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  • [Updated] 2D Benchmark Reacting Flow Dataset for Reduced Order Modeling Exploration

    Creator:
    Huang, Cheng MI
    Description:
    A 2D planar representation of a generic laboratory-scale combustor is established to assess the capabilities of ROMs for representing realistic combustion flowfields. The purpose of this dataset is to provide a testbed to build reduced model for relevant challenging reacting flow problems using different methods. The dataset was generated under the Air Force Center of Excellence on Multi-Fidelity Modeling of Rocket Combustion Dynamics and the goal of the center is to advance the state-of-the-art in Reduced Order Models (ROMs) and enable efficient prediction of instabilities in liquid fueled rocket combustion systems. Instrument and/or Software specifications: - recommendation: Matlab and Tecplot 1. Data_150000to159999.tar: the unsteady flow field data from time step 150000 to 159999 (time increment, dt, between each time step is 1E-7 sec). 2. Data_160000to169999.tar: the unsteady flow field data from time step 160000 to 169999 (time increment, dt, between each time step is 1E-7 sec). 3. Data_170000to179999.tar: the unsteady flow field data from time step 170000 to 179999 (time increment, dt, between each time step is 1E-7 sec). 4. Data_180000to189999.tar: the unsteady flow field data from time step 180000 to 189999 (time increment, dt, between each time step is 1E-7 sec). 5. Data_190000to199999.tar: the unsteady flow field data from time step 190000 to 199999 (time increment, dt, between each time step is 1E-7 sec). 6. Data_200000to209999.tar: the unsteady flow field data from time step 200000 to 209999 (time increment, dt, between each time step is 1E-7 sec). 7. Data_210000to219999.tar: the unsteady flow field data from time step 210000 to 219999 (time increment, dt, between each time step is 1E-7 sec). 8. Data_220000to229999.tar: the unsteady flow field data from time step 220000 to 229999 (time increment, dt, between each time step is 1E-7 sec). 9. grid.dat: the topology of the CFD mesh used to generate this data (can be directly loaded in Tecplot). 10. the file "sample_code.zip" contains the sample Matlab scripts to load and output the .dat files to help the researchers to get started. To run the script, the software Matlab is required and the researchers can simply run sampleIO.m script in Matlab to test the code. Detailed documentation of how the data is generated can be found in:  https://afcoe.engin.umich.edu/benchmark-data
    Citation to related publication:
    Huang, C., Duraisamy, K., and Merkle, C.L., Investigations and Improvement of Robustness of Reduced-Order Models of Reacting Flow, AIAA Journal, 2019., Swischuk, R., Kramer, B., Huang, C., and Willcox, K., Learning Physics-Based Reduced-Order Models for a Single-Injector Combustion Process , AIAA Journal, 2020., and Harvazinski, M.E., Huang, C., Sankaran, V., Feldman, T.W., Anderson, W.E., Merkle, C.L., and Talley, D.G., Coupling between hydrodynamics, acoustics, and heat release in a self-excited unstable combustor, Physics of Fluids, 2015.
    Discipline:
    Engineering
    Title:
    [Updated] 2D Benchmark Reacting Flow Dataset for Reduced Order Modeling Exploration

  • Hierarchical Test Problems for Reduced Order Modeling Exploration

    User Collection
    Creator:
    Huang, Cheng MI
    Description:
    This collection contains a hierarchy of test problems for turbulent reacting flow simulations. It is meant to provide a testbed to build reduced model for relevant challenging reacting flow problems using different methods. In addition, this collection also serves to engage a broad community of experts in computational science and the field of engineering to address certain challenges in constructing reduced models for reacting flow simulations. All the datasets in this collection were generated under the Air Force Center of Excellence on Multi-Fidelity Modeling of Rocket Combustion Dynamics and the goal of the center is to advance the state-of-the-art in Reduced Order Models (ROMs) and enable efficient and accurate prediction of instabilities in liquid fueled rocket combustion systems.
    Discipline:
    Engineering
    2Works

  • .stl file of Circle of Willis Benchmark geometric model for hemodynamic simulation software

    Creator:
    Figueroa, C. Alberto
    Description:
    This .stl file represents the largest vessels of the cerebral circulation, specifically around the Circle of Willis. The file was created from a Computed Tomography Angiography (CTA) of a relatively healthy patient. It consisted of a 512 x 512 x 709 voxel image with a resolution of 0:35 mm x 0:35 mm x 0:5 mm. The model includes the basilar artery (1), left and right internal carotid arteries (2, and 3), left and right anterior cerebral arteries (4, and 5), left and right middle cerebral arteries (6, and 7), left and right posterior cerebral arteries (8, and 9), and various communicating arteries (10, 11, and 12).
    Keyword:
    Circle of Willis, Blood flow simulation, Hemodynamics, and Benchmarking blood flow
    Citation to related publication:
    N. Wilson, K. Wang, R. Dutton, C.A. Taylor, "A software framework for creating patient specific geometric models from medical imaging data for simulation based medical planning of vascular surgery", Medical Image Computing and Computer-Assisted Intervention MICCAI 2001, Springer, 2001, pp. 449–456. doi: 10.1007/3-540-45468-3_54 and N. Xiao, J.D. Humphrey, C.A. Figueroa, "Multi-Scale Computational Model of Three-Dimensional Hemodynamics within a Deformable Full-Body Arterial Network”, Journal of Computational Physics, 2013, Vol 244, pp. 22-40. doi: 10.1016/j.jcp.2012.09.016
    Discipline:
    Engineering and Health Sciences
    Title:
    .stl file of Circle of Willis Benchmark geometric model for hemodynamic simulation software

  • Topological transitions of spiral eutectics

    Creator:
    Moniri, Saman and Shahani, Ashwin J.
    Description:
    The data is comprised of 20 .hdf files of the X-ray projections recorded during isothermal annealing of Zn-Mg samples, at discrete time-steps shown below for files names ending in ‘...30141’ to ‘…30161’: 30141: prior to annealing; 30142: 1 min annealing; 30143: 3 min; 30144: 5 min; 30145: 7 min; 30146: 10 min; 30147: 15 min; 30148: 20 min; 30150: 31 min; 30151: 1 hr; 30152: 2 hr; 30153: 3 hr; 30154: 4 hr; 30155: 5 hr; 30156: 6 hr; 30157:7 hr; 30158: 8 hr; 30159:9 hr; 30160: 9 hr, 10 min; 30161: 10 hr The raw data file is in .hdf format and can be reconstructed into .tiff, e.g., by using the TomoPy toolbox in Python.
    Keyword:
    Spiral eutectics
    Discipline:
    Engineering
    Title:
    Topological transitions of spiral eutectics

  • Small Female Pelvis Geometry Model

    Creator:
    University of Michigan Transportation Research Institute, Rupp, Jonathan D., Klein, Katelyn F., and Reed, Matthew P.
    Description:
    The files include an Excel file with the x-, y-, and z- coordinates that make up the nodal coordinates for a surface model of small (5th percentle) female pelvis geometry, the finite element model (.k file) that represents the nodal coordinates, and two surface files that represent the geometry (.obj and .ply).
    Citation to related publication:
    Katelyn F. Klein, Matthew P. Reed, and Jonathan D. Rupp. "Development of Geometric Specifications for the Pelvis of a Small Female Anthropomorphic Test Device." IRCOBI Conference 2016, IRC-16-79.  http://www.ircobi.org/wordpress/downloads/irc16/pdf-files/79.pdf
    Discipline:
    Engineering
    Title:
    Small Female Pelvis Geometry Model

  • Data for "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model"

    Creator:
    Fries, Kevin J
    Description:
    This data is in support of the publication in review "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model". It is all the raw data extracted from the NWM flow forecasts for Iowa and the IFIS stage readings. For the NWM data, each date has it's own tab-delimited file with columns being the time (hrs) and rows being the NHD site. For the IFIS gages, each tab delimited file is for a single site for the period of record.
    Citation to related publication:
    Fries, K. J., & Kerkez, B. (2018). Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the national water model. Water Resources Research, 54, 5636-5653.  https://doi.org/10.1029/2017WR022498
    Discipline:
    Engineering
    Title:
    Data for "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model"

  • A Simple Method for Correcting Empirical Model Densities during Geomagnetic Storms Using Satellite Orbit Data

    Creator:
    Brandt, Daniel, A., Bussy-Virat, Charles, D., and Ridley, Aaron, J.
    Description:
    The Multifaceted Optimization Algorithm (MOA) is a tool for generating corrected empirical model thermospheric densities during geomagnetic storms. It consists of a suite of Python functions that operate around the Spacecraft Orbit Characterization Kit (SpOCK), an orbital propagator developed by Charles D. Bussy-Virat, PhD, Joel Getchius, and Aaron J. Ridley, PhD at the University of Michigan, and it estimates new densities for the NRLMSISE-00 atmospheric model. MOA generates new model densities by estimating modifications to inputs to the NLRMSISE-00 model that minimize the orbit error between modeled spacecraft in SpOCK, and their actual altitudes as described in publicly-available Two-Line Element Sets (TLEs), made available online via Space-track.org. MOA consists of three sub-process: (1) The Area Optimization Algorithm (AROPT), (2) the F10.7 Optimization Algorithm (FOPT), and (3) the Ap Optimization Algorithm (APOPT). AROPT computes the contribution to the drag of the modeled spacecraft due to their varying projected area. FOPT estimates modifications to the 10.7 cm solar radio flux in NRLMSISE-00, and APOPT estimates modifications to the Earth's magnetic activity in NRLMSISE-00. MOA finds these modifications across many spacecraft, and the medians of those modifications are then applied in NLRMSISE-00 along the orbit of another satellite to generate new densities for verification. In this instance, modifications are applied along the orbits of the Swarm spacecraft and compared to Swarm GPS-derived densities.
    Keyword:
    Orbit, Satellite, Two-line Element Set, Thermosphere, and Drag
    Discipline:
    Engineering
    Title:
    A Simple Method for Correcting Empirical Model Densities during Geomagnetic Storms Using Satellite Orbit Data

  • Dataset for 'Multi‑Step Crystallization of Self‑Organized Spiral Eutectics'

    Creator:
    Moniri, Saman, Bale, Hrishikesh , Volkenandt, Tobias, Wang, Yeqing, Gao, Jianrong, Lu, Tianxian, Sun, Kai, and Shahani, Ashwin J.
    Description:
    The data file contains (1) the grayscale images of the nano-tomography experiments that can be segmented into binary images and visualized to show the 3D morphology of spiral eutectics; and (2) crystallographic orientation maps of serial-sectioned sample, which can be processed in a variety of EBSD software packages.
    Keyword:
    crystallization, chirality, self-organization, and spiral eutectics
    Citation to related publication:
    Moniri, S., Bale, H., Volkenandt, T., Wang, Y., Gao, J., Lu, T., Sun, K., Ritchie, R.O., & Shahani, A.J. (23 January 2020). Multi‐Step Crystallization of Self‐Organized Spiral Eutectics. Small (1906146).  https://doi.org/10.1002/smll.201906146
    Discipline:
    Engineering
    Title:
    Dataset for 'Multi‑Step Crystallization of Self‑Organized Spiral Eutectics'

  • Data for Solar Flare Intensity Prediction with Machine Learning Models

    Creator:
    Jiao, Zhenbang, Chen, Yang, and Manchester, Ward
    Description:
    GOES_flare_list: contains a list of more than 12,013 flare events. The list has 6 columns, flare classification, active region number, date, start time end time, emission peak time. SHARP_data.hdf5 files contain time series of 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.
    Keyword:
    Solar Flare Prediction and Machine Learning
    Citation to related publication:
    Jiao, Z., Sun, H., Wang, X., Manchester, W., Gombosi, T., Hero, A., Chen, Y., Solar Flare Intensity Prediction with Machine Learning Models, 2020, Space Weather Journal, in press
    Discipline:
    Science and Engineering
    Title:
    Data for Solar Flare Intensity Prediction with Machine Learning Models

  • A Simulated Wind-field Dataset for Testing Energy Efficient Path-Planning Algorithms for UAVs in Urban Environment

    Creator:
    Baskar, Deepika and Gorodetsky, Alex
    Description:
    Studying the effect of wind on urban air mobility typically requires comprehensive fluid dynamics simulations in a realistic urban geometry. Motivated to enable wide-spread autonomous drone activity in urban centers, such studies have indeed been considered by several authors in the recent literature. However, the accessibility of these approaches to those with less fluid dynamics experience and/or without access to purpose built simulation tools has limited validation and application of the resulting path planning strategies. and The .dat files contain the flow variables for each of the 402240 points sampled from the region under study. For flow visualization purposes, the .dat files are readable using Tecplot Software.
    Keyword:
    UAM, Energy efficient path planning , CFD, and City of Boston
    Citation to related publication:
    D. Baskar, A.A. Gorodetsky (2019). A Simulated Wind-field Dataset for Testing Energy Efficient Path-Planning Algorithms for UAVs in Urban Environment. Forthcoming.
    Discipline:
    Engineering and Other
    Title:
    A Simulated Wind-field Dataset for Testing Energy Efficient Path-Planning Algorithms for UAVs in Urban Environment