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- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/ , and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Smith, J., Gronewald, A. et al. Summary Report: Development of the Large Lake Statistical Water Balance Model for Constructing a New Historical Record of the Great Lakes Water Balance. Submitted to: The International Watersheds Initiative of the International Joint Commission. Accessible at https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf, Large Lake Statistical Water Balance Model (L2SWBM). https://www.glerl.noaa.gov/data/WaterBalanceModel/, and Gronewold, A.D., Smith, J.P., Read, L. and Crooks, J.L., 2020. Reconciling the water balance of large lake systems. Advances in Water Resources, p.103505.
- Discipline:
- Science and Engineering
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- Creator:
- Danforth, Shannon M.
- Description:
- This dataset includes three MATLAB data files for each subject: raw motion capture and force plate data, processed motion capture and force plate data, and sagittal-plane data segmented into individual trials labeled “nominal” or “tripped.” We include two example scripts for using the segmented trial data to tabulate trip recovery strategies across subjects and plot the sorted recovery strategies.
- Keyword:
- Trip recovery, Biomechanics, and Human locomotion
- Citation to related publication:
- S. M. Danforth, X. Liu, M. J. Ward, P.D. Holmes, and R. Vasudevan, "Predicting sagittal-plane swing hip kinematics in response to trips," IEEE Robotics and Automation Letters, 2022.
- Discipline:
- Engineering
-
- Creator:
- McSherry, Sean
- Description:
- This repository includes the analysis code and raw data for a paper titled "Nanophotonic control of thermal emission under extreme temperatures in air, " in Nature Nanotechnology (see citation). In our work, well defined structure-color effects guided the design of a nanostructure containing stratified layers of two oxides, magnesium oxide (MgO) and barium zirco-hafnate (BaZr0.5Hf0.5O3 or BZHO). The repeating layers were tuned in such a way to manipulate incident infrared wavelengths. The infrared is the spectral range in which heat (in the form of electromagnetic radiation) is emitted from objects. Therefore, the nanostructure serves as a way to alter the thermal emission spectrum of hot objects, controlling how much heat can flow. This can have significant impacts on a range of technologies, such as thermal photovoltaics (TPVs), which generate electricity from the infrared light emission of hot objects (compared to visible light emission from the sun in solar photovoltaics). We envision that our MgO/BZHO nanostructure can be paired with a thermal emitter in TPV systems to beneficially manipulate the flow of infrared light, leading to more efficient electricity production. To characterize the thermal stability of this structure, we had to characterize the thermal stability and optical performance at room temperature and at 1100 °C. This lead us to conduct several experiments using ellipsometry, TEM, EDS, and FTIR.
- Keyword:
- FTIR, Infrared, Photonic Crystal, MgO, Refractory , Ellipsometry, Spectroscopy, Superlattice, and Thermal Emission
- Citation to related publication:
- McSherry et al. Nature Nanotechnology (In Press). 2022
- Discipline:
- Engineering
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- 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:
- Baskar, D., & Gorodetsky, A. (2020). A Simulated Wind-field Dataset for Testing Energy Efficient Path-Planning Algorithms for UAVs in Urban Environment. In AIAA AVIATION 2020 FORUM. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2020-2920
- Discipline:
- Other and Engineering
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- Creator:
- Payam Mirshams Shahshahani
- Description:
- The two R codes are related to the feasible balance region calculations for Figures 2, 3, and 4 in the paper. The MATLAB codes are related to the simulations of the recoverable initial quasi-static states, the results of which are shown in Figure 5 of the paper.
- Keyword:
- One-legged balance, Biomechanics, Hip Abductor, and Unipedal Stance
- Citation to related publication:
- Shahshahani, P. M., & Ashton-Miller, J. A. (2020). On the importance of the hip abductors during a clinical one legged balance test: A theoretical study. PLOS ONE, 15(11), e0242454. https://doi.org/10.1371/journal.pone.0242454
- Discipline:
- Health Sciences and Engineering
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- Creator:
- Huffaker, Jordan S., Kummerfeld, Jonathan K., Lasecki, Walter S., and Ackerman, Mark S.
- Description:
- The following files include supplementary materials for our CHI 2020 paper "Crowdsourced Detection of Emotionally Manipulative Language". Namely, these materials include the dataset that was used in the evaluation. See the paper for more details.
- Keyword:
- Crowdsourcing, Media Manipulation, Rhetoric, and Emotion
- Citation to related publication:
- J.S. Huffaker, J.K. Kummerfeld, W.S. Lasecki, M.S. Ackerman. Crowdsourced Detection of Emotionally Manipulative Language. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2020). Honolulu, HI. 2020.
- Discipline:
- Engineering
-
- 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. (2020). Solar Flare Intensity Prediction With Machine Learning Models. Space Weather, 18(7), e2020SW002440. https://doi.org/10.1029/2020SW002440 and Chen, Y., & Manchester, W. (2019). Data and Data products for machine learning applied to solar flares [Data set], University of Michigan - Deep Blue. https://doi.org/10.7302/qnsq-cs38
- Discipline:
- Engineering and Science
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- Creator:
- BIRDS Lab U. Michigan
- Description:
- These data were produced for ARO W911NF-14-1-0573 "Morphologically Modulated Dynamics" and ARO MURI W911NF-17-1-0306 "From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems" to explore the trade-offs between various oscillator coupling models in modeling multilegged locomotion. The data were also used extensively in examining multi-contact slipping, in the studying the influence of number of legs on otherwise identical locomotion patterns, and in the use of geometric mechanics models for multilegged locomotion. Folder and file names encode the meta-data, with names following an informative naming convention documented in the README.
- Keyword:
- phase, multilegged, robot, and locomotion
- Citation to related publication:
- Zhao, D. & Revzen, S. Multi-legged steering and slipping with low DoF hexapod robots Bioinspiration & biomimetics, 2020, 15, 045001 https://doi.org/10.1088/1748-3190/ab84c0 and Zhao, D. Ph.D. Thesis "Locomotion of low-DOF multi-legged robots" University of Michigan 2021 https://deepblue.lib.umich.edu/handle/2027.42/169985
- Discipline:
- Science and Engineering
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- Creator:
- Arthurs, Christopher J., Khlebnikov, Rostislav, Melville, Alexander, Marčan, Marija, Gomez, Alberto, Dillon-Murphy, Desmond, Cuomo, Federica, Vieira, Miguel, Schollenberger, Jonas, Lynch, Sabrina, Tossas-Betancourt, Christopher, Iyer, Kritika, Hopper, Sara, Livingston, Elizabeth, Youssefi, Pouya, Noorani, Alia, Ben Ahmed, Sabrina, Nauta, Foeke J.N., van Bakel, Theodorus M.J., Ahmed, Yunus, van Bakel, Petrus A.J., Mynard, Jonathan, Di Achille, Paolo, Gharahi, Hamid, Lau, Kevin D., Filonova, Vasilina, Aguirre, Miquel, Nama, Nitesh, Xiao, Nan, Baek, Seungik, Garikipati, Krishna, Sahni, Onkar, Nordsletten, David, and Figueroa, Carlos A.
- Description:
- This repository contains the source code for the CRIMSON Flow Solver as required in the PLOS Computational Biology publication: CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation by the same authors., This is a snapshot of the software. Please visit https://github.com/carthurs/CRIMSONFlowsolver/releases/tag/PLOS_Comp_Bio & www.crimson.software for more general information and the most up to date version of the software. , and Software can be compiled in Cygwin and Linux.
- Keyword:
- Blood Flow Simulation, Patient-specific, Open-source Software, Image-based simulation, Cardiovascular Medical Image, Segmentation, and Finite Element Simulation
- Citation to related publication:
- CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation C.J. Arthurs, R. Khlebnikov, A. Melville, M. Marčan, A. Gomez, D. Dillon-Murphy, F. Cuomo, M.S. Vieira, J. Schollenberger, S.R. Lynch, C. Tossas-Betancourt, K. Iyer, S. Hopper, E. Livingston, P. Youssefi, A. Noorani, S. Ben Ahmed, F.J.H. Nauta, T.M.J. van Bakel, Y. Ahmed, P.A.J. van Bakel, J. Mynard, P. Di Achille, H. Gharahi, K. D. Lau, V. Filonova, M. Aguirre, N. Nama, N. Xiao, S. Baek, K. Garikipati, O. Sahni, D. Nordsletten, C.A. Figueroa bioRxiv 2020.10.14.339960; doi: https://doi.org/10.1101/2020.10.14.339960 and Arthurs, C., Khlebnikov, R., Melville, A., Marčan, M., Gomez, A., Dillon-Murphy, D., Cuomo, F., Vieira, M., Schollenberger, J., Lynch, S., Tossas-Betancourt, C., Iyer, K., Hopper, S., Livingston, E., Youssefi, P., Noorani, A., Ben Ahmed, S., Nauta, F., van Bakel, T., Ahmed, Y., van Bakel, P., Mynard, J., Di Achille, P., Gharahi, H., Lau, K., Filonova, V., Aguirre, M., Nama, N., Xiao, N., Baek, S., Garikipati, K., Sahni, O., Nordsletten, D., Figueroa, C. (2021). CRIMSON open source project - Graphical User Interface (GUI) Source Code for PLOS Computational Biology [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/679b-dw96
- Discipline:
- Engineering and Health Sciences
-
- Creator:
- Ayumi Fujisaki-Manome
- Description:
- Precipitation impacts on ice cover and water temperature in the Laurentian Great Lakes were examined using state-of-art coupled ice-hydrodynamic models. Numerical experiments were conducted for the recent anomalously cold (2014-2015) and warm (2015-2016) winters that were accompanied by high and low ice coverage over the lakes, respectively. The results of numerical experiments showed that, snow cover on the ice, which is the manifestation of winter precipitation, reduced the total ice volume (or mean ice thickness) in all of the Great Lakes, shortened the ice duration, and allowed earlier warming of water surface. The reduced ice volume was due to the thermal insulation of snow cover. The surface albedo was also increased by snow cover, but its impact on the delay the melting of ice was overcome by the thermal insulation effect. During major snowstorms, snowfall over the open lake caused notable cooling of the water surface due to latent heat absorption. Overall, the sensible heat flux from rain in spring and summer was found to have negligible impacts on the water surface temperature. Although uncertainties remain in over-lake precipitation estimates and model’s representation of snow on the ice, this study demonstrated that winter precipitation, particularly snowfall on the ice and water surfaces, is an important contributing factor in Great Lakes ice production and thermal conditions from late fall to spring.
- Keyword:
- Great Lakes, lake ice, numerical modeling, and precipitation
- Citation to related publication:
- Fujisaki-Manome, A., Anderson, E. J., Kessler, J. A., Chu, P. Y., Wang, J., & Gronewold, A. D. (2020). Simulating Impacts of Precipitation on Ice Cover and Surface Water Temperature Across Large Lakes. Journal of Geophysical Research: Oceans, 125(5), e2019JC015950. https://doi.org/10.1029/2019JC015950
- Discipline:
- Science and Engineering