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- Creator:
- Towne, Aaron
- Description:
- This database contains six datasets intended to aid in the conception, training, demonstration, evaluation, and comparison of reduced-complexity models for fluid mechanics. The six datasets are: large-eddy-simulation data for a turbulent jet, direct-numerical-simulation data for a zero-pressure-gradient turbulent boundary layer, particle-image-velocimetry data for the same boundary layer, direct-numerical-simulation data for laminar stationary and pitching flat-plate airfoils, particle-image-velocimetry and force data for an airfoil encountering a gust, and large-eddy-simulation data for the separated, turbulent flow over an airfoil. All data are stored within hdf5 files, and each dataset additionally contains a README file and a Matlab script showing how the data can be read and manipulated. Since all datafiles use the hdf5 format, they can alternatively be read within virtually any other programing environment. An example.zip file included for each dataset provides an entry point for users. The database is an initiative of the AIAA Discussion Group on Reduced-Complexity Modeling and is detailed in the paper listed below. For each dataset, the paper introduces the flow setup and computational or experimental methods, describes the available data, and provide an example of how these data can be used for reduced-complexity modeling. All users should cite this paper as well as appropriate primary sources contained therein. Towne, A., Dawson, S., Brès, G. A., Lozano-Durán, A., Saxton-Fox, T., Parthasarthy, A., Biler, H., Jones, A. R., Yeh, C.-A., Patel, H., Taira, K. (2022). A database for reduced-complexity modeling of fluid flows. AIAA Journal 61(7): 2867-2892.
- Keyword:
- fluid dynamics, reduced-complexity models, and data-driven models
- Discipline:
- Engineering and Science
6Works -
Biologically Inspired Robotics and Dynamical Systems (BIRDS) Lab
User Collection- Creator:
- Revzen, Shai
- Description:
- Professor Revzen and his team at the Biologically Inspired Robotics and Dynamical Systems (BIRDS) Lab are working on discovering, modeling, and reproducing the strategies animals use when interacting with physical objects. This work consists of collaboration with biomechanists to analyze experimental data, developing new mathematical tools for modeling and estimation of model parameters, and construction of robots which employ the new principles.
- Discipline:
- Science
7Works -
CT Data of UMMP VP 68409, Plesiadapis gingerichi (holotype)
User Collection- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Five CT scans of dental elements (see metadata for individual scans for additional information)
- Discipline:
- Science
5Works -
Defect patterns on the curved surface of fish retinae suggest a mechanism of cone mosaic formation
User Collection- Creator:
- Nunley, Hayden, Nagashima, Mikiko, Martin, Kamirah, Lorenzo Gonzalez, Alcides, Suzuki, Sachihiro C., Norton, Declan A., Wong, Rachel O. L., Raymond, Pamela A., and Lubensky, David K.
- Description:
- The outer epithelial layer of zebrafish retinae contains a crystalline array of cone photoreceptors, called the cone mosaic. As this mosaic grows by mitotic addition of new photoreceptors at the rim of the hemispheric retina, topological defects, called “Y-Junctions”, form to maintain approximately constant cell spacing. The generation of topological defects due to growth on a curved surface is a distinct feature of the cone mosaic not seen in other well-studied biological patterns like the R8 photoreceptor array in the _ Drosophila compound eye. Since defects can provide insight into cell-cell interactions responsible for pattern formation, here we characterize the arrangement of cones in individual Y-Junction cores (see Set of images for Figures 1 and 2 and 6 and Supplementary Figure 7) as well as the spatial distribution of Y-junctions across entire retinae (see Dataset for analyzing spatial distribution of Y-junctions in flat-mounted retinae). We find that for individual Y-junctions, the distribution of cones near the core corresponds closely to structures observed in physical crystals (see Set of images for Figures 1 and 2 and 6 and Supplementary Figure 7). In addition, Y-Junctions are organized into lines, called grain boundaries, from the retinal center to the periphery (see Dataset for analyzing spatial distribution of Y-junctions in flat-mounted retinae and Dataset for measuring tendency of Y-junctions to line up into grain boundaries during incorporation into retinae). In physical crystals, regardless of the initial distribution of defects, defects can coalesce into grain boundaries via the mobility of individual particles. By imaging in live fish, we demonstrate that grain boundaries in the cone mosaic instead appear during initial mosaic formation, without requiring defect motion (see Dataset for measuring tendency of Y-junctions to line up into grain boundaries during incorporation into retinae and Dataset for analyzing Y-junction motion in live fish retinae). Motivated by this observation, we show that a computational model of repulsive cell-cell interactions generates a mosaic with grain boundaries (see Code and example simulations of phase-field crystal model (for cone mosaic formation)). In contrast to paradigmatic models of fate specification in mostly motionless cell packings (see Code and accompanying input data for simulating lateral inhibition on motionless cell packing), this finding emphasizes the role of cell motion, guided by cell-cell interactions during differentiation, in forming biological crystals. Such a route to the formation of regular patterns may be especially valuable in situations, like growth on a curved surface, where the resulting long-ranged, elastic, effective interactions between defects can help to group them into grain boundaries.
- Keyword:
- zebrafish cone mosaic, lattice vectors, topological defects, tissue patterning, grain boundaries, lateral inhibition, photoconversion, phase-field crystal model, and defect motion
- Discipline:
- Science
7Works -
Division of Birds
User Collection- Creator:
- University of Michigan Museum of Zoology
- Description:
- University of Michigan Museum of Zoology Division of Birds
- Discipline:
- Science
1Works -
Division of Fishes
User Collection- Creator:
- University of Michigan Museum of Zoology
- Description:
- Division of Fishes
- Discipline:
- Science
48Works -
Division of Mammals
User Collection- Creator:
- University of Michigan Museum of Zoology
- Description:
- The Division of Mammals at the Museum of Zoology was established in 1837, and has grown steadily to its current size, with over 150,000 specimens. An important feature of the mammal collection at the Museum of Zoology is our emphasis on non-traditional specimens.
- Discipline:
- Science
310Works -
Division of Reptiles and Amphibians
User Collection- Creator:
- University of Michigan Museum of Zoology
- Description:
- The Division of Reptiles and Amphibians maintains a collection that is worldwide in scope. The research collections contain over 200,000 catalogued lots representing approximately 435,000 individual specimens.
- Discipline:
- Science
13Works -
Estimates of the water balance of the Laurentian Great Lakes using the Large Lakes Statistical Water Balance Model (L2SWBM)
User Collection- Creator:
- Smith, Joeseph P., Fry, Lauren M., Do, Hong X., and Gronewold, Andrew D.
- Description:
- This collection contains estimates of the water balance of the Laurentian Great Lakes that were produced by the Large Lakes Statistical Water Balance Model (L2SWBM). Each data set has a different configuration and was used as the supplementary for a published peer-reviewed article (see "Citations to related material" section in the metadata of individual data sets). The key variables that were estimated by the L2SWBM are (1) over-lake precipitation, (2) over-lake evaporation, (3) lateral runoff, (4) connecting-channel outflows, (5) diversions, and (6) predictive changes in lake storage. and Contact: Andrew Gronewold Office: 4040 Dana Phone: (734) 764-6286 Email: drewgron@umich.edu
- Keyword:
- Great Lakes water levels, statistical inference, water balance, data assimilation, Great Lakes, Laurentian, Machine learning, Bayesian, and Network
- Citation to related publication:
- Smith, J. P., & Gronewold, A. D. (2017). Development and analysis of a Bayesian water balance model for large lake systems. arXiv preprint arXiv:1710.10161., Gronewold, A. D., Smith, J. P., Read, L., & Crooks, J. L. (2020). Reconciling the water balance of large lake systems. Advances in Water Resources, 103505., and Do, H.X., Smith, J., Fry, L.M., and Gronewold, A.D., Seventy-year long record of monthly water balance estimates for Earth’s largest lake system (under revision)
- Discipline:
- Science and Engineering
5Works -
F3UEL: Flaring & Fossil Fuels: Uncovering Emissions & Losses
User Collection- Creator:
- Kort, Eric and Plant, Genevieve
- Description:
- Fossil energy production, processing, flaring, and transmission all can harm climate and air quality by emitting greenhouse gases and air pollutants. Studies now show that onshore oil and gas production emit much more methane than what is inventoried, and that local air quality impacts can be significant, however, natural gas flaring and offshore systems have been largely overlooked. The F3UEL (Flaring & Fossil Fuels: Uncovering Emissions & Losses) project aims to address these gaps by improving our understanding of offshore emissions, characterizing how flares behave in the real world, identifying what portion of the offshore system is responsible for emissions, and determining how such systems can be monitored. Spanning three years (2020-2022), the project employed an aircraft platform to measure including both greenhouse gas and air quality measurements. To sample the largest regions of current and potential future offshore production and flaring, airborne measurements targeted the Gulf of Mexico, offshore California and Alaska, the Bakken Formation (North Dakota) and the Permian and Eagle Ford Basins (Texas). Data provided here includes the airborne measurements collected using Scientific Aviation’s Mooney aircraft platform, equipped with spectroscopic instrumentation to measure methane, carbon dioxide, water vapor, nitrous oxide, and nitrogen oxide, in addition to meteorological variables such as wind speed and direction. Data products from our analysis of these airborne measurements are also provided, including estimated flare destruction removal efficiency for the Bakken, Eagle Ford, and Permian basins. Each data file is in .csv format and is accompanied by a readme file with further information and descriptors of the variables included. All users should cite the papers and datasets provided in the readme files for each individual dataset. Website: https://graham.umich.edu/f3uel This project is funded by the Alfred P. Sloan Foundation with additional support from the Environmental Defense Fund, Scientific Aviation, and University of Michigan (College of Engineering, Climate and Space Sciences and Engineering; Graham Sustainability Institute).
- Keyword:
- offshore oil & gas, flaring, methane, Nitrogen oxides, natural gas flaring, and oil & gas
- Discipline:
- Science
4Works
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