systems2atoms is a suite of models that can simulate the performance of hydrogen infrastructure across multiple scales. Examples of the different scale levels include:
-
System Scale - techno-economic analysis for hydrogen applications, integration of hydrogen infrastructure with the electrical grid, and supply and demand constraints across applications
-
Component Scale - continuous-flow catalyst beds, electrochemical conversion units, gas-phase separators, pumps, compressors, storage tanks, evaporators, heaters, and coolers
-
Material Scale - surface reactions, degradation mechanisms, and catalyst poisoning
The scope of the software is limited to hydrogen in its most abundant isotopic form, as protium. Further, it is limited to the use of hydrogen (protium) as a fuel; that is, as an energy carrier capable of producing energy via exothermic reactions. This includes: production, storage, distribution, and use as a fuel; the development of related technologies; and compounds and mixtures in gaseous, liquid, and solid states.
Python 3.8 or higher is recommended.
Individual submodules (e.g. s2a.surrogates
, s2a.systems
) have associated requirements. Please
check the READMEs for the individual submodules to find the requirements.
Install this package:
pip install git+https://github.com/LLNL/systems2atoms
Quick demo of surrogate model optimization (requires s2a.surrogates
requirements):
import systems2atoms as s2a
model = s2a.surrogates.model_initializer()
s2a.surrogates.solve(model, solver='glpk')
s2a.surrogates.pprint(model)
Quick demo of hydrogen delivery cost calculations:
import systems2atoms as s2a
print(s2a.systems.calcs())
Please submit any bugfixes or feature improvements as pull requests.
- Sneha Akhade
- Matthew McNenly
systems2atoms is distributed under the terms of the MIT license. All new contributions must be under this license.
See LICENSE and NOTICE for details.
SPDX-License-Identifier: MIT
LLNL-CODE-856566
The development of systems2atoms is supported by the Laboratory Directed Research and Development (LDRD) program
at Lawrence Livermore National Laboratory (LLNL). The project identifier is GS 23-ERD-016
with Sneha Akhade as
principal investigator.