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At least 145 records · Page 8

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DOE OSTI2024

Enhanced Bottom Anode Monitoring in DC Electric Arc Furnaces Using Fiber-Optic Sensors

A pin style bottom anode employs conductive steel rods that serve as the pathway for the high electrical power through rammed refractory at the bottom of a DC Electric Arc Furnace (EAF). Anode wear during operation is important to monitor, as anode replacement is expensive and impacts EAF productivity. Liquid steel penetration into the un-sintered refractory layer can result from rapid electrical power ramp-up, dips in furnace temperature, or operating the anode for too long between EAF campaigns. In extreme cases, the liquid steel may penetrate the bottom of the furnace when anode wear progresses too close to the bottom shell, which is extremely dangerous and must be avoided. The current state of the art for monitoring bottom anode wear employs thermocouples imbedded in the anode pins at points in the anode. However, this approach is not sensitive enough to detect localized damage to the anode, especially when cracking occurs. Here, the present work utilizes fiber optic sensors to monitor the health of the anode, by creating a real-time spatially distributed temperature map of the anode. Unlike the traditional thermocouples, these sensors can be mounted at significantly greater depths, provide distributed temperature measurements, and can withstand temperatures of up to 900°C. Additionally, they are able to perform temperature measurements with a spatial resolution of 1.3 mm at a 5 Hz acquisition rate, providing unprecedented high-density real time monitoring of anode health and increasing the efficiency, and safety of EAF operation.

Bottom Anode↗

DOE OSTI2020

SRS Composite Analysis Monitoring Plan (FY2019 Model Validation)

Using a projected end-state date of 2065 (SRNS 2015b), the Savannah River Site (SRS) Composite Analysis (CA) modeling for each facility and waste site began on the inventory year assigned to it so that source depletion and radionuclide transport out of the system could be appropriately captured. Some SRS waste sites that have already achieved their end states (i.e. end-state inventories and end-state configuration) are currently contributing to the potential off-site public dose through source release, groundwater transport, discharge to on-site surface streams, and stream transport to the CA point of assessments (POAs). The inventory year assigned to these waste sites is 2002 or before. This means that SRS CA results from 2002 and beyond are a reasonable representation for these waste sites that have already achieved their end states and are currently contributing to the potential off-site public dose. The SRS Annual Environmental Report (AER) monitoring can differentiate and separate liquid pathway data allowing the data representing only waste sites at their end state to be produced. Because the SRS CA has projected reasonable end-state impacts from 2002 and beyond, and the AER monitoring can differentiate and separate operating and end-state contributions to annual liquid pathway release, an opportunity exists to use the AER monitoring data to validate the SRS CA model. The CA model validation program uses a graded and systematic approach for taking corrective action, starting with an SRS established administrative dose limit of 15 mrem/yr, below which no action is required. Based on the location of the 2010 SRS CA POAs, the only potential exposure pathway for the public is through surface water. The completion of the FY2019 CA model validation indicates that the SRS CA projected dose, while generally conservative, provides a reasonable representation of the maximum annual doses. These doses are well below the administrative limit; therefore, no additional action is required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Model Validation for the FY2021 SRS Composite Analysis Monitoring Plan

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Developing a Deep Learning-Computer Vision Framework to Monitor Avian Interactions with Solar Energy Facility Infrastructure (Final Technical Report)

The project addressed an inability to monitor avian interactions with photovoltaic (PV) solar energy facilities necessary for understanding PV solar impacts on birds. In the project, machine-vision technology that continuously monitors avian activities at PV solar facilities was developed. The technology includes four machine-learning (ML) models, each of which accomplishes a specific task in detecting birds and classifying their activities in live or recorded videos—detecting and tracking moving objects, differentiating birds from other objects, detecting bird collisions with solar panels, and classifying non-collision bird activities around PV facilities. Major project outcomes include adoption by two of DOE SETO’s SolWEB projects, providing novel observational data on birds to promote co-location of PV solar development and habitat conservation, known as ecovoltaics.

14 SOLAR ENERGY↗

DOE OSTI2021

Mitigating Smart Meter Asynchrony Error Via Multi-Objective Low Rank Matrix Recovery

Not provided.

Engineering↗

DOE OSTI2021

Cavern Leaching Monitoring CY18 And CY19

The U.S. Strategic Petroleum Reserve (SPR) is a crude oil storage system run by the U.S. Department of Energy (DOE). The reserve consists of 60 active storage caverns spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR began executing U.S. congressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 MMB, requires raw water to be used instead of saturated brine for oil withdrawals such as for sales. All sales will produce leaching within the caverns used for oil delivery. Thirty-six caverns had a combined total of over 29 MMB of water injected from CY18-CY19 for mandatory sales. Leaching effects were monitored in these caverns to understand how the sales operations may impact the long-term integrity of the caverns. While frequent sonars are the best way to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An intermediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code (SANSMIC). The results indicate that leaching induced features are not of concern in the majority of the caverns, 32 of 36. Four caverns, BH-107, BH-108, BH-114 and WH-114 have features that may grow with additional leaching and should be monitored as leaching continues in those caverns. Six caverns had post sale sonars which were compared with SANSMIC results. SANSMIC was able to capture the leaching well. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results suggest SANSMIC is a useful tool for monitoring changes in cavern shape due to leaching effects related to sales and exchanges.

02 PETROLEUM↗

DOE OSTI2021

Strategic Petroleum Reserve Cavern Leaching Monitoring CY20

The U.S. Strategic Petroleum Reserve is a crude oil storage system run by the U.S. Department of Energy. The reserve consists of 60 active storage caverns spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR began executing U.S. congressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 MMB, requires raw water to be used instead of saturated brine for oil withdrawals such as for sales. All sales will produce leaching within the caverns used for oil delivery. Twenty-five caverns had a combined total of over 39 MMB of water injected in CY 20 as part of the Exchange for Storage program; oil was withdrawn in the same manner as for congressionally mandated sales. Leaching effects were monitored in these caverns to understand how the oil withdrawals may impact the long-term integrity of the caverns. While frequent sonars are the best way to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An intermediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code (SANSMIC) . The results indicate that leaching induced features are not of concern in the majority of the caverns, 19 of 25. Six caverns, BH-107, BH-113, BH-114, BM-4, BM-106, and WH-114 have features that may grow with additional leaching and should be monitored as leaching continues in those caverns. Ten caverns had post sale sonars that were compared with SANSMIC results. SANSMIC was able to capture the leaching well , particularly the formation of shelves and flares. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results suggest SANSMIC is a useful tool for monitoring changes in cavern shape due to leaching effects related to sales and exchanges.

02 PETROLEUM↗

DOE OSTI2022

Strategic Petroleum Reserve Cavern Leaching Monitoring CY21

Th e U.S. Strategic Petroleum Reserve (SPR) is a crude oil storage system administered by the U.S. Department of Energy. The reserve consists of 60 active storage caverns located in underground salt domes spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR started executing C ongressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 million barrels ( MMB ) , re quires that unsaturated water (referred to herein as ?raw? water) is injected into the storage caverns to displace oil for sales , exchanges, and drawdowns . As such, oil sales will produce cavern growth to the extent that raw water contacts the salt cavern walls and dissolves (leaches) the surrounding salt before reaching brine saturation. SPR injected a total of over 45 MMB of raw water into twenty - six caverns as part of oil sales in CY21 . Leaching effects were monitored in these caverns to understand how the sales operations may impact the long - term integrity of the caverns. While frequent sonars are the most direct means to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An interm ediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code , SANSMIC . The modeling results indicate that leaching - induced features do not raise co ncern for the majority of the caverns, 15 of 26. Eleven caverns, BH - 107, BH - 110, BH - 112, BH - 113, BM - 109, WH - 11, WH - 112, WH - 114, BC - 17, BC - 18, and BC - 19 have features that may grow with additional leaching and should be monitored as leaching continues in th ose caverns. Additionally, BH - 114, BM - 4, and BM - 106 were identified in previous leaching reports for recommendation of monitoring. Nine caverns had pre - and post - leach sonars that were compared with SANSMIC results. Overall, SANSMIC was able to capture the leaching well. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results validate that SANSMIC continues to serve as a useful tool for mon itoring changes in cavern shape due to leaching effects related to sales and exchanges.

02 PETROLEUM↗

DOE OSTI2022

Giant kelp genetic monitoring before and after disturbance reveals stable genetic diversity in Southern California

Given the impacts of climate change and other anthropogenic stressors on marine systems, there is a need to accurately predict how species respond to changing environments and disturbance regimes. The use of genetic tools to monitor temporal trends in populations gives ecologists the ability to estimate changes in genetic diversity and effective population size that may be undetectable by traditional census methods. Although multiple studies have used temporal genetic analysis, they usually involve commercially important species, and rarely sample before and after disturbance. In this study, we run a temporal analysis of giant kelp, Macrocystis pyrifera , genetic diversity over the scope of 10 years (2008-2018) using the same microsatellite marker panel to assess the genetic consequences of disturbance in several populations of giant kelp ( Macrocystis pyrifera ) in the Southern California Bight. The study is a rare pre- and post-disturbance microsatellite analysis that included declines to giant kelp caused by the 2015/16 El Nino Southern Oscillation event. We used canopy biomass estimated by remote sensing (Landsat) to quantify the extent of disturbance to kelp beds, and sea surface temperature data to understand how kelp was pushed towards its temperature limits during this period. Despite prolonged periods with decreased canopy at several sites, no changes in genetic structure and allelic richness were observed. We argue that giant kelp in the region is best described as a “patchy population” system where true extinctions are rare. We discuss how deep refugia of subsurface sporophytes and cryptic microscopic life stages could have kept genetic diversity through disturbance. Given the increasing effects of climate change and uncertainty in modeling impacts of species with cryptic life history stages, we suggest further investigation to reveal the role such stages play in species resilience. Genetic monitoring studies of sites selected by remote census demographic and climate surveys should be continued in the future given the predicted impacts of climate change.

Klingbeil, III, William H.↗

DOE OSTI2021

Is satellite Sun-Induced Chlorophyll Fluorescence more indicative than vegetation indices under drought condition?

Droughts represent one of the most severe abiotic stress factors that could result in great crop yield loss. Numerous vegetation indices have been proposed for monitoring the vegetation condition under stress and assessing drought impacts on yield loss. However, the understanding and comparison between traditional vegetation indices (VIs) and the newly emerging satellite Sun-Induced Chlorophyll Fluorescence (SIF) for monitoring vegetation condition is still limited especially under drought stress and at multiple spatial scales. In this study, the potential of satellite observation SIF for monitoring corn response to drought was investigated based on the 2012 drought in the US Corn Belt. The standardized precipitation evapotranspiration index (SPEI) was used here to quantify drought. We found that all SPEI were above –1, except for July (–1.27), August (–1.39) and September (–1.14) in 2012, indicating the severity of this drought. We examined the relationship between satellite measurements of SIF, SIF yield , VIs (e.g., NDVI and EVI) and SPEI. Results indicated that SIF yield was sensitive to drought and SIF captured the stress more accurately both at the regional and state scales for the US Corn Belt. Quantitatively, SIF yield had a high correlation with SPEI (r = 0.987, p < 0.05) over the entire Corn Belt, and it indicated losses in response to drought approximately one month earlier than SIF/NDVI/EVI. Furthermore, our results demonstrated that SIF could be trusted as an effective indicator to study the relationship between GPP (R 2 ≥ 0.8664, p < 0.01) under drought conditions across the Corn Belt. Finally, this study highlighted the advantage of using satellite SIF observations to monitor the drought stress on crop growth especially GPP at regional scale.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Informing forest carbon inventories under the Paris Agreement using ground-based forest monitoring data

Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net-zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi-automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net-zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well-documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi-automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground-based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground-based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A New Framework for the Attribution of Air‐Sea CO 2 Exchange

Abstract The air‐sea transfer of carbon dioxide can be viewed as a dynamic system through which atmospheric and oceanic processes push surface waters away from thermodynamic equilibrium, while diffusive gas transfer pulls them back toward local equilibrium. These push/pull processes drive significant sub‐seasonal, seasonal, and interannual variability in air‐sea carbon fluxes, the quantification of which is critical both for diagnosing the ocean response to fossil fuel emissions and for attempts to mitigate anthropogenic climate disruption through intentional modification of surface ocean biogeochemistry. In this study, we present a new approach for attributing air‐sea carbon fluxes to specific mechanisms. The new framework is first applied to a two‐box ocean nutrient and carbon cycle model as an illustrative example. Next, outputs from a regional eddy‐resolving model of the Southern Ocean are analyzed. The roles of multiple physical and biogeochemical processes are identified. The decomposition of the seasonal air‐sea carbon flux shows the dominant role of biological carbon pumps that are partially compensated by the transport convergence. Finally, the framework is used to diagnose the response to mesoscale iron and alkalinity release, explicitly quantifying transport feedback and eventual impacts on net air‐sea carbon flux. Ocean carbon transport has divergent influences between iron and alkalinity release, due to opposing near‐surface gradients of dissolved inorganic carbon. We suggest that our attribution framework may be a useful analytical technique for monitoring natural ocean carbon fluxes and quantifying the impacts of human intervention on the ocean carbon cycle.

Ito, Takamitsu [School of Earth and Atmospheric Sc↗

DOE OSTI2020

Transfer Factors for the FRMAC Assessment Manual and Turbo FRMAC to Improve Radiological Dose Assessment

The Turbo FRMAC analysis tool is used to perform complex calculations to quickly evaluate radiological consequences and aid in decision making during an emergency response by assessing impacts to the public, workers, and the food supply. Turbo FRMAC calculations are based on methods established by the Federal Radiological Monitoring and Assessment Center (FRMAC). To be able to assess impacts, input data called transfer factors that describe radionuclide uptake by local plants and animals are required. During the code application exercises in late 2016, identifying, finding, and validating nonstandard transfer factors proved to be time consuming and diverted the teams’ activity away from other critical tasks. As a result, a task was undertaken to dramatically expand the list of available transfer factors (food and non-food) and incorporate these factors into Turbo FRMAC. This will ultimately result in improved efficiency of the assessment team to perform calculations during times when the FRMAC is activated and provide more defensible, vetted data from which to calculate results. As a result of these and subsequent exercises, transfer factors were needed for the following items: bell peppers, Christmas tree, deer, flowers, fresh cucumbers, tomatoes, grapefruit, lichens, mushrooms, oranges, snap beans, squash, strawberries, sugarcane for sugar and seed, sweet corn, tea, tobacco, tree bark, and watermelon. To expand the applicability of the information tables, generic transfer data were also provided for common categories and recommendations were made for expanding the list of chemicals based on chemical similarity. The data presented in this report were compiled from recent literature with most of the data encompassing the period from 2000 to 2018. The following radionuclides were targeted during the literature search: elements associated with reactor accidents or nuclear detonations (Sr 89/90, Cs 134/137, Ce 141/144, Ru 103/106, I 129/131/133, Pu 238/239, Am 241, Zr 95, and Nb 95) and elements associated with industrial accidents or dirty bombs (Ir 192 and Co 60). Data from other elements were evaluated if they were identified during the literature search. In addition, reports were evaluated that were recommended by the research consultants. For each plant or animal transfer factor, the goal was to determine the geometric mean, the geometric standard deviation, the minimum, the maximum, and the number of measurements used. If only one measurement was available that was presented as the mean. Concentration ratios with large geometric standard deviations (GSDs) were generally the result of a paucity of measurements or a few disparate measurements. Measurement disparity was observed for data from different soil types. The geometric mean (GM) is a good reference value for planning and responses purposes, but the location-specific concentrations are unlikely to be similar to the model results. Recommendations for further work include: segregating the data to reflect the influence of soil type, developing approaches to incorporate animal data based on aggregated transfer measurements, and including data for foliar deposition on plants.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2022

Best Practices for Enhancing Performance Contracts with Monitoring-Based Commissioning

The Federal Energy Management Program (FEMP) promotes best practices for impactful utilization of Energy Management Information Systems (EMIS) at federal facilities. This fact sheet highlights best practices from the FEMP technical report, Enhancing Performance Contracts Using Monitoring-based Commissioning (MBCx).

EMIS↗

DOE OSTI2026

Measuring Climate and Water Risk across the Bulk Power System

As climate impacts increase and power systems transition to renewables, planners and operators need insights into climate risks to power generation and infrastructure to ensure reliable decision-making in the short and long-term. We present a standardized, consistent mechanism for utilities and system operators to evaluate the climate- and water-related risks of their current and future grid assets. Using a risk-based approach on the combined outcomes of high-fidelity climate drivers together with water and power system models, we examine the temperature and water availability impacts within the contiguous United States to power system assets at the water basin level in three different time periods and report resulting outcomes on lost capacity across different expansion scenarios and climate models. The results indicate that air temperature has the highest effect on derating. Changes in streamflow do not have a large impact on generation capacity at the national level. Electric sector buildout scenarios each have a unique regional risk profile, depending on the technology mix and total capacity, although risks from high temperatures are significant for both traditional and renewable energy generation. Stakeholders can use this approach to monitor effects of generation capacity losses and potential impacts as climate, generation mix, and infrastructure change.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Surface Doping Boosts Triplet Generation Yield in Perovskite-Sensitized Upconversion

Triplet–triplet annihilation-based photon upconversion (TTA-UC) can efficiently generate higher energy photons at low relative fluences. Bulk metal halide perovskites have offered promise in efficiently sensitizing molecular triplet states in the solid state, necessary for the integration of TTA-UC into device-based applications. Recent work focused on TTA-UC from a rubrene triplet annihilator sensitized by perovskite thin films has established relatively efficient charge extraction from the perovskite, forming the triplet exciton in rubrene. Yet, the specifics underpinning charge transfer at the perovskite/rubrene interface are not fully elucidated. Here, to improve device performance and study the properties governing charge transfer at the interface, various organic solvents are explored to treat the perovskite surface. Scanning tunneling microscopy and spectroscopy show a difference in the electronic band structure, where both n- and p-type terminated perovskite surfaces are observed depending on the solvent used. Supported by optical spectroscopy, the impact of the perovskite electronic structure is monitored, indicating that n-type perovskite sensitizers feature higher TTA-UC efficiencies due to favorable band bending resulting in efficient hole-mediated triplet formation. Overall, the tuning of the electronic structure of the perovskite sensitizer through solvent treatment is shown to be a key force in tuning the mechanism of efficient triplet generation.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Underground sources of drinking water chemistry changes in response to potential CO 2 leakage

The purpose of this study was to quantify changes to underground sources of drinking water (USDW) quality in response to potential CO 2 leakage from geologic CO 2 sequestration (GCS) reservoirs. Here, the developed a framework of combined laboratory experiments and reactive transport simulations and used this framework to evaluate the Ogallala aquifer overlying the Farnsworth Unit (FWU), an active GCS site, as a case study. Using chemical reaction parameters obtained from laboratory experiments and numerical simulations, site-specific mechanisms of CO 2 -water-sediment interactions at the USDW aquifer were interpreted. Long-term risks of potential CO 2 leakage were then evaluated with field-scale numerical models using the regional hydrogeological characteristics and reaction parameters obtained from our experiments and simulations. Results suggest that carbonate mineral impurity and cation exchange are key mechanisms for interactions between CO 2 and the aquifer sediment. Additionally, for a large leakage rate of 0.1 % injection from one leaky well, the leakage plume might impact an area of 300 m in diameter and significantly affect the local water quality by changing pH and cation concentrations (e.g., Zn, Ba and Sr). After leakage ceases, the zone of impacted fluids would not migrate significantly in subsequent decades due to a low regional groundwater flowrate (for this case study). The relatively small area of impact might not be detected in a monitoring well given the broader spacing in a typical field scenario. Effective early leakage detection may require additional tools, e.g., borehole CO 2 movement, four-dimensional seismicity, CO 2 soil flux, samples from deeper aquifers, etc., to ensure effective leakage detection and long-term safety of GCS projects.

58 GEOSCIENCES↗

DOE OSTI2020

WEC fault modelling and condition monitoring: A graph-theoretic approach

The nature of wave resources usually requires wave energy converter (WEC) components to handle peak loads (i.e., torques, forces, and powers) that are many times greater than their average loads, accelerating equipment degradation. Moreover, due to their isolated nature and harsh operating environment, WEC systems are projected to possess high operations and maintenance (O&M) cost, i.e., around 27% of their leveled cost of energy. As such, developing techniques to mitigate these costs through the application of condition monitoring and fault tolerant control will significantly impact the economic feasibility of grid connected WEC power. Toward this goal, models of faulty components are developed in the open source modeling platform, WEC-Sim, to estimate the performance and measurable states of a WEC operating with likely device and sensor failures. Two types of faulty component models are then applied to a point absorber WEC model with basic controller damping and spring forces. Resulting changes in device behavior are recorded as a benchmark, and a graph-theoretic approach is proposed for fault detection and identification utilizing multivariate time series. Simulation results demonstrate that these faults can greatly affect the WEC performance, and that the proposed method can effectively detect and classify different types of faults.

16 TIDAL AND WAVE POWER↗