| 2021 |
spring |
Ball Aerospace |
Analysis of inclination variation of satellite coverage for the Contiguous United States |
Ball Aerospace uses CIRiS (Compact Infrared Radiometer in Space) and ground tracking to examine areas of the surface of the Earth. Previous semesters focused primarily on how many satellites were needed to fully cover the Earth's equator or a fixed-latitude arc between 2 longitudes. This project studies how the number of satellites and the angle of inclination (with respect to the equatorial plane) of the orbits of those satellites affects the overall coverage for a desired region within a given 24-hour period. In this context, coverage is represented by the aggregate set of satellite swath crossings of 2 arcs. |
| 2021 |
spring |
Colorado Energy Office |
Analyzing and modeling building electricity consumption patterns toward greening government (and its faster non-interactive version) |
The Colorado Energy Office provided data for 15 buildings’ total electricity consumption every 15 minutes for several years. This project studied the variability of these data in terms of averages and cycles on daily, weekly and longer time scales, plus random variability on shorter time scales, and differences between buildings. Simulations of the data were constructed and validated using ARMA (autoregressive moving average) and other methods e.g., assuming the consumption at any time, or the difference from the previous time etc., could be modeled as a simple function of recent data values. |
| 2021 |
spring |
National Renewable Energy Laboratory |
Optimal assignment of relaxation parameter in successive over-relaxation vs in algebraic multigrid |
Owing to the convoluted nature of reality, mathematicians often encounter problems involving systems of large, sparse matrices. Finding a solution to said problems which involve these matrices can be a very time-intensive proposition. From a mathematical point of view, different algorithms exist to assist in solving them. Focusing on the Successive Over Relaxation solver, this paper looks to investigate the optimal relaxation parameter ω for the solver. By applying algorithms in tandem with appropriate parameters, the efficiency of solving large, sparse matrices may be drastically improved. Initial findings include differences in the SOR solver as a standalone algorithm versus as a smoother. The choice of solver and role may drastically improve convergence rates. |
| 2021 |
spring |
National Renewable Energy Laboratory |
Sketching to accelerate computing QR factors |
NREL performs many massively parallel computations simulating time-dependent processes in volumes with n grid-point values, n being in the billions. Part of those computations involve solving sparse n-by-n linear equations quickly and accurately e.g., by finding an orthogonal basis Q for the 1st m unknowns of the n equations, with m no greater than n. This project studies the use of “sketching” i.e., embedding n dimensions randomly into k dimensions to accelerate computing Q, with k no less than m but k much less than n. |
| 2021 |
spring |
U.S. Geological Survey |
Study of hydrocarbon play data |
USGS provides many geological science and information services e.g., analysis of oil & gas well productivity. In this project, we created a Python notebook to read in a large quantity of publicly available oil & gas data in various file formats, scrub the data, create basic visualizations, partition data by hydrocarbon play (shared geological circumstances), calculate annual well counts, estimate annual production, analyse production rate by decline curve and perform further analyses. |
| 2020 |
fall |
Ball Aerospace |
Toward satellite coverage optimization for the Contiguous United States (and its notebook ---download and change filename extension from "txt" to "ipynb") |
Ball Aerospace is using the CIRiS (Compact Infrared Radiometer in Space) technology to better examine evapotranspiration at the Earth’s surface and to provide full coverage of the Earth within a 24-hour period. With this technology, Ball is able to track surface-level temperatures throughout the world daily. These data will help scientists and decision makers with evaluating drought conditions and climate modeling. This project will estimate satellite coverage of the contiguous United States and optimize the global coverage that was explored in previous projects. The goals of this project are to encompass the Contiguous United States as well as optimize the number of satellites that achieve full coverage, all of these data being collected in daylight. The impact of the project could lead to better visualization and optimization of more finite areas of the globe such as the coastal regions like the Gulf Coast of the United States to help analyze changing surface-level temperatures in order to more accurately depict extreme weather patterns. |
| 2020 |
fall |
CAIC |
A study on the correlation of weather station data and the occurence of wet avalanches (and its ipynb file) |
Wet avalanches are not well understood. Our goal is to analyze the data and find the major predictors and create a model to predict when a wet avalanche will occur within approximately an hour. This is to educate future students on the matter and to help them know more about wet avalanches. This is also for the sponsor, whom we can hopefully help with predicting these wet avalanches so that they can act to prevent injury to people in the backcountry e.g., giving enough time to block off a road or warning users about a predicted-avalanche area. |
| 2020 |
fall |
CEO |
Analysis of electric vehicle charging stations (and its ipynb file) |
Electric vehicles’ (EV) charging demand for electricity as well as the cost and fees of such varies over location and time. During peak demand times the demand fees tend to be higher as well, this results in a high rate for those who use EV. In order to determine a plan that is more cost-effective for users, it is helpful to determine the distribution of the EV charging events based on historical data. This will be accomplished by understanding the peak-demand charging energy in the different locations across the state as well as the peak-demand charging time throughout different periods e.g., hourly, daily, weekly. |
| 2020 |
fall |
NREL |
An Investigation on the optimal parameters of the SOR and GMRES solvers (and its ipynb file) |
Algebraic multigrid (AMG) solvers are computing methods that use hierarchical meshes and are designed to solve extremely large systems of equations with speed and efficiency. The goal of this project is to determine the optimal parameters for AMG to solve a given system of equations in the fewest iterations possible with the least error possible. Hopefully, doing this will mean that it can be upscaled to larger systems with reasonable accuracy. Mainly this project will consist of using the Python code package PyAMG to solve a problem suggested by Dr. Thomas, which was primarily provided in MATLAB. This will provide some knowledge to Dr. Thomas on the Python package and how it compares to the MATLAB solvers already in use at NREL. This Python code will create a foundation for future projects on the subject, both through the code developed and in the understanding of the basics of AMG solvers. Most of the work of this project will be on toy problems, which are used for testing, but once those solutions are optimized it can be used successfully on the simulated data that represent the air flow around wind turbines. |
| 2020 |
spring |
Ball Aerospace |
Ball Aerospace satellite coverage optimization (and its ipynb file) |
Ball Aerospace is preparing to launch satellites into orbit that are equipped with CIRiS (Compact Infrared Radiometer in Space) technology used to track evapotranspiration from the earth’s surface. It is crucial that Ball Aerospace can achieve full earth coverage in a twenty-four-hour period, and that this be done with the least amount of satellites possible. Given the initial results, we have reason to believe that seven satellites will not sufficiently achieve full earth coverage in a twenty-four hour period. This, of course, is assuming that all coverage must be attained during the day. |
| 2020 |
spring |
CAIC |
Predicting avalanche field in images using convolutional neural networks and edge detection (and its ipynb file) |
The Colorado Avalanche Information Center (CAIC) aims to detect the location and shape of avalanches from satellite images. We establish an optimal Convolutional Neural Network architecture by comparing a densely connected CNN with already established architectures VGG16, IRNv2 and RN50. By adjusting data generation parameters we determine that high dimensional data is preferred for training models as larger window size indicates better model fit and feature detection. Prediction outcome analysis suggests further refinement of prediction architecture with RGB data and polygon coordinates. |
| 2020 |
spring |
Colorado Energy Office |
Analysis of Charge Ahead Colorado grant program electric vehicle charging stations (and its ipynb file) |
This report summarizes and provides analysis for data gathered from Colorado Energy Office (CEO) electric-vehicle charging stations from May to December 2019. We emulated a third-party report which summarized similar data from May 2016 to April 2019, and verified that annual trends observed in the report continued through 2019. The CEO is also concerned with identifying peak demand times as a means of reducing demand charges. We were able to conclude that peak demand-times differ on weekdays from weekends, and identified peak demand-time intervals. Peak demand-times occur near midday on weekdays. |
| 2019 |
fall |
Ball Aerospace |
A study into satellite coverage and orbital equations (commentary by Prof. Fournier) (and its pynb file) |
Ball is developing a number of small satellite cameras for their evapotranspiration mission that will be placed on satellites within a fixed near polar orbit. The purpose is to provide full camera coverage of the Earth within a 24-hour time period. It is the intention of this report to explore the orbits and provide tools to answer the question of how many satellites are necessary to achieve the full coverage of the Earth in a given time-frame. We will do this by creating an Earth centered Earth fixed model of a satellite’s orbit imposing a swath projection onto the orbit to evaluate coverage. We are using the assumption that when the equator has been fully covered we have achieved full Earth coverage. |
| 2019 |
fall |
Water Systems Optimization |
Analyses of water-meter accuracies with respect to meter manufacturers and flow rates (commentary by Prof. Fournier) |
Are residential water meters accurate enough? Most likely not, but in order to estimate the accuracy for a specific make and model of water meter, adequate testing is required. To perform these tests, it is also important to procure an adequate sample size that is representative of the population, without being too costly. To that end, on Water Systems Optimization’s (WSO) behalf, we aspire to review their bootstrapping analysis and determine the minimum sample size that should be acquired. We also analyze the statistics of water-meter performance under different flow rates. |
| 2019 |
spring |
Ascend |
Identifying relationships and simulating pricing across weather and energy market nodes (and its ipynb files 1, 2, 3, 4) |
Identify key relationships in high-resolution market and weather data that inform the load and (non-)renewable production of energy; apply machine learning to reproduce and simulate the price of energy in the California market. |
| 2019 |
spring |
CAIC |
Applying the Kalman filter to SNOTEL snow depth data (and its ipynb file) |
Use Kalman filtering to decrease error in snow telemetry measurements and improve avalanche forecasts and risk assessment about travel into the back-country. |
| 2019 |
spring |
Spire |
Nonlinear statistical models for predicting stations surface fields |
Evaluate the use of a neural network and another nonlinear model to compare with a linear statistical model to improve windspeed forecasting. |
| 2019 |
spring |
Tech-X |
Tetrahedron meshes and hexahedron metrics (and its ipynb file) |
Take a physical model comprising a tessellation of some physical shape by thousands of joined tetrahedra, partition each tetrahedron into 4 cuboids (quadrilateral hexahedra) sharing an appropriately defined center vertex, and diagnose the resulting cuboidal tessellation in view of the sample distribution of aspect-ratio, skew and similar shape metrics over the model. |
