Idaho National Laboratory Research Projects
This is a location for Idaho National Laboratory software that is tied to research papers and experiments.
Idaho Falls, ID, USA
Pinned Repositories
5GAD
This is a dataset of 5G network traffic for use with machine learning tools to benchmark attack detection capabilities for multiple different models. The dataset contains simulated normal and attack 5G network traffic.
AcCCS
A collection of tools and scripts used to communicate and emulate Electric Vehicle Communication Controllers (EVCC) and Supply Equipment Communication Controllers (SECC).
BIhNNs
The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).
CIACS
CoCuNi
HEA_Code
This code describes the process to estimate material properties using elemental properties and machine learning.
HydroGenerate
The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the “head” provided by the user.
HyPAT
The Hydrogen Permeation Analysis Tool (HyPAT) provides a user friendly interface for batch analysis of dynamic hydrogen permeation data to calculate the transport properties permeability, solubility, and diffusivity. A built in literature database provides an easy comparison to known values.
PyEmission
PyEmission is a Python library for estimation of vehicular emissions and fuel consumption. This tool covers a wide range of light duty motor vehicles including passenger car, SUV, passenger truck, and light commercial truck. The tool only takes second-by-second driving cycle and vehicle characteristics data as inputs and generate results of vehicular emissions (CO2, CO, NOx, and HC) and fuel consumption.
TAPsolver
TAPsolver is a python package, which automates TAP simulation and analysis routines. TAPsolver is built around the python packages FEniCS and Dolfin-Adjoint, which help take advantage of model adjoints to provide automatic derivatives. TAPsolver is flexible, with reaction mechanisms and rate constants that can be set through input files that allow users to take advantage of the different functionalities, which include sensitivity analyses, parameter optimization and uncertainty quantification.
Idaho National Laboratory Research Projects's Repositories
IdahoLabResearch/DREEM
A System Dynamics Model for Assessing Dynamic Rare Earth Production, Demand and U.S. Wind Energy Demand
IdahoLabResearch/CIACS
IdahoLabResearch/LISA
This model was developed to assess the viability of US Lithium supply from geothermal brine and the potential supply chain impact of extracting Lithium from this source. This model links global demand and supply of lithium (Li) considering different electric vehicle (EV) demand scenarios. We seek to answer the following questions: • What is the economic potential of Li extraction from US geothermal sources? • Is geothermal Li extraction technology a viable investment in the US? • What is the potential supply chain impact of Li supply from US geothermal sources?
IdahoLabResearch/MFSCO
This Multi-feedstock Supply Chain Optimization (MFSCO) tool can be used to determine a least-cost feedstock mix from crop residue, energy crop and MSW to meet conversion specifications, while also identifying appropriate depot locations and size, given that depot can be co-located with the biorefinery or can be located in any counties in the biofinery’s supply shed.
IdahoLabResearch/WOODCOM
Woody Biomass Companion Markets Model
IdahoLabResearch/CoCuNi
IdahoLabResearch/TAPsolver
TAPsolver is a python package, which automates TAP simulation and analysis routines. TAPsolver is built around the python packages FEniCS and Dolfin-Adjoint, which help take advantage of model adjoints to provide automatic derivatives. TAPsolver is flexible, with reaction mechanisms and rate constants that can be set through input files that allow users to take advantage of the different functionalities, which include sensitivity analyses, parameter optimization and uncertainty quantification.