def get_corrected_density_and_viscosity(oil):
'''
Get coefficients for calculating resin (and asphaltene) fractions
based on Merv Fingas' empirical analysis of ESTC oil properties
database.
- Bill has clarified that we want to get the coefficients for just
the 15C Density
- Mervs calculations depend on a density measured in g/mL and a
viscosity measured in mPa.s, so we do a conversion here.
'''
try:
temperature = 273.15 + 15
P0_oil = density_at_temperature(oil, temperature)
V0_oil = get_viscosity(oil, temperature)
a = 10 * exp(0.001 * P0_oil)
b = 10 * log(1000.0 * P0_oil * V0_oil)
except:
print 'get_corrected_density_and_viscosity() generated exception:'
print '\toil = ', oil
print '\toil.kvis = ', oil.kvis
print '\tP0_oil = ', density_at_temperature(oil, temperature)
print '\tV0_oil = ', get_viscosity(oil, temperature)
raise
return a, b
def test_get_viscosity(temps, exp_value, use_out):
if use_out:
out = np.zeros_like(temps)
get_viscosity(oil_, temps, out)
else:
out = get_viscosity(oil_, temps)
assert np.all(out == exp_value) # so it works for scalar + arrays
def get_corrected_density_and_viscosity(oil):
'''
Get coefficients for calculating resin (and asphaltene) fractions
based on Merv Fingas' empirical analysis of ESTC oil properties
database.
- Bill has clarified that we want to get the coefficients for just
the 15C Density
- Mervs calculations depend on a density measured in g/mL and a
viscosity measured in mPa.s, so we do a conversion here.
'''
try:
temperature = 273.15 + 15
P0_oil = density_at_temperature(oil, temperature)
V0_oil = get_viscosity(oil, temperature)
a = 10 * exp(0.001 * P0_oil)
b = 10 * log(1000.0 * P0_oil * V0_oil)
except:
print 'get_corrected_density_and_viscosity() generated exception:'
print '\toil = ', oil
print '\toil.kvis = ', oil.kvis
print '\tP0_oil = ', density_at_temperature(oil, temperature)
print '\tV0_oil = ', get_viscosity(oil, temperature)
raise
return a, b
def test_get_viscosity(temps, exp_value, use_out):
if use_out:
out = np.zeros_like(temps)
get_viscosity(oil_, temps, out)
else:
out = get_viscosity(oil_, temps)
assert np.all(out == exp_value) # so it works for scalar + arrays
def show_uncategorized_oils(session):
oils = (session.query(Oil)
.filter(Oil.categories == None)
.all())
fd = open('temp.txt', 'w')
fd.write('adios_oil_id\t'
'product_type\t'
'api\t'
'viscosity\t'
'pour_point\t'
'name\n')
print ('{0} oils uncategorized.'
.format(len(oils)))
for o in oils:
if o.api >= 0:
if o.api < 15:
category_temp = 273.15 + 50
else:
category_temp = 273.15 + 38
viscosity = uc.convert('Kinematic Viscosity', 'm^2/s', 'cSt',
get_viscosity(o, category_temp))
else:
viscosity = None
fd.write('{0.imported.adios_oil_id}\t'
'{0.imported.product_type}\t'
'{0.api}\t'
'{1}\t'
'({0.pour_point_min_k}, {0.pour_point_max_k})\t'
'{0.name}\n'
.format(o, viscosity))
def link_refined_fuel_oil_6(session):
'''
Category Name:
- Fuel Oil #6/Bunker/Heavy Fuel Oil/Group V
Sample Oils:
- Bunker C
- Residual Oil
Density Criteria:
- API < 15
Kinematic Viscosity Criteria:
- 200.0 <= v cSt @ 50 degrees Celcius
'''
top_category = (session.query(Category)
.filter(Category.parent == None)
.filter(Category.name == 'Refined').one())
categories = [c for c in top_category.children
if c.name in ('Fuel Oil 6',
'Bunker',
'Heavy Fuel Oil',
'Group V')
]
oils = get_oils_by_api(session, 'Refined',
api_min=0.0, api_max=15.0)
count = 0
category_temp = 273.15 + 50
for o in oils:
viscosity = uc.convert('Kinematic Viscosity', 'm^2/s', 'cSt',
get_viscosity(o, category_temp))
if viscosity >= 200.0:
for category in categories:
o.categories.append(category)
count += 1
print ('{0} oils added to {1} -> {2}.'
.format(count, top_category.name,
[n.name for n in categories]))
transaction.commit()
def link_refined_fuel_oil_2(session):
'''
Category Name:
- Fuel oil #2/Diesel/Heating Oil
Sample Oils:
- Diesel
- Heating Oil
- No. 2 Distillate
Density Criteria:
- 30 <= API < 35
Kinematic Viscosity Criteria:
- 2.5 < v <= 4.0 cSt @ 38 degrees Celcius
'''
top_category = (session.query(Category)
.filter(Category.parent == None)
.filter(Category.name == 'Refined').one())
categories = [c for c in top_category.children
if c.name in ('Fuel Oil 2',
'Diesel',
'Heating Oil')
]
oils = get_oils_by_api(session, 'Refined',
api_min=30.0, api_max=35.0)
count = 0
category_temp = 273.15 + 38
for o in oils:
viscosity = uc.convert('Kinematic Viscosity', 'm^2/s', 'cSt',
get_viscosity(o, category_temp))
if viscosity > 2.5 or viscosity <= 4.0:
for category in categories:
o.categories.append(category)
count += 1
print ('{0} oils added to {1} -> {2}.'
.format(count, top_category.name,
[n.name for n in categories]))
transaction.commit()
def link_refined_fuel_oil_1(session):
'''
Category Name:
- Fuel oil #1/gasoline/kerosene
Sample Oils:
- gasoline
- kerosene
- JP-4
- avgas
Density Criteria:
- API >= 35
Kinematic Viscosity Criteria:
- v <= 2.5 cSt @ 38 degrees Celcius
'''
top_category = (session.query(Category)
.filter(Category.parent == None)
.filter(Category.name == 'Refined').one())
categories = [c for c in top_category.children
if c.name in ('Light Products (Fuel Oil 1)',
'Gasoline',
'Kerosene')
]
oils = get_oils_by_api(session, 'Refined', api_min=35.0)
count = 0
category_temp = 273.15 + 38
for o in oils:
viscosity = uc.convert('Kinematic Viscosity', 'm^2/s', 'cSt',
get_viscosity(o, category_temp))
if viscosity <= 2.5:
for category in categories:
o.categories.append(category)
count += 1
print ('{0} oils added to {1} -> {2}.'
.format(count, top_category.name,
[n.name for n in categories]))
transaction.commit()
def link_refined_ifo(session):
'''
Category Name:
- Intermediate Fuel Oil
Sample Oils:
- IFO 180
- Fuel Oil #4
- Marine Diesel
Density Criteria:
- 15 <= API < 30
Kinematic Viscosity Criteria:
- 4.0 < v < 200.0 cSt @ 38 degrees Celcius
'''
top_category = (session.query(Category)
.filter(Category.parent == None)
.filter(Category.name == 'Refined').one())
categories = [c for c in top_category.children
if c.name in ('Intermediate Fuel Oil',)
]
oils = get_oils_by_api(session, 'Refined',
api_min=15.0, api_max=30.0)
count = 0
category_temp = 273.15 + 38
for o in oils:
viscosity = uc.convert('Kinematic Viscosity', 'm^2/s', 'cSt',
get_viscosity(o, category_temp))
if viscosity > 4.0 or viscosity < 200.0:
for category in categories:
o.categories.append(category)
count += 1
print ('{0} oils added to {1} -> {2}.'
.format(count, top_category.name,
[n.name for n in categories]))
transaction.commit()
(np.asarray(density_tests), np.asarray(density_exp), False),
(np.asarray(density_tests), np.asarray(density_exp), True)])
def test_get_density(temps, exp_value, use_out):
if use_out:
out = np.zeros_like(temps)
get_density(oil_, temps, out)
else:
out = get_density(oil_, temps)
assert np.all(out == exp_value) # so it works for scalar + arrays
# Test case - get ref temps from kvis then append ref_temp for
# kvis at 0th index for a few more values:
# viscosity_tests = [d.ref_temp_k for d in oil_.densities]
# viscosity_tests.append(oil_.densities[0].ref_temp_k)
v_max = get_viscosity(oil_, get_pour_point(oil_), clip_to_vmax=False)
viscosity_tests = [
oil_.kvis[ix].ref_temp_k
if ix < len(oil_.kvis) else oil_.kvis[0].ref_temp_k
for ix in range(0,
len(oil_.kvis) + 3)
]
viscosity_exp = [(d.m_2_s, v_max)[v_max < d.m_2_s] for temp in viscosity_tests
for d in oil_.kvis if abs(d.ref_temp_k - temp) == 0]
@pytest.mark.parametrize(
("temps", "exp_value", "use_out"),
[(viscosity_tests[0], viscosity_exp[0], False),
from pyramid.paster import get_appsettings, setup_logging
from oil_library import _get_db_session
from oil_library.models import Base, ImportedRecord, Oil, Density, Toxicity, Category
from oil_library.oil_props import OilProps
from oil_library.utilities import get_viscosity, get_boiling_points_from_api
from oil_library.init_oil import density_at_temperature
session = _get_db_session()
oil_obj = session.query(Oil).filter(Oil.name == "ALASKA NORTH SLOPE").one()
props_obj = OilProps(oil_obj)
viscosity = uc.convert("Kinematic Viscosity", "m^2/s", "cSt", get_viscosity(oil_obj, 273.15 + 38))
print oil_obj, "\n\tviscosity at 38C =", viscosity
for v in oil_obj.kvis:
v_ref, t_ref = v.m_2_s, v.ref_temp_k
print "\tviscosity: {0} m^2/s at {1}K".format(v.m_2_s, v.ref_temp_k)
print "imported pour points:", (oil_obj.imported.pour_point_min_k, oil_obj.imported.pour_point_max_k)
print "oil pour points:", (oil_obj.pour_point_min_k, oil_obj.pour_point_max_k)
def get_ptry_values(oil_obj, component_type, sub_fraction=None):
"""
This gives an initial trial estimate for each density component.
In theory the fractionally weighted average of these densities,
combined with the fractionally weighted average resin and asphaltene
(np.asarray(density_tests),
np.asarray(density_exp), True)])
def test_get_density(temps, exp_value, use_out):
if use_out:
out = np.zeros_like(temps)
get_density(oil_, temps, out)
else:
out = get_density(oil_, temps)
assert np.all(out == exp_value) # so it works for scalar + arrays
# Test case - get ref temps from kvis then append ref_temp for
# kvis at 0th index for a few more values:
# viscosity_tests = [d.ref_temp_k for d in oil_.densities]
# viscosity_tests.append(oil_.densities[0].ref_temp_k)
v_max = get_viscosity(oil_, get_pour_point(oil_), clip_to_vmax=False)
viscosity_tests = [oil_.kvis[ix].ref_temp_k if ix < len(oil_.kvis)
else oil_.kvis[0].ref_temp_k
for ix in range(0, len(oil_.kvis) + 3)]
viscosity_exp = [(d.m_2_s, v_max)[v_max < d.m_2_s]
for temp in viscosity_tests
for d in oil_.kvis
if abs(d.ref_temp_k - temp) == 0]
@pytest.mark.parametrize(("temps", "exp_value", "use_out"),
[(viscosity_tests[0], viscosity_exp[0], False),
(viscosity_tests, viscosity_exp, False),
(tuple(viscosity_tests), viscosity_exp, False),
