array(self.betai)*np.array(self.Vyi)
ultdisp = yileddisp + (ultforce - np.array(self.Vyi))/(self.K0*np.array(self.etai))
data = {
'No. of story': list(range(1,self.N+1)),
'Floor mass (kg)': [self.mass]*self.N,
'Elastic shear stiffness (N/m)': [self.K0]*self.N,
'Design shear force (N)': self.Vdi,
'Design displacement (m)': designdisp.tolist(),
'Yield shear force (N)': self.Vyi,
'Yield displacement (m)': yileddisp.tolist(),
'Ultimate shear force (N)': ultforce.tolist(),
'Ultimage displacement (m)': ultdisp.tolist(),
'Complete damage displacement (m)': self.DeltaCi,
}
pd.DataFrame(data).to_csv(filename +'.csv',index=0,sep=',',mode='a')
# Generate detailed structural types (like S2) according to reference [1], if only a general type (like S) is provided.
# [1] FEMA. Hazus Inventory Technical Manual [R]. Hazus 4.2 SP3. FEMA, 2021.
def __Read_StructuralType(self,StructuralType):
current_path = Path(__file__).resolve().parent
HazusInventoryTable4_2 = pd.read_csv(current_path/"./Resources/HazusInventory Table 4-2.csv",
index_col=0, header=0)
rownames = HazusInventoryTable4_2.index.to_list()
rownames_NO_LMH = rownames.copy()
for i in range(0,len(rownames)):
if rownames[i][-1] in 'LMH':
rownames_NO_LMH[i] = rownames[i][:-1]
if StructuralType in rownames:
self.StructuralType = StructuralType
elif StructuralType in rownames_NO_LMH:
ind = [i for i in range(0,len(rownames_NO_LMH)) if StructuralType==rownames_NO_LMH[i]]
storyrange = HazusInventoryTable4_2.iloc[ind]['story range'].values.tolist()
for i in range(0,len(storyrange)):
if '~' in storyrange[i]:
Story_low = int(storyrange[i].split('~')[0])
Story_high = int(storyrange[i].split('~')[1])
elif storyrange[i]=='all':
Story_low = 1
Story_high = float('inf')
elif '+' in storyrange[i]:
Story_low = int(storyrange[i][:-1])
Story_high = float('inf')
else:
Story_low = int(storyrange[i])
Story_high = int(storyrange[i])
if self.NumOfStories>=Story_low and self.NumOfStories<=Story_high:
self.StructuralType = rownames[ind[i]]
break
else:
self.StructuralType = StructuralType + ' is UNKNOWN'
# Set seismic design level according to city
# [1] GB 50011-2010(2016) Appendix A
def __Set_DesignLevelbyCity(self, city: str):
current_path = Path(__file__).resolve().parent
GBApp_A = pd.read_csv(current_path/"./Resources/GB50011-2010(2016)-Appendix-A.csv",
na_values='-')
Row = GBApp_A[GBApp_A['City'].str.contains(city,na=False)]
if Row.empty:
print("Error: cannot find such city")
raise SystemExit
else:
SDL = Row['Design Level'].values[-1]
SDL = re.findall(r"\d+\.?\d*", SDL)[0]
PGA = Row['PGA'].values[-1]
PGA = re.findall(r"\d+\.?\d*", PGA)[0]
PGA = float(PGA)
alphaMax = PGA*2.4
if SDL == '8' and alphaMax == 0.3:
SDL = '8.5'
elif SDL == '7' and alphaMax == 0.15:
SDL = '7.5'
self.SeismicDesignLevel = SDL
EQGroup = Row['EQgroup'].values[-1]
if EQGroup[1] == '一':
EQGroup = '1'
elif EQGroup[1] == '二':
EQGroup = '2'
elif EQGroup[1] == '三':
EQGroup = '3'
self.EQGroup = EQGroup
# Set site class according to location per GB 50011-2010(2016) Table 4.1.6
# [1] GB 50011-2010(2016) Table 4.1.6
# [2] Zhou J, Li X, Tian X, Xu G. New Framework of Combining Observations with Topographic Slope to Estimate VS30 and Its Application on Building a VS30 Map for Mainland China. Bulletin of the Seismological Society of America, 2022, 112(4): 2049-2069.
def __Set_SiteClassbyLoc(self, Longitude: float, Latitude: float):
current_path = Path(__file__).resolve().parent
VS30Table = pd.read_excel(current_path/"./Resources/China_Mainland_SCK_Vs30.xlsx",header=1)
distances = np.sqrt((VS30Table['Longitude (°)'] - Longitude)**2 \
+ (VS30Table['Latitude (°)'] - Latitude)**2)
closest_index = distances.idxmin()
VS30 = VS30Table.iloc[closest_index-1, 4]
if VS30 > 800:
SiteClass = '1_0'
elif VS30 > 500:
SiteClass = '1_1'
elif VS30 > 250:
SiteClass = '2'
elif VS30 > 150:
SiteClass = '3'
else:
SiteClass = '4'
self.SiteClass = SiteClass