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At least 163 records · Page 9

Quality Guidelines for Energy System Studies - Capital Cost Scaling Methodology: Revision 4a Report

Costs are frequently required as part of systems analysis work at NETL. Many of the cost results provided as part of systems analysis work were created with the use of scaling, since obtaining new vendor-supplied cost quotes for each category developed by NETL would be prohibitively time consuming and costly. Additionally, many of the technologies being investigated by NETL have not progressed far enough to have quotable costs. The costs are scaled from a quote for a similar plant configuration by use of various equations that typically employ at least one process parameter (e.g., coal-feed rate, oxidant-feed rate) and often an exponent. The primary purpose of the exponent is to account for economies of scale (i.e., as equipment size gets larger, it gets progressively cheaper to add additional capacity). The purpose of this section of the QGESS report is to provide a standard basis for scaling costs, with specific emphasis on scaling exponents. The intention of having a standardized document is to provide guidelines for proper procedures to reduce the potential of errors and increase credibility through consistency.

99 GENERAL AND MISCELLANEOUS↗

Collaborative VR/AR Data Visualization Tool

This is the final report on Phase II SBIR for the development of a collaborative VR data visualization tool. In the 15 months of the Phase II, we have met and exceeded most objectives that we outlined for ourselves in the proposal. COVID19 has caused us to do some thing differently, but in fact the outcome is better for the development - we were meant to have traveled to institutions in the UK and EU to show the capabilities in April, but instead we have got into an iterative cycle in-house of weekly testing of the new features and functions. This is working well, so we will soon have the ability to share the application with collaborators in remote locations, without the need to travel. We are also making short videos of the features to share with those afar, again mitigating the need to travel and demonstrate in-person our new capabilities. That said, we are behind on getting input from the Beta testers, but when we do get their input it will be to test features and functions that are working, and not failing due to some glitch, which in turn will more likely lead to the acceptance of the product. One of our goals is to have a near-term commercial product, and we are tantalizingly close to it with commercial interest from LANL, Survice and other entities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Puerto Rico Historical Climate Analysis: A closer look at complex tropical terrain

Small tropical islands like Puerto Rico are especially vulnerable to climate change impacts, yet are often underrepresented in most datasets because the spatial resolution is too coarse to sufficiently cover their complex terrain. This study was done to better understand how the climate has changed in the various regions of Puerto Rico, which will support a transition to renewable energy and aid in projecting future climate impacts on the residents and land they live on. This study used multiple datasets including Daymet, a daily surface weather and climatological summary; European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5); and station observations. The climate variables examined here include minimum and maximum near-surface air temperature, daily precipitation, incident shortwave radiation, and large-scale upper atmosphere conditions. The time periods cover the years 1950–2019. Results in both Daymet and station observations show long-term warming trends throughout every season. In particular, the minimum winter temperatures increased the most compared with maximum and mean air temperature. Northeast Puerto Rico, where the majority of the island’s population is located, experienced the largest warming. Summertime precipitation has decreased over time, and spring and fall precipitation has increased. The largest increase in fall is because there has been more available precipitable water, lower sea-level pressure, and favorable cyclonic circulations from the trade winds over the past seven decades. Overall, wet days are getting wetter, while dry days are getting drier. While there are good solar energy potential, we see a long-term decreasing trend in shortwave radiation over time in all seasons across entire island, possibly due to the increase of cloud cover.

54 ENVIRONMENTAL SCIENCES↗

Transmission Optimization with Grid Enhancing Technologies Fact Sheet

The Transmission Optimization with Grid Enhancing Technologies (TOGETs) project is funded by the Department of Energy (DOE) Office of Electricity (OE) and Wind Energy Technologies Office (WETO). Idaho National Laboratory’s TOGET Task force consists of regulatory, utility, system operator, vendor, academic, and other industry participants, who will guide a two-pronged approach to fill in gaps on publicly available knowledge of GETs and conduct a full scale, multi-faceted field exercise. Ultimately the project aims to test, verify, and validate deployed GETs in a transmission system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

TOGETs Overview

The Transmission Optimization with Grid Enhancing Technologies (TOGETs) project will guide future research to fill in gaps on publicly available knowledge of Grid Enhancing Technologies (GETs) and conduct a full scale, multi-faceted field exercise. Ultimately the project aims to test, verify and validate deployed GETs in a transmission system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

FRAM Isotopic Analysis of High-Resolution CZT Data

H3D Inc. has introduced a new type of CZT detectors that has resolution several times better than that of a typical, single crystal CZT detector. The better resolution has made it easier for software codes to analyze its spectra for isotopic composition of nuclear materials. The Fixed-energy Response-function Analysis with multiple efficiency (FRAM) is one of such software codes. The good peak resolution of the H3D CZT detectors allows the current FRAM v.6.1 and earlier to successfully analyze uranium spectra with minimal modification of the parameter sets and get reasonable results. (A parameter set governs how an analysis is performed.) The exceptionally large high-energy tail of the peaks makes it difficult to achieve good uranium results and impossible to successfully analyze plutonium spectra. The FRAM code needed to be modified to better fit the high-energy tail of the peaks in order to analyze plutonium data and to get better uranium analysis results. Results of this modification, encoded in beta version FRAM v.7.0i, are reported herein.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

FRAM Isotopic Analysis of High-Resolution CZT Data [Slides]

Abstract: H3D Inc. introduced a new type of CZT detectors with resolution several times better than that of a typical CZT; The current FRAM v.6.1 can analyze uranium spectra with minimal modification of the parameter sets and get acceptable results; The exceptionally large high-energy tail of the peaks makes it difficult to achieve good uranium results and impossible to successfully analyze plutonium spectra; The FRAM code needed to be modified to better fit the high-energy tail of the peaks to analyze plutonium data and to get better uranium analysis results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗

End-Use Savings Shapes: Measure Documentation: Add Exhaust Air Heat/Energy Recovery

This documentation focuses on a single end-use savings shape measure—Add Exhaust Air Heat/Energy Recovery. This measure adds exhaust air energy recovery or heat recovery to existing air handling units (AHU) with outdoor air. Systems that already have energy/heat recovery are not modified. Furthermore, food service building types are also not modified by this measure due to the added complication of integrating cooking hood exhaust that could cause heat exchanger fouling from kitchen exhaust. In total, this measure is applicable airloops serving ~70% of the floor area in ComStock. In practice, energy/heat recovery systems are retrofitted to existing air delivery systems either as separate systems that provide outdoor air to the AHUs or are directly integrated to an AHU; the modeling approach used in this study is agnostic of the energy recovery type and simply accounts recovery effectiveness, added static pressure, and other controls which are described further in this document. Energy recovery with sensible and latent exchange gets added in humid climate zones, while heat recovery with sensible-only exchange gets added in drier climate zones. Energy recovery is modeled as a fixed membrane plate counterflow heat exchanger, while heat recovery is modeled as a sensible-only fixed aluminum plate counterflow heat exchanger. Both systems include a bypass (for temperature control and economizer lockout) and electric resistance preheat coil for frost prevention.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Connecting Nitrogen Transformations Mediated by the Rhizosphere Microbiome to Perennial Cropping System Productivity in Marginal Lands

The demand for energy from biofuel production is increasing, prompting concerns about the environmental impact and long-term sustainability of bioenergy cropping systems. These cropping systems will make up much of our future landscapes, and threaten to take the place of food cropping systems. Many life cycle analyses of bioenergy sustainability focus on carbon accrual and budgets, since they want to maximize carbon accrual while producing alternative fuel. Less attention has been given to nitrogen (N) dynamics in these systems. N is the most commonly limiting nutrient for plants, but applying nitrogen fertilizer- as we do for most cropping systems – is harmful to the environment, energetically costly, and produces greenhouse gases. In other words, adding nitrogen by fertilizer bioenergy systems could add to the very problems (climate change) it is trying to address. This is especially true for the areas that are proposed for bioenergy systems: marginal lands. These more degraded lands do not complete with food crops, but do have limited nitrogen. If we are to use these marginal lands for bioenergy, we need to understand the mechanisms regulating nutrient acquisition, and identify ways that bioenergy crops can get nitrogen in sustainable ways. Nutrient acquisition in the soil is performed by microbes in the root zone, or rhizosphere. Microbes can either mineralize nitrogen in the soil (from organic forms) or fix nitrogen from the air, in a process called nitrogen fixation. The goal of our project was thus to understand how the rhizosphere microbiome provides nutrients to bioenergy crops on marginal lands. We focus especially on the process of nitrogen fixation, since it has potential to get “fertilizer for free” that has much less environmental harm. We investigated this goal using sites from the DOE Great Lakes Bioenergy Research Center (GLBRC) in the upper Midwest, and associated lab and ‘omics methods. We group our findings into three major areas. First, we showed that nitrogen fixation, the conversion of N2 gas from the air to ammonium that is usable by plants, is performed in bioenergy soils, and benefits switchgrass crops. While more well-studied in leguminous plants, free-living nitrogen fixation can occur in some systems, and represents a potential opportunity to gain ‘free’ sustainable nitrogen source. We identified the nitrogen fixing bacteria that were most active in providing switchgrass with N, and showed that the drivers of nitrogen fixation occurred at a microscale; it is not well-predicted by bulk variables like soil moisture or plant phenology. Second, we showed that nitrogen fixation is not suppressed by long-term fertilizer. We expected that plentiful nitrogen would reduce the symbiotic relationship between nitrogen fixers and plants, and ‘downregulate’ fixation. We did not find evidence for this, either after long-term fertilizer in the field, or short-term fertilizer in the greenhouse. Finally, we identified the root exudates, carbon compounds that are emitted from the root, that best stimulate nitrogen fixation. We found that carbohydrates were better at stimulating fixation than organic acids. We expected these exudates to be emitted from the plant in periods of high N demand, but we found they are emitted when N is plentiful. This suggests that the stimulation of N fixation by plants is a passive process. Overall, we show that nitrogen fixation has potential to support bioenergy cropping system, and future management could develop ways to maximize it. However, this may not be best achieved via the plant – we found very little evidence of a ‘transactional’ system by which plants are controlling when and where nitrogen fixation is stimulated. It will be better to understand how management practices like planting and fertilizer application affect the microscale soil dynamics, which will determine nitrogen fixation rates.

59 BASIC BIOLOGICAL SCIENCES↗

Efficient and choreographed quality-of- service management in dense 6G verticals with high-speed mobility requirements

Future 6G networks are envisioned to support very heterogeneous and extreme applications (known as verticals). Some examples are further-enhanced mobile broadband communications, where bitrates could go above one terabit per second, or extremely reliable and low-latency communications, whose end-to-end delay must be below one hundred microseconds. To achieve that ultra-high Quality-of-Service, 6G networks are commonly provided with redundant resources and intelligent management mechanisms to ensure that all devices get the expected performance. But this approach is not feasible or scalable for all verticals. Specifically, in 6G scenarios, mobile devices are expected to have speeds greater than 500 kilometers per hour, and device density will exceed ten million devices per square kilometer. In those verticals, resources cannot be redundant as, because of such a huge number of devices, Quality-of-Service requirements are pushing the effective performance of technologies at physical level. And, on the other hand, high-speed mobility prevents intelligent mechanisms to be useful, as devices move around and evolve faster than the usual convergence time of those intelligent solutions. New technologies are needed to fill this unexplored gap. Therefore, in this paper we propose a choreographed Quality-of-Service management solution, where 6G base stations predict the evolution of verticals at real-time, and run a lightweight distributed optimization algorithm in advance, so they can manage the resource consumption and ensure all devices get the required Quality-of-Service. Prediction mechanism includes mobility models (Markov, Bayesian, etc.) and models for time-variant communication channels. Besides, a traffic prediction solution is also considered to explore the achieved Quality-of-Service in advance. The optimization algorithm calculates an efficient resource distribution according to the predicted future vertical situation, so devices achieve the expected Quality-of-Service according to the proposed traffic models. An experimental validation based on simulation tools is also provided. Results show that the proposed approach reduces up to 12% of the network resource consumption for a given Quality-of-Service.

42 ENGINEERING↗

Host genetics and gut microbiota composition: Baseline gut microbiota composition as a possible prognostic factor for the severity of COVID-19 in patients with familial Mediterranean fever disease

It is known that the gut microbiome of a healthy person affects the process of COVID-19 after getting infected with SARS-CoV-2 virus. It is also believed that colchicine can alleviate the severity of COVID-19. Current investigations aimed to evaluate the associations between the baseline gut microbiota composition of healthy and Familial Mediterranean fever (FMF) - carrier Armenian men populations, and the severity of the COVID-19 disease after their infection with the SARS-CoV-2. The study has a purpose of answering three core questions: i. Do the characteristics of gut microbiome of Armenians affect the course of COVID-19 severity? ii. How does the COVID-19 disease course on go for FMF patients who have been taking colchicine as a medication over the years after getting infected with SARS-CoV-2? iii. Is there an initial gut micribiota structure pattern for non-FMF and FMF patients in the cases when COVID-19 appears in mild form? The gut microbiota composition in non-FMF and FMF patients before the first infection (mild and moderate course of COVID-19) was considered. COVID-19 was diagnosed by SARS-CoV-2 nucleic acid RT-PCR in nasopharyngeal swab and/or sputum. The number of patients with male FMF with mild COVID-19 was approximately two times higher than that of non-FMF male subjects with COVID-19. In addition, an association of COVID-19 disease severity with the baseline gut Prevotella, Clostridium hiranonis, Eubacterium biforme, Veillonellaceae, Coprococcus, and Blautia diversities in the non-FMF and FMF populations were revealed by us, which can be used as risk/prognostic factor for the severity of COVID-19.

60 APPLIED LIFE SCIENCES↗

An Electron-scattering Time Delay in Black Hole Accretion Disks

Abstract Universal to black hole X-ray binaries, the high-frequency soft lag gets longer during the hard-to-intermediate state transition, evolving from ≲1 to ∼10 ms. The soft lag production mechanism is thermal disk reprocessing of nonthermal coronal irradiation. X-ray reverberation models account for the light-travel time delay external to the disk, but assume instantaneous reprocessing of the irradiation inside the electron-scattering-dominated disk atmosphere. We model this neglected scattering time delay as a random walk within an α -disk atmosphere, with approximate opacities. To explain soft lag trends, we consider a limiting case of the scattering time delay that we dub the thermalization time delay, t th ; this is the time for irradiation to scatter its way down to the effective photosphere, where it gets thermalized, and then scatter its way back out. We demonstrate that t th plausibly evolves from being inconsequential for low mass accretion rates m ̇ characteristic of the hard state, to rivaling or exceeding the light-travel time delay for m ̇ characteristic of the intermediate state. However, our crude model confines t th to a narrow annulus near peak accretion power dissipation, so cannot yet explain in detail the anomalously long-duration soft lags associated with larger disk radii. We call for time-dependent models with accurate opacities to assess the potential relevance of a scattering delay.

79 ASTRONOMY AND ASTROPHYSICS↗

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗

Semi-Transparent Perovskite Solar Cells in a Stacked Tandem Module: Cooperative Research and Development Final Report, CRADA Number CRD-19-00810

This project seeks to develop device design, materials composition, and processing tools and parameters to fabricate semi-transparent perovskite solar cells and modules for application in stand-alone products or added to other solar cells in a mechanically stacked tandem configuration. This technology presents significant advanced manufacturing challenges and opportunities in getting to scale, including development of perovskite inks, scalable perovskite and heterojunction deposition and annealing processes, heterojunction composition, transparent electrode composition and deposition process, anti-reflection layer composition and deposition process, and cell to module integration processes. Modification 5: The proposed project seeks to develop device design, materials composition, and processing tools and parameters to fabricate semi-transparent perovskite solar cells and modules for application in stand-alone products or added to other solar cells in a mechanically-stacked tandem configuration. This technology presents significant advanced manufacturing challenges and opportunities in getting to scale, including development of perovskite inks, scalable perovskite and heterojunction deposition and annealing processes, heterojunction composition, transparent electrode composition and deposition process, passivation layers including in module scribes, anti-reflection layer composition and deposition process, and cell to module integration processes. Advanced metrology and characterization will be performed on perovskite films, cells and module. Furthermore, we will examine module or materials recycling for circular economy considerations. Modifcation 6: Gigahertz frequency microwave pump-probe spectroscopies are highly sensitive to thin film semiconductor photoconductivity of individual and stacks of layers that comprise perovskite solar cells. As such, these techniques will be used to qualify reproducibility and quality correlations during the manufacturing process. Modification 7: Mechanical adhesion of top contacts within perovskite modules significantly impacts the durability of the module when exposed to accelerated degradation testing. The adhesion between the perovskite/transport layer interface and the transport layer/top contact interface are both very sensitive small changes in processing. ALD processing conditions of the transport layer will be tuned to optimize the mechanical adhesion within the perovskite module stack.

14 SOLAR ENERGY↗

Dual Energies in the LCLS Copper Linac

For LCLS-II two undulators were installed at SLAC, one for soft and one for hard x-rays. Before the super-conducting linac gets turned on the copper linac is providing beams at 120 Hz to these two beam destinations. The 120 Hz can be split in many different ratios between soft and hard via a pulsed magnet. To get an optimized beam for the quite different photon energies the pulsed linac components like modulators and RF can provide many different beam parameters, mainly energies and bunch lengths for the two undulator lines. How this was implemented with timing setups of triggers and finally after the split the necessary matching of the transverse phase space will be discussed.

Decker, Franz-Josef↗

Incorporating the Impacts of Climate Change on Hydrology in a Performance Assessment Model - 20403

The evidence of climate change is increasingly well-documented and impacts should be incorporated in performance assessment studies. The current climate literature provides both observational evidence and climate model projections of climate trends and/or climate change in the late 20. and early 21. centuries for North America and the northeast United States. Probabilistic modeling is a core requirement for quantifying uncertainty and evaluating its impacts. Not evaluating future climate states in a performance assessment because of the existence of uncertainty is contradictory to good modeling practices - the most uncertain issues and parameters require the most attention in effective probabilistic modeling. Excluding climate change limits development of modeling information that could aid in effective decision making. In this work we develop methods to use the output from hydrologic models and analysis of historical aerial imagery to quantify and implement the impacts of climate change on hydrologic processes at a nuclear waste site in West Valley, New York. Specifically, we used the HELP (Hydraulic Performance of Landfill Performance) model to characterize key hydrologic processes under both current and future climate conditions to assess the impacts of changing climate on hydrology. A suite of previous climatic models were reviewed and synthesized to produce a cohesive representation of the current state of knowledge of the impact of climate change on important model inputs such as precipitation. Output from the HELP simulations was coupled to the GoldSim model that was used to develop the Probabilistic Performance Assessment (PPA) approach through the application of a novel 'nearest neighbor' technique. First, several thousand realizations were generated from the HELP model using a Latin Hypercube experimental design to ensure adequate coverage of the parameter space of explanatory variables used to drive HELP. For example, porosity is a physical parameter that is used as an input to both HELP and the GoldSim PA model. We then ran sensitivity analysis (SA) algorithms on the output of HELP for each of the responses of interest. For each predictor, each time we build an SA model we get a different value for the sensitivity index (SI). From the collection of all the SA models, the average was computed among all of the SIs to represent the predictor within the context of the nearest neighbor approach. That is, we conduct SA on each HELP outcome for each scenario. This gives us parameter sensitivity indices for the outcomes. We average the parameter sensitivity indices across the outcomes to get the average SI for a scenario. For each realization that is generated from the Goldsim PA model, Goldsim generates random values for physical/empirical parameters that HELP uses as well. For each vector of physical/empirical parameters that Goldsim generates, the vector from the 5,000 HELP runs that is most 'similar' to the Goldsim vector is computed using the nearest neighbor approach. In this context 'similar' means minimization of the SA-weighted sum of the absolute differences among the 5,000 values computed for this statistic, where each value corresponds to a different HELP realization. In order to account for the impacts of climate change, this process was repeated using the spatially downscaled future climate projections. For each of the key parameters of interest, it was assumed that a linear change depicted the relationship between the values for the present day and those for 2100. In this way, the climatically-driven changes in key parameters used to inform the GoldSim model are quantified and incorporated into the PA model output for the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Exploring the Neutron Substructure with Advanced Polarized Helium-3 Targets (Or: How I Learned to Stop Worrying and Love Spectroscopy)

As we seek to understand the smallest, physical aspects of our universe, we cannot simply rely on our senses to probe the world around us as we did in the past. The smallest physical elements of our universe behave in strange, probabilistic ways and are completely invisible to the naked eye/ear/etc. So, we design clever experiments (such as scattering experiments) to probe these minute realms. Then, just as with the larger, observable world, we devise models and equations to describe what we think is happening. Due to the nature of the physical universe at the quantum scale and with the aid of symmetries such as Lorentz invariance, we can write down equations that describe the scattering, but the expressions contain functions, which we call ?form factors? and ?structure functions?, that we cannot compute from first principles. We can, however, formulate models that make predictions for these functions. By comparing our predictions with the observed data, we can gain insight into the validity of our models and thus a better physical understanding of what is happening at these minuscule scales. Studying the constituents inside of the nucleus of an atom adds another layer of difficulty if we can?t remove those components from the nucleus. This is the case with the neutron. When not bound in the nucleus with protons and other neutrons, the neutron will decay into a proton after about 15 minutes. So, we?re forced to study the neutron while it is still bound in the nucleus of an atom such as helium-3 (3He). For the last 1,000 years (rounding up), our group has developed high quality, polarized 3He targets made of an aluminosilicate glass. These targets are made in order to perform experiments at Jefferson Lab (JLab), experiments which let us determine the form factors and structure functions of the neutron by scattering polarized electrons from polarized neutrons (or rather polarized 3He). The specific experiments reported on in this thesis push the bounds of our understanding of the internal structure of the neutron. Good science is often about pushing experimental techniques to a new level. Toward that goal we study our polarized 3He targets both to advance the technology and to choose the best ones for our experiments. We do this using a process called nuclear magnetic resonance (NMR) to gauge the maximum polarization of a target and how fast the polarization decays with time. While these tests primarily provide us information that make analysis of our experimental scattering data possible, they also let us determine whether or not a target-cell is useful or even, dare I say, of spectacular quality. Our latest targets utilize a novel convection design allowing 3He to be polarized and quickly moved in front of the electron-beam, making it possible to use larger targets with higher electron-beam currents than ever before. This means more electrons scatter and we get more data. And by studying our targets in detail prior to using them in our experiments, we have found techniques to take effects which could have been detrimental to target quality and turn them to our advantage! It?s a real case of making lemonade out of lemons. We also use laser spectroscopy to study the absorption lines of alkali-metals in the target (potassium and rubidium, specifically). We add these alkali-metals to our target to facilitate polarizing the 3He. We can use the measurement of these pressure broadened absorption lines to determine the 3He density inside of the target with great precision. Historically, we understood the width of these lines would be dependent on the temperature of the target. Specifically, if I raise the temperature, the width should get bigger. I found that was not the case, which was very confusing at first, though very exciting now that I realize the data are self-consistent and suggestive of unexpected behavior. This thesis details the development of high quality, glass, polarized 3He targets for the 2020 An 1 /dn 2 and 2023 Gn E experiments, which utilized the first 3He convection targets and broke records in target quality. This thesis also covers the initial development of metal windows for the next-generation of 3He target-cells. Finally, this thesis documents the temperature dependence of the width of potassium (K) and rubidium (Rb) absorption lines as measured with laser spectroscopy.

Jantzi, Christopher↗