The dataset contains bulk sedimentary d15N, TOC, and TN data measured every 2 mm on the core SPR0901-03KC. Flood and turbidite layers are shaded with blue and orange in the files. and This work is supported by NSF OCE-1304327.
GOES_flare_list: contains a list of more than 10,000 flare events. The list has 6 columns, flare classification, active region number, date, start time end time, emission peak time, GOES_B_flare_list: contains time series data of SDO/HMI SHARP parameters for B class solar flares
, GOES_MX_flare_list: contains time series data of SDO/HMI SHARP parameters for M and X class solar flares, SHARP_B_flare_data_300.hdf5 and SHARP_MX_flare_data_300.hdf5 files contain time series more than 20 physical variables derived from the SDO/HMI SHARP data files. These data are saved at a 12 minute cadence and are used to train the LSTM model., and B_HARPs_CNNencoded_part_xxx.hdf5 and M_X HARPs_CNNencoded_part_xxx.hdf5 include neural network encoded features derived from vector magnetogram images derived from the Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager (HMI). These data files typically contains one or two sequences of magnetograms covering an active region for a period of 24h with a 1 hour cadence. We encode each magnetogram with frames of a fixed size of 8x16 with 512 channels.
The modeling research conducted to produce this dataset focuses on the solar wind dynamic pressure drop events and how they affect the Earth's intrinsically coupled Magnetosphere, Ionosphere and Thermosphere systems. This study specifically focuses on the 11 June 2017 event, where the solar wind dynamic pressure dropped significantly following a period of higher pressure. We model the response to this pressure drop using University of Michigan Space Weather Modeling Framework ( http://csem.engin.umich.edu/tools/swmf/). The simulation results were created using BATS-R-US and GITM models. The observational data required for model comparisons were taken from OMNI ( https://omniweb.gsfc.nasa.gov) and CDAWeb ( https://cdaweb.gsfc.nasa.gov/sp_phys/) Databases.
The Liquid Metal Battery (LMB), a promising energy-storage device that contains liquid-metal interior, is studied numerically in the paper. The metal pad roll instability was modeled based on the open-source CFD software, OpenFOAM. It's based on the solver for simulations of incompressible multiphase flows multiphaseInterFoam modified to include the electromagnetic fields and account for the sharp variations of the electrical conductivity.