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- Creator:
- Ponder, Brandon M., Ridley, Aaron J., Goel, Ankit, and Bernstein, Dennis S.
- Description:
- 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.
- Keyword:
- Thermosphere, GITM, CHAMP, GRACE, MSIS, Upper Atmosphere Modeling, and Data Assimilation
- Citation to related publication:
- 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
- Discipline:
- Engineering and Science
-
- 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:
- 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, University of Michigan
- 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, 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
-
- 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
-
- 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
-
- Creator:
- Towne, Aaron, Jones, Anya, and Biler, Hulya
- Description:
- This dataset contains experimental measurements of a flat-plate airfoil passing through a large-amplitude transverse gust. The dataset contains an ensemble of of the airfoil-gust encounter to account for variability in the gust profile, and each realization contains time-resolved force measurements and planar PIV velocity fields. All data are stored within hdf5 files, and a Matlab script showing how the data can be read and manipulated is provided. Please see the ‘airfoilEXP_README.pdf’ file for more information. We recommend using the ‘airfoilEXP_example.zip’ file as an entry point to the dataset. and The dataset is part of “A database for reduced-complexity modeling of fluid flows” (see references below) and is intended to aid in the conception, training, demonstration, evaluation, and comparison of reduced-complexity models for fluid mechanics. The paper introduces the flow setup and computational methods, describes the available data, and provides an example of how these data can be used for reduced-complexity modeling. Users of these data should cite the papers listed below.
- Keyword:
- fluid mechanics and aerodynamics
- Citation to related publication:
- 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., Biler, H., Sedky, G., Jones, A. R., Saritas, M. and Cetiner, O. (2021) Experimental investigation of transverse and vortex gust encounters at low Reynolds numbers. AIAA Journal, 59(3):786–799., and Andreu-Angulo, I., Babinsky, H., Biler, H., Sedky, G. and Jones, A. R. (2020) Effect of transverse gust velocity profiles. AIAA Journal, 58(12):5123–5133.
- Discipline:
- Science and Engineering
-
- Creator:
- Towne, Aaron and Dawson, Scott
- Description:
- This dataset contains data from direct numerical simulations of two-dimensional stationary and pitching flat-plate airfoils at Reynolds number 100. The dataset contains time-resolved snapshots of the velocity field, lift and drag coefficients, and airfoil kinematics spanning 40-100 convective time units. Cases include a stationary airfoil and eight different pitching frequencies. All data are stored within hdf5 files, and a Matlab script showing how the data can be read and manipulated is provided. Please see the ‘airfoilDNS_README.pdf’ file for more information. We recommend using the ‘airfoilDNS_example.zip’ file as an entry point to the dataset. and The dataset is part of “A database for reduced-complexity modeling of fluid flows” (see references below) and is intended to aid in the conception, training, demonstration, evaluation, and comparison of reduced-complexity models for fluid mechanics. The paper introduces the flow setup and computational methods, describes the available data, and provides an example of how these data can be used for reduced-complexity modeling. Users of these data should cite the papers listed below.
- Keyword:
- fluid mechanics and aerodynamics
- Citation to related publication:
- 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. and Dawson, S. T. M., Floryan, D. C., Rowley, C. W., and Hemati, M. S. (2016) Lift enhancement of high angle of attack airfoils using periodic pitching. AIAA Paper 2016-2069.
- Discipline:
- Engineering and Science
-
- Creator:
- Bougher, S. W. (CLaSP Department, University of Michigan)
- Description:
- The NASA MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft, which is currently in orbit around Mars, has been taking systematic measurements of the densities and deriving temperatures in the upper atmosphere of Mars between about 140 to 240 km above the surface since late 2014. Wind measurement campaigns are also conducted once per month for 5-10 orbits. These densities, temperatures and winds change with time (e.g. solar cycle, season, local time) and location, and sometimes fluctuate quickly. Global dust storm events are also known to significantly impact these density, temperature and wind fields in the Mars thermosphere. For the current project, the inert light species helium is used to trace the circulation patterns and constrain wind magnitudes throughout the Mars thermosphere. Presently, more than 6 years of Neutral Gas and Ion Mass Spectrometer (NGIMS) measurements of helium densities have been obtained by the MAVEN team (e.g. Elrod et al., 2017; 2021; Gupta et al., 2021). Measured helium distributions are compared to simulations from a computer model of the Mars atmosphere called M-GITM (Mars Global Ionosphere-Thermosphere Model), developed at U. of Michigan. Since the global circulation plays a role in the structure, variability, and evolution of the atmosphere, understanding the processes that drive the winds in the upper atmosphere of Mars also provides the needed context for understanding helium distributions and how the atmosphere behaves as a whole system. Three dimensional M-GITM simulations for the Mars four cardinal seasons (Ls = 0, 90, 180, 270, for Mars Year 33) were conducted for detailed comparisons with NGIMS helium and CO2 distributions (Gupta et al. 2021). The M-GITM datacubes used to extract these densities (plus winds) along the trajectory of each orbit path between 140 and 240 km, are provided in this Deep Blue Data archive. README files are also provided for each datacube, detailing the contents of each file. In addition, a general README file is provided that summarizes the inputs and outputs of the M-GITM code simulations for this study. Finally, a basic version of the M-GITM code can be found on Github at https:/github.com/dpawlows/MGITM.
- Keyword:
- Mars, MAVEN Spacecraft Mission, Mars Thermosphere, Helium Density Distributions, and Neutral Gas and Ion Mass Spectrometer (NGIMS)
- Citation to related publication:
- Gupta, N., N. V. Rao, S. W. Bougher, and M. K. Elrod, Latitudinal and Seasonal Asymmetries of the Helium Bulge in the Martian Upper Atmosphere J. Geophys. Res., 126, XXXX-XXXX. doi:10.1002/2021JEXXXXXX
- Discipline:
- Engineering and Science
-
- Creator:
- Bougher, Stephen W. (CLaSP Department, U. of Michigan) and Roeten, Kali J. (CLaSP Department, U. of Michigan)
- Description:
- The NASA MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft, which is currently in orbit around Mars, has been taking monthly measurements of the speed and direction of the winds in the upper atmosphere of Mars between about 140 to 240 km above the surface. The observed wind speeds and directions change with time and location, and sometimes fluctuate quickly. These measurements are compared to simulations from a computer model of the Mars atmosphere called M-GITM (Mars Global Ionosphere-Thermosphere Model), developed at U. of Michigan. This is the first comparison between direct measurements of the winds in the upper atmosphere of Mars and simulated winds and is important because it can help to inform us what physical processes are acting on the observed winds. Some wind measurements have similar wind speeds or directions to those predicted by the M-GITM model, but sometimes, there are large differences between the simulated and measured winds. The disagreements between wind observations and model simulations suggest that processes other than normal solar forcing may become relatively more important during these observations and alter the expected circulation pattern. Since the global circulation plays a role in the structure, variability, and evolution of the atmosphere, understanding the processes that drive the winds in the upper atmosphere of Mars provides key context for understanding how the atmosphere behaves as a whole system. A basic version of the M-GITM code can be found on Github as follows: https:/github.com/dpawlows/MGITM and About 30 Neutral Gas and Ion Mass Spectrometer (NGIMS) wind campaigns (of 5 to 10 orbits each) have been conducted by the MAVEN team (Benna et al., 2019). Five of these campaigns are selected for detailed study (Roeten et al. 2019). The Mars conditions for these five campaigns have been used to launch corresponding M-GITM code simulations, yielding 3-D neutral wind fields for comparison to these NGIMS wind observations. The M-GITM datacubes used to extract the zonal and meridional neutral winds, along the trajectory of each orbit path between 140 and 240 km, are provided in this Deep Blue Data archive. README files are provided for each datacube, detailing the contents of each file. A general README file is also provided that summarizes the inputs and outputs of the M-GITM code simulations for this study.
- Keyword:
- Mars, MAVEN spacecraft, Mars thermosphere, and Mars global upper atmosphere winds
- Citation to related publication:
- Roeten, K. J., Bougher, S. W., Benna, M., Mahaffy, P. R., Lee, Y., Pawlowski, D., et al. (2019). MAVEN/NGIMS thermospheric neutral wind observations: Interpretation using the M‐GITM general circulation model. Journal of Geophysical Research: Planets, 124, 3283– 3303. https://doi.org/10.1029/2019JE005957
- Discipline:
- Science and Engineering
-
- Creator:
- Bougher, S. W. (CLaSP Department, U. of Michigan), Roeten, K. J. (CLaSP Department, U. of Michigan), and Sharrar, R. (Astronomy Department, U. of Michigan)
- Description:
- The NASA MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft, which is currently in orbit around Mars, has been taking daily (systematic) measurements of the densities and temperatures in the upper atmosphere of Mars between about 140 to 240 km above the surface. Wind measurement campaigns are also conducted once per month for 5-10 orbits. These densities, temperatures and winds change with time (e.g. season, local time) and location, and sometimes fluctuate quickly. Global dust storm events are also known to significantly impact these density, temperature and wind fields in the Mars thermosphere. Such global dust storm period measurements can be compared to simulations from a computer model of the Mars atmosphere called M-GITM (Mars Global Ionosphere-Thermosphere Model), developed at U. of Michigan. This is the first detailed comparison between direct global dust storm period measurements in the upper atmosphere of Mars and simulated MGITM fields and is important because it can help to inform us what physical processes are acting on the upper atmosphere during such large dust events. Since the global circulation plays a role in the structure, variability, and evolution of the atmosphere, understanding the processes that drive the winds in the upper atmosphere of Mars also provides key context for understanding how the atmosphere behaves as a whole system. A basic version of the M-GITM code can be found on Github as follows: https:/github.com/dpawlows/MGITM and About 4 months of Neutral Gas and Ion Mass Spectrometer (NGIMS) measurements of densities and winds have been made by the MAVEN team during the summer of 2018 (Elrod et al., 2019). Nine reference measurement intervals during this global dust storm (1-June through 30-August 2018) are selected for detailed study (Elrod et al. 2019). The Mars conditions for these nine intervals have been used to launch corresponding M-GITM code simulations, yielding 3-D neutral density, temperature and wind fields for comparison to these NGIMS measurements. The M-GITM datacubes used to extract the density, temperature and neutral winds, along the trajectory of each orbit path between 140 and 240 km, are provided in this Deep Blue Data archive. README files are provided for each datacube, detailing the contents of each file. A general README file is also provided that summarizes the inputs and outputs of the M-GITM code simulations for this study.
- Keyword:
- Mars, MAVEN Spacecraft, Mars Thermosphere, and Mars Global Dust Storm of 2018
- Citation to related publication:
- Elrod, M. K., S. W. Bougher, K. Roeten, R. Sharrar, J. Murphy, Structural and Compositional Changes in the Upper Atmosphere related to the PEDE-2018 Dust Event on Mars as Observed by MAVEN NGIMS, Geophys. Res. Lett., (2019). doi: 10.1029/2019GL084378. and Jain, S. K., Bougher, S. W., Deighan, J., Schneider, N. M., Gonzalez‐Galindo, F., Stewart, A. I. F., et al. ( 2020). Martian thermospheric warming associated with the Planet Encircling Dust Event of 2018. Geophysical Research Letters, 47, e2019GL085302. https://doi.org/10.1029/2019GL085302
- Discipline:
- Engineering and Science
-
- Creator:
- Moore, Talia Y, Villacis Nunez, C Nathaly, Ray, Andrew P, and Cooper, Kimberly L
- Description:
- Hind limbs can undergo dramatic changes in loading conditions during the transition from quadrupedal to bipedal locomotion. For example, the most early diverging bipedal jerboas (Rodentia: Dipodidae) are some of the smallest mammals in the world, with body masses that range 2-4 grams. The larger jerboa species exhibit developmental and evolutionary fusion of the central three metatarsals into a single cannon bone. We hypothesize that body size reduction and metatarsal fusion are mechanisms to maintain the safety factor of the hind limb bones despite the higher ground reaction forces associated with bipedal locomotion. Using finite element analysis to model collisions between the substrate and the metatarsals, we found that body size reduction was insufficient to reduce bone stress on unfused metatarsals, based on the scaled dynamics of larger jerboas, and that fused bones developed lower stresses than unfused bones when all metatarsals are scaled to the same size and loading conditions. Based on these results, we conclude that fusion reinforces larger jerboa metatarsals against high ground reaction forces. Because smaller jerboas with unfused metatarsals develop higher peak stresses in response to loading conditions scaled from larger jerboas, we hypothesize that smaller jerboas use alternative dynamics of bipedal locomotion that reduces the impact of collisions between the foot and substrate.
- Keyword:
- finite element, functional morphology, bipedal, jerboa, metatarsus, and bone fusion
- Citation to related publication:
- Villacis Nunez, Ray, Cooper, Moore (submitted). Body size reduction and metatarsal fusion were distinct mechanisms to resist bending as jerboas (Dipodidae) transitioned from quadrupedal to bipedal.
- Discipline:
- Science and Engineering
-
- Creator:
- Elvati, Paolo, Luyet, Chloe, Wang, Yichun, Liu, Changjiang, VanEpps, J. Scott, Kotov, Nicholas A., and Violi, Angela
- Description:
- Amyloid nanofibers are abundant in microorganisms and are integral components of many biofilms, serving various purposes, from virulent to structural. Nonetheless, the precise characterization of bacterial amyloid nanofibers has been elusive, with incomplete and contradicting results. The present work focuses on the molecular details and characteristics of PSMa1-derived functional amyloids present in Staphylococcus aureus biofilms, using a combination of computational and experimental techniques, to develop a model that can aid the design of compounds to control amyloid formation. Results from molecular dynamics simulations, guided and supported by spectroscopy and microscopy, show that PSMa1 amyloid nanofibers present a helical structure formed by two protofilaments, have an average diameter of about 12 nm, and adopt a left-handed helicity with a periodicity of approximately 72 nm. The chirality of the self-assembled nanofibers, an intrinsic geometric property of its constituent peptides, is central to determining the fibers' lateral growth.
- Keyword:
- molecular self-assembly, computational nanotechnology, nanobiotechnology, and structural properties
- Citation to related publication:
- Paolo Elvati, Chloe Luyet, Yichun Wang, Changjiang Liu, J. Scott VanEpps, Nicholas A. Kotov, and Angela Violi ACS Applied Nano Materials 2023 6 (8), 6594-6604 DOI: 10.1021/acsanm.3c00174
- Discipline:
- Engineering and Science
-
- Creator:
- Shah, Bhavarth
- Description:
- The three approaches used three distinct datasets named as follows: Historicalwater_levels.csv, Historical_Precipitation.csv, and Bayesian Statistical dataset.csv. These files are accessible using Microsoft Office or similar software. The machine learning models are developed in Jupyter Notebook (.ipynb) files, named according to the datasets they utilize. However, for the third approach, the models are named Random Forest, LSTM Model Base, and Multivariate LSTM Models. More details are available on the Shah_Bhavarth_Readme.txt. These notebooks can be accessed through Python, Project Jupyter, or Google Colab, and dependencies include libraries such as Pandas, NumPy, Matplotlib, Scikit-learn, Keras, and TensorFlow. The supplementary material also includes Excel files for stage-curve calculations and diversions, named Water_levels_Stage_Curve_Calculations1970-2018.xlsx and Diversions_calculation.xlsx, respectively.
- Keyword:
- Machine learning, Forecasting, Water levels, Mono lake, and Hydrology
- Citation to related publication:
- Shah, Bhavarth. 2024. "Mono Lake Water Levels Forecasting Using Machine Learning." Master’s thesis, University of Michigan, School for Environment and Sustainability. ORCID iD: 0000-0002-2391-8610. https://dx.doi.org/10.7302/22659
- Discipline:
- Science and Engineering
-
- Creator:
- Szuromi, Matthew P. and Stacey, William C.
- Description:
- The data and scripts are meant to show how burster dynamics determine response to a single biphasic stimulus. The files include data which show trends in the propensity of termination for different burster types and the MATLAB scripts used to generate this data. The MATLAB scripts also allow the user to generate their own data sets for alternative bursting paths and stimulus parameter combinations. Furthermore, they allow the user to visually examine the effects of single stimuli in the voltage timeseries and in state space. How the user can access these features of the script is described in the file "ReadMe.pdf."
- Keyword:
- Epilepsy, Stimulation, Modelling, Dynamics, Seizure, and Dynamotype
- Citation to related publication:
- (PROVISIONAL) Optimization of Ictal Aborting Stimulation Using the Dynamotype Taxonomy
- Discipline:
- Health Sciences, Engineering, and Science
-
- Creator:
- Thompson, Ellen P. and Ellis, Brian R.
- Description:
- Accurate prediction of physical alterations in carbonate reservoirs under dissolution is critical for development of subsurface energy technologies. The impact of mineral dissolution on flow characteristics depends on the connectivity and tortuosity of the pore network. Persistent homology is a tool from algebraic topology that describes the size and connectivity of topological features. When applied to 3D X-ray computed tomography (XCT) imagery of rock cores, it provides a novel metric of pore network heterogeneity. Prior works have demonstrated the efficacy of persistent homology in predicting flow properties in numerical simulations of flow through porous media. Its ability to combine size, spatial distribution, and connectivity information make it a promising tool for understanding reactive transport in complex pore networks, yet limited work has been done to apply persistence analysis to experimental studies on natural rocks. In this study, three limestone cores were imaged by XCT before and after acid-driven dissolution flow through experiments. Each XCT scan was analyzed using persistent homology. In all three rocks, permeability increase was driven by the growth of large, connected pore bodies. The two most homogenous samples saw an increased effect nearer to the flow inlet, suggesting emerging preferential flow paths as the reaction front progresses. The most heterogeneous sample showed an increase in along-core homogeneity during reaction. Variability of persistence showed moderate positive correlation with pore body size increase. Persistence heterogeneity analysis could be used to anticipate where greatest pore size evolution may occur in a reservoir targeted for subsurface development, improving confidence in project viability.
- Keyword:
- Carbonate dissolution, X-ray computed tomography, Porous media, Topology, and Persistent homology
- Citation to related publication:
- Thompson, E.P.; Ellis, B.R. (2023) Persistent Homology as a Heterogeneity Metric for Predicting Pore Size Change in Dissolving Carbonates. In Review.
- Discipline:
- Science and Engineering
-
- Creator:
- Hall, Ryan J. and Larson, Ronald G.
- Description:
- This is data is a large assortment of over 50 1,4-polybutadiene star-linear blends that can be used for assessing and developing predictive models. The data are presented in CSV files.
- Keyword:
- polymers, rheology, star-linear polymer blends, and shear rheology
- Citation to related publication:
- Hall, R., Desai, P. S., Kang, B.-G., Huang, Q., Lee, S., Chang, T., Venerus, D. C., Mays, J., Ntetsikas, K., Polymeropoulos, G., Hadjichristidis, N., & Larson, R. G. (2019). Assessing the Range of Validity of Current Tube Models through Analysis of a Comprehensive Set of Star–Linear 1,4-Polybutadiene Polymer Blends. Macromolecules, 52(20), 7831–7846. https://doi.org/10.1021/acs.macromol.9b00642
- Discipline:
- Science and Engineering
-
Resources for Training Machine Learning Algorithms Using CAM6 Simple Physics Packages
User Collection- Creator:
- Limon, Garrett
- Description:
- The collection contains the code and the data used to train machine learning algorithms to emulate simplified physical parameterizations within the Community Atmosphere Model (CAM6). CAM6 is the atmospheric general circulation model (GCM) within the Community Earth System Model (CESM) framework, developed by the National Center for Atmospheric Research (NCAR). GCMs are made up of a dynamical core, responsible for the geophysical fluid flow calculations, and physical parameterization schemes, which estimate various unresolved processes. Simple physics schemes were used to train both random forests and neural networks in the interest of exploring the feasibility of machine learning techniques being used in conjunction with the dynamical core for improved efficiency of future climate and weather models. The results of the research show that various physical forcing tendencies and precipitation rates can be effectively emulated by the machine learning models.
- Keyword:
- Machine Learning, Climate Modeling, and Physics Emulators
- Discipline:
- Science and Engineering
2Works -
- 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:
- Regoli, Leonardo H.
- Description:
- The research analyzed the response of nine PNI RM3100 magnetometers to radiation doses expected during a Europa lander mission. The radiation levels are drawn from the Europa Lander Science Definition Team report ( https://europa.nasa.gov/resources/58/europa-lander-study-2016-report). The sensors were tested up to a total ionization dose (TID) level of 500 kRad.
- Keyword:
- Magnetometer, Magneto-inductive, Europa, and Radiation
- Citation to related publication:
- Regoli, L. H., Moldwin, M. B., Raines, C., Nordheim, T. A., Miller, C. A., Carts, M., and Pozzi, S. A.: Radiation tolerance of the PNI RM3100 magnetometer for a Europa lander mission, Geosci. Instrum. Method. Data Syst., 9, 499–507, https://doi.org/10.5194/gi-9-499-2020, 2020.
- Discipline:
- Science and Engineering
-
- Creator:
- Limon, Garrett C.
- Description:
- The work guides the processing of CAM6 data for use in machine learning applications. We also provide workflow scripts for training both random forests and neural networks to emulate physic s schemes from the data, as well as analysis scripts written in both Python and NCL in order to process our results.
- Keyword:
- Machine Learning, Climate Modeling, and Physics Emulation
- Citation to related publication:
- Limon, G. C., Jablonowski, C. (2022) Probing the Skill of Random Forest Emulators for Physical Parameterizations via a Hierarchy of Simple CAM6 Configurations [Pre Print]. ESSOAr. https://10.1002/essoar.10512353.1
- Discipline:
- Engineering and Science
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