Input-Output Dataset for Physics-inspired Artificial Neural Network for Dynamic Systemhttps://doi.org/10.18419/darus-633Praditia, TimothyDaRUS2020-07-212020-07-21T10:28:12ZThis dataset contains two .mat files, one pre-processed (direct simulation results) and the other one is with added noise. The simulated problem is a thermochemical energy storage problem using CaO/Ca(OH)2 as the material choice. This dataset is used as input-output data pairs necessary for training, validating, and testing the ANN. The input data consist of CaO density, Ca(OH)2 density, CaO specific heat capacity, Ca(OH)2, porosity, permeability, reaction rate constant, initial and outlet pressure, initial temperature, inlet temperature, N2 molar inflow rate, H2O molar inflow rate, and specific reaction enthalpy. The output data consist of pressure, temperature, CaO volume fraction, and H2O molar fraction. Additionally, there is an automated script file for the DuMuX run.Computer and Information ScienceEarth and Environmental SciencesThermochemical Energy StoragePorous medium flowPraditia, T., Walser, T., Oladyshkin, S. and Nowak, W.: Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. Energies 20202020-07-21Praditia, TimothyWalser, ThiloOladyshkin, SergeyNowak, Wolfgang2020-02-07Praditia, T. (2020): Trained ANN Parameters for Physics-inspired Artificial Neural Network for Dynamic System, <a href="https://doi.org/10.18419/darus-634">doi: 10.18419/darus-634</a>, DaRUS.CC BY 4.0