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- Creator:
- Zhang, Kaihua and Collette, Matthew D.
- Description:
- This Ph.D. research focuses on two subject areas: experimental and numerical model, which serves as two essential parts of a digital twin. A digital twin contains models of real-world structures and fuses data from observations of the structures and scale experiment to pull the models into better agreement with the real world. Digital twin models have the promise of representing complex marine structures and providing enhanced lifecycle performance and risk forecasts. Experimentally verifying the updating approaches is necessary but rarely performed. Thus, the proposed work is designing an experiment and developing a numerical model updated by the experimental data. The dataset contains all the data collected in the experiment of a four-crack hexagon- shaped specimen is presented, designed to mimic many of the properties of complex degrading marine structural systems, such as crack interaction, component inter- dependence, redundant load path, and non-binary failure.
- Keyword:
- System Reliability, Dynamic Bayesian Networks, Fatigue Experiment, Crack Length Measurement, Experimental Validation, Reliability Prediction
- Citation to related publication:
- "Evaluating Crack Growth Prediction in Structural Systems with Dynamic Bayesian Networks", submitted to Computers and Structure and Zhang, K., & Collette, M. (2021). Experimental investigation of structural system capacity with multiple fatigue cracks. Marine Structures, 78, 102943. https://doi.org/10.1016/j.marstruc.2021.102943
- Discipline:
- Engineering
-
- Creator:
- James, David A. and Lokam, Nikhil
- Description:
- The object of this project is to provide researchers and students with a tool to allow them to develop an intuitive understanding of singular vectors and singular values. 2x2 matrices A with real entries map circles to ellipses; in particular, unit circles centered at the origin to ellipses centered at the origin. It is known that the points on the ellipse farthest from the origin correspond to the singular vectors of A. Users can use the GUI to enter matrices of their choice and explore to visually self-determine the singular vectors/values.
- Keyword:
- SVD, Singular Value Decomposition, Singular Vector, Singular Value, and Matrix
- Discipline:
- Science and Engineering
-
- Creator:
- Swiger, Brian M., Liemohn, Michael W., and Ganushkina, Natalia Y.
- Description:
- We sampled the near-Earth plasma sheet using data from the NASA Time History of Events and Macroscale Interactions During Substorms mission. For the observations of the plasma sheet, we used corresponding interplanetary observations using the OMNI database. We used these data to develop a data-driven model that predicts plasma sheet electron flux from upstream solar wind variations. The model output data are included in this work, along with code for analyzing the model performance and producing figures used in the related publication. and Data files are included in hdf5 and Python pickle binary formats; scripts included are set up for use of Python 3 to access and process the pickle binary format data.
- Keyword:
- neural network, plasma sheet, solar wind, machine learning, keV electron flux, deep learning, and space weather
- Citation to related publication:
- Swiger, B. M., Liemohn, M. W., & Ganushkina, N. Y. (2020). Improvement of Plasma Sheet Neural Network Accuracy With Inclusion of Physical Information. Frontiers in Astronomy and Space Sciences, 7. https://doi.org/10.3389/fspas.2020.00042
- Discipline:
- Science and Engineering
-
- Creator:
- Agrawal, Mayank and Glotzer, Sharon C
- Description:
- Micron-scale robots require systems that can morph into arbitrary target configurations controlled by external agents such as heat, light, electricity, and chemical environment. Achieving this behavior using conventional approaches is challenging because the available materials at these scales are not programmable like their macroscopic counterparts. To overcome this challenge, we propose a design strategy to make a robotic machine that is both programmable and compatible with colloidal-scale physics. Our strategy uses motors in the form of active colloidal particles that constantly propel forward. We sequence these motors end-to-end in a closed chain forming a two-dimensional loop that folds under its mechanical constraints. We encode the target loop shape and its motion by regulating six design parameters, each scale-invariant and achievable at the colloidal scale. The research dataset includes simulation, visualization, and analysis scripts and results generated for the 2D chain loops of self-propelling particles. File Description:, -- arrows_folding - Contains the data for the folded chain loop shapes resembling an arrowhead., -- bending_vs_variation - Contains the data to study the stability of a particular shape in simulations as one of the segments of the shape bends and/or the distribution of propulsion on it varies., -- curved_triangle - Contains the data to study motion and bending of a triangle shape made using chain loop., -- example_shapes - Contains data for various examples of shapes that can be generated by designing the chain loops., -- nskT_vs_fakT - Contains the data for a specific shape to study the effect of scaling up the number of particles (governed by ns) and the propulsion (governed by fa) in its chain., -- stability - Contains the data and theoretical model (stability.py) to study the stability of the six different shapes., -- tuning_design_forM - Contains the data for sequential tuning the design parameters to fold the shape "M" as described in the corresponding publication., and -- two_neighboring_cds_segments_ - Contains the data to study a system of two neighboring chain segments with respect to different parameters discussed in the publication.
- Keyword:
- active particles, colloidal robotics, design, kilobots, and morphological control
- Citation to related publication:
- Agrawal, M, Glotzer SC. (2020). Scale-free, programmable design of morphable chain loops of kilobots and colloidal motors. PNAS. www.pnas.org/cgi/doi/10.1073/pnas.1922635117
- Discipline:
- Engineering
-
- Creator:
- Moniri, Saman, Xiao, Xianghui, and Shahani, Ashwin J.
- Description:
- The data is comprised of 22 directories, each housing a .hdf file of the X-ray projections recorded during solidification of Al-Si-Cu-Sr. The flat and dark projections are also included as two separate .hdf files (total file count: 24). The raw data file is in .hdf format and can be reconstructed into .tiff, e.g., by using the TomoPy toolbox in Python.
- Keyword:
- Crystallization, growth modifiers, silicon, in situ, X-ray tomography
- Citation to related publication:
- Wang, Y., Gao, J., Ren, Y., De Andrade, V., & Shahani, A. J. (2020). Formation of a Three-Phase Spiral Structure Due to Competitive Growth of a Peritectic Phase with a Metastable Eutectic. JOM, 72(8), 2965–2973. https://doi.org/10.1007/s11837-020-04237-x
- Discipline:
- Engineering
-
- Creator:
- Ahluwalia, Vinayak S., Steimle, Lauren N., and Denton, Brian T.
- Description:
- This repository includes test instances of infinite-horizon Markov decision processes with multiple models of parameters (i.e., "Multi-model Markov decision processes"). We generated each test instance in the dataset using a Python script. The test instances can be read in using the provided C++ and Python script. See the README for details.
- Keyword:
- Markov decision processes, mixed-integer programming, stochastic programming, and dynamic programming
- Citation to related publication:
- Ahluwalia, Steimle, and Denton. "Policy-based branch-and-bound for infinite-horizon Multi-model Markov decision processes". 2020.
- Discipline:
- Engineering
-
- Creator:
- Crisp, Dakota N., Cheung, Warwick, Gliske, Stephen V., Lai, Alan, Freestone, Dean R., Grayden, David B., Cook, Mark J., and Stacey, William C.
- Description:
- 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
- Keyword:
- evoked response, stimulation, bifurcation, epilepsy, seizure, divergence, and dynamics
- Citation to related publication:
- 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
- Discipline:
- Science, Engineering, and Health Sciences
-
- Creator:
- Minallah, Samar and Steiner, Allison L.
- Description:
- Data format: netcdf4 , Time series duration: 2016-06-01 to 2020-10-31, Temporal resolution: Daily, and Spatial resolution: The model output was regridded to a 0.05 degree rectilinear (lat/lon) grid using the conservative remapping method ("cdo remapcon" tool).
- Keyword:
- Land surface hydrology, Great Lakes, Land surface model, NOAH-MP, WRF-Hydro, and Hydrologic modeling
- Citation to related publication:
- Minallah, S. (2022). A Study on the Atmospheric, Cryospheric, and Hydrologic Processes Governing the Evolution of Regional Hydroclimates (Doctoral dissertation, University of Michigan Ann Arbor). https://dx.doi.org/10.7302/6223
- Discipline:
- Science and Engineering
-
- Creator:
- Brady P. Strabel
- Description:
- The contained data comprises what was collected during the characterization of the quad-magnetometer as described in 'Quad-Mag Board for CubeSat Applications'. There are approximately 38 hours of data that compromise a stability test, 10 hours of noise floor testing data, and 10 minutes of sensitivity testing data. Each data file has three-axis measurements from four individual magnetometers over the specified time period at a 65 Hz sampling rate.
- Keyword:
- Magnetometer, COTS, and CubeSat
- Citation to related publication:
- Strabel, B. P., Regoli, L. H., Moldwin, M. B., Ojeda, L. V., Shi, Y., Thoma, J. D., Narrett, I. S., Bronner, B., and Pellioni, M.: Quad-Mag board for CubeSat applications, Geosci. Instrum. Method. Data Syst., 11, 375–388, https://doi.org/10.5194/gi-11-375-2022, 2022.
- Discipline:
- Engineering
-
- Creator:
- Curlis, JD, Renney, TJ, Davis Rabosky, AR, and Moore, TY
- Description:
- Efficient comparisons of biological color patterns are critical for understanding the mechanisms by which organisms evolve in ecosystems, including sexual selection, predator-prey interactions, and thermoregulation. However, elongate or spiral-shaped organisms do not conform to the standard orientation and photographic techniques required for automated analysis. Currently, large-scale color analysis of elongate animals requires time-consuming manual landmarking, which reduces their representation in coloration research despite their ecological importance. We present Batch-Mask: an automated and customizable workflow to facilitate the analysis of large photographic data sets of non-standard biological subjects. First, we present a user guide to run an open-source region-based convolutional neural network with fine-tuned weights for identifying and isolating a biological subject from a background (masking). Then, we demonstrate how to combine masking with existing manual visual analysis tools into a single streamlined, automated workflow for comparing color patterns across images. Batch-Mask was 60x faster than manual landmarking, produced masks that correctly identified 96% of all snake pixels, and produced pattern energy results that were not significantly different from the manually landmarked data set. The fine-tuned weights for the masking neural network, user guide, and automated workflow substantially decrease the amount of time and attention required to quantitatively analyze non-standard biological subjects. By using these tools, biologists will be able to compare color, pattern, and shape differences in large data sets that include significant morphological variation in elongate body forms. This advance will be especially valuable for comparative analyses of natural history collections, and through automation can greatly expand the scale of space, time, or taxonomic breadth across which color variation can be quantitatively examined.
- Keyword:
- convolutional neural network, photography, sensory ecology, color evolution, vision, and image segmentation
- Citation to related publication:
- Curlis, Renney, Davis Rabosky, Moore (submitted) Batch-Mask: An automated Mask R-CNN workflow to isolate non-standard biological specimens for color pattern analysis.
- Discipline:
- Engineering and Science