def test_invalid_instantiation(self):
# x_series
with pytest.raises(ValueError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[0] = [['x', 'y', 'z']]
for invalid_args in list(itertools.product(*invalid_arg_combos)):
SSV.create_vis(*invalid_args)
# x_series_unit
with pytest.raises(TypeError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[1] = [1, True]
for invalid_args in itertools.product(*invalid_arg_combos):
SSV.create_vis(*invalid_args)
# svg_path
with pytest.raises(FileNotFoundError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[2] = ['']
for invalid_args in itertools.product(*invalid_arg_combos):
SSV.create_vis(*invalid_args)
# title
with pytest.raises(TypeError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[3] = [1, True]
for invalid_args in itertools.product(*invalid_arg_combos):
SSV.create_vis(*invalid_args)
# font_size
with pytest.raises(TypeError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[4] = ['x']
for invalid_args in itertools.product(*invalid_arg_combos):
SSV.create_vis(*invalid_args)
def test_invalid_instantiation(self):
# x_series
with pytest.raises(ValueError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[0] = [['x', 'y', 'z']]
for invalid_args in list(itertools.product(*invalid_arg_combos)):
SSV.create_vis(*invalid_args)
# x_series_unit
with pytest.raises(TypeError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[1] = [1, True]
for invalid_args in itertools.product(*invalid_arg_combos):
SSV.create_vis(*invalid_args)
# svg_path
with pytest.raises(FileNotFoundError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[2] = ['']
for invalid_args in itertools.product(*invalid_arg_combos):
SSV.create_vis(*invalid_args)
# title
with pytest.raises(TypeError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[3] = [1, True]
for invalid_args in itertools.product(*invalid_arg_combos):
SSV.create_vis(*invalid_args)
# font_size
with pytest.raises(TypeError):
invalid_arg_combos = [[args[0]] for args in self._valid_inputs]
invalid_arg_combos[4] = ['x']
for invalid_args in itertools.product(*invalid_arg_combos):
SSV.create_vis(*invalid_args)
def run():
with open(os.path.join('examples', 'example_5', 'data.json')) as f:
data = json.load(f)
ssv_model = SSV.from_json(data)
ssv_model.save_visualization(
os.path.join('examples', 'example_5', 'example_5'))
return True
def run():
# Generate fake cutset data
cutset_data = [['%LDHR','ACB-A-F','ACB-B-F','RCIC-F','HPCI-F'],
['%ATWS','SLC-F','RHR-F'],
['%LOSP','EDG-A-F','EDG-B-F','RCIC-F','HPCI-F'],
['%LDHR','DCB-A-F','DCB-B-F','LPCI-A-F','LPCI-B-F']]
be_data = {'%LDHR':['Loss of Decay Heat Removal', 1.0E-2],
'%LOSP':['Loss of Offsite Power', 1.0E-3],
'%ATWS':['Anticipated Transient Without SCRAM', 1.0E-2],
'SLC-F':['Failure of Standby Liquid Coolant',1.0E-3],
'ACB-A-F':['Failure of AC Bus A',3.0E-3],
'ACB-B-F':['Failure of AC Bus B',3.0E-3],
'XFMR-F':['Failure of Main Transformer',2.0E-4],
'EDG-A-F':['Failure of Emergency Diesel Generator A',1.0E-4],
'EDG-B-F':['Failure of Emergency Diesel Generator B',1.0E-4],
'DCB-A-F':['Failure of DC Bus A',2.0E-2],
'DCB-B-F':['Failure of DC Bus B',2.0E-2],
'RHR-F':['Failure of Residual Heat Removal',1.0E-4],
'RCIC-F':['Failure of Reactor Core Isolation Cooling',4.0E-3],
'LPCI-A-F':['Failure of Low Pressure Coolant Injection A',5.0E-2],
'LPCI-B-F':['Failure of Low Pressure Coolant Injection B',5.0E-2],
'HPCI-F':['Failure of High Pressure Cooland Injection',1.0E-3]}
cutset_freqs = [np.prod([be_data[be][1] for be in cutset]) for cutset in cutset_data]
be_list = be_data.keys()
be_map = {be:[True if be in cutset else False for cutset in cutset_data] for be in be_list}
report = [[[i] + be_data[i] for i in cutset] for cutset in cutset_data]
# Initiate and hook up SSV model
ssv_model = SSV.create_vis(cutset_freqs, 'per year', os.path.join('examples', 'example_4', 'example_4.svg'),
title="Cutset Visualization", font_size=8)
# Add tablular data
ssv_model.add_element('table', 'cutset-report', tabular_data=report,
headers=['Basic Event', 'Description', 'Probability'])
# Wire up svg elements
svg_id = ''
for eq in be_list:
if "%" in eq:
svg_id = eq[1:]
else:
svg_id = eq[:-2]
el = ssv_model.add_element('cell', svg_id.lower())
el.add_condition('logical', data=be_map[eq], true_color='#F44336', false_color='#FFFFFF')
ssv_model.save_visualization(os.path.join('examples', 'example_4', 'example_4'))
return True
def run():
# Let's use the freely available CFAST code from NIST to generate data
# http://www.nist.gov/el/fire_research/cfast.cfm
# This file is from the sample problem provided with the code
data_f = os.path.join('examples', 'example_2', 'standard_n.csv')
data = pd.read_csv(data_f, skiprows=[2], header=[0, 1])
data.columns = [', '.join(col) if i > 0 else col[0] for i, col in enumerate(data.columns)]
# Initiate and hook up SSV model
ssv_model = SSV.create_vis(data['Time'], 'seconds', os.path.join('examples', 'example_2', 'example_2.svg'),
title="CFAST Example", font_size=8)
gas_color_scale = ['#fd8d3c','#fc4e2a','#e31a1c','#bd0026','#800026']
gas_color_levels = np.linspace(min(data['Upper Layer Temperature, Comp 2']),
max(data['Upper Layer Temperature, Comp 3']), 5)
# Add nodes
for i in range(1,4):
data['Layer Height Upper, Comp %d' % i] = 3.0
node = ssv_model.add_element('cell', 'node-%d' % i, 'Node %d' % i, cell_report_id='node-%d-report' % i)
node.add_condition('zonaly', description='Zone Heights', unit='m',
data=data[['Layer Height, Comp %d' % i, 'Layer Height Upper, Comp %d' % i]],
data_dynamic=data[
['Lower Layer Temperature, Comp %d' % i,
'Upper Layer Temperature, Comp %d' % i]],
color_scale=gas_color_scale,
color_levels=gas_color_levels,
max_height=3, description_dynamic='Zone Temperatures', unit_dynamic='C',
min_height=0, section_label='Zone')
node.add_condition('info', data=data[['Pressure, Comp %d' % i]], description='Pressure', unit='Pa')
if i == 1:
node.add_condition('info', data=data[['HRR, bunsen']], description='HRR', unit='W')
elif i == 2:
node.add_condition('info', data=data[['HRR, Wood_Wall']], description='HRR', unit='W')
# Add fires
fire_1 = ssv_model.add_element('toggle', 'fire-1', 'Fire 1')
fire_1.add_condition('showhide', data=data['HRR, bunsen'])
fire_2 = ssv_model.add_element('toggle', 'fire-2', 'Fire 2')
fire_2.add_condition('showhide', data=data['HRR, Wood_Wall'])
# Show gas color scale
ssv_model.add_element('legend', 'color-scale', 'Gas Temperature (C)',
color_scale=gas_color_scale,
color_levels=gas_color_levels)
ssv_model.save_visualization(os.path.join('examples', 'example_2', 'example_2'))
return True
def run():
# Load steam tables and build interpolation functions for several features
sat_tables = pd.read_excel(
os.path.join('examples', 'example_1', 'steam_tables.xls'))
f_press = interp1d(sat_tables['vg'], sat_tables['Mpa'])
f_temp = interp1d(sat_tables['vg'], sat_tables['deg C'])
f_wtr_sp_vol = interp1d(sat_tables['vg'], sat_tables['vf'])
f_wtr_enthalpy = interp1d(sat_tables['vg'], sat_tables['hf'])
f_vap_enthalpy = interp1d(sat_tables['vg'], sat_tables['hg'])
f_lat_heat = interp1d(sat_tables['vg'], sat_tables['hfg'])
# Function to get properties of saturated water+vapor given vapor density
def get_props_from_vap_density(density):
props_out = {}
sp_vol = 1 / density
props_out['press'] = float(f_press(sp_vol))
props_out['temp'] = float(f_temp(sp_vol) + 273.15)
props_out['wtr_density'] = float(1 / f_wtr_sp_vol(sp_vol))
props_out['wtr_enthalpy'] = float(f_wtr_enthalpy(sp_vol))
props_out['vap_enthalpy'] = float(f_vap_enthalpy(sp_vol))
props_out['lat_heat'] = float(f_lat_heat(sp_vol))
return props_out
def th_run(initial_wtr_mass, initial_wtr_level, downstream_height,
steam_flow, discharge_press, time_step, end_time):
"""
Simple Thermal-Hydraulic analysis code for water between 2 compartments.
Assume downstream is water/steam compartment always at saturated conditions.
Assume upstream is saturated steam environment that discharges to downstream.
Heat loss to environment and Condensation is assumed to be negligible. Inputs:
initial_wtr_mass = initial downstream water mass in kg.
initial_wtr_level = initial downstream water level in m. Note that
the downstream volume is assumed to increase linearly with height
based on this input.
downstream_height = total height of downstream compartment (m)
steam_flow = 4 x n array of n occurences of upstream to downstream steam flow.
Row 1 is start time of flow in S
Row 2 is end time of flow in S
Row 3 is specific enthalpy of flow in kJ/kg
Row 4 is total mass of flow in kg
discharge_press = pressure control point of downstream compartment in MPa.
Downstream compartment is modeled as instantly opening and relieving
conditions down to atmospheric over a single time step.
time_step = time step of analysis in S.
end_time = analysis end time is S.
Returns downstream pressure, temperature, water level, and logical states
of relief valve and steam discharge as a function of time.
"""
# Assign initial conditions
vap_density = 0.59
wtr_mass = initial_wtr_mass
wtr_lvl = initial_wtr_level
wtr_lvl_vol_slope = wtr_lvl / wtr_mass
# Determine downstream conditions using steam tables - assume saturated conditions
props = get_props_from_vap_density(vap_density)
press = props['press']
temp = props['temp']
wtr_enthalpy = props['wtr_enthalpy']
wtr_density = props['wtr_density']
vap_enthalpy = props['vap_enthalpy']
lat_heat = props['lat_heat']
wtr_vol = wtr_mass / wtr_density
total_vol = wtr_vol * downstream_height / wtr_lvl
vap_vol = total_vol - wtr_vol
vap_mass = vap_density * vap_vol
lvl_vol_slope = wtr_lvl / wtr_vol
# Cast steam_flow as numpy array
steam_flow = np.array(steam_flow)
# Flag for relief valve
rv_flag = False
# Record conditons at t=0
conditions_out = {
'press': [press],
'temp': [temp],
'wtr_lvl': [wtr_lvl],
'rv': [rv_flag],
'disch': [False],
'time': [0]
}
# Run through time span, calculating conditions at each step
for t in np.arange(1, end_time + time_step, time_step):
# Check if current time span is within or includes any steam_flow entry
# and calculate integrated enthalpy addition
time_mask = ((steam_flow[0] >= t) &
(steam_flow[0] < t + time_step)) | (
(steam_flow[0] < t) & (steam_flow[1] > t))
start_times = steam_flow[0][time_mask]
start_times[start_times < t] = t
end_times = steam_flow[1][time_mask]
end_times[end_times > t + time_step] = t + time_step
time_deltas = end_times - start_times
upstream_enthalpy = steam_flow[2][time_mask]
flow_mass = steam_flow[3][time_mask] * time_deltas
# Calculate vaporized water mass
excess_enthalpy = (upstream_enthalpy - wtr_enthalpy) * flow_mass
vaporized_wtr_mass = (excess_enthalpy / lat_heat).sum()
# Update water mass and vapor mass and density
wtr_mass += flow_mass.sum() - vaporized_wtr_mass
vap_mass += vaporized_wtr_mass
vap_density = vap_mass / (total_vol * (1 - wtr_vol / total_vol))
# If we are at relief pressure reset to saturated conditions and calculate
# change in water mass
if press > discharge_press:
vap_density = 0.59
props = get_props_from_vap_density(vap_density)
wtr_enthalpy_new = props['wtr_enthalpy']
lat_heat = props['lat_heat']
wtr_mass -= (wtr_enthalpy -
wtr_enthalpy_new) * wtr_mass / lat_heat
rv_flag = True
else:
rv_flag = False
# Calculate new properties
# Assume water density has negligible change between time steps
props = get_props_from_vap_density(vap_density)
press = props['press']
temp = props['temp']
wtr_density = props['wtr_density']
wtr_enthalpy = props['wtr_enthalpy']
lat_heat = props['lat_heat']
wtr_lvl = lvl_vol_slope * wtr_mass / wtr_density
vap_mass = vap_density * (total_vol * (1 - wtr_vol / total_vol))
# Record new properties
conditions_out['time'].append(t)
conditions_out['press'].append(press)
conditions_out['temp'].append(temp)
conditions_out['wtr_lvl'].append(wtr_lvl)
conditions_out['disch'].append(flow_mass.sum())
conditions_out['rv'].append(rv_flag)
return conditions_out
# Run the code
initial_wtr_mass = 1000000 # kg ~ 2200000 lbm
initial_wtr_level = 5 # m ~ 16.405 ft
downstream_height = 10 # m ~ 32.81 ft
steam_flow = [
[2, 15, 45, 65], # S - Steam discharge start
[10, 40, 60, 90], # S - Steam discharge end
[2650, 2650, 2650, 2650], # kJ/kg - steam at ~2000 psi or 14 MPa
[50, 100, 150, 150]
] # kg/s - flowrate
discharge_press = 0.79 # Mpa ~ 100 psig
time_step = 1 # Seconds
end_time = 100 # Seconds
sim_data = th_run(initial_wtr_mass, initial_wtr_level, downstream_height,
steam_flow, discharge_press, time_step, end_time)
# Initiate and hook up SSV model
ssv_model = SSV.create_vis(sim_data['time'],
'seconds',
os.path.join('examples', 'example_1',
'example_1.svg'),
title="Steam Quench Tank Simulation",
font_size=8)
water_color_scale = ['#0570b0', '#3690c0', '#74a9cf']
water_color_levels = np.linspace(min(sim_data['temp']),
max(sim_data['temp']),
len(water_color_scale))
gas_color_scale = ['#fdd49e', '#fdbb84', '#fc8d59']
gas_color_levels = np.linspace(min(sim_data['temp']),
max(sim_data['temp']), len(gas_color_scale))
# Wire up svg elements
tank = ssv_model.add_element('cell',
'tank-1',
'Quench Tank',
report_id='tank-1-report')
tank.add_condition('background',
description='Vapor Temp',
unit='K',
color_data=sim_data['temp'],
color_scale=gas_color_scale,
color_levels=gas_color_levels)
tank.add_condition('dynamiclevel',
description='Water Level',
unit='m',
level_data=sim_data['wtr_lvl'],
color_data=sim_data['temp'],
color_scale=water_color_scale,
color_levels=water_color_levels,
max_height=10,
color_data_description='Water Temp',
color_data_unit='K',
overlay='bubbles',
min_height=0)
tank.add_condition('info',
data=sim_data['press'],
description='Press',
unit='MPa')
tank.add_popover("sparkline", sim_data['wtr_lvl'], label='Tank #1 Wtr Lvl')
relief_valve = ssv_model.add_element('cell', 'relief-valve',
'Relief Valve')
relief_valve.add_condition('logical',
data=sim_data['rv'],
true_color='#4CAF50',
false_color='#F44336')
steam_discharge = ssv_model.add_element('cell',
'steam-discharge',
'Steam Discharge',
report_id='disch-report')
steam_discharge.add_condition('logical',
description='Flowrate',
data=sim_data['disch'],
true_color='#4CAF50',
false_color='#F44336',
unit='kg/s')
steam_toggle = ssv_model.add_element('toggle', 'steam-toggle',
'Steam Toggle')
steam_toggle.add_condition('showhide', data=sim_data['disch'])
relief_toggle = ssv_model.add_element('toggle', 'relief-toggle',
'Relief Toggle')
relief_toggle.add_condition('showhide', data=sim_data['rv'])
water_temp_legend = ssv_model.add_element('legend', 'color-scale-water',
'Water Temperature (F)')
water_temp_legend.add_condition("colorscale", water_color_scale,
water_color_levels)
gas_temp_legend = ssv_model.add_element('legend', 'color-scale-gas',
'Gas Temperature (F)')
gas_temp_legend.add_condition("colorscale", gas_color_scale,
gas_color_levels)
ssv_model.save_visualization(
os.path.join('examples', 'example_1', 'example_1'))
return True
def test_bad_svg_(self):
with pytest.raises(ET.ParseError):
SSV.create_vis([0], 'Title', os.path.join('tests', 'data', 'bad_svg.svg'))
def run():
# Let's build assume our core flux distribution takes the form of:
# Φ(r,z) = J0(2.405r/R) cos(πz/H)
#
# Where:
# r is the radius from the center of the core
# z is the height from the bottom of the core
# J0 is the bessel function of the first kind, zero order
# R is the total radius of the core
# H is the total height of the core
#
# Let's also assume the temperature distribution in the core matches this profile.
# Build profile function for entire core
def get_temp(rv, zv, peak_temp):
# Core height and radius, in m
core_h = 3.7
core_r = 1.7
# Assume there is a ratio of core reflector dimensions to active core dimensions
refl_ratio = 0.5
temp = peak_temp * ((special.jv(0, 2.405 * rv / core_r * refl_ratio) *
np.cos(np.pi * zv / core_h / 2 * refl_ratio)))
# Reflect r and z axis to build full core
# Start with r axis
temp_reflect = np.fliplr(temp[:, :, :])
temp = np.append(temp_reflect, temp, 1)
# Flip z axis
temp_reflect = np.flipud(temp[:, :, :])
temp = np.append(temp_reflect, temp, 0)
return temp
# Raise peak core temperature from 500 K to 800 K over 24 hours
# Nodalize core into 5 radial regions x 30 axial regions (15 above center and 15 below center)
# Take data point every 15 minutes
r = np.linspace(0, 1.7, 5)
z = np.linspace(0, 3.7 / 2, 15)
t = np.linspace(0, 24, 96)
rv, zv, tz = np.meshgrid(r, z, t, indexing='ij')
temp_initial = 500
temp_final = 800
peak_temp = temp_initial + (temp_final - temp_initial) * (t / t[-1])
core_temp = get_temp(rv, zv, peak_temp)
# Transpose data
core_temp = core_temp.transpose((2, 1, 0))
# Initiate and hook up SSV model
ssv_model = SSV.create_vis(t,
'hours',
os.path.join('examples', 'example_3',
'example_3.svg'),
title="Core Heatmap Example",
font_size=8)
core_color_scale = ['#ffffb2', '#fecc5c', '#fd8d3c', '#f03b20', '#bd0026']
core_color_levels = np.linspace(300, 800, 5)
node = ssv_model.add_element('heatmap', 'core', 'Core')
node.add_condition('rect',
description='Core Heatmap',
unit='K',
color_data=core_temp,
color_scale=core_color_scale,
color_levels=core_color_levels)
# Use outer vertical rows of heatmap to represent temperature in vessel wall
walls = ssv_model.add_element('line', ['wall-left', 'wall-right'],
'Vessel Wall')
walls.add_condition('equaly',
description='Vessel Wall Temp',
unit='K',
color_data=core_temp[:, :, 0],
color_scale=core_color_scale,
color_levels=core_color_levels)
# Track average and max core temperature
core_temp_avg = core_temp.mean(axis=2).mean(axis=1)
core_temp_max = core_temp.max(axis=2).max(axis=1)
report = ssv_model.add_element('report', 'report-1', 'Core Metrics')
report.add_condition('info',
description='Avg Temp',
unit='F',
data=core_temp_avg)
report.add_condition('info',
description='Max Temp',
unit='F',
data=core_temp_max)
core_temp_legend = ssv_model.add_element('legend', 'core-color-scale',
'Core Temperature (K)')
core_temp_legend.add_condition("colorscale", core_color_scale,
core_color_levels)
ssv_model.save_visualization(
os.path.join('examples', 'example_3', 'example_3'))
return True
def test_element_id_collision(self):
with pytest.raises(ValueError):
vis = SSV.create_vis(*[i[0] for i in self._valid_inputs])
vis.add_element('cell', 'id_1')
vis.add_element('heatmap', 'id_1')
def test_from_json(self):
with open('tests/data/data.json') as f:
data = json.load(f)
SSV.from_json(data)
def test_element_id_collision(self):
with pytest.raises(ValueError):
vis = SSV.create_vis(*[i[0] for i in self._valid_inputs])
vis.add_element('cell', 'id_1')
vis.add_element('heatmap', 'id_1')
def test_bad_svg_(self):
with pytest.raises(ET.ParseError):
SSV.create_vis([0], 'Title',
os.path.join('tests', 'data', 'bad_svg.svg'))
def test_valid_instantiation(self):
for args in list(itertools.product(*self._valid_inputs)):
SSV.create_vis(*args)
def test_valid_instantiation(self):
for args in list(itertools.product(*self._valid_inputs)):
SSV.create_vis(*args)
def run():
# Let's build assume our core flux distribution takes the form of:
# Φ(r,z) = J0(2.405r/R) cos(πz/H)
#
# Where:
# r is the radius from the center of the core
# z is the height from the bottom of the core
# J0 is the bessel function of the first kind, zero order
# R is the total radius of the core
# H is the total height of the core
#
# Let's also assume the temperature distribution in the core matches this profile.
# Build profile function for entire core
def get_temp(rv, zv, peak_temp):
# Core height and radius, in m
core_h = 3.7
core_r = 1.7
# Assume there is a ratio of core reflector dimensions to active core dimensions
refl_ratio = 0.5
temp = peak_temp * ((special.jv(0, 2.405 * rv / core_r * refl_ratio) *
np.cos(np.pi * zv / core_h / 2 * refl_ratio)))
# Reflect r and z axis to build full core
# Start with r axis
temp_reflect = np.fliplr(temp[:,:,:])
temp = np.append(temp_reflect, temp, 1)
# Flip z axis
temp_reflect = np.flipud(temp[:,:,:])
temp = np.append(temp_reflect, temp, 0)
return temp
# Raise peak core temperature from 500 K to 800 K over 24 hours
# Nodalize core into 5 radial regions x 30 axial regions (15 above center and 15 below center)
# Take data point every 15 minutes
r = np.linspace(0, 1.7, 5)
z = np.linspace(0, 3.7/2, 15)
t = np.linspace(0,24,96)
rv,zv,tz = np.meshgrid(r,z,t,indexing='ij')
temp_initial = 500
temp_final = 800
peak_temp = temp_initial + (temp_final - temp_initial) * (t / t[-1])
core_temp = get_temp(rv, zv, peak_temp)
# Transpose data
core_temp = core_temp.transpose((2,1,0))
# Initiate and hook up SSV model
ssv_model = SSV.create_vis(t, 'hours', os.path.join('examples', 'example_3', 'example_3.svg'),
title="Core Heatmap Example", font_size=8)
core_color_scale = ['#ffffb2','#fecc5c','#fd8d3c','#f03b20','#bd0026']
core_color_levels = np.linspace(300,800,5)
node = ssv_model.add_element('heatmap', 'core', 'Core')
node.add_condition('rect', description='Core Heatmap', unit='K', data=core_temp,
color_scale=core_color_scale, color_levels=core_color_levels)
# Use outer vertical rows of heatmap to represent temperature in vessel wall
walls = ssv_model.add_element('line', ['wall-left', 'wall-right'], 'Vessel Wall')
walls.add_condition('equaly', description='Vessel Wall Temp', unit='K', data=core_temp[:,:,0],
color_scale=core_color_scale, color_levels=core_color_levels)
# Track average and max core temperature
core_temp_avg = core_temp.mean(axis=2).mean(axis=1)
core_temp_max = core_temp.max(axis=2).max(axis=1)
report = ssv_model.add_element('report', 'report-1', 'Core Metrics')
report.add_condition('info', description='Avg Temp', unit='F', data=core_temp_avg)
report.add_condition('info', description='Max Temp', unit='F', data=core_temp_max)
ssv_model.add_element('legend', 'core-color-scale', 'Core Temperature (K)',
color_scale=core_color_scale,
color_levels=core_color_levels)
ssv_model.save_visualization(os.path.join('examples', 'example_3', 'example_3'))
return True
def run():
# Let's use the freely available CFAST code from NIST to generate data
# http://www.nist.gov/el/fire_research/cfast.cfm
# This file is from the sample problem provided with the code
data_f = os.path.join('examples', 'example_2', 'standard_n.csv')
data = pd.read_csv(data_f, skiprows=[2], header=[0, 1])
data.columns = [
', '.join(col) if i > 0 else col[0]
for i, col in enumerate(data.columns)
]
# Initiate and hook up SSV model
ssv_model = SSV.create_vis(data['Time'],
'seconds',
os.path.join('examples', 'example_2',
'example_2.svg'),
title="CFAST Example",
font_size=8)
gas_color_scale = ['#fd8d3c', '#fc4e2a', '#e31a1c', '#bd0026', '#800026']
gas_color_levels = np.linspace(
min(data['Upper Layer Temperature, Comp 2']),
max(data['Upper Layer Temperature, Comp 3']), 5)
# Add nodes
for i in range(1, 4):
data['Layer Height Upper, Comp %d' % i] = 3.0
node = ssv_model.add_element('cell',
'node-%d' % i,
'Node %d' % i,
report_id='node-%d-report' % i)
node.add_condition('zonaly',
description='Zone Heights',
unit='m',
level_data=data[[
'Layer Height, Comp %d' % i,
'Layer Height Upper, Comp %d' % i
]],
color_data=data[[
'Lower Layer Temperature, Comp %d' % i,
'Upper Layer Temperature, Comp %d' % i
]],
color_scale=gas_color_scale,
color_levels=gas_color_levels,
max_height=3,
color_data_description='Zone Temperatures',
color_data_unit='C',
min_height=0,
section_label='Zone')
node.add_condition('info',
data=data[['Pressure, Comp %d' % i]],
description='Pressure',
unit='Pa')
if i == 1:
node.add_condition('info',
data=data[['HRR, bunsen']],
description='HRR',
unit='W')
elif i == 2:
node.add_condition('info',
data=data[['HRR, Wood_Wall']],
description='HRR',
unit='W')
# Add fires
fire_1 = ssv_model.add_element('toggle', 'fire-1', 'Fire 1')
fire_1.add_condition('showhide', data=data['HRR, bunsen'])
fire_2 = ssv_model.add_element('toggle', 'fire-2', 'Fire 2')
fire_2.add_condition('showhide', data=data['HRR, Wood_Wall'])
# Show gas color scale
gas_temp_legend = ssv_model.add_element('legend', 'color-scale',
'Gas Temperature (C)')
gas_temp_legend.add_condition("colorscale", gas_color_scale,
gas_color_levels)
ssv_model.save_visualization(
os.path.join('examples', 'example_2', 'example_2'))
return True
def run():
# Load steam tables and build interpolation functions for several features
sat_tables = pd.read_excel(os.path.join('examples', 'example_1', 'steam_tables.xls'))
f_press = interp1d(sat_tables['vg'], sat_tables['Mpa'])
f_temp = interp1d(sat_tables['vg'], sat_tables['deg C'])
f_wtr_sp_vol = interp1d(sat_tables['vg'], sat_tables['vf'])
f_wtr_enthalpy = interp1d(sat_tables['vg'], sat_tables['hf'])
f_vap_enthalpy = interp1d(sat_tables['vg'], sat_tables['hg'])
f_lat_heat = interp1d(sat_tables['vg'], sat_tables['hfg'])
# Function to get properties of saturated water+vapor given vapor density
def get_props_from_vap_density(density):
props_out = {}
sp_vol = 1 / density
props_out['press'] = float(f_press(sp_vol))
props_out['temp'] = float(f_temp(sp_vol) + 273.15)
props_out['wtr_density'] = float(1 / f_wtr_sp_vol(sp_vol))
props_out['wtr_enthalpy'] = float(f_wtr_enthalpy(sp_vol))
props_out['vap_enthalpy'] = float(f_vap_enthalpy(sp_vol))
props_out['lat_heat'] = float(f_lat_heat(sp_vol))
return props_out
def th_run(initial_wtr_mass, initial_wtr_level,
downstream_height, steam_flow, discharge_press, time_step, end_time):
"""
Simple Thermal-Hydraulic analysis code for water between 2 compartments.
Assume downstream is water/steam compartment always at saturated conditions.
Assume upstream is saturated steam environment that discharges to downstream.
Heat loss to environment and Condensation is assumed to be negligible. Inputs:
initial_wtr_mass = initial downstream water mass in kg.
initial_wtr_level = initial downstream water level in m. Note that
the downstream volume is assumed to increase linearly with height
based on this input.
downstream_height = total height of downstream compartment (m)
steam_flow = 4 x n array of n occurences of upstream to downstream steam flow.
Row 1 is start time of flow in S
Row 2 is end time of flow in S
Row 3 is specific enthalpy of flow in kJ/kg
Row 4 is total mass of flow in kg
discharge_press = pressure control point of downstream compartment in MPa.
Downstream compartment is modeled as instantly opening and relieving
conditions down to atmospheric over a single time step.
time_step = time step of analysis in S.
end_time = analysis end time is S.
Returns downstream pressure, temperature, water level, and logical states
of relief valve and steam discharge as a function of time.
"""
# Assign initial conditions
vap_density = 0.59
wtr_mass = initial_wtr_mass
wtr_lvl = initial_wtr_level
wtr_lvl_vol_slope = wtr_lvl / wtr_mass
# Determine downstream conditions using steam tables - assume saturated conditions
props = get_props_from_vap_density(vap_density)
press = props['press']
temp = props['temp']
wtr_enthalpy = props['wtr_enthalpy']
wtr_density = props['wtr_density']
vap_enthalpy = props['vap_enthalpy']
lat_heat = props['lat_heat']
wtr_vol = wtr_mass / wtr_density
total_vol = wtr_vol * downstream_height / wtr_lvl
vap_vol = total_vol - wtr_vol
vap_mass = vap_density * vap_vol
lvl_vol_slope = wtr_lvl / wtr_vol
# Cast steam_flow as numpy array
steam_flow = np.array(steam_flow)
# Flag for relief valve
rv_flag = False
# Record conditons at t=0
conditions_out = {'press':[press], 'temp':[temp], 'wtr_lvl':[wtr_lvl],
'rv':[rv_flag], 'disch':[False], 'time':[0]}
# Run through time span, calculating conditions at each step
for t in np.arange(1, end_time+time_step, time_step):
# Check if current time span is within or includes any steam_flow entry
# and calculate integrated enthalpy addition
time_mask = ((steam_flow[0] >= t) & (steam_flow[0] < t + time_step)) | ((steam_flow[0] < t) & (steam_flow[1] > t))
start_times = steam_flow[0][time_mask]
start_times[start_times < t] = t
end_times = steam_flow[1][time_mask]
end_times[end_times > t + time_step] = t + time_step
time_deltas = end_times - start_times
upstream_enthalpy = steam_flow[2][time_mask]
flow_mass = steam_flow[3][time_mask] * time_deltas
# Calculate vaporized water mass
excess_enthalpy = (upstream_enthalpy - wtr_enthalpy) * flow_mass
vaporized_wtr_mass = (excess_enthalpy / lat_heat).sum()
# Update water mass and vapor mass and density
wtr_mass += flow_mass.sum() - vaporized_wtr_mass
vap_mass += vaporized_wtr_mass
vap_density = vap_mass / (total_vol * (1 - wtr_vol/total_vol))
# If we are at relief pressure reset to saturated conditions and calculate
# change in water mass
if press > discharge_press:
vap_density = 0.59
props = get_props_from_vap_density(vap_density)
wtr_enthalpy_new = props['wtr_enthalpy']
lat_heat = props['lat_heat']
wtr_mass -= (wtr_enthalpy - wtr_enthalpy_new) * wtr_mass / lat_heat
rv_flag = True
else:
rv_flag = False
# Calculate new properties
# Assume water density has negligible change between time steps
props = get_props_from_vap_density(vap_density)
press = props['press']
temp = props['temp']
wtr_density = props['wtr_density']
wtr_enthalpy = props['wtr_enthalpy']
lat_heat = props['lat_heat']
wtr_lvl = lvl_vol_slope * wtr_mass / wtr_density
vap_mass = vap_density * (total_vol * (1 - wtr_vol/total_vol))
# Record new properties
conditions_out['time'].append(t)
conditions_out['press'].append(press)
conditions_out['temp'].append(temp)
conditions_out['wtr_lvl'].append(wtr_lvl)
conditions_out['disch'].append(flow_mass.sum())
conditions_out['rv'].append(rv_flag)
return conditions_out
# Run the code
initial_wtr_mass = 1000000 # kg ~ 2200000 lbm
initial_wtr_level = 5 # m ~ 16.405 ft
downstream_height = 10 # m ~ 32.81 ft
steam_flow = [[2,15,45,65], # S - Steam discharge start
[10,40,60,90], # S - Steam discharge end
[2650,2650,2650,2650], # kJ/kg - steam at ~2000 psi or 14 MPa
[50,100,150,150]] # kg/s - flowrate
discharge_press = 0.79 # Mpa ~ 100 psig
time_step = 1 # Seconds
end_time = 100 # Seconds
sim_data = th_run(initial_wtr_mass, initial_wtr_level,
downstream_height, steam_flow, discharge_press, time_step, end_time)
# Initiate and hook up SSV model
ssv_model = SSV.create_vis(sim_data['time'], 'seconds', os.path.join('examples', 'example_1', 'example_1.svg'),
title="Steam Quench Tank Simulation", font_size=8)
water_color_scale = ['#0570b0', '#3690c0', '#74a9cf']
water_color_levels = np.linspace(min(sim_data['temp']), max(sim_data['temp']), len(water_color_scale))
gas_color_scale = ['#fdd49e','#fdbb84','#fc8d59']
gas_color_levels = np.linspace(min(sim_data['temp']), max(sim_data['temp']), len(gas_color_scale))
# Wire up svg elements
tank = ssv_model.add_element('cell', 'tank-1', 'Quench Tank', cell_report_id='tank-1-report')
tank.add_condition('background', description='Vapor Temp', unit='K', data=sim_data['temp'],
color_scale=gas_color_scale,
color_levels=gas_color_levels)
tank.add_condition('dynamiclevel', description='Water Level', unit='m', data=sim_data['wtr_lvl'],
data_dynamic=sim_data['temp'], color_scale=water_color_scale,
color_levels=water_color_levels,
max_height=10, description_dynamic='Water Temp', unit_dynamic='K', overlay='bubbles',
min_height=0)
tank.add_condition('info', data=sim_data['press'], description='Press', unit='MPa')
tank.add_popover("sparkline", sim_data['wtr_lvl'], label='Tank #1 Wtr Lvl')
relief_valve = ssv_model.add_element('cell', 'relief-valve', 'Relief Valve')
relief_valve.add_condition('logical', data=sim_data['rv'], true_color='#4CAF50', false_color='#F44336')
steam_discharge = ssv_model.add_element('cell', 'steam-discharge', 'Steam Discharge', cell_report_id='disch-report')
steam_discharge.add_condition('logical', description='Flowrate', data=sim_data['disch'], true_color='#4CAF50', false_color='#F44336', unit='kg/s')
steam_toggle = ssv_model.add_element('toggle', 'steam-toggle', 'Steam Toggle')
steam_toggle.add_condition('showhide', data=sim_data['disch'])
relief_toggle = ssv_model.add_element('toggle', 'relief-toggle', 'Relief Toggle')
relief_toggle.add_condition('showhide', data=sim_data['rv'])
ssv_model.add_element('legend', 'color-scale-water', 'Water Temperature (F)',
color_scale=water_color_scale,
color_levels=water_color_levels)
x = ssv_model.add_element('legend', 'color-scale-gas', 'Gas Temperature (F)',
color_scale=gas_color_scale,
color_levels=gas_color_levels)
ssv_model.save_visualization(os.path.join('examples', 'example_1', 'example_1'))
return True
