Now showing items 41-60 of 19258

    • Cobalt recovery from the Iron Creek deposit using physical beneficiation

      Anderson, Corby G.; Bishop, Emma; Spiller, D. Erik; De Moor, Emmanuel; Puvvada, George (Colorado School of Mines. Arthur Lakes Library, 2023)
      Cobalt is defined as a critical mineral by the U.S. Department of Energy, commonly used in lithium-ion batteries, jet turbines, and steel alloys. Currently, the U.S. is nearly completely dependent on imports for its cobalt supply. Due to this, efforts to mine and refine cobalt domestically are being pursued. This thesis describes part of the effort of Electra Battery Materials to create a functional cobalt mine at the Iron Creek deposit, located in the Idaho Cobalt Belt. The focus of this research is to examine the feasibility of physical beneficiation methods on different mineral samples in an attempt to improve the cobalt grade, and to create an economically feasible flowsheet when combined with the other research sections of this project. Specifically, the physical beneficiation methods tested were magnetic separation, heavy liquid separation, and electrostatic separation. The feed materials tested were a deposit sample, a bulk flotation concentrate, a thermal decomposition product of the bulk flotation concentrate, a differential flotation concentrate, and a thermal decomposition product of the differential flotation concentrate. Bond work index testing and sortation sampling was also performed on the deposit samples. It was determined that magnetic separation of the thermal decomposition products showed the most success in increasing the cobalt grade in the concentrate of all methods tested and is the most likely to be used in a flowsheet. Testing of the deposit samples and bulk flotation concentrate also showed promising results in the heavy liquid separation and electrostatic separation but are less likely to be used due to being less efficient than other already established methods. Preliminary leaching testing was then performed on the magnetic product of the thermal decomposition magnetic separation testing to examine the response.
    • Modeling and imaging marine vibrator data

      Sava, Paul C.; Almuteri, Khalid; Shragge, Jeffery; Jin, Ge; Ganesh, Mahadevan; Wang, Hua (Colorado School of Mines. Arthur Lakes Library, 2023)
      Marine vibrators are an emerging alternative technology to conventional air guns in ocean-bottom seismic acquisition. They promise to deliver greater low-frequency information about the subsurface while minimizing the adverse impact on marine wildlife. However, using marine vibrators introduces challenges not found in conventional air-gun-based acquisition. Even though marine vibrators move at a much slower velocity than the acoustic wave subsurface speed, source motion introduces a noticeable offset and time-dependent frequency shift to the data. Phase distortions also occur in seismic signals and are proportional to the source velocity and moveout of seismic events. The time-varying nature of the sea surface and the long duration of the seismic sweep present an additional set of modeling, processing, and imaging challenges. A dynamic sea surface significantly affects the phase and amplitude of seismic data, posing challenges for time-lapse studies, seismic deghosting, and surface-related multiple elimination. Conventional seismic data processing assumes a horizontal sea surface for simplification. However, characterizing the sea surface state and accurately modeling seismic data under such conditions is important for investigating the implications of realistic acquisition and for proper processing and imaging workflow design. In this thesis, I develop a numerical approach to model long-emitting non-impulsive sources in the presence of a time-varying sea surface using the tensorial acoustic wave equation. I also derive analytical expressions to predict the frequency shifts in the seismic signal due to source motion (Doppler effect) and predict the seismic wavefield in homogeneous media triggered by a moving source (Green’s function), which I use to validate the developed modeling approach. Furthermore, I use the developed tools to account for the source motion effects in reverse-time migration, mitigating the need for pre-processing steps to remove such effects from the seismic data. I present numerical examples that demonstrate the accuracy, stability, and robustness of the tensorial formulation of the acoustic wave equation in modeling and imaging marine vibrator data, even for typically unincorporated high source velocities in field data acquisition.
    • Rare-earth nickelates and novel III-V growth for neuromorphic computing

      Zimmerman, Jeramy D.; Warren, Emily L.; Schneble, Olivia D.; Brennecka, Geoffrey; Singh, Meenakshi; Wolden, Colin Andrew; Tellekamp, Brooks (Colorado School of Mines. Arthur Lakes Library, 2023)
      Neuromorphic computing aims to mimic the principles or functions of biological brains for improved speed and energy efficiency in computing. The popularity of bio-inspired neural network algorithms has already begun to show the potential improvements in speed and accuracy when processing large sets of data or performing abstract tasks, but improvements in energy efficiency only come from biomimetic hardware. With increasing demand for computing resources, increasing energy efficiency is a crucial goal. Developing neuromorphic hardware that approaches the spatial density and energy efficiency needed will require investment in new materials and fabrication techniques that will supplement or replace existing complementary metal-oxide-semiconductor technologies. These efforts must also consider scalability and repeatability for eventual large artificial neural network implementations. This work first presents a novel technique for the growth of III-V semiconductors on silicon that would enable their use for optoelectronic neuromorphic devices. Templated liquid-phase epitaxy is a scalable and low-cost technique that bypasses the need for organometallic precursors and can significantly improve material utilization. We focus on heteroepitaxial growth, as control of the crystallographic orientation is critical for device fabrication. These improvements make III-V semiconductors more applicable to low-cost device applications. The rest of this work will describe artificial neuron devices implemented in insulator-metal transition (IMT) materials. First, we use circuit simulations to evaluate the impact of thermal and electronic properties on the behavior of volatile neuron-like devices. By independently varying material parameters, we identify control of the IMT as a fundamental task for device engineering. Second, we discuss the growth of rare-earth nickelates and their application to artificial neuron devices. We show that these devices can be driven electrically via resistive heating consistent with the thermally-driven behavior of the film, and highlight some challenges in the implementation of neuronal devices.
    • Influence of alloy level, retained strain, and post-rolling cooling rate on microstructure development in hot-rolled steels

      De Moor, Emmanuel; Schweitzer, Jessie A.; Findley, Kip Owen; Cho, Lawrence (Colorado School of Mines. Arthur Lakes Library, 2023)
      There has been continued demand for hot-rolled, microalloyed steels with high strength, high toughness, and good weldability for applications such as oil and gas pipelines. Thermomechanical controlled processing (TMCP) coupled with accelerated cooling has been shown to produce high quality as-rolled plate and reduce costs. Judicious alloying with Nb and Mo can provide strengthening through grain refinement and transformation strengthening, while maintaining toughness. It is therefore pertinent to understand the relationships between deformation, alloying, and accelerated cooling to optimize TMCP schedules, alloy levels, and resultant plate microstructures. Four 0.05C microalloyed steel compositions were studied with Nb and Mo content ranging from 0.03-0.045 and 0.03-0.15 wt pct, respectively. Dilatometry was performed in situ during simulated TMCP processing with a Gleeble® 3500 system to study transformation behavior with different levels Nb and Mo content as well as different levels of deformation. Continuous cooling transformation (CCT) diagrams were constructed for each alloy utilizing cooling rates between 2 °C/s and a target 100 °C/s and 2 deformation levels, -0.4 and -0.6 total true strain in the austenite regime, to develop a range of microstructures. Isothermal testing to evaluate transformation after 2 levels of deformation was also performed to closer simulate plate coiling and examine isothermal transformation kinetics. Additionally, dilatometry testing without prior deformation was performed to decouple deformation and alloying effects on the kinetics of phase transformations. Increased deformation in the austenite non-recrystallization region increased formation of polygonal ferrite and acicular ferrite transformation through the creation of additional nucleation sites and led to finer resultant microstructures across all cooling rates. With increased cooling rate, transformation start temperatures were reduced and non-polygonal transformation products, such as acicular ferrite, bainite, and martensite, were favored. Increased Nb and Mo content increased the hardenability of the steel. Both were found to retard the polygonal ferrite transformation. However, Mo was found to have a complex effect. In the high Mo alloy, the bainite transformation kinetics were increased and bainite transformation was favored compared to acicular ferrite transformation.
    • Applications of porous organic cages for gas separations and storage

      Trewyn, Brian; Krishnan, Keerthana; Koh, Carolyn A. (Carolyn Ann); Crawford, James M.; Delgado-Linares, Jose G.; Kwon, Stephanie (Colorado School of Mines. Arthur Lakes Library, 2023)
      Porous Organic Cages (POCs) possess high surface area, uniform micropores and thermal and chemical stability which when combined with solid state molecular packing, not only makes them applicable in various functional applications, but also makes them stand apart from materials like metal organic frameworks, covalent organic frameworks, and zeolites. Held together by covalent bonds, POCs display a 3-dimensional pore connectivity in their crystalline form. Typically synthesized by imine bond condensation between a trialdehyde and diamine, the morphology control is directed by the diamine leading to unique packing of the cage molecule designated as CCX, and X can change from 1 denoting the name specific to the cage. Uniform pore size POCs have found themselves suitable for applications including catalysis, gas storage and gas separations. In this work, the capability of two prototypical POCs denoted as CC3 and CC2 with limiting pore aperture of 3.6 Å to selectively separate CO2 from N2 and H2 has been demonstrated. The adsorption selectivity of CC3 for CO2/N2 and CO2/H2 were ~8 and ~20 respectively. The adsorption selectivity of CC2 for CO2/N2 and CO2/H2 were ~9 and ~35 respectively. The synthesis of continuous and defect-free CC3 membranes were validated with helium permeability as high as 4.45 × 10−7 mol/ (m2 s Pa) and He/CH4 separation selectivity as high as 8. To expand knowledge of the formation of POCs, a new POC was synthesized from CC3 and CC2 POCs by “covalent scrambling” and extensive characterization was performed on the material to perceive its structure-property relation better. Programming with R was used to comprehend the crystallinity of the material with respect to its X-ray diffraction pattern. Some preliminary work was completed (sandwich membranes and composite membranes using mesoporous MCM-41 crystals) to pave the way for the future directions of this research is also presented in this work.
    • Efforts for durability enhancement for polymer electrolyte membranes and electrochemical devices

      Herring, Andrew M.; Kim, ChulOong "Christoph"; Knauss, Daniel M.; Wu, Ning; Samaniuk, Joseph R. (Colorado School of Mines. Arthur Lakes Library, 2023)
      Global warming and climate change are urgent global challenges driven by the notable increase in atmospheric carbon dioxide (CO2) resulting from fossil fuel combustion. International agreements, such as the Paris Agreement and the Kyoto Protocol, signify collective efforts to curtail greenhouse gas emissions and combat global warming. To achieve near-zero net CO2 emissions, transitioning to renewable energy sources, particularly hydrogen, is pivotal. Hydrogen offers promise as an energy carrier and industrial feedstock, with applications ranging from methanol and ammonia production, steel manufacturing, and using hydrogen as an energy carrier for fuel cell device applications. However, establishing a hydrogen-based energy grid necessitates prioritizing 'green hydrogen' production, generated using renewable energy sources, and development of efficient and economically feasible hydrogen-based energy devices, such as fuel cells and electrolyzers. For economic feasibility of the hydrogen economy, significant enhancement in durability coupled with performance of the electrochemical devices is crucial. In this study, efforts were made to enhance the chemical durability of proton exchange membrane fuel cells (PEMFCs) through the utilization of a heteropoly acid functionalized perfluorosulfonic acid (PFSA-VDF-HPA) membrane. A composite membrane was fabricated by applying the doctor-blade method onto a Kapton® liner, blending PFSA-VDF-HPA and 3M-PFSA. Notably, the density of HPA particles varied between the two sides of the membrane, with the liner-side exhibiting a higher concentration. When the HPA-dense liner-side was integrated into a fuel cell, specifically facing the anode, a significant improvement in chemical durability was observed under accelerated stress conditions (AST), utilizing a 25 cm2 active area fuel cell. To delve deeper into the properties of the PFSA-VDF-HPA membrane, four variations were synthesized by controlling the HPA loading through adjustments in the VDF anchoring group ratio of the starting polymer. Additionally, expanded-polytetrafluoroethylene (ePTFE) support was introduced to create reinforced membranes, to fabricate thin membranes (ca. 12μm), to mitigate mechanical degradation and the risk of electrical short circuits during chemical durability tests. The inclusion of ePTFE led to a more crystalline polymer structure. However, despite increased crystallinity, the synergistic effects of sulfonic acid and HPA functionalities contributed to higher water uptake and consequently, improved proton conductivity. Chemical durability testing was conducted under AST conditions with a larger active area (50 cm2). The results indicated that HPA loading was not the sole determinant of chemical durability enhancement, but an overall improvement was evident. In the final phase of this study, the performance and durability of anion exchange membrane water electrolyzers (AEMWE) were explored with a focus on transitioning away from precious platinum group metal catalysts and fluorinated polymers that are often produced with carcinogenic solvents. Three transition metal oxides—Co3O4, Mn2O3, and MnO2—with low kinetic overpotential and high catalytic activity were selected for the oxygen evolution reaction side of the AEMWE. The addition of these electrocatalysts improved kinetics and performance, although a limitation arose due to the maximum loading capacity of the catalysts. This limitation stemmed from the transition metal oxides' lack of electrical conductivity, effectively acting as insulators. Subsequently, 100 h durability tests were conducted at 750 mA/cm2 and 50˚C for each catalyst, revealing conditioning of the membrane electrode assembly (MEA) for all samples, with Co3O4 and MnO2 exhibiting more pronounced conditioning effects. No signs of membrane thinning nor statistically meaningful ion-exchange capacity were registered. Comparing before and after durability test electrochemical impedance spectroscopy (EIS) measurements and Fourier Transform Infrared Spectroscopy (FTIR) mapping indicated micron-sized rearrangements in the bulk membrane, with Co3O4 and MnO2 showing more significant changes compared to minimal alterations in Mn2O3. Furthermore, a shift in the OH peak in FTIR post-test suggested that water became less tightly hydrogen-bound to the polymer after 100 h operation.
    • Identifying thermo-kinetic parameters in lithium-sulfur battery models with optimization algorithms and the effect on model predictive capability

      DeCaluwe, Steven C.; Korff, Daniel; Ranville, James F.; Porter, Jason M.; Kee, R. J. (Colorado School of Mines. Arthur Lakes Library, 2023)
      The work presented here explores the impact of reaction mechanism complexity on model-predictive capability for physics-based lithium-sulfur (Li-S) battery models. The conversion nature of Li-S cathodes includes intermediate species, called polysulfides, that are produced which are soluble in liquid electrolyte. These soluble polysulfides (PSs) lead to many challenges for commercializing Li-S batteries. Physics-based models provide a route to improving understanding of Li-S batteries; however, there are many questions remaining with regards to reaction mechanism complexity, thermo-kinetic parameters for species and reactions, and the impact these things have on model veracity. This work demonstrates that assumptions regarding the solvation structure of species being modeled and the reaction mechanism used has a significant impact on results at multiple levels. Due to the complexity of Li-S batteries, cell voltage during charge/discharge cycles is only one quantitative element to phenomena that are occurring during use. The evolution of species concentrations throughout charge/discharge is also crucial to guide design and operation decisions for Li-S batteries to avoid rapid degradation in battery performance. Increasing reaction mechanism complexity increases the interplay between species in the electrolyte. However, the increase in mechanism complexity increases the number of thermo-kinetic parameters, for which there is little or no good knowledge of physically meaningful values. In order to address this gap, the global optimization method differential evolution (DE) is used to explore parameter spaces in a much more thorough way than could be done by hand. The results demonstrate that improvement in goodness of fit with experimental data is significant and the impact on model predictive capability further shows the importance of the reaction mechanism used.
    • Development and application of a modified rock mass rating system for fault zones

      Gutierrez, Marte S.; Dosch, John M.; Pei, Shiling; Zhou, Wendy (Colorado School of Mines. Arthur Lakes Library, 2023)
      One of the most problematic geological conditions that can be encountered in a tunnel excavation is a fault zone. Fault zones are zones of sheared discontinuities that can range from tens of meters to hundreds of kilometers in length. When a tunnel excavation is unprepared to deal with these fault zones, a fault has the potential to cause damages to structural support systems, clogging of a tunnel boring machine (TBM), very large deformations, increases to project time and cost, and even total project stoppages. Understanding the characteristic of a fault zone and the expected responses from the excavation can help prevent these issues. This thesis focuses on these steps for a new bore of the Eisenhower Johnson Memorial Tunnel (EJMT), a tunnel about 60 miles west of Denver, Colorado. The EJMT runs through a clay-rich fault zone and experienced significant convergences, problems, and delays during its construction. Avoiding these mistakes of the past for a new bore is key. This thesis first focuses on a qualitative discussion on faults, fault infilling, and excavation methodology effectiveness for fault zones. This thesis then covers the history of the rock mass rating system (RMR) and the system’s deficiencies when evaluating fault zones. It was found that the current RMR system overpredicts the rock quality of fault zones. A modified RMR system is proposed that accounts for the various behaviors of fault zones and this new RMR system is applied to the fault zones of the Eisenhower Memorial Tunnel. With these new RMR values, insights into tunneling through fault zones, and existing correlations to the advance rates of excavation methods of drill and blast and various TBM types, the double shield TBM was selected as the excavation method that will provide the highest overall advance rate and expected stability for a new bore of the EJMT.
    • Bringing optical super-resolution metrology into advanced manufacturing

      Squier, Jeff A.; Cottrell, Seth T.; Gockel, Joy; Adams, Daniel E.; Durfee, Charles G. (Colorado School of Mines. Arthur Lakes Library, 2023)
      Spatial Frequency Modulated Imaging (SPIFI) is a method of structured light imaging. The method to modulate the light is a temporally-varying sweep through a linear set of supported frequencies. In this dissertation I present a method to increase the speed of modulation. This increases the line image creation speed. I demonstrate this method by creating line images 10 times faster than current methods, and discuss the feasibility of creating line images 1,000 times faster than current methods with commercially available scan mirrors. The high-speed SPIFI system is benchmarked for resolution and used to image in an Additive Manufacturing (AM) environment. Next I introduce a method to modulate the entire spatial field at once. This single-shot SPIFI technique spatially modulates a broadband source by wavelength. Single-shot SPIFI enables modulation at the pulse duration of the source and at the repetition rate of the source. I demonstrate the technique using a single 30 femtosecond pulse.
    • Learning-based adaptive and stable in-hand manipulation in simulation and real-world environments

      Zhang, Xiaoli; Tao, Lingfeng; Petruska, Andrew J.; Williams, Thomas; Wakin, Michael B. (Colorado School of Mines. Arthur Lakes Library, 2023)
      Dexterous in-hand manipulation is one of the essential functions for intelligent robots but also challenging to solve due to the high degrees of freedom in control and the complex interaction with objects. Deep Reinforcement Learning (DRL) has shown its abilities to solve dexterous in-hand manipulation, which enables the robot to learn a control policy by interacting with the environment. Even though learning-based in-hand manipulation is promising for the broad adoption of dexterous robot hands, the training and deployment of the DRL policy still hold significant challenges: 1) existing approaches focus on training a single robot-structure-specific policy through the centralized learning mechanism, lacking adaptability to changes like robot malfunction; 2) the sparse reward is preferred to dense rewards because it focuses on task completion with no constraints to the manipulation behaviors, making the training easier. However, training without behavior constraints may lead to aggressive and unstable policies, which are insufficient for safety-critical tasks; 3) current simulation to real-world transfer methods force the DRL to accommodate and adapt to the limited information in the real world with ambiguous and high-dimensional input that cannot maximize the benefit of the simulation’s rich information, reducing data explicitly and learning efficiency. Three research objectives are developed to address these issues: 1) developing a multi-agent approach that models the in-hand manipulation as a cooperation task and enables local observation and experience synchronization to improve policy adaptability and generalizability; 2) constraining the manipulation behavior with finger-specific shadow rewards constructed from the state-action occupancy measure and enabling information sharing across the policies updating for consensus training; 3) proposing a curriculum-based sensing reduction method to enable the DRL to start the training with the rich feature space for higher training performance, then get rid of the hard-to-extract features step-by-step to gradually adapt to the real-world. The reduced sensor signals are replaced with random signals generated by a deep random generator to remove the dependency between the output and the reduced sensors and avoid creating new dependencies. Overall, this dissertation presents a comprehensive learning-based framework that improves the practicability of the training-to-deployment process of the DRL-based in-hand manipulation.
    • Satellite data reveals the start of Canada's wildfire season

      Zhizhin, Mikhail; Ziv, Kristin; Elvidge, Christopher; Bazilian, Morgan; Colorado School of Mines. Payne Institute for Public Policy (Colorado School of Mines. Arthur Lakes LibraryColorado School of Mines. Payne Institute for Public Policy, 2024-05-16)
      Payne Institute Earth Observation Group Research Associate Mikhail Zhizhin, Communications Associate Kristin Ziv, Senior Research Associate Christopher Elvidge, and Director Morgan Bazilian write about how as of May 14, 2024, there are 143 active wildfires in Canada, and 39 are out of control, according to Canadian experts and officials. The Earth Observation Group has calculated the temperatures and spatial extent of active burning across Canada with their Nightfire algorithm applied to data collected by NOAA's Visible Infrared Imaging Spectrometer Suite (VIIRS).
    • Navigating commercial advisory in the VCM

      Andreatta, Jared; Handler, Bradley P.; Colorado School of Mines. Payne Institute for Public Policy (Colorado School of Mines. Arthur Lakes LibraryColorado School of Mines. Payne Institute for Public Policy, 2024-05-16)
      School of Mines Mineral and Energy Economics Masters candidate Jared Andreatta and Sustainable Finance Lab Program Manager Brad Handler write an explainer of the various types of commercial advisory services firms that participate in the Voluntary Carbon Market (VCM). These advisory firms primarily help buyers find, evaluate and transact carbon offset credits, but offer distinct approaches.
    • Satellite data captures power outages in Sudan's civil war

      Zhizhin, Mikhail; Ziv, Kristin; Elvidge, Christopher; Bazilian, Morgan; Colorado School of Mines. Payne Institute for Public Policy (Colorado School of Mines. Arthur Lakes LibraryColorado School of Mines. Payne Institute for Public Policy, 2024-05-19)
      Payne Institute Earth Observation Group Research Associate Mikhail Zhizhin, Communications Associate Kristin Ziv, Senior Research Associate Christopher Elvidge, and Director Morgan Bazilian write about how a horrible full-scale civil war in Sudan is creating chaos, anarchy, mass starvation, and the world's largest population of internal refugees – approximately nine million.  The researchers have created a temporal profile of nighttime lights for Khartoum where seasonal variations in lights within a year can be seen, but the interannual radiance was stable until the conflict started in April 2023.
    • Classifying pulse shapes from superconducting tunnel junctions for the BeEST experiment

      BeEST Collaboration; Taylor, John; Leach, Kyle G.
      The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment aims to detect physics beyond the Standard Model by measuring atomic recoils from the electron capture decay of Beryllium-7 (Be-7). The experiment utilizes Superconducting Tunnel Junction (STJ) sensors to measure the daughter recoil kinetic energy spectrum to search for neutrino-coupled Beyond-Standard-Model physics. This work presents systematic studies that aim to distinguish between events occurring in the top and bottom electrodes of the STJs to search for the presence of a line-splitting artifact that could mimic a heavy neutrino signal. This is accomplished by analyzing the rise and fall times of the electrical pulses generated by the nuclear decays. Two primary techniques, 10-90% Rise Time Analysis and Charge Integration, are employed to investigate the pulse characteristics. While the former exhibits challenges in noise and pile-up events, the latter reveals a clear separation in the data, indicating a splitting effect caused by the STJ detector or the data acquisition system. The study proposes further investigation into the segregation observed and explores alternative methods for event separation.
    • Reconstructing high-resolution 2D data from low-resolution inputs using a super-resolution conditional generative adversarial network

      Alnabbat, Mohammed; Bernstein, Brett; Zhang, Mengli
      Super-resolution is an image processing technique that takes a low-resolution image and makes it high-resolution (Nasrollahi and Moeslund, 2014). Recent studies in image processing and medical imaging use Super-Resolution Conditional Generative Adversarial Networks (SRCGANs) to achieve super-resolution, successfully generating high-resolution images that are perceptually indistinguishable from real images (Nasser et al., 2022). We apply the concept of super-resolution to gridded gravity anomalies and train an SRCGAN to learn their complex signal structures and generate high-resolution data from coarsely-sampled grids. Typical generative adversarial networks (GANs) consist of two neural networks, a generator G and discriminator D, which learn and improve by competing with each other. G generates an image and D attempts to determine if it is a real or generated image. G then updates to make the generated output more realistic, and D updates to better distinguish between real and generated images. We adapt the SRCGAN architecture from Ledig et al. (2017) for use with gridded gravity data. Our generator G takes a low-resolution grid X, coarsely-sampled from a full data set Y, as input, and outputs an up-sampled, high resolution grid ˆY . Our network is trained and tested using gridded, regional gravity data from Australia (GeoscienceAustralia, 2023). These fully-sampled data Y are resized to a common shape of 128x128 and down-sampled by a factor of 4 to shape 32x32 to obtain the network inputs X. A total of 3546 pairs of fully-sampled and coarsely-sampled grids are used for training, 799 pairs are used for validation during training, and 88 pairs are reserved to test the network after training. The trained generator is tested with one of the reserved data pairs. Figure 1 shows the fully-sampled grid Y, coarse grid X, and the high-resolution grid ˆY generated from X. We are interested in how well the generator can reconstruct high-resolution signal from just the low-resolution input, so we quantify the increase in information by comparing the differences Y −X and Y −ˆY , histograms of which are in figure 1, their mean absolute error (MAE), and their root mean square error (RMSE). These metrics are summarized in table 1. The difference between the fully-sampled data and the coarse data Y −X produces a high MAE and RMSE and is characterized by a noticeably-broad spectrum of differences. The comparison between Y and ˆY yields lower metrics and a sharpening of the histogram. The improved metrics from the generated high-resolution data show that our trained SRCGAN generator can reconstruct missing signal structure from coarsely-sampled, gridded gravity data. The generated grid is upscaled in size by a factor of 4 in both directions while maintaining the integrity of the input signal. From the histogram of differences, we understand that the generated high-resolution data closely resembles the full data, discrepancies in which are due to the SRCGAN not completely reconstructing the high-frequency content. This may be improved through further adjusting and tuning of the network and the network training process. These results are a promising look into what may be a robust and versatile data reconstruction method.
    • LEEDing power back to communities through green building codes: advice for policymakers considering LEED certification

      Li, Nathan; Colorado School of Mines. Payne Institute for Public Policy (Colorado School of Mines. Arthur Lakes LibraryColorado School of Mines. Payne Institute for Public Policy, 2024-05-10)
      Payne Institute Student Researcher Nathan Li compares goals of original, local green building codes and their potential for projects to use LEED certification as a path of compliance. By using his professional experience in LEED certification to analyze these codes' language and priorities, he provides guidance on the applicability of LEED to achieve energy efficiency and renewable energy goals set by jurisdictions.  Nathan then makes suggestions to policymakers not to rely on the widespread acceptance of LEED to communicate a sustainability commitment, but instead use locally specific codes that require needed changes in their communities.