Rule Input Network Generator (RING)
RING is an automated reaction network generation and analysis tool that outputs reaction networks for complex reactive systems from user-defined inputs of initial reactants and chemical reaction rules. RING also takes user-provided post-processing instructions to analyze the topology of the generated network; possible post-processing instructions include: reaction pathway queries to isolate routes from defined reactants to products, lumping instructions to group functionally equivalent species (e.g. isomers) for network reduction, and mechanism queries to establish sequences of elementary steps describing the overall transformations of reactants to products. The following schematic depicts the overall protocol of RING:
RING can be downloaded here: RING-2.1.0.zip (release date May 26, 2018) with installation instructions here: install.pdf. Additional user documentation is included in the archive. Contact Professor Prodromos Daoutidis (daout001 AT umn DOT edu) with questions or bug reports.
Acknowledgments:
Financial support from the Initiative for Renewable Energy at the University of Minnesota, the National Science Foundation, and the U. S. Department of Energy. The reaction language interface of RING was developed in collaboration with Prof. Eric Van Wyk and Ted Kaminski, Department of Computer Science & Engineering at the University of Minnesota, using the tools SILVER and COPPER developed in the MELT group.
MATLAB files for the Performance Driven Agglomerative Clustering method :
Optimal Combined Design-Scheduling for Ammonia-Based Sustainable Energy Agriculture (ABSEA) System
The ABSEA system uses renewable energy to (i) make ammonia as fertilizer and fuel for tractors and grain drying, (ii) meet local power demands, and (iii) allow for consistent export of excess generated renewable power to the grid. The optimal combined design-scheduling model determines the optimal size of chemical production, power generation and storage units to meet the requirements listed above, as well as the respective hourly production rates or storage levels of those units over a representative operating period. The model can be downloaded here, along with documentation:
http://www.dropbox.com/s/94bqbbd1ag31e6d/ABSEA_CDS_Model.zip?dl=1
Contact Professor Prodromos Daoutidis ([email protected]) with any questions.
The parameters currently included in the model represent a case study for ABSEA installation and operation in Morris, Minnesota at the West Central Research and Outreach Center (WCROC) and the nearly located University of Minnesota Morris (UMM) Campus. These parameters can be easily modified to consider different geography, spatial scale or unit specifications.
Acknowledgements:
This work was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0000804; in part by the Minnesota Environment and Natural Resources Trust Fund as recommended by the Legislative-Citizen Commission on Minnesota Resources (LCCMR,/ ML 2015, CH 76, SEC 2, SUBD 07A); and in part by the MnDRIVE initiative of the University of Minnesota (MNT11). The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.