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  • Flexible Energy Scheduling Tool for Integrating Variable generation (FESTIV) is a tool that simulates the realistic representation of steady-state power system operations and scheduling performed by an independent system operator, regional transmission organization, or a vertically integrated regulated utility. The tool integrates security-constrained unit commitment (SCUC), security-constrained economic dispatch (SCED), and automatic generation control (AGC) into one model. These are the three modes of power system scheduling that are used to meet the changing net demand. Each of these submodels have different time characteristics and are used to meet the changing demand at different time resolutions and horizons. This allows multiple timescales to be studied where FESTIV accounts for intertemporal coupling between each submodel and the submodels themselves. It does this while having different objectives between the submodels; commitment of resources, dispatch and reserve commitment, and finally control.
    Data Types:
    • Software/Code
  • We provide a self-contained package to load, process, and test the ICF JAG dataset. In particular, we include a Neural Network designed to act as a surrogate for the JAG 1D Simulator. The neural network is implemented in Tensorflow. We include a Jupyter notebook which allows a user to load the dataset, load the neural network and train it such that given just the 5 input parameters, it predicts the scalars and images accurately. This can be done directly in the notebook, without any additional modifications. During training, intermediate predictions are also saved to disk (as specified by the user). We hope this serves as a starting point to build, test and play with the ICF-JAG simulation dataset.
    Data Types:
    • Software/Code
  • Polycubes are arrangements of unit cubes connected by their faces. This code generates all possible polycubes with a specified number of unit cubes that are unique under 3D rotation (the family of polycubes of size N) and also finds a globally and locally valid edge unfolding for either a single polycube or a specified family of polycubes.
    Data Types:
    • Software/Code
  • The Connected and Automated Vehicles Scenario Generation (CSG) model is a system dynamics model. It was built by NREL and funded by the U.S. Department of Energy under the Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility initiative. The purpose of the model is to simulate the “transitions from predominantly individual ownership of non-CAVs to various future scenarios of high connectivity/automation”(Bush, Vimmerstedt, and Gonder 2019).
    Data Types:
    • Software/Code
  • This computer software is a MATLAB standalone code for implementation of the Lumped Particle Domain model. The model solves charge transfer kinetics, lithium diffusion dynamics, charge conservation and energy conservation occurring across the porous electrode pair unit cell sandwich to predict electrical and thermal response of a battery. Physico-chemical states of batteries are also evaluated by the model.
    Data Types:
    • Software/Code
  • The principal purpose of this code is to determine bulk constitutive properties and response of polycrystalline materials. This is a nonlinear quasi-static, implicit solid mechanics code built on the MFEM library based on an updated Lagrangian formulation (velocity based). Within this context, there is flexibility in the type of constitutive model employed, with the code allowing for various UMATs to be interfaced within the code framework or for the use of the ExaCMech library. Using crystal-mechanics-based constitutive models, the code can be used, for example, to compute homogenized response behavior over a polycrystal.
    Data Types:
    • Software/Code
  • The main purpose of the software is to model energy use for individual and community scale solar water heating projects in California. Usage The user provides a climate zone for a project, an occupancy for each household and whether any of the occupants stay at home during the day. The software can then load a set of example California specific hourly domestic hot water end-use load profiles from a database, size and locate the systems. The user can now simulate the hourly system performance over a period of one representative year, visualize and explore the simulation results using time-series plots for temperature profiles, heat and power rates, or look at annual summaries. Similarly the user can model individual household solar water heating projects and base case conventional gas tank water heater systems, such that the results can be compared between the individual, community and base case systems. This functionality is readily available through a Jupyter notebook and a Django web framework, depending on what level of detail the user would like to access. Features - Python module to calculate solar irradiation on a tilted surface - Python module with simplified component models for Converter (solar collectors, electric resistance heater, gas burner, photovoltaic panels, heat pump), Storage (solar thermal tank, heat pump thermal tank, conventional gas tank water heater), and Distribution (distribution and solar pump, piping losses) components - Python module with preconfigured system simulation models for: base case gas tank water heaters, solar thermal water heaters (solar collector feeding a storage tank, with a tankeless gas water heater backup in a new installation cases and a base case gas tank water heater in a retrofit case) and solar electric water heaters (heat pump storage tank with an electric resistance backup) - Database with component performance parameters, California specific weather data and domestic hot water end-use load profiles - Django web framework to configure project, parametrize components and run simulation from a web browser The package contains functional and unit tests and it is structured so that it can be extended with further technologies, applications and locations.
    Data Types:
    • Software/Code
  • Code to perform operation count minimization for the evaluation of a large number of tensor contractions. A possible application is the efficient evaluation of correlation functions in lattice QCD calculations, where a reduction of computational complexity by an order of magnitude is achieved
    Data Types:
    • Software/Code
  • This package is a set of tools in the Python language for preprocessing GPS trajectory data gathered from consumer devices, to detect and flag potentially erroneous data.
    Data Types:
    • Software/Code
  • H2OI95 is a stand-alone Fortran code for evaluating the IAPWS-95 equation-of-state model (Wagner and Pruss, 2002) for the thermodynamic properties of water. It further evaluates the corresponding thermochemical properties of water consistent with the CODATA recommendations (Cox et al., 1989). The IAPWS-95 model is based on a model equation for the dimensionless Helmholtz energy for which the primary variables are the inverse reduced temperature and reduced density. Here is the absolute temperature (K), is density (kg/m3), and the subscript refers to the critical point of water (647.096 K and 22.064 MPa pressure in this model, for which is 322 kg/m3). The code solves four basic types of problems, distinguished by the specified inputs: 1, Temperature (K) and density (kg/m3) or reduced density 2. Temperature (K) and pressure (MPa). 3. Temperature (K) on the saturation (liquid-vapor equilibrium) curve 4. Pressure (MPa) on the saturation curve Each type of problem is run using a corresponding input (text) file. All but the first type of problem require iteration. For example, to solve for desired temperature and pressure, the reduced density must be adjusted to give the desired pressure. Iteration is accomplished using the Newton-Raphson method, though the secant method is also used in solving the fourth type of problem. H2OI95 has been used to conduct numerical studies of convergence and the problem of multiple numerical solutions, only some of which correspond to valid results. Obtaining valid results depends mainly on appropriate choice of starting values. The default values in H2OI95 appear to consistently lead to generally desired results. With modification (not addressed here), H2OI95 can be used to support SUPCRT92 (Johnson et al., 1992) and similar codes that compute chemical thermodynamic properties of species and reactions over a wide range of temperature and pressure (273.16-1273K and 0-1000 MPa).
    Data Types:
    • Software/Code
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