"""Special archetypes provided as necessary to the Rickshaw input file.
Used for fuel cycle niches that have more than just one incommodity and outcommodity.
"""
import random
[docs]def generate_throwsink(commod, name):
"""Generic sink for outcommodities that do not become the
incommodity of the following archetype.
Parameters
----------
commod : String
Name of the commidity that the throwsink is receiving.
name : String
Name for the archetype in the input file.
Returns
-------
config : Dictionary
Dictionary formatted to represent the archetype in the input file.
"""
vals = {}
vals["capacity"] = 1.0e100
vals["in_commods"] = {"val": [commod]}
config = {"name": name, "config": {"agents_sink": vals}}
return config
[docs]def generate_throwsource(commod, name):
"""Generic source for commidities.
Parameters
----------
commod : String
Name of the commidity that the throwsource is generating.
name : String
Name for the archetype in the input file.
Returns
-------
config : Dictionary
Dictionary formatted to represent the archetype in the input file.
"""
vals = {}
vals["capacity"] = 1.0e100
vals["commod"] = commod
vals["recipe_name"] = 'natural_uranium'
config = {"name": name, "config": {"agents_source": vals}}
return config
[docs]def enrich_tails(name, vals, commod):
"""Generates a sink for the tails commodity stream.
Parameters
----------
name : String
Name for the archetype in the input file.
vals : Dictionary
Dictionary containing the specifications for the facilities
in the simulation.
commod : String
The commod name will be tailcommd in this case.
Returns
-------
sink : Dictionary
Dictionary formatted to represent the archetype in the input file.
"""
vals[name] = 'tailcommod'
sink = generate_throwsink('tailcommod', 'enrichsink')
return sink
[docs]def sep_streams(name, vals, commod):
"""Generates random separation effiencies
for the separations facility.
Parameters
----------
name : String
Name for the archetype in the input file.
vals : Dictionary
Dictionary containing the specifications for the facilities
in the simulation.
commod : String
Name of the commodity to be separated.
"""
sep_rand = random.uniform(0.0, 1.0)
sep = 1 - (0.0000001)**(1-sep_rand)*(0.1)**sep_rand
nucs = ["U", "Pu"]
streams = {"streams":{
"item":[{
"commod": commod,
"info": {
"buf_size": 1e298,
"efficiencies": {
"item": []
}
}
}]
}}
choice = random.choice(nucs)
if choice == "U" or choice =="Pu":
temp = {"comp": choice, "eff": sep}
streams["streams"]["item"][0]["info"]["efficiencies"]["item"].append(temp)
vals[name] = streams["streams"]
return 0
[docs]def sep_leftover(name, vals, commod):
"""Generates a sink facility for the waste
material after separation.
Parameters
----------
name : String
Name for the archetype in the input file.
vals : Dictionary
Dictionary containing the specifications for the facilities
in the simulation.
commod : String
Name of the commodity to be sent to the sink.
Returns
-------
sink: Dictionary
Dictionary containing the specifications for a sink
facility.
"""
vals[name] = 'leftovercommod'
sink = generate_throwsink('leftovercommod', 'sepsink')
return sink
[docs]def ff_fill(name, vals, commod):
"""Generates a DU source facility for a fuel fabrication
facility.
Parameters
----------
name : String
Name for the archetype in the input file.
vals : Dictionary
Dictionary containing the specifications for the facilities
in the simulation.
commod : String
Name of the commodity for the source.
Returns
-------
source: Dictionary
Dictionary containing the specifications for a source
facility.
"""
vals[name] = {"val": 'fillcommod'}
source = generate_throwsource('fillcommod', 'ffsource')
return source
[docs]def ff_fill_recipe(name, vals, commod):
vals[name] = "natural_uranium"
return 0
[docs]def skip(name, vals, commod):
return 0
[docs]def generate_region_inst(sim, sim_spec):
"""Creates a null region and inst for the randomized runs.
This operated in-place.
Parameters
----------
sim : Dictionary
Simulation specifications for the cyclus input file.
sim_spec : SimSpec
The prebuild SimSpec for the simulation.
"""
sim["region"] = region = {
"name": "SingleRegion",
"config": {"NullRegion": None},
"institution": {
"name": "SingleInstitution",
"initialfacilitylist": {"entry": []},
}
}
entries = sim["region"]["institution"]["initialfacilitylist"]["entry"]
if sim_spec.ni == True:
sim['region']['institution']['config'] = {"DeployInst": generate_deploy(sim,
sim_spec.parameters)}
for facility in sim["facility"]:
if facility in sim_spec.parameters['facs']:
continue
else:
entry = {"prototype": facility["name"], "number": 1}
entries.append(entry)
else:
sim['region']['institution']['config'] = {"NullInst": None}
for facility in sim["facility"]:
entry = {"prototype": facility["name"], "number": 1}
entries.append(entry)
[docs]def generate_deploy_inst(sim):
"""This creates a deploy institution for randomized runs.
It will generate a number of deployment times, randomize
the times and determine the what to deploy at those times.
It operates in place.
Parameters
----------
sim : Dictionary
Simulation specifications for the cyclus input file.
"""
randtimes = sim['control']['duration']/12
months = []
config = {'prototypes': {'val':[]}, 'build_times': {'val': []}, 'n_build':{'val': []}, 'lifetimes': {'val':[]}}
i = 0
while i < randtimes:
months.append(random.randrange(1, sim['control']['duration'], 1))
i+=1
months.sort()
for date in months:
for facility in sim["facility"]:
config['prototypes']['val'].append(facility['name'])
config['build_times']['val'].append(date)
config['n_build']['val'].append(random.randint(1,10))
config['lifetimes']['val'].append(random.randint(40, 60))
return config
[docs]def trans_init_facs(sim, parameters, config):
pstart, facpower = parameters['pstart'], parameters['facpower']
lin = parameters['lin']
facs, facstart, facend = parameters['facs'], lin['facstart'], lin['facend']
startfacs, facnum, power = [], {}, 0.0
for fac in facs:
i = facs.index(fac)
if facstart[i] == 0:
startfacs.append(i)
facnum[i] = 0.0
while power < pstart:
fac = random.choice(startfacs)
facnum[fac] += 1.0
power += facpower[fac]
for fac in startfacs:
i = 0
while i < facnum[fac]:
config['prototypes']['val'].append(facs[fac])
config['build_times']['val'].append(0)
config['lifetimes']['val'].append(random.randrange(0,60,1))
config['n_build']['val'].append(1)
i+=1
return config
[docs]def generate_deploy(sim, parameters):
"""Determines the function used to build the deploy institution.
Parameters
----------
sim : Dictionary
Simulation specifications for the cyclus input file.
parameters: Dictionary
Parameters used to define the deploy institution.
"""
config = {}
if 'schedule' in parameters.keys():
config = generate_deploy_sch(sim, parameters)
if 'lin' in parameters.keys():
config = generate_deploy_lin(sim, parameters)
return config
[docs]def generate_deploy_lin(sim, parameters):
"""This creates a deploy institution for randomized runs.
This deploy institutation is designed to test a given parameter
space for the possibility of transition between facilities.
Parameters
----------
sim : Dictionary
Simulation specifications for the cyclus input file.
parameters: Dictionary
Parameters used to define the deploy institution.
"""
randtimes = sim['control']['duration']/12
months = []
lin = parameters['lin']
config = {'prototypes': {'val':[]}, 'build_times': {'val': []}, 'n_build':{'val': []}, 'lifetimes': {'val':[]}}
i = 0
facs, facstart, facend, types = parameters['facs'], lin['facstart'], lin['facend'], lin['type']
try:
gen_c = parameters['generalchance']
except:
print("No generalchance parameter set, using default of 10%")
gen_c = 0.1
deploy_c = lin['deploychoice']
config = trans_init_facs(sim, parameters, config)
while i < randtimes:
months.append(random.randrange(1, sim['control']['duration'], 1))
i+=1
months.sort()
for date in months:
for facility in sim["facility"]:
if facility["name"] in facs:
i = facs.index(facility["name"])
if facstart[i] > date or facend[i] < date:
continue
num = random.choice(deploy_c[i])
if num == 0:
continue
value, mid = 0, (date-facstart[i])/(facend[i]-facstart[i])
if types[i] is 'inc':
value = mid
elif types[i] is 'dec':
value = 1-mid
elif types[i] is 'unity':
value = 1
if random.random() < value:
config['prototypes']['val'].append(facility['name'])
config['build_times']['val'].append(date)
config['lifetimes']['val'].append(random.choice([40, 60]))
config['n_build']['val'].append(num)
else:
if random.random() < gen_c:
config['n_build']['val'].append(1)
config['prototypes']['val'].append(facility['name'])
config['build_times']['val'].append(date)
config['lifetimes']['val'].append(random.choice([40, 60]))
return config
[docs]def generate_deploy_sch(sim, parameters):
"""This creates a deploy institution for randomized runs.
This deploy institutation is designed to test a given parameter
space for the possibility of transition between facilities.
Parameters
----------
sim : Dictionary
Simulation specifications for the cyclus input file.
parameters: Dictionary
Parameters used to define the deploy institution.
"""
config = {'prototypes': {'val':[]}, 'build_times': {'val': []}, 'n_build':{'val': []}, 'lifetimes': {'val':[]}}
sched = parameters['schedule']
for fac, dates in sched.items():
for date, values in dates.items():
seed = random.random()
i = 0
while seed > values[i]:
i+=1
if i > 0:
config['prototypes']['val'].append(fac)
config['build_times']['val'].append(date)
config['lifetimes']['val'].append(40)
config['n_build']['val'].append(i)
return config
