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/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.
IdahoLabResearch/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.
IdahoLabResearch/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.
IdahoLabResearch/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).
IdahoLabResearch/AcCCS
A collection of tools and scripts used to communicate and emulate Electric Vehicle Communication Controllers (EVCC) and Supply Equipment Communication Controllers (SECC).
IdahoLabResearch/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.
IdahoLabResearch/CDB_Analysis_Program
A graphical user interface (GUI) that helps analyze data from coincidence Doppler broadening positron annihilation spectroscopy. It is a quick tool to rapidly reduce large data and conveniently analyze multiple datasets.
IdahoLabResearch/CMAT
The CMAT software provides the user with a fully customizable decision support framework that analyzes the optimal supply chain configurations for a given industrial electronic waste (e-waste) recycling and refurbishment process. The software optimizes the logistics operations, helps to identify the best recycling process configuration, and generates valuable insights regarding the economic performance of different categories of e-waste. The ultimate purpose of the model is to provide insights on questions pertinent to the e-waste recycling industry including how to increase efficiency and reduce costs, energy consumption, and greenhouse gas emissions.
IdahoLabResearch/OMDD
Model that supports drone deployment. Analysis on speed, package weight, energy consumption, # of drones, and battery replacements.
IdahoLabResearch/PowDDeR-Python
The number of power outages have been on the rise as extreme weather patterns have been occurring more frequently due to climate change. These outages have an economic impact in the billions of dollar. The modernization of the power grid and adoption of high penetration of distributed generation such as wind and solar have the potential to reduce the number and length of time of these power outages. However, planners and operators need a way to value the resilience the distributed assets provide to the grid. PowDDeR is a tool that allows them to evaluate the resilience each asset provides as well as how they provide resilience over the connected network.
IdahoLabResearch/HFVT
The optimization tool denoted as the “Hydropower Flexibility Valuation Tool” aims to maximize the revenue from market participation after satisfying flow requirements, considering a range of power market price signals and water availability scenarios.
IdahoLabResearch/tapsap
Temporal analysis of products statistical analysis package (tapsap) is a package for reading, cleaning, analyzing and making inference of temporal analysis of products (TAP) information. This package is designed with the intent for collaboration within the TAP community for advancing TAP analysis.
IdahoLabResearch/TROPFE
The code models the operation of a high temperature steam electrolysis (HTSE) plant.
IdahoLabResearch/HPC_Natural_Language_Understanding_-NLU-_Dataset
This code provides natural language annotation and labels for multiple activities in high performance. The purpose is to enable machine learning for natural language processing algorithms with high performance computing systems.
IdahoLabResearch/HPCACT-2022
Anomalous temporal action detection code and dataset for activities in a High Performance Computing datacenter.
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/ReMAIn
Resilience of Microgrids with Adaptive capacity and Inertia calculates the maximum size of a disturbance a microgrid could withstand before frequency limits are violated.
IdahoLabResearch/HEA_Code
This code describes the process to estimate material properties using elemental properties and machine learning.
IdahoLabResearch/AquaPV
The AquaPV toolset provides foundational data and analyses for policymakers, developers, utilities, and financial firms seeking to understand floating PV (FPV) project viability on the United States (US) reservoirs and estuaries, assisting in scaling the systematic evaluation and implementation of this concept in the US.
IdahoLabResearch/Buggy-Program-Program
The purpose of this code is to automatically create random C programs that are guaranteed to have bugs of a particular "interestingness". We are using this to train learning machines to fuzz programs better. Other people might want to use it for training humans to examine software.
IdahoLabResearch/Digital-Twin-Analytics-SEARCH
This package applies the different aspects of SEARCH (store, explore, assess, reduce, confirm, and holistic) to initial machine learning results to an unknown data set.
IdahoLabResearch/EVIRS
In post-crash situations, passengers, bystanders, and first responders are exposed to the immediate safety risks of stranded energy in electric vehicle (EV) batteries. This software tool will directly help the emergency responders to handle EV post-crash situations effectively and safely.
IdahoLabResearch/Hydropower_Unit_Models
This repository presents different hydropower unit models on various platforms.
IdahoLabResearch/INLIDD
IdahoLabResearch/MAGNET-Heat-Pipe-Data
This is a dataset that was produced on March 30, 2022 during the demonstration and run of the Microreactor AGile Non-nuclear Experimental Testbed (MAGNET). The MAGNET Digital Twin was run alongside a single heat pipe within MAGNET during this demonstration. Published works: https://www.sciencedirect.com/science/article/pii/S0149197023002482
IdahoLabResearch/Multiplayer_Engineering
Multiplayer Engineering is a software framework that enables real-time collaboration in virtual environments
IdahoLabResearch/Scramble
The purpose of Scramble is to provide a cross validation method to ensure machine learning model accuracy in cases where model classes have heterogeneous N values.
IdahoLabResearch/SFWDSubsurface
This code allows for a geologic cross-sectional profile to be obtained from a user-drawn profile line within a web map application.
IdahoLabResearch/Type_5_Wind_Turbine_Drivetrain
The purpose of this code is to provide a high-fidelity model of Type-5 wind turbine drivetrain for grid integration and transient stability studies.