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.
Chen, Y., Manchester, W., Hero, A., Toth, G., DuFumier, B. Zhou, T., Wang, X., Zhu, H., Sun, Zeyu, Gombosi, T., Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters, Space Weather, 17, 1404–1426. https://doi.org/10.1029/2019SW002214 and Jiao, Z., Chen, Y., Manchester, W. (2020). Data for Solar Flare Intensity Prediction with Machine Learning Models [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/b07j-bj08
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.
Linyan Xiang (相林言) and Oleg Zikanov, “Numerical simulation of rolling pad instability in cuboid liquid metal batteries,” Physics of Fluids, vol. 31, no. 12, p. 124104, 2019, https://doi.org/10.1063/1.5123170 and Oleg Zikanov, "Shallow water modeling of rolling pad instability in liquid metal batteries." Theoretical and Computational Fluid Dynamics, 32, 325–347, 2018, https://doi.org/10.1007/s00162-018-0456-2
The project outputs summarize all the publications, talks, and codes we accomplished under this NSF funding. In the project, we develop methodologies to manage uncertainty in future electric power systems and quantify how uncertainty affects power system sustainability. and Talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/149653
B. Li and J. L. Mathieu, "Analytical reformulation of chance-constrained optimal power flow with uncertain load control," 2015 IEEE Eindhoven PowerTech, Eindhoven, 2015, pp. 1-6. https://doi.org/10.1109/PTC.2015.7232803, B. Li, J. L. Mathieu and R. Jiang, "Distributionally Robust Chance Constrained Optimal Power Flow Assuming Log-Concave Distributions," 2018 Power Systems Computation Conference (PSCC), Dublin, 2018, pp. 1-7. https://doi.org/10.23919/PSCC.2018.8442927, B. Li, M. Vrakopoulou and J. L. Mathieu, "Chance Constrained Reserve Scheduling Using Uncertain Controllable Loads Part II: Analytical Reformulation," in IEEE Transactions on Smart Grid, vol. 10, no. 2, pp. 1618-1625, March 2019. https://doi.org/10.1109/TSG.2017.2773603, B. Li, R. Jiang and J. L. Mathieu, "Distributionally Robust Chance-Constrained Optimal Power Flow Assuming Unimodal Distributions With Misspecified Modes," in IEEE Transactions on Control of Network Systems, vol. 6, no. 3, pp. 1223-1234, Sept. 2019. https://doi.org/10.1109/TCNS.2019.2930872, B. Li, R. Jiang and J. L. Mathieu, "Distributionally robust risk-constrained optimal power flow using moment and unimodality information," 2016 IEEE 55th Conference on Decision and Control (CDC), Las Vegas, NV, 2016, pp. 2425-2430. https://doi.org/10.1109/CDC.2016.7798625, B. Li, S. D. Maroukis, Y. Lin and J. L. Mathieu, "Impact of uncertainty from load-based reserves and renewables on dispatch costs and emissions," 2016 North American Power Symposium (NAPS), Denver, CO, 2016, pp. 1-6. https://doi.org/10.1109/NAPS.2016.7747830, G. Martínez, J. Liu, B. Li, J. L. Mathieu and C. L. Anderson, "Enabling renewable resource integration: The balance between robustness and flexibility," 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, 2015, pp. 195-202. https://doi.org/10.1109/ALLERTON.2015.7447004, J. Liu, M. G. Martinez, B. Li, J. Mathieu and C. L. Anderson, "A Comparison of Robust and Probabilistic Reliability for Systems with Renewables and Responsive Demand," 2016 49th Hawaii International Conference on System Sciences (HICSS), Koloa, HI, 2016, pp. 2373-2380. https://doi.org/10.1109/HICSS.2016.297, Li, B., Jiang, R. & Mathieu, J.L. "Ambiguous risk constraints with moment and unimodality information." Math. Program. 173, 151–192 (2019). https://doi.org/10.1007/s10107-017-1212-x, M. Vrakopoulou, B. Li and J. L. Mathieu, "Chance Constrained Reserve Scheduling Using Uncertain Controllable Loads Part I: Formulation and Scenario-Based Analysis," in IEEE Transactions on Smart Grid, vol. 10, no. 2, pp. 1608-1617, March 2019. https://doi.org/10.1109/TSG.2017.2773627, Y. Zhang, S. Shen and J. L. Mathieu, "Data-driven optimization approaches for optimal power flow with uncertain reserves from load control," 2015 American Control Conference (ACC), Chicago, IL, 2015, pp. 3013-3018. https://doi.org/10.1109/ACC.2015.7171795, Y. Zhang, S. Shen and J. L. Mathieu, "Distributionally Robust Chance-Constrained Optimal Power Flow With Uncertain Renewables and Uncertain Reserves Provided by Loads," in IEEE Transactions on Power Systems, vol. 32, no. 2, pp. 1378-1388, March , and Y. Zhang, S. Shen, B. Li and J. L. Mathieu, "Two-stage distributionally robust optimal power flow with flexible loads," 2017 IEEE Manchester PowerTech, Manchester, 2017, pp. 1-6. https://doi.org/10.1109/PTC.2017.7981202
This section contains work related to the modeling of voltage degradation in a 24 cell PEM fuel cell stack with 300 cm2 cross-sectional area. The experimental hardware used to validate the model consists of a computer controlled system that coordinates air, hydrogen, cooling, and electrical subsystems to operate the stack. Dry hydrogen is pressure regulated for full utilization in the dead-ended anode. Using a solenoid valve, the anode is periodically purged to recover the gradual degradation in voltage. A membrane based humidifier controls the vapor content of the cathode gas stream while a mass flow controller is used to regulate the flow to the desired stoichiometry.
Citation to related publication:
Denise A. McKay, Jason B. Siegel, William Ott, and Anna G. Stefanopoulou. Parameterization and prediction of temporal fuel cell voltage behavior during flooding and drying conditions. Journal of Power Sources, 178(1):207 - 222, 2008. https://doi.org/10.1016/j.jpowsour.2007.12.031
The work on accelerating authenticated boot for embedded system resulted in designing an algorithm in python to perform the random address generation and cryptographic MAC calculation.
The Sampled Boot schemes implemented in this package allow a significant reduction of the time
needed to authenticate firmware images during startup, while still retaining a high degree of trust.
This is particularly useful for automotive applications in which startup time constraints make secure boot a time prohibitive process. and Citation for this dataset: Nasser, A., Gumise, W. (2019). Authenticated Boot Acceleration Algorithm [Code and data]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/yeh1-1x17
Nasser, A., Gumise, W., and Ma, D., "Accelerated Secure Boot for Real-Time Embedded Safety Systems," SAE Int. J. Transp. Cyber. & Privacy 2(1) : 35-48, 2019, https://doi.org/10.4271/11-02-01-0003
The data and the scripts are to show that seizure onset dynamics and evoked responses change over the progression of epileptogenesis defined in this intrahippocampal tetanus toxin rat model. All tests explored in this study can be repeated with the data and scripts included in this repository. and Dataset citation: Crisp, D.N., Cheung, W., Gliske, S.V., Lai, A., Freestone, D.R., Grayden, D.B., Cook, MJ., Stacey, W.C. (2019). Epileptogenesis modulates spontaneous and responsive brain state dynamics [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/r6vg-9658
Crisp, D. N., Cheung, W., Gliske, S. V., Lai, A., Freestone, D. R., Grayden, D. B., Cook, M. J., & Stacey, W. C. (2020). Quantifying epileptogenesis in rats with spontaneous and responsive brain state dynamics. Brain Communications, 2(1). https://doi.org/10.1093/braincomms/fcaa048
Johnson, J. E., & Molnar, P. H. ( 2019). Widespread and persistent deposition of iron formations for two billion years. Geophysical Research Letters, 46, 3327– 3339. https://doi.org/10.1029/2019GL081970
The work on the Bangime language, spoken by the Bangande people, was carried out as part of a larger linguistic fieldwork project focused on Dogon languages. Bangime is confirmed as a language isolate with no demonstrable linguistic relatives—possibly the only such isolate in West Africa.
The research aims to demonstrate judgment accuracy about other individuals' socio-political opinions produced by prototype matching and base/shift heuristics or people's own strategies (control).
The dataset contains the Fortran programs applied in the latest CESM/IMPACT model as well as the data created from this model, which are used in the referenced paper.
Zhu, J. et al. Decrease in radiative forcing by organic aerosol nucleation, climate, and land use change. Nature Communications 10, 423 (24 January 2019). https://doi.org/10.1038/s41467-019-08407-7