The goal here is to study the voltage and expansion response of lithium-ion batteries at different charging rates. Specifically, the goal is to capture the observation of the smoothing of the peaks in dV/dQ and retention of the peaks in d^2 (backslash)delta/dQ^2 at higher C-rates. The retention of the peaks at higher charging rates enables better estimation of the cell capacity. To achieve this goal a reduced order electrochemical and mechanical model with multiple particles with a size distribution is developed. This allows us to capture the smoothing and preservation of the phase transitions in the voltage and expansion measurements at high C-rates, respectively. The model is written in Matlab software.
Mohtat, P., Lee, S., Sulzer, V., Siegel, J. B., & Stefanopoulou, A. G. (2020). Differential Expansion and Voltage Model for Li-ion Batteries at Practical Charging Rates. Journal of The Electrochemical Society, 167(11), 110561. https://doi.org/10.1149/1945-7111/aba5d1
Data used in the paper "Theory of Magnetic Switchbacks Fully Supported by Parker Solar Probe Observations" by G. Toth, M. Velli and B. van der Holst, ApJ 2023.
The Observations directory contains the PSP observations as simple text files that can be easily read by the IDL macros in the BATSRUS/share/IDL/General/ or any other plotting software.
The Simulations directory contains BATSRUS simulations including input and output files. The runlog files show the Git references. The output files are in binary format that can be read by the IDL macros in the BATSRUS/share/IDL/General/ or with the SpacePy software.
The BATSRUS directory contains the source code that can be used to reproduce the simulations.
G. Toth, M. Velli, B. van der Holst, 2023, Theory of Magnetic Switchbacks Fully Supported by Parker Solar Probe Observations, The Astrophysical Journal, in press
As part of the Flaring & Fossil Fuels: Uncovering Emissions & Losses (F3UEL) project, in 2022 the aircraft measurement platform sampled offshore oil & gas facilities in the US Gulf of Mexico to quantify facility-level emissions using the approach detailed in Conley et al. (2017). Vertical profiles were conducted on each flight to capture the vertical structure and mixing depths of the atmosphere. The data file contains all merged flight data from each flight day.
Reference: Conley, S., Faloona, I., Mehrotra, S., Suard, M., Lenschow, D. H., Sweeney, C., Herndon, S., Schwietzke, S., Pétron, G., Pifer, J., Kort, E. A., and Schnell, R.: Application of Gauss’s theorem to quantify localized surface emissions from airborne measurements of wind and trace gases, Atmos. Meas. Tech., 10, 3345 – 3358, 2017.
This data set is my analysis of data management plans (DMPs) that were written by researchers at the University of Michigan for awards made between March 2020 and February 2021. I conducted this analysis to explore the potential utility of DMPs as a tool to aid data curators in understanding and working with the associated data set. Variables collected include: the types and formats of the expected data sets, information about the metadata and documentation to be generated, the anticipated methods for making the data set publicly available, references to Intellectual Property allowances or concerns, and the stated duration for preserving the data sets.
Carlson, J. (2023) Untapped Potential: A Critical Analysis of the Utility of Data Management Plans in Facilitating Data Sharing. Journal of Research Administration. Fall 2023. Forthcoming.
Single molecule data and analysis code for Figure4 in the paper titled: "A rhythmically pulsing leaf-spring DNA-origami nanoengine that drives a passive follower".
Follow the readme file for deiails.
This research was completed to statistically validate that a data-model refinement technique could integrate real measurements to remove bias from physics-based models via changing the forcing parameters such as the thermal conductivity coefficients.
Ponder, B. M., Ridley, A. J., Goel, A., & Bernstein, D. S. (2023). Improving forecasting ability of GITM using data-driven model refinement. Space Weather, 21, e2022SW003290. https://doi.org/10.1029/2022SW003290
This is the model and observational data referenced in our manuscript entitled “surface and sub-subsurface internal gravity wave kinetic energy spectra from global ocean models and observations.” The model data for the 7 regions from the two global simulations (HYCOM and MITgcm) can be found here.
These files contain the raw data and processing parameters to go with the paper "Hierarchical structure guides rapid linguistic predictions during naturalistic listening" by Jonathan R. Brennan and John T. Hale. These files include the stimulus (wav files), raw data (BrainVision format), data processing parameters (matlab), and variables used to align the stimuli with the EEG data and for the statistical analyses reported in the paper (csv spreadsheet).
and Updates in Version 2:
- data in BrainVision format
- added information about data analysis
- corrected prePROCessing information for S02
Brennan, J. R., & Hale, J. T. (2019). Hierarchical structure guides rapid linguistic predictions during naturalistic listening. PLoS ONE 14(1). e0207741
As part of a larger research study on social sustainability and human rights, this research examines the supplier codes of conduct lead firms adopt to achieve their social supply chain sustainability goals.
Cao, Y., Lawson, B., & Pil, F. K. (2023). Social sustainability and human rights in global supply chains, International Journal of Operations & Production Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJOPM-10-2022-0670.
Research Overview:
In situ magnetic field measurements are often difficult to obtain due to the presence of stray magnetic fields generated by spacecraft electrical subsystems. The conventional solution is to implement strict magnetic cleanliness requirements and place magnetometers on a deployable boom. However, this method is not always feasible on low-cost platforms due to factors such as increased design complexity, increased cost, and volume limitations. To overcome this problem, we propose using the Quad-Mag CubeSat magnetometer with an improved Underdetermined Blind Source Separation (UBSS) noise removal algorithm. The Quad-Mag consists of four magnetometer sensors in a single CubeSat form-factor card that allows distributed measurements of stray magnetic fields. The UBSS algorithm can remove stray magnetic fields without prior knowledge of the magnitude, orientation, or number of noise sources. UBSS is a two-stage algorithm that identifies signals through cluster analysis and separates them through compressive sensing. We use UBSS with single source point (SSP) detection to improve the identification of noise signals and iteratively-weighted compressed sensing to separate noise signals from the ambient magnetic field. Using a mock CubeSat, we demonstrate in the lab that UBSS reduces four noise signals producing more than 100 nT of noise at each magnetometer to below the expected instrument resolution (near 5 nT). Additionally, we show that the integrated Quad-Mag and improved UBSS system works well for 1U, 2U, 3U, and 6U CubeSats in simulation. Our results show that the Quad-Mag and UBSS noise cancellation package enables high-fidelity magnetic field measurements from a CubeSat without a boom.
Hoffmann, A. P., Moldwin, M. B., Strabel, B. P., & Ojeda, L. V. (2023). Enabling Boomless CubeSat Magnetic Field Measurements with the Quad-Mag Magnetometer and an Improved Underdetermined Blind Source Separation Algorithm. Journal of Geophysical Research: Space Physics, 128, e2023JA031662. https://doi-org.proxy.lib.umich.edu/10.1029/2023JA031662