cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6075/j08p5xwj
title: HDSS RR1413 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Port of departure: Apra, Guam Port of arrival: Apra, Guam The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
description: Cruise type: NOAA VENTS: Submarine Ring of Fire 2014 (Ironman) Vessel ID: Roger Revelle Call sign: KAOU
DOI: 10.6075/j0df6pm8
title: HDSS RR1411 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Port of departure: Chi-Lung, Taiwan Port of arrival: Apra, Guam The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
description: Cruise type: Transit Vessel ID: Roger Revelle Call sign: KAOU
DOI: 10.6075/j0j67fb0
title: HDSS RR1407 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Cruise type: Air Sea Interaction in Northern Indian Ocean Vessel ID: Roger Revelle Call sign: KAOU
description: Port of departure: Trincomalee, Sri Lanka Port of arrival: Trincomalee, Sri Lanka The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
DOI: 10.6075/j0nz862d
title: HDSS RR1405 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Port of departure: Chennai, India Port of arrival: Chennai, India The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
description: Cruise type: Air-Sea Interactions in the Northern Indian Ocean (ASIRI) Vessel ID: Roger Revelle Call sign: KAOU
DOI: 10.6075/j06q1vns
title: HDSS RR1607 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Port of departure: Palau, Republic of Palau Port of arrival: Palau, Republic of Palau The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
description: Cruise type: Flow Encountering Abrupt Topography Vessel ID: Roger Revelle Call sign: KAOU
DOI: 10.6075/j0bg2mch
title: HDSS RR1606 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Cruise type: Flow Encountering Abrupt Topography Vessel ID: Roger Revelle Call sign: KAOU
description: Port of departure: Palau, Republic of Palau Port of arrival: Palau, Republic of Palau The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
DOI: 10.6075/j0g73c2s
title: HDSS RR1605 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Port of departure: Phuket, Thailand Port of arrival: Palau, Republic of Palau The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
description: Cruise type: Multibeam survey with closely repeating ship tracks at a speed of 6 knots Vessel ID: Roger Revelle Call sign: KAOU
DOI: 10.6075/j0m043s3
title: HDSS RR1604 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Cruise type: Global Ocean Repeat Hydrography, Carbon, and Tracer Measurements Vessel ID: Roger Revelle Call sign: KAOU
description: Port of departure: Fremantle, Australia Port of arrival: Phuket, Thailand The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
DOI: 10.6075/j0qr4vh4
title: HDSS RR1603 Cruise Data. In Hydrographic Doppler Sonar System (HDSS): Acoustic ocean current profiling data from the R/V Revelle

description: Cruise type: GO-SHIP/Climate Variability and Predictability (CLIVAR) I08S Vessel ID: Roger Revelle Call sign: KAOU
description: Port of departure: Fremantle, Australia Port of arrival: Fremantle, Australia The Hydrographic Doppler Sonar System (HDSS) on the R/V Revelle provides profiles of absolute ocean current and acoustic scattering strength in support of scientific operations. The HDSS consists of a 50 kHz Doppler sonar which returns data in a depth range between 20 m and 700-1100 m (depending on conditions), and a 140 kHz Doppler sonar which returns data in a depth range between 20 m and 150-350 m (depending on conditions). The system was created to provide measurements with higher depth resolution than is available from commercial Doppler sonars. Both the acoustic pulse length and the angular width of an acoustic beam affect depth resolution. HDSS uses large transducers to get narrower beams and greater power to get greater range without sacrificing vertical resolution. Just as ocean bathymetry is routinely collected from research vessels, the HDSS has the parallel tasks of monitoring ocean currents and acoustic scattering wherever the R/V Revelle sails, while simultaneously supporting individual science missions. The established policy is to have the system running and recording data at all times that the ship is underway, unless restricted by political regulation or acoustic interference.
DOI: 10.6075/j0b858b0
title: X-Yield: A Multi-Fidelity Yield Strength Dataset for Refractory High Entropy Alloys. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative

description: The created data is a yield strength prediction for all ternary-septenary alloys from the Al-Cr-Fe-Hf-Mo-Nb-Ta-Ti-V-W-Zr element family. The yield strength was predicted in 1% composition increments for ternary and quaternary alloys and in 5% increments for quinary, senary, and septenary alloys. Each prediction was done at temperatures between 300 - 2500 K in 100 K increments. This data was generated with an in-house code based on the yield strength prediction model introduced by Maresca and Curtin (https://doi.org/10.1016/j.actamat.2019.10.015). The collected data contains 334 experimental yield strength measurements from the public open-source database, Citrine MPEA database (https://citrination.com/datasets/190954/show_search?searchMatchOption=fuzzyMatch), which is described in this publication (https://doi.org/10.1038/s41597-020-00768-9). All data consisting of a yield strength measurement that was taken at or above room temperature from an alloy in the 11 element family that has a body centered cubic (BCC) structure was extracted. For each extracted experimental point, a simulated prediction was generated for comparison using the referenced model.
DOI: 10.6075/j0gm87g6
title: Physically simulated x-ray CT data of additively manufactured octet lattice structures with common defects. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative

description: The datasets are simulations, containing input and output models of x-ray CT simulations showing additively manufactured lattice structures with common defects. There are in total seven datasets, each one has an input file (CAD triangle mesh model in *.obj format) and an output file (a 3D numpy array, in *.npy format, where each value corresponds to an x-ray CT density value). The input files were created using Blender (https://www.blender.org/), and five defects were manually inserted (bent strut, broken strut, missing strut, thin strut, dross defect). The output files are simulations created using LTT (https://ipo.llnl.gov/technologies/it-and-communications/livermore-tomography-tools-ltt).
DOI: 10.6075/j0hm58mk
title: Partial Differential Equations (PDE) and Solutions: Darcy Flow, Convection-Diffusion, Poisson Problems. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative

description: The datasets are in .npz format and can be accessed in your Python program with `numpy.load` module or with a desktop viewer [npzviewer](https://pypi.org/project/npzviewer/).
description: These data represent inputs and solutions to Darcy flow, convection-diffusion, and Poisson problems over 2D square domains. Scripts to generate the datasets are included. Convection-Diffusion and Poisson Dataset These two datasets contain 10,000 steady-state convection-diffusion and pure diffusion problems, respectively, on the 2-D unit square. The problems were discretized by finite element methods (FEM) using [1,2,4]. The input data include the (convection-) diffusion coefficients, mesh point coordinates and heat source (the right-hand sides of the equations). The target data are the numerical solutions obtained by using [3] and the flux of the heat. * [1] FEniCS open source PDE solver https://fenicsproject.org/ * [2] DOLFIN C++/Python interface of FEniCS https://pypi.org/project/DOLFIN/ * [3] Numpy open-source Python library https://numpy.org/ * [4] Sympy open-source Python library https://www.sympy.org/en/index.html Darcy Flow Data This dataset contains finite element solutions of the Darcy Flow equation. Numerical simulations were performed using tools developed in ParELAG[4], a parallel C++ library for performing numerical upscaling of finite element discretizations and AMG techniques, and ParELAGMC [5], a parallel element agglomeration MLMC library. These libraries use MFEM [3] to generate the fine grid finite element discretization and HYPRE [2] to handle massively parallel linear algebra. * [1] GLVis: Opengl finite element visualization tool. glvis.org. * [2] HYPRE: High performance preconditioners. http://www.llnl.gov/CASC/hypre/. * [3] MFEM: Modular finite element methods library. mfem.org. * [4] ParELAG: Element-agglomeration algebraic multigrid and upscaling library, version 2.0. http://github.com/LLNL/parelag, 2015. * [5] ParELAGMC: Parallel element agglomeration multilevel Monte Carlo library. http://github.com/LLNL/parelagmc, 2018.
DOI: 10.6075/j0765fg7
title: LLNL D4DCT Datasets: Dynamic 4DCT Datasets using MPM-based Deformation, 256^3 volume resolution. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative

description: Dynamic computed tomography (DCT) refers to reconstruction of moving or non-rigid objects over time while x-ray projections are acquired over a range of angles. The measured x-ray sinogram data represents a time-varying sequence of dynamic scenes, where a small angular range of the sinogram will correspond to a static or quasi-static scene, depending on the amount of motion or deformation as well as the system setup. The reconstruction of DCT is widely applicable to the study of object deformation and dynamics in a number of industrial and clinical applications (e.g., heart CT). In the material science and additive manufacturing applications, the DCT capabilities aid in the study of damage evolution due to dynamic thermal loads and mechanical stresses over time which provides crucial information about their overall performance and safety. We provide two dynamic CT datasets (D4DCT-DFM, D4DCT-AFN) where the sinogram data represent a time-varying object deformation to demonstrate damage evolution due to several mechanical stresses (compression). The provided datasets enable training and evaluation of the data driven machine learning methods for DCT reconstruction. To build the datasets, we used Material Point Method (MPM)-based methods to simulate deformation of objects under mechanical loading, and then simulated CT sinogram data using Livermore Tomography Tools (LTT).
DOI: 10.6075/j0862dz8
title: Hurricane Dataset for Deep-Hurricane-Tracker model. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative

description: We use 20-year-long records from 1996 to 2015 of Community Atmospheric Model v5 (CAM5) dataset. It contains snapshots of the global atmospheric states for every three hours (1 timestep = 3 hours). Each snapshot contains multiple physical variables among which we use the six most important climate variables to define hurricane from scientific literature, such as PSL (Sea level pressure), U850 (Zonal wind), V850 (Meridional wind), PRECT (Precipitation), TS (Surface temperature), QREFHT (Reference high humidity) by order. From global scaled CAM5 reanalysis data, we only used data for the region around the Northern hemisphere which is 180 degree to 340 degree longitude and 0 degree to 60 degree latitude. For the purpose of training proposed tracking model, we fixed time length as 10 (which is 30 hours long). The input image size is 128 times 257 pixels with around 0.50 degree (around 50.0 km) resolution. Basically, the file contains multiple spatio-temporal hurricane data (video) channeled by 6 climate variables with time length 10. All climate variables are normalized between 0 and 1 accordingly (each channel has max value as 1 and min value as 0).
DOI: 10.6075/j0c24wmw
title: Derived Products from HCP-YA fMRI. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative

description: All subject data from the Human Connectome Project- Young Adult (HCP-YA) dataset were processed. This release contains timeseries parcellated using the Schaefer parcellation at resolutions ranging from 100 to 900 parcels. The fMRI data contain resting state and task data for both LR and RL polarity. For the resting state data, we use a bandpass filter of .009 Hz - 0.08 Hz and 0.009 Hz - 0.25 Hz for task data. This release contains outputs with and without Global Signal Regression (GSR). In addition to the timeseries data, we also include correlation connectome matrices for both GSR and non-GSR.
DOI: 10.6075/j0sn094n
title: Dataset of Simulated Intracardiac Transmembrane Voltage Recordings and ECG Signals. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative

description: The dataset consists of pairs of computationally simulated intracardiac transmembrane voltage recordings and ECG signals. In total, 16140 organ-level simulations were conducted to create this dataset, using a range of cardiac geometries and physiological parameters. Simulations were performed at LLNL's Lassen supercomputer, concurrently utilizing 4 GPUs and 40 CPU cores. Each simulation produced pairs of 500ms-by-10 ECG signals and 500ms-by-75 transmembrane voltage signals. For convenience, the signals are concatenated and saved as matrices. Each of these matrices is then stored as a numpy array. See the documentation for further details.