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DOE OSTI2022

Looking Beyond Bill Savings to Equity in Renewable Energy Microgrid Deployment

Microgrids powered by renewable energy can provide backup power to critical infrastructure during grid outages. These systems can also play an important role in advancing energy justice by providing economic, environmental, health, and resilience benefits for underserved communities. The value of microgrids is often measured by the economic savings and resilience provided, but there are other energy justice factors that should be considered. This paper describes a methodology for quantifying broader costs and benefits including utility bill savings, value of resilience, social cost of carbon, public health costs, and jobs associated with the construction and operation of microgrids. We evaluate these factors at three case study sites and find that including energy justice values in the cost-benefit analysis of microgrids can change investment decisions. When climate, health, resilience, and job creation are considered, cost-optimal microgrids include more renewable generation, leading to a 52-82% reduction in emissions and diesel fuel use. The net present values of the microgrids grow from negative $626,000-843,000 in the diesel only case to $10-16 million in the hybrid microgrid case and $12-19 million in the renewable microgrid case, indicating potential for greater microgrid deployment if energy justice values are incorporated in decision making. However, we also see large increases in capital expenses, which could limit deployment unless accompanied by innovative financing measures. These findings may be useful to communities as they seek to strengthen resilience to natural disasters while also improving public health, meeting climate goals, and providing economic opportunity for residents.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Precise β branching-ratio measurement for the 0 + → 0 + superallowed decay of 34 Ar

We have measured the branching ratio for the superallowed 0 + → 0 + β transition from 34 Ar to be 0.9448(8), and determined its ft value to be 3058.1(28) s, a result with ±0.09% precision, which is a factor of three improvement over the previous result based on current world data. The ft-value ratio for the mirror pair of superallowed transitions 34 Ar → 34 Cl and 34 Cl → 34 S, becomes the most precise yet measured and, in a sensitive test of the method used to calculate the isospin-symmetry-breaking correction, δ C , it agrees well with the ratio as calculated with Woods-Saxon radial wave functions. This confirms the method used in the most recent survey of superallowed decays to extract V ud , the up-down quark-mixing element of the Cabibbo-Kobayashi-Maskawa matrix. Additionally, our branching-ratio results for the four observed Gamow-Teller branches to 1 + states in 34 Cl are shown to agree well with shell-model calculations based on the same effective interactions that were used in the determination of δ C .

39 ≤ A ≤ 58↗

DOE OSTI2024

Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize–Soybean Rotation in Nebraska

Precise soil water content (SWC) measurement is crucial for effective water resource management. This study utilizes the Cosmic-Ray Neutron Sensor (CRNS) for area-averaged SWC measurements, emphasizing the need to consider all hydrogen sources, including time-variable plant biomass and water content. Near Mead, Nebraska, three field sites (CSP1, CSP2, and CSP3) growing a maize–soybean rotation were monitored for 5 (CSP1 and CSP2) and 13 (CSP3) years. Data collection included destructive biomass water equivalent (BWE) biweekly sampling, epithermal neutron counts, atmospheric meteorological variables, and point-scale SWC from a sparse time domain reflectometry (TDR) network (four locations and five depths). In 2023, dense gravimetric SWC surveys were collected eight (CSP1 and CSP2) and nine (CSP3) times over the growing season (April to October). The N0 parameter exhibited a linear relationship with BWE, suggesting that a straightforward vegetation correction factor may be suitable (fb). Results from the 2023 gravimetric surveys and long-term TDR data indicated a neutron count rate reduction of about 1% for every 1 kg m−2 (or mm of water) increase in BWE. This reduction factor aligns with existing shorter-term row crop studies but nearly doubles the value previously reported for forests. This long-term study contributes insights into the vegetation correction factor for CRNS, helping resolve a long-standing issue within the CRNS community.

Chemistry↗

DOE OSTI2020

Default Radioactive and Hazardous Waste Management (RHWM) Dose Conversion Factors (DCFs) and Weighting Factors and plutonium-239 equivalent Curie (PE-Ci) methodology for acceptance into the Waste Storage Facilities

DOE-STD-5506-2007 (Ref. 1) is the standard that provides the methodology for preparing hazard analysis and accident analysis for transuranic (TRU) waste facilities. The Waste Storage Facilities hazard and accident analysis for the DSA is developed in accordance with DOE-STD- 5506-2007. Two related issues need to be addressed when implementing DOE-STD-5506-2007 regarding the calculation of consequences from TRU waste releases in accident analysis: Consequences determined in accident analysis must be modeled using inhalation Dose Conversion Factors (DCFs) that are consistent with those from the International Commission on Radiological Protection Publication 72 (ICRP-72, Ref. 2).; The use of a statistical Material at Risk (MAR) representing the distribution of radiological loading of TRU waste containers based on the use of a plutonium-239 equivalent Curie (PE-Ci) methodology. The PE-Ci methodology simplifies accident analysis by allowing one to model releases based on the Curie value of one standard nuclide (e.g., Pu-239) instead of needing to model releases for every potential nuclide of interest. This is accomplished by normalizing the Curie value of all nuclides to a single Curie value of a standard nuclide by using a Weighting Factor that is a ratio of the DCFs associated with the nuclides and that of the standard nuclide. By using the ICRP-72 DCFs to calculate PE-Ci values used in the statistical MAR, the accident analysis that uses that statistical MAR will be consistent with the consequence methodology identified in DOE-STD- 5506-2007.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Assessment of the Amplification Factor Transport Transition Model for High-Mach Number Flows

In its present state, the Amplification Factor Transport (AFT) model provides an efficient alternative for high-fidelity stability methods for complex geometries subject to low-speed conditions considered in the industrial-production CFD environment. Its performance has not yet been documented for the typical transition scenarios in hypersonic conditions. The goal of the present study is to apply the AFT model to a yawed- and flared-cone configuration, for which the laminar flows respectively support the crossflow and second-mode instability mechanisms, and to compare the amplification results against high-fidelity results computed with Linear Parabolized Stability Equations (LPSE). High-resolution viscous-flow solutions are provided with OVERFLOW and COFFE. For the yawed-cone case, the AFT model yields the largest amplification in a region of the flow where the expected crossflow instability is not amplified (in the leeward symmetry plane) according to LPSE. For the flared-cone case with a wall-temperature slightly lower than the adiabatic value, the AFT model yields extremely large amplification factors (in excess of 100), exceeding the computed LPSE amplification of second-mode instability results by a factor 14. Upon considering a cold-wall condition, the model shows much smaller amplification factors, which is the opposite with respect to the expected behavior of the second mode. The AFT model does not adequately capture the crossflow and second-mode instability mechanisms in its present state.

Groot, Koen J.↗

DOE OSTI2022

Pre-combustion mercury removal with co-production of hydrogen via coal electrolysis

Here, pre-combustion mercury removal via coal electrolysis was performed and investigated on a bench-scale coal electrolytic cell (CEC) systemically, and factorial design was used to determine the effect of different operating conditions (coal particle size, operating temperature, operating cell voltage, and flow rate of slurry) on the percentage of mercury removal, percentage of ash removal, and dry heating value change. The results showed that the operating cell voltage, as well as the interaction between operating cell voltage and coal particle size, are significant factors in the percentage of mercury removal. There is no significant factor in the percentage of ash removal and the dry heating value change, but the coal could be purified while keeping the dry heating value almost constant after electrolysis. A co-product of hydrogen could be produced during coal electrolysis with 50% lower energy consumption compared with water electrolysis. Meanwhile, a mechanism for mercury removal in coal was proposed. The facts indicate that coal electrolysis is a promising method for pre-combustion mercury removal.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Analysis of Completion Design Impact on Cluster Efficiency and Pressure-Based Well Communication in HFTS-2 Delaware Basin

The Hydraulic Fracturing Test Site 2 (HFTS-2) is a joint industry project in the Delaware basin to advance hydraulic fracturing understanding and improve productivity in shale reservoirs. The project integrates multi-disciplinary approaches to evaluate different completion designs, well spacing, inter-well communication, and stimulated rock volume, among other factors. This paper focused on two major areas related to hydraulic fracture performance. First, an analysis of different completion designs on cluster efficiency based on near well Distributed Acoustic Sensing (DAS). Second, an evaluation of well and completion designs on inter-well fracture driven interactions (FDIs) based on downhole pressure monitoring. Fluid/sand distribution and cluster efficiency analyses were based on near wellbore DAS data collected from two adjacent horizontal wells completed in two different landing zones in the Wolfcamp formation. These wells had different completion designs aiming to evaluate the effect of normal vs. extended stage lengths, perforation hole tapering and limited entry. Standard deviation from ideal fluid/sand distribution and waterfall plots were used to evaluate cluster efficiency for each design and stage. Inter-well FDIs analysis was conducted among the horizontal wells and a vertical monitor well. One horizontal well served as the monitor well while the other horizontal well was being treated. The vertical well was instrumented with downhole pressure and temperature gauges to aid monitoring fracture height growth. The pressure response during and after fracturing was characterized based on maximum pressure increase value and slope. Pressure response vs. FDIs trigger factors such distance, cluster efficiency and stage fluid volume were also analyzed. Based on the different completion and perforation designs tested, DAS analysis suggests that limited entry design worked best. Extreme limited entry showed the potential of high perforation erosion and reduced cluster efficiency. Here, the limited entry and tapered perforation design demonstrated potential to improve the cluster efficiency for extended stage lengths. Pressure monitoring across formation units proved to be critical to understand fracture interactions and fracture vertical growth. Pressure communication across different formation units during hydraulic fracturing operation indicate fractures grew upwards during Wolfcamp wells fracturing. However, this pressure communication dissipated over time. High intensity FDIs were recorded when the frac stages Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S018R001/2477607/urtec-2021-5289-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5289 were closer to the pressure gauge location in the monitor wells. Some of these stages that produced high intensity FDIs also had high fluid volume per cluster and low cluster efficiency. The multi-disciplinary and high-quality data collected from HFTS-2 helped to further understand why completion approaches such as limited entry and tapered perforation design are successful in improving cluster efficiency. The DAS data combined with downhole high-resolution pressure measurements also helped to quantify the effect of lower cluster efficiency data on the incidence and intensity of FDIs.

58 GEOSCIENCES↗

DOE OSTI2022

The estimation of Poisson’s ratio by time-averaging and Cornu’s method for isotropic beams

Prior research suggests that direct static (e.g., uniaxial testing) and dynamic (e.g., ultrasonic wave propagation analysis) measurements differ in the estimation of Poisson’s ratio because anisotropies and heterogeneities in the sample material affect the two types of tests differently. Even assuming isotropic and homogeneous material properties, prior research further suggests that discrepancies between static/dynamic test results will exist because the error of the diagnostic techniques for the measurand are inherently different. Finally, thermodynamic effects are not present in static tests but can significantly affect dynamic test results. Given the potential for all these variables to produce discrepancies, it would be helpful to have the measurement of Poisson’s ratio obtainable from the same theory and experimental measurements by either static or dynamic testing methods. Our finite element calculations show that by combining time-averaged scanning digital holography with Cornu’s method, it is theoretically possible to estimate the effective Poisson’s ratio from the anticlastic contours at the antinode of the first out-of-plane bending mode shape. This is true regardless of frequency and therefore applicable for both static and dynamic measurements. Our results show that the estimate of Poisson’s ratio by Cornu’s method using data from simulations of mode shapes approaches the true value of Poisson’s ratio. Additionally, our research suggests that beam geometry and boundary conditions are fundamental factors limiting the convergence of the estimate of Poisson’s ratio to the true value of Poisson’s ratio regardless of performing a static or dynamic test.

42 ENGINEERING↗

DOE OSTI2025

The Impact of Cultural Values and Organizational Processes on Nuclear Security Operations

Human performance is a pivotal factor in the design, testing, maintenance, and operation of security systems. The effectiveness of these systems relies not only on the capabilities, limitations, motives, and attitudes of the individuals involved, but also on the quality of training, instructional content, and evaluation methods provided. To uphold security standards, seamless integration between technologies and operators necessitates reliable human input. In security operations, human errors, often attributed to blame, sanctions, low motivation, individual accountability, or complacency, are primary causes of system failures. Complacency, characterized by a false sense of security, reflects a lack of awareness of potential threats and is a significant contributing factor to lapses in security. Security incidents arise from various factors, many extend beyond individual control, highlighting the need for a holistic approach to human performance that integrates organizational processes and team collaboration. Historically, errors have been attributed to individual moral or cognitive failures. However, insights from Operational Experiences (OEs) suggest that organizational processes weakness and deficiencies in nuclear cultural values contribute more significantly to security failures than individual mistakes. This paper consolidates lessons learned from diverse international nuclear security cultures and aims to highlight the importance of security culture in shaping global perspectives on nuclear security. It underscores the role of cultural values in shaping nuclear security practices and enhancing the resilience of security systems in the nuclear sector.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗

DOE OSTI2025

Approach to evaluate the effect of selected additives on the environmental impacts of plastic product manufacturing and recycling

Plastic waste management has become a topic of increasing public interest due to the growing amount of plastic waste entering landfills, being combusted, or being leaked into the environment due to mismanagement. The portion of plastic products that is currently recycled remains low (< 9 % in the U.S.). This is driven by numerous factors including infrastructure and collection needs to improve the recycling rate of plastic waste, technological constraints in recycling the wide variety of plastic products associated with the diverse range of (non-transparent) formulations, and economic limitations for recycling plastic and using recycled plastic in new plastic products (e.g., consumer incentives to recycle, economic value of recycled plastic). The relative importance of these factors is not well understood, and each requires additional research.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Socioeconomic Effects of Pension Spending: Evidence from Spain

The purpose of this study is to provide broader understanding of the significant role that the pension system has in the Spanish economy by estimating the sectoral production, employment and income sustained by pensioners' consumption. Based on input-output tables by the World Input-Output Database and consumption data from the Household Budget Survey by the Spanish Statistical Office, a demoeconomic model is applied to quantify the direct impacts, indirect impacts from interindustry links and induced impacts from income-consumption connections over a nine-year period (2006–2014). Then, the factors driving the evolution of total output, employment and value added during such period have been examined by using structural decomposition analysis. The growing participation of consumption by pensioner households in final demand had proven crucial during the 2008 crisis to alleviate the negative trend in production and employment derived from the collapse in consumption suffered by the rest of households. Determining the underlying factors driving changes in both employment and income during the 2008 crisis can be of interest in political decision-making on the sustainability of the Spanish pension system. The results of estimating both the employment and income supported by pensioners' consumption reveal the significant stabilizing effect of the public spending on pensions, particularly during the 2008 crisis. The current Spanish approach of attaining the pension system sustainability by merely reducing social protection costs ignores the adverse consequences of a lower pensioners' demand. This paper addresses an alternative view in which pension spending is not considered a burden on economic growth but rather a means of improving the level of production and employment.

employment↗

DOE OSTI2024

Geomagnetically Induced Current Field Test on Large Grid-Connected Power Transformers: Analysis, Model Development, and Simulations

Geomagnetic-induced current (GIC) flow in power grids can cause undesirable effects such as transformer overheating, harmonics, higher reactive power demand, etc. Many simulation models have been developed to study these effects, but real-world verification on modern transformer designs is rare. Here, this paper presents the first long-duration GIC field test in the U.S. performed on high-voltage, grid-connected transformers featuring winding clamps and tie rods instead of conventional tie bars. Field measurements were taken to evaluate GIC effects. These measurements also aided in developing and validating thermal and electromagnetic transient (EMT) models of the transformers. During the test, significant current and voltage distortions were observed along with considerable transformer reactive power losses. Analysis of the field measurements showed that the transformers’ hottest spot was at the inner windings, and their k-factors were close to factory test and software default values. Thermal simulations indicated that the transformers would not violate their thermal limits even for a GIC waveform that peaks at about 200 A/phase. EMT simulations revealed that increased transformer loading may reduce GIC-induced reactive power demand and harmonics in certain scenarios. The study also highlighted potential inaccuracies in using the k-factor method to calculate transformer reactive power losses.

EMTDC↗

DOE OSTI2021

QBTNs - Quantum Boolean Tensor Networks

We develop algorithms and software that uses the D-Wave 2000Q quantum annealer to solve several types of Boolean tensor factorization problems. Boolean tensor factorization refers to the problem of representing a high-dimensional tensor filled with Boolean values as a product of smaller Boolean core tensors and Boolean matrices. We consider different tensor factorization models, including Boolean Tensor Train, Boolean Tucker, and Boolean Hierarchical Tucker. As an exact decomposition of a given type may not exist in the general case, the objective is to minimize the difference between the input high-dimensional tensor and the product of the lower-dimensional tensors of the proposed factorization, using a specified tensor norm. In our approach, we reduce the Boolean tensor factorization problem to a sequence of quadratic unconstrained binary optimization problems suitable for the D-Wave 2000Q quantum annealer. Although current quantum technology is still fairly restricted in the problems it can tackle, we show that complex tensor factorization problems as the ones addressed by us can be solved efficiently and accurately.

Alexandrov, Boian↗

DOE OSTI2024

Optimizing the quality factor of InP nanobeam cavities using atomic layer deposition

Photonic crystal nanobeam cavities are valued for their small mode volume, CMOS compatibility, and high coupling efficiency-crucial features for various low-power photonic applications and quantum information processing. However, despite their potential, nanobeam cavities often suffer from low quality factors due to fabrication imperfections that create surface states and optical absorption. In this work, we demonstrate InP nanobeam cavities with up to 140% higher quality factors by applying a coating of Al 2 O 3 via atomic layer deposition to terminate dangling bonds and reduce surface absorption. Additionally, changing the deposition thickness allows precise tuning of the cavity mode wavelength without compromising the quality factor. This Al 2 O 3 atomic layer deposition approach holds great promise for optimizing nanobeam cavities that are well-suited for integration with a wide range of photonic applications.

42 ENGINEERING↗

DOE OSTI2020

Camera settings and biome influence the accuracy of citizen science approaches to camera trap image classification

Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion-activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy is poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best-practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photograph was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photograph using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g., false species or false empty), and reason for the false classification (e.g., misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open-grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail camera set up protocol with a burst of three consecutive photographs, a short field of view, and determine camera sensitivity settings based on in situ testing. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Daily, 30 m Resolution NDSI Data for the East River Watershed, CO for 2000-2020

This dataset contains daily Normalized Difference Snow Index (NDSI) values at 30 m spatial resolution for the East River watershed in Colorado, USA. The temporal range of these data includes water years 2001-2020. These data were created using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). This model fuses low spatial and high temporal resolution data from MODIS (500 m, daily) with high spatial and low temporal resolution data from Landsat (30 m, 16 days) to create a 30m synthetic daily snow product. This product allows for the analysis of historical snow covered area trends in the East River Watershed at fine spatiotemporal resolutions where it was not available previously. This research was performed as a part of the Department of Energy’s Subsurface Biogeochemical Research Program with the primary intent of better understanding the timing and spatial patterns of water delivery to the Critical Zone in mountain watersheds. Each .zip file contains one "water year" of data (October 1 - September 30; i.e., water year 2010 starts October 1, 2010 and ends September 30, 2011). Each zip file contains the following: STARFM daily Normalized Difference Snow Index (NDSI) fusion data files in GeoTiff format with one layer for each day between Landsat data acquisition dates (i.e., for dates of Landsat acquisition, the Landsat image is included for that date). The study area is located in an area of Landsat path overlap, so Landsat dates acquisitions are every 7-9 days. Landsat NDSI files containing the high spatial (30m), low temporal (7-9 days due to Landsat path overlap) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Dates for which no Landsat data were obtained are included as NoData layers. MODIS NDSI files containing the high temporal (daily), low spatial (500m) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Please note the MODIS data were resampled to 30m pixels for input into the STARFM model. The data have a scale factor of 10,000 and a no data value of -32767. The projection of all datasets is WGS 84 (EPSG: 4326), which has a latitude/longitude based degree resolution of 0.0002694946 X 0.0002694946, and approximates to the 30 m spatial resolution mentioned above. The Layer Index files in .csv format. They contain information for each layer in the above GeoTiff files regarding the corresponding date for each layer, the fraction of pixels in the image that contain valid data (missing data is due to either cloud cover or poor data quality; these values are not percent snow cover). Dates of Landsat overpass are indicated in these files. If no Landsat data were able to be obtained due to cloud cover or lack of Landsat Tier 1 data available on Google Earth Engine, this is also noted.

EARTH SCIENCE > CRYOSPHERE > SNOW/ICE↗

DOE OSTI2022

Choosing the Best Carbon Factor for the Job: Exploring Available Carbon Emissions Factors and the Impact of Factor Selection

Over 600 local governments in the United States, including nearly half of the largest 100 cities, have enacted climate action plans that include carbon reduction goals and greenhouse gas inventories (Markolf et al. 2020). The magnitude of these goals ranges from modest reduction targets to carbon neutrality. None will be met without significant contributions from the buildings sector. Understanding how energy efficiency and building electrification impact greenhouse gas emissions requires local, time-sensitive, and forward-looking carbon emissions factors for electricity use in buildings. There are a variety of emissions factors currently available from various sources, including average emissions factors and historical short-run marginal emissions factors. Long-run marginal emissions factors and future-year short-run marginal emissions factors are also now available from the National Renewable Energy Laboratory's (NREL's) Cambium data sets. In this paper, we describe the different carbon emissions factors available, including both conventional sources and newly available options. We discuss the types of analyses each emissions factor is best suited to support. Then, using residential energy efficiency and electrification load profiles, we demonstrate how different conclusions result from different choices of carbon emissions factors. For two grid regions, we explore takeaways of using current versus future-year emissions, short-run versus long-run, and levelized versus single-year values. We include a framework for selecting the best carbon emissions factor for the job.

carbon emissions factors↗

DOE OSTI2024

Choosing the Best Carbon Factor for the Job: Exploring Available Carbon Emissions Factors and the Impact of Factor Selection: Preprint

carbon emissions factors↗