Hello, my name is Daniel Vázquez Vázquez. I am a researcher at ETH Zürich, with a background
on Chemical and Process Engineering. My research focuses on process modeling and optimization, using both commercial simulation solvers
such as Aspen PLUS/HYSYS and mathematical algebraic formulation. To add to these fields, I also try to use machine learning tools together
with sustainability assessment methodologies in order to optimize not only one, but multiple objectives. For any question or comment,
please do not hesitate to contact me!
University of Santiago de Compostela, Galicia, Spain
University of Alicante, Com.Valenciana, Spain
Universitat Rovira i Virgili, Catalunya, Spain
University of Alicante, Com. Valenciana, Spain
ETH Zurich, Zürich, Switzerland
PySIS
: Python-Aspen HYSYS high level interface using win32 COM
# Import the main class and load the file
from pysis import Simulation
hy_file = r"path/to/simulation.hsc"
FS = Simulation(path = hy_file)
FS.set_visible(1) # Sets the flowsheet to visible
# Specify objects
F1 = FS.MatStreams["Feed"]
F2 = FS.MatStreams["Feed2"]
Output = FS.MatStreams["1"]
Mixer = FS.Operations["MIX-100"]
# Read properties
prop_to_read = {
"Temperature":"C",
"Pressure":"bar",
"CompMolarFlow": "kgmole/h",
...
}
F1prop = F1.get_properties(prop_to_read)
# Set properties
prop_to_set = {
"Temperature":(150, "K"),
"Pressure":(4, "atm"),
"CompMolarFlow": {"CO2":(43, "kgmole/h"), ...}
...
}
F1.set_properties(prop_to_set)
# Save (If you want to)
FS.save()
# Close (Important)
FS.close()
PyAPLUS
: Python-Aspen Plus high level interface using win32 COM
# Import the main class and load the file
from pyaplus.flowsheet import Simulation
ap_file = r"path/to/simulation.bkp"
FS = Simulation(path = ap_file)
FS.set_visible(1) # Sets the flowsheet to visible
# Specify objects
F1 = FS.get_stream["FEED"]
F2 = FS.get_stream["FEED2"]
Output = FS.get_stream["1"]
Mixer = FS.get_block["MIX-100"]
# Read properties. It comes in the flowsheet
# Aplus units
prop_to_read = [
"TEMP",
"PRES",
("COMPMOLEFLOW", "ChemicalName"),
...
]
F1prop = F1.get_properties(prop_to_read)
# Set properties. The units are the same as the
# flowsheet
prop_to_set = {
"TEMP":100,
"PRES":4,
("COMPFLOW", "ChemicalName"): 43
...
}
F1.set_properties(prop_to_set)
# Save (If you want to)
FS.save()
# Close (Important)
FS.close()
.gdx
generated by GAMS and transforms it
in a Pandas dataframe in Python. Or you can use Pyomo. Or Jump, which is even cooler.
PyGDX
: Python-based reader of GDX files
# Import the main class and load the file
import pygdx.core as gdx
import pandas as pd
# State the path to the GDX file and to GAMS executable
GAMS_FOLDER = r"C:\GAMS\38" # May look something like this.
GDX_File = r"GDX_File.gdx"
# Generate an instance of the class and use the read method
results = gdx.GDXFile(gdx_path= GDX_File, gams_path=GAMS_FOLDER)
results.read_gdx()
# You can now read sets, parameters and variables dictionaries
sets = results.sets_df
parameters = results.parameters_df
variables = results.variables_df
Title | Citations | Year |
---|---|---|
Bayesian Symbolic Learning to Build Analytical Correlations
from Rigorous Process Simulations: Application to CO2 Capture Technologies Valentina Negri, Daniel Vázquez, Marta Sales-Pardo, Roger Guimerà, and Gonzalo Guillén-Gosálbez ACS Omega 2022, 7, 45, 41147–41164 |
0 | 2022 |
Automatic modeling of socioeconomic drivers of energy consumption and pollution
using Bayesian symbolic regression Daniel Vázquez, Roger Guimerà, Marta Sales-Pardo, Gonzalo Guillén-Gosálbez Sustainable Production and Consumption, Volume 30, March 2022, Pages 596-607 |
3 | 2022 |
Process design within planetary boundaries: Application to CO2 based methanol production Daniel Vázquez, Gonzalo Guillén-Gosálbez Chemical Engineering Science, Volume 246, December 2021, 116891 |
11 | 2021 |
Delaying carbon dioxide removal in the European Union puts climate targets at risk Daniel Vázquez, Ángel Galán-Martín, Selene Cobo, Niall Mac Dowell, José Antonio Caballero, Gonzalo Guillén-Gosálbez Nature Communications, 12, 6490, 2021 |
13 | 2021 |
Mixed integer non-linear programming model for reliable and safer design at an early stage Daniel Vázquez, Rubén Ruiz-Femenia, José Antonio Caballero Computers & Chemical Engineering, 147, 107256, 2021 |
3 | 2021 |
Alternative carbon dioxide utilization in dimethyl carbonate
synthesis and comparison with current technologies Juan Diego Medrano-García, Juan Javaloyes-Antón, Daniel Vázquez, Rubén Ruiz-Femenia, José Antonio Caballero Journal of CO2 Utilization, 45, 101436, 2021 |
6 | 2021 |
OFISI, a novel optimizable inherent safety index based on fuzzy logic Daniel Vázquez, Rubén Ruiz-Femenia, José Antonio Caballero Computers & Chemical Engineering, 129, 106526, 2019 |
8 | 2019 |
MILP models for objective reduction in multi-objective optimization:
Error measurement considerations and non-redundancy ratio Daniel Vázquez, Rubén Ruiz-Femenia, José Antonio Caballero Computers & Chemical Engineering, 115, 323-332, 2018 |
3 | 2018 |
Multiobjective early design of complex distillation sequences
considering economic and inherent safety criteria Daniel Vázquez, Rubén Ruiz-Femenia, Laureano Jiménez, José Antonio Caballero Industrial & Engineering Chemistry Research, 57, 20, 6992-7007, 2018 |
18 | 2018 |
MILP method for objective reduction in multi-objective optimization Daniel Vázquez, María José Fernández-Torres, Rubén Ruiz-Femenia, Laureano Jiménez, José Antonio Caballero Computers & Chemical Engineering, 108, 382-394, 2018 |
14 | 2018 |