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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The Next Generation System Analysis Model: Capabilities for Simulating a Waste Management System - 19131

The U.S. Department of Energy (DOE) Office of Nuclear Energy Office of Spent Fuel and Waste Disposition's Integrated Waste Management System (IWMS) program is applying integrated waste management system architecture analysis, system engineering, and decision analysis principles to inform potential future decisions regarding potential nuclear waste management system architectures. Architecture analyses of the IWMS are being conducted to support the future deployment of a comprehensive system for managing nuclear waste that considers all major aspects of the back end of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The system architecture analyses consider alternative disposition pathways for commercial spent nuclear fuel (SNF) being stored dry in at-reactor Independent Spent Fuel Storage Installations (ISFSIs) or wet in spent-fuel pools. One method for evaluating these alternatives is simulating the movement of SNF throughout the system components. Successfully simulating a system on the scale of a national waste management system requires - accurate baseline information (e.g., historic fuel discharges from reactors and dry storage loadings at reactor sites), - modeling all logistic interactions between components of the proposed system, and - tracking and reporting all relevant details regarding the simulation's execution. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool designed for the express purpose of modeling the IWMS. It is based on the Performance Analysis Tool, a simulation platform that has been used to model logistics for the Department of Defense and the Federal Emergency Management Agency. Using existing, government-owned software allows NGSAM developers to modify the software at the level of source code and to develop flexible usability and modeling solutions for developing and running simulations of the IWMS. NGSAM imports data from the Oak Ridge National Laboratory (ORNL) Unified Database (e.g., historic assembly information, thermal profiles for assembly heat, at-reactor dry storage loadings) to ensure that the simulation initializes with a realistic representation of the state of commercial SNF in the United States. NGSAM is designed with the flexibility to model and track the behavior of virtually any IWMS architecture assumptions or design considerations. For example, NGSAM can model multiple interim storage facilities or repositories or none at all. Similarly, all assumptions regarding shipment schedules, operating schedules, and reactor operation assumptions can be modeled and adjusted in NGSAM with relative ease. The development of NGSAM was targeted to waste management system analysts as the primary users. With that in mind, analysts from ORNL, Sandia National Laboratories (SNL), and Argonne National Laboratory (ANL) were intimately involved in the development process. That involvement extended beyond merely defining requirements. System analysts have been involved with design decisions and software benchmarking and tests, and they have provided subject-matter expertise where necessary. The result is a high degree of interaction between professional software developers and system analysts, with a multitude of benefits to both groups. This paper explores some of the underlying methodology of the agile software development process used in the creation of NGSAM. It illustrates the capabilities of NGSAM. Some example use cases are discussed as well, with relevant results providing context for how NGSAM is used by system analysts to gain a greater understanding of alternative waste management system architectures. This is a technical paper that does not take into account the contractual limitations under the Standard Contract for Disposal of Spent Nuclear Fuel and/or High-Level Radioactive Waste (Standard Contract) (10 CFR Part 961). Under the provisions of the Standard Contract, DOE does not consider spent nuclear fuel in multi-assembly canisters to be an acceptable waste form, absent a mutually agreed-to contract amendment. To the extent discussions or recommendations in this paper conflict with the provisions of the Standard Contract, the Standard Contract provisions prevail. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Creative absorber design and optimization for CO 2 capture with aqueous piperazine

The Texas Carbon Management Program is preparing a Front-End Engineering Design (FEED) of the PZASTM (Piperazine with the Advanced Stripper TM ) for CO 2 capture at a natural gas combined cycle power plant in West Texas. This paper develops the absorber design for the capture system and studies the operational strategies of the absorber in response to ambient temperature swing. The design uses 2 absorber trains, and each train integrates absorption and a water-wash section in one column. Each column has a cross-section area of 174 m 2 and consists of 3 sections of MellapakPlus® 252Y structured packing. Packing heights for each section are 3, 4.9, and 2.7 m from top to bottom. A pump-around intercooler applied at the bottom bed circulates solvent and eliminates the direct contact cooler. The baseline CO 2 removal rate is 90% and will vary between 78% and 90% with ambient temperature. The system uses air cooling to eliminate cooling water usage. The water balance in the system will be managed by operating the water wash at a high circulation rate (1300 kg/h) to condense water during the night and make up for water loss during the day. Finally, the proposed design reduces the capital cost of the absorber column by minimizing the packing height and eliminating the direct contact cooler (DCC), and improves the energy cost by lowering the pump-around intercooling temperature and increasing the pump-around rate.

03 NATURAL GAS↗
DOE OSTI2015

Criteria Considered in Selecting Feed Items for Americium-241 Oxide Production Operations

The analysis in this document serves the purpose of defining a number of attributes in selection of feed items to be utilized in recovery/recycle of Pu and also production operations of 241 AmO 2 material intended to meet specification requirements. This document was written in response to a specific request on the part of the 2014 annual program review which took place over the dates of October 28-29, 2014. A number of feed attributes are noted including: (1) Non-interference with existing Pu recovery operations; (2) Content of sufficient 241 Am to allow process efficiency in recovery operations; (3) Absence of indications that 243 Am might be mixed in with the Pu/ 241 Am material; (4) Absence of indications that Cm might be mixed in with the Pu/ 241 Am material; (5) Absence of indications of other chemical elements that would present difficulty in chemical separation from 241 Am; (6) Feed material not expected to present difficulty in dissolution; (7) Dose issues; (8) Process efficiency; (9) Size; (10) Hazard associated with items and package configuration in the vault; (11) Within existing NEPA documentation. The analysis in this document provides a baseline of attributes considered for feed materials, but does not presume to replace the need for technical expertise and judgment on the part of individuals responsible for selecting the material feed to be processed. This document is not comprehensive as regards all attributes that could prove to be important. The value of placing a formal QA hold point on accepting feed items versus more informal management of feed items is discussed in the summation of this analysis. The existing planned QA hold points on 241 AmO 2 products produced and packaged may be adequate as the entire project is based on QA of the product rather than QA of the process. The probability of introduction of items that would inherently cause the 241 AmO 2 products produced to be outside of specification requirements appears to be rather small.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Sister Rod Destructive Examinations (FY23) Appendix C: Rod Internal Pressure, Void Volume, and Gas Transmission Tests

As a part of the DOE NE High Burnup Spent Fuel Data Project, Oak Ridge National Laboratory (ORNL) is performing destructive examinations (DEs) of high burnup (HBU) (>45 GWD/MTU) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy. The SNF rods, called the sister rods or sibling rods, are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4 (Zirc-4), low-tin (LT) Zirc-4, ZIRLO, and M5. The DEs are being conducted to obtain a baseline of the HBU rod’s condition before dry storage and are focused on understanding overall SNF rod strength and durability. Both fuel rods and empty cladding will be tested to derive material properties. Although the data generated can be used for multiple purposes, one primary goal for obtaining the postirradiation examination data and the associated measured mechanical properties is to support SNF dry storage licensing and relicensing activities by (1) addressing identified knowledge gaps and (2) enhancing the technical basis for post-storage transportation, handling, and consolidation activities. This appendix documents the status of the ORNL Phase 1 DE activities related to rod internal pressure and void volume measurement techniques, fission gas stack flow measurements applied to selected sister rods, and fission gas release calculations in Phase 1 of the sister rod test program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California Independent System Operator’s (ISO) load forecasts by integrating behind-the-meter (BTM) PV forecasts. The three, new, state-of-the-art solar irradiance forecasting models included: the infrared (IR) satellite-based cloud motion vector (CMV) model; the WRF-SolarCA model and variants; and the Optimized Deep Machine Learning (ODML)-training model. The first two forecasting models targeted known weaknesses in current operational solar forecasts. They were benchmarked against existing operational numerical weather prediction (NWP) forecasts, visible satellite CMV forecasts, and measured PV plant power production. IR CMV, WRF-SolarCA, and ODML-training forecasting models all improved the forecast to a significant degree. Improvements varied depending on time of day, cloudiness index, and geographic location. The fourth objective was to demonstrate that the California ISO’s load forecasts could be improved by integrating BTM PV forecasts. This objective represented the project’s most exciting and applicable gains. Operational BTM forecasts consisting of 200,000+ individual rooftop PV forecasts were delivered into the California ISO’s real-time automated load forecasting (ALFS) environment. They were then evaluated side-by-side with operational load forecasts with no BTM-treatment. Overall, ALFS-BTM day-ahead (DA) forecasts performed better than baseline ALFS forecasts when compared to actual load data. Specifically, ALFS-BTM DA forecasts were observed to have the largest reduction of error during the afternoon on cloudy days. Shorter term 30 minute-ahead ALFS-BTM forecasts were shown to have less error under all sky conditions, especially during the morning time periods when traditional load forecasts often experience their largest uncertainties. This work culminated in a GO decision being made by the California ISO to include zonal BTM forecasts into its operational load forecasting system. The California ISO’s Manager of Short Term Forecasting, Jim Blatchford, summarized the research performed in this project with the following quote: “The behind-the-meter (BTM) California ISO region forecasting research performed by Clean Power Research and sponsored by the Department of Energy’s SUNRISE program was an opportunity to verify value and demonstrate improved load forecast capability. In 2016, the California ISO will be incorporating the BTM forecast into the Hour Ahead and Day Ahead load models to look for improvements in the overall load forecast accuracy as BTM PV capacity continues to grow.”

14 SOLAR ENERGY↗
DOE OSTI2024

Differentiable vertex fitting for jet flavor tagging

This work explores the use of differentiable programming to integrate domain knowledge, in the form of domain specific software, into neural networks to develop scientific machine learning systems. We propose a differentiable vertex fitting algorithm that estimates the crossing point of multiple curves. In the high energy physics setting, these curves are defined by particle equations of motion and the crossing point represents the origin of particle production. This differentiable vertex fitting algorithm can be seamlessly integrated into neural networks, and we show its utility and efficacy in the high energy physics application of the classification of jets, i.e., collimated streams of particles in particle detectors whose originating parent particle we aim to classify. We demonstrate how differentiable vertex fitting can be integrated into larger transformer-based models for jet flavor tagging and show improvements in heavy flavor jet classification when compared to baseline models. Published by the American Physical Society 2024

Smith, Rachel E. C. (ORCID:0000000335851262)↗
DOE OSTI2014

Report on High-Contrast Advanced Radiographic Capability Review

The Advanced Radiographic Capability (ARC) project at the National Ignition Facility (NIF) is designed to generate picosecond duration, kilo-Joule laser pulses to produce xrays for backlighting NIF experiments. The baseline concept (Figure 1), utilizing a single NIF beam quad, diverts the beamline(s) using insertable pick-off mirrors to a compressor chamber in the target bay and focuses it to target chamber center. When fully implemented, ARC will use a quad of NIF beamlines to deliver eight Petawatt-class, high-intensity pulses in a split aperture configuration (2 short pulse apertures per NIF beamline). These short pulses will be adjustable in energy (up to 13.2 kJ in full implementation), delays (0-80 ns) and pulse durations (1-50 ps) and can be individually pointed to targets. ARC will enable dynamic, multi-frame x-ray imaging (radiography) on NIF for applications in laser driven fusion and other high-energy density science missions. The near-term missions in support of the SSP program are described below.

42 ENGINEERING↗
DOE OSTI2023

Sister Rod Destructive Examinations (FY22) Appendix C: Rod Internal Pressure, Void Volume, and Gas Transmission Tests

As a part of the DOE NE High Burnup Spent Fuel Data Project, Oak Ridge National Laboratory (ORNL) is performing destructive examinations (DEs) of high burnup (HBU) (>45 GWD/MTU) spent nuclear fuel (SNF) rods from the North Anna Nuclear Power Station operated by Dominion Energy [C-1]. The SNF rods, called the sister rods or sibling rods, are all HBU and include four different kinds of fuel rod cladding: standard Zircaloy-4 (Zirc-4), low-tin (LT) Zirc-4, ZIRLO, and M5. The DEs are being conducted to obtain a baseline of the HBU rod’s condition before dry storage and are focused on understanding overall SNF rod strength and durability. Both fuel rods and empty cladding will be tested to derive material properties. Although the data generated can be used for multiple purposes, one primary goal for obtaining the postirradiation examination data and the associated measured mechanical properties is to support SNF dry storage licensing and relicensing activities by (1) addressing identified knowledge gaps and (2) enhancing the technical basis for post-storage transportation, handling, and consolidation activities. This appendix documents the status of the ORNL Phase 1 DE activities [C-2, C-3] related to rod internal pressure and void volume measurement techniques, fission gas stack flow measurements applied to selected sister rods, and fission gas release calculations in Phase 1 of the sister rod test program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Topical Report – Findings on Subtask 2.7 – Wet ESP and Aerosol Testing at Coal Creek Station

Growing concerns over the impact of CO 2 emissions from combustion sources on global climate change have prompted numerous research and development projects aimed at developing cost-effective technologies for CO 2 capture. One family of technologies being demonstrated at pilot and full scale globally is postcombustion carbon capture (PCCC) systems that employ amine-based solvents. The captured CO 2 can be compressed and permanently stored underground or used for enhanced oil recovery. The proximity of North Dakota’s lignite-fired fleet of power plants to potential CO 2 storage options creates a unique atmosphere for PCCC within the state. However, the unique components present in lignite flue gas present a challenge for large-scale PCCC at North Dakota power plants by contributing to aerosol formation. Aerosols can negatively impact the long-term performance of amine-based solvents for CO 2 capture. Amine-based solvents are volatile, and flue gas particulate provides nucleation sites where amine vapors can condense as aerosols. Because aerosols cannot be easily captured at the column outlet using conventional technologies, the amine-laden aerosols escape the system and lead to accelerated solvent losses. Moreover, particulate components can chemically react with amines to form degradation products that can permanently deactivate the amine, cause fouling, and lead to hazardous emissions. Many of the elements that have been shown to catalyze solvent degradation are present in lignite coals and can exacerbate solvent replacement economics. Understanding this issue is critical to the implementation of solvent-based CO 2 capture systems as applied to lignite-fired generation systems. The Energy & Environmental Research Center (EERC) designed and carried out this project to fully characterize aerosol behavior with various control technologies installed to better optimize aerosol mitigation technology for CO 2 capture. To meet the goal of this project, the following objectives were identified: Determine the effectiveness of a wet electrostatic precipitator (WESP) on mitigating formation of problematic aerosols at Great River Energy’s Coal Creek Station, upstream of the PCCC system. Determine the effectiveness of the Mitsubishi Heavy Industries (MHI) proprietary amine emission reduction unit (AERU) as a postcapture solvent recovery system for reducing aerosol emissions and extending solvent life downstream of the PCCC system. Determine the impact of aerosols on the efficiency and degradation products of both commercial and advanced solvents within the PCCC system. Work was conducted at Coal Creek Station Unit 1 using a slipstream of flue gas from the outlet of the plant’s flue gas desulfurization (FGD) unit. Flue gas was routed through a pilot-scale FGD unit to remove SO 2 to very low levels (~1 ppm) and then through a direct contact cooler (DCC) to further cool the gas and to remove moisture. The gas exiting the DCC was then optionally routed through a WESP before passing to the CO 2 absorber columns. The MHI solvent was used to scrub CO 2 from the slipstream through a set of two absorber columns. The rich solvent was regenerated in a stripper column by heating to drive off captured CO 2 . Flue gas exiting the absorber column was routed to MHI’s proprietary AERU to recover entrained solvent. The system operated using a catch-and-release method where the CO 2 was separated to provide data on the process, but the captured CO 2 was released back into the host site stack. Particulate was measured, collected, and analyzed from multiple locations throughout the pilot-scale system. Unlike the performance observed in prior work, the inlet FGD and DCC did not remove significant particulate matter from the flue gas. This appears to be due to a difference in the nature of the particulate. The DCC seemed to increase particulate size and count, most likely owing to water condensing onto the surfaces of fly ash particles. When the WESP was operated, it achieved >95% particulate capture. Very little particulate matter or indications of solvent were detected at the AERU outlet. When operating with advanced KS 21 solvent, the particulate material at the AERU outlet was even further decreased. Solvent analysis showed that some species derived from flue gas and ash were slowly concentrating in the solvent over the duration of the test. The levels observed were reported to be within expected ranges and were not of concern to MHI. A high-level techno-economic assessment of installing CO 2 capture at Coal Creek Station suggested that, when using a standard monoethanolamine (MEA)-based solution with simple heat integration, the energy penalty to net generation would be 34%. The bulk of this was due to steam losses for regenerating solvent, followed by parasitic electrical demand for CO 2 compression and then by increased parasitic load for pushing flue gas through the absorber column. These demands could be decreased with a more advanced solvent that exhibits lower heat of regeneration and lower pressure drop than does a simple MEA solution. Further energy could be saved with more thorough heat integration to recover useful energy from the steam used for solvent regeneration. Installing a WESP was predicted to increase the cost of electricity by nearly $5/MWh. This would become cost-effective if solvent losses were roughly 10 times the baseline estimate when not using a WESP but could be returned to baseline by installing the WESP. Piping CO 2 for storage in more favorable geology could help with carbon capture and storage economics. Although storing off-site would necessitate construction of a CO 2 transport pipeline, the cost of this pipeline might be more than offset by reducing the number of wells required, the depths of the wells required, and the electrical demand for the CO 2 compressor. Additional factors that favor off-site storage costs include smaller expected CO 2 plume sizes, which translates to less monitoring and fewer landowner agreements. More detailed assessment of the specific geology in the region under and around Coal Creek Station would be needed to accurately assess the costs and benefits of different storage site options. This subtask was cofunded through the Energy & Environmental Research Center–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission.

Strege, Joshua↗
DOE OSTI2014

FutureGen 2.0 Monitoring Program: An Overview of the Monitoring Approach and Technologies Selected for Implementation

The FutureGen 2.0 Project will design and build a first-of-its-kind, near-zero emissions coal-fueled power plant with carbon capture and storage (CCS). To assess storage site performance and meet the regulatory requirements of the Class VI Underground Injection Control (UIC) Program for CO2 Geologic Sequestration, the FutureGen 2.0 project will implement a suite of monitoring technologies designed to 1) evaluate CO2 mass balance and 2) detect any unforeseen loss in CO2 containment. The monitoring program will include direct monitoring of the injection stream and reservoir, and early-leak-detection monitoring directly above the primary confining zone. It will also implement an adaptive monitoring strategy whereby monitoring results are continually evaluated and the monitoring network is modified as required, including the option to drill additional wells in out-years. Wells will be monitored for changes in CO2 concentration and formation pressure, and other geochemical/isotopic signatures that provide indication of CO2 or brine leakage. Indirect geophysical monitoring technologies that were selected for implementation include passive seismic, integrated surface deformation, time-lapse gravity, and pulsed neutron capture logging. Near-surface monitoring approaches that have been initiated include surficial aquifer and surface- water monitoring, soil-gas monitoring, atmospheric monitoring, and hyperspectral data acquisition for assessment of vegetation conditions. Initially, only the collection of baseline data sets is planned; the need for additional near- surface monitoring will be continually evaluated throughout the design and operational phases of the project, and selected approaches may be reinstituted if conditions warrant. Given the current conceptual understanding of the subsurface environment, early and appreciable impacts to near-surface environments are not expected.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Development of Advanced Instrumentation for Transient Testing

A fuel safety research program centered on in-pile transient testing experiments is being developed to support assessment and qualification of advanced nuclear fuel systems using the recently restarted Transient Reactor Test (TREAT) facility at the Idaho National Laboratory (INL). While resumption of transient testing at TREAT is crucial to enable these programs, full recovery and cutting-edge transient testing capability also requires a well-coordinated and innovative instrumentation development and qualification program to support near-term and future objectives. This paper summarizes the experimental approach of transient testing to focus on measuring the response of nuclear fuel to off-normal (or power-cooling mismatch) conditions for modern and advanced reactor environments requiring capabilities extending over wide measurement and environment conditions. It also highlights unique attributes of transient testing of importance to in-pile instruments including relatively low total neutron fluence, high gamma heating, and the need for well-defined and possibly short time response. Historical approaches to instrumentation for transient testing are also reviewed to provide context to the modern instrument strategy. The instrumentation needs of a modern transient testing are detailed while summarizing several ongoing R&D activities are supporting the development of state-of-the-art and ‘advanced’ measurement technologies that will provide baseline capability for Light Water Reactor (LWR) and Sodium-Cooled Fast Reactor (SFR) experiment objectives, while extending to other advanced reactor needs and advanced sensing technology opportunities. Examples of specific sensors planned for near-term deployment with ongoing development includes prompt-response self-powered neutron detectors (SPND), miniature fission chambers, optical-fiber-coupled infrared pyrometer, cladding surface thermocouples, electrical-impedance based boiling detector, and Linear Variable Differential Transformer (LVDT) based sensors for fuel elongation and pressure measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Model-based predictive control of multi-stage air-source heat pumps integrated with phase change material-embedded ceilings

This paper presents a model-based predictive control strategy to optimize the operations of phase change material (PCM) ceiling panels coupled with a multi-stage air-source heat pump. A three-stage prototype heat pump unit has been built and tested in the laboratory, with the low and medium stages designed for space heating/cooling and the high compression stage dedicated to charging of the PCM energy storage. To facilitate optimal control of the integrated heat pump system, a mixed-integer linear programming formulation is derived through linearization of the heat pump model and a mixed-integer reformulation of the PCM dynamic governing equations. A predictive control strategy is synthesized based on the resultant control formulation and implemented in a receding horizon scheme that optimizes the PCM charging and the zone temperature schedules simultaneously to leverage both the passive (associated with building construction materials) and active (PCM) storage capacities of a building. The control strategy has been tested along with three benchmarking control scenarios using a co-simulation platform for a prototypical detached house in Atlanta, GA. In this study, test results showed that application of the proposed control strategy to the PCM-integrated heat pump could provide 27.1% electricity cost savings while a fine tuned rule-based control strategy could achieve cost savings of 20.4%, compared to a baseline case without PCM storage, under a time-of-use rate tariff.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

A Cooperative Multi-Agent Deep Reinforcement Learning Framework for Real-Time Residential Load Scheduling

Internet-of-Things (IoT) enabled monitoring and control capabilities are enabling increasing numbers of household users with controllable loads to actively participate in smart grid energy management. Realizing an efficient real-time energy management system that takes advantage of these developments requires novel techniques for managing the increased complexity of the control action space in resolving multiple challenges such as the uncertainty in energy prices and renewable energy output along with the need to satisy physical grid constraints such as transformer capacity. Addressing these challenges, we develop a multi-household energy management framework for residential units connected to the same transformer and containing DERs such as PV, ESS and controllable loads. The goal of our framework is to schedule controllable household appliances and ESS such that the cost of procuring electricity from the utility over a horizon is minimized while physical grid constraints are satisfied at each scheduling step. Traditional energy management frameworks either perform global optimization to satisfy grid constraints but suffer from high computational complexity (for example Integer Program, Mixed Integer Programming frameworks and centralized reinforcement learning) or perform decentralized real-time energy management without satisfying global grid constraints (for example multi-agent reinforcement learning with no cooperation). In contrast, we propose a cooperative multiagent reinforcement learning (MARL) framework that i) operates in real-time, and ii) performs explicit collaboration to satisfy global grid constraints. The novelty in our framework is two fold. Firstly, our framework trains multiple independent learners (IL) for each household in parallel using historical data and performs real-time inferencing of control actions using the most recent system state. Secondly, our framework contains a low complexity knapsack based cooperation agent which combines the outputs of ILs to minimize cost while satisfying grid constraints. Simulation results show that our cooperative MARL approach achieves significant cost improvement over centralized reinforcement learning and day-ahead planning baselines. Moreover, our approach strictly satisfies physical constraints with no apriori knowledge of system dynamics while the baseline approaches have occasional violations. We also measure the training and inference time by ranging the number of households from 1 to 25. Results show that our cooperative MARL approach scales best among various approaches.

14 SOLAR ENERGY↗
DOE OSTI2022

Fine resolution remote sensing spectra improves estimates of gross primary production of croplands

Gross primary production (GPP) is a fundamental measure of the terrestrial carbon cycle critical to our understanding of ecosystem function under the changing climate and land use. Remote sensing enables access to continuous spatial coverage, but remains challenged in heterogeneous croplands. Coarse resolution products, like MOD17A (500 m), may aggregate fragmented land cover types commonly found in heavily managed landscapes and misrepresent their respective contribution to carbon production. Consequently, this study demonstrates the capability of fine-resolution imagery (20-30 m) and available red-edge vegetation indices to characterize GPP across seven Midwest cropping systems. Four sites were established on a 22-year-old USDA Conservation Reserve Program (CRP); and the other three on land conventionally farmed with corn-soybean-wheat rotation (AGR). We compare in situ GPP estimates from eddy-covariance towers with ten satellite models: eight variants of the vegetation photosynthesis models (VPM), of which five include a red-edge vegetation index, as well as conventional products Landsat CONUS GPP (30 m) and MOD17A2H V6 (500 m). Daily and cumulative fine-resolution imagery integrated within VPM generally agreed with tower-based GPP in heterogeneous landscapes more than those from MODIS 500 m VPM or conventional GPP products from MOD17AH V6 or Landsat 8 CONUS. Here, replacing EVI2 with red-edge indices NDRE2, NDRE1, and MTCI in Sentinel 2 VPMs notably improved explanation of variance and estimation of cumulative GPP. While existing methods using MODIS- and Landsat-derived GPP are important baselines for regional and global studies, future research may benefit from the higher spatial, temporal, and radiometric resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

San Francisco Biofuel Program: Brown Grease to Biodiesel Demonstration (Project Report)

Municipal wastewater treatment facilities have typically been limited to the role of accepting wastewater, treating it to required levels, and disposing of its treatment residuals. However, a new view is emerging which includes wastewater treatment facilities as regional resource recovery centers. This view is a direct result of increasingly stringent regulations, concerns over energy use, carbon footprint, and worldwide depletion of fossil fuel resources. Resources in wastewater include chemical and thermal energy, as well as nutrients, and water. A waste stream such as residual grease, which concentrates in the drainage from restaurants (referred to as Trap Waste), is a good example of a resource with an energy content that can be recovered for beneficial reuse. If left in wastewater, grease accumulates inside of the wastewater collection system and can lead to increased corrosion and pipe blockages that can cause wastewater overflows. Also, grease in wastewater that arrives at the treatment facility can impair the operation of preliminary treatment equipment and is only partly removed in the primary treatment process. In addition, residual grease increases the demand in treatment materials such as oxygen in the secondary treatment process. When disposed of in landfills, grease is likely to undergo anaerobic decay prior to landfill capping, resulting in the atmospheric release of methane, a greenhouse gas (GHG). This research project was therefore conceptualized and implemented by the San Francisco Public Utilities Commission (SFPUC) to test the feasibility of energy recovery from Trap Waste in the form of Biodiesel or Methane gas. The research goals are given below: To validate technology performance; To determine the costs and benefits [including economic, socioeconomic, and GHG emissions reduction] associated with co-locating this type of operation at a municipal wastewater treatment plant (WWTP); To develop a business case or model for replication of the program by other municipal agencies (as applicable). In order to accomplish the goals of the project, the following steps were performed: 1. Operation of a demonstration facility designed to receive 10,000 to 12,000 gallons of raw Trap Waste each day from private Trap Waste hauling companies. The demonstration facility was designed and built by Pacific Biodiesel Technologies (PBTech). The demonstration facility would also recover 300 gallons of Brown Grease per day from the raw Trap Waste. The recovered Brown Grease was expected to contain no more than 2% Moisture, Insolubles, and Unsaponifiables (MIU) combined. 2. Co-digestion of the side streams (generated during the recovery of 300 gallons of Brown Grease from the raw Trap Waste) with wastewater sludge in the WWTP's anaerobic digesters. The effects of the side streams on anaerobic digestion were quantified by comparison with baseline data. 3. Production of 240 gallons per day of ASTM D6751-S15 grade Biodiesel fuel via a Biodiesel conversion demonstration facility, with the use of recovered Brown Grease as a feedstock. The demonstration facility was designed and built by Blackgold Biofuels (BGB). Side streams from this process were also co-digested with wastewater sludge. Bench-scale anaerobic digestion testing was conducted on side streams from both demonstration facilities to determine potential toxicity and/or changes in biogas production in the WWTP anaerobic digester. While there is a lot of theoretical data available on the lab-scale production of Biodiesel from grease Trap Waste, this full-scale demonstration project was one of the first of its kind in the United States. The project's environmental impacts were expected to include: Reduction of greenhouse gas emissions by prevention of the release of methane at landfills. Although the combustion product of Biodiesel and Methane gas produced in the Anaerobic digester, Carbon Dioxide, is also a greenhouse gas; it is 20 times weaker for the same amount (per mole) released, making its discharge preferable to that of Methane. The use of Biodiesel in place of fossil-fuel derived Diesel was expected to reduce net Carbon Dioxide, Ash Particulate, Sulfate, Silicate, and Soot emissions, thereby improving air quality.

09 BIOMASS FUELS↗
DOE OSTI2023

Neutrino Scattering in the NOvA Near Detector

aNOvA is a long-baseline accelerator-based neutrino experiment based in the USA. NOvA uses an intense neutrino beam produced at Fermilab’s accelerator complex to make physics measurements of neutrino oscillations, neutrino cross sections, and much more. For its physics goals, NOvA uses two functionally-identical detectors. The Near Detector (ND) is situated at Fermilab, 1 km from the neutrino target and the Far Detector (FD) is located at Ash River, MN, a distance of 810 km from the neutrino source. The ND receives a high statistics neutrino flux which gives a unique opportunity for high-precision neutrino cross-section measurements and is used as a control for the oscillation analyses. In this talk/poster, I will give an overview of the NOvA experiment. I will also talk about the current and future status of the NOvA’s cross-section physics program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

2022 GETEM Geothermal Drilling Cost Curve Update: Preprint

The Geothermal Electricity Technology Evaluation Model (GETEM) is an essential tool for the Department of Energy's (DOE) Geothermal Technology Office (GTO) to understand the performance and cost of technologies it is seeking to improve. This detailed model is used for supply curve analyses, assessing the current economic feasibility and Levelized Cost of Energy (LCOE) of hydrothermal geothermal systems and EGS, and evaluating the potential impact of advanced geothermal technologies. GETEM can be used to estimate the performance and costs of currently available U.S. geothermal power systems. It is also used to estimate the costs of technologies 5 to 20 years in the future, given the direction of potential research, development, and demonstration (RD&D) projects. The model is intended to help GTO determine which proposed RD&D programs and projects might offer the most efficient improvement when using taxpayer funding. The model requires annual updates as well as revisions to reflect the current state of the art. Drilling costs are a significant portion of total geothermal development costs. The current GETEM drilling cost inputs rely on drilling data from 2009 and require an updated analysis of more recent data to ensure they remain representative of current technologies. An updated, more accurate understanding of costs could help the geothermal industry secure project development financing and investment funding and better allow the oil and gas (O&G) industry (both operators and service companies) weigh potential geothermal market participation and customization. This report details recent drilling improvements from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) and O&G, comparing drilling performance and costs with values in GETEM, particularly the baseline drilling cost curves. Though drilling performance at FORGE has improved significantly, we did not find associated cost decreases that would justify lowering the GETEM baseline cost curves as of now.

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DOE OSTI2022

Destructive Examination of Shipping Package 9975-02731

Destructive and non-destructive examinations were performed on the components of the package 9975-02731 as part of a comprehensive Savannah River Site surveillance program for plutonium materials stored in the K-Area Complex (KAC). The package stored nuclear materials in KAC for 13.8 years. Inspection of the package during opening in KAC noted one non-conforming condition: a large discolored area on the upper fiberboard subassembly. The package was subsequently transferred to Savannah River National Laboratory for more detailed examination. In addition to the observation noted in KAC, the following conditions were observed: (1) Axial gap of 1.021 inch slightly exceeded the 1 inch maximum criterion, and (2) Lead shield height exceeded drawing tolerance of 24.7 inch by 0.019 inch. Visual examination of the upper fiberboard assembly and analysis of the discolored fiberboard indicate the discoloration was due to wood glue residue. The physical, thermal, and mechanical properties of the fiberboard met the acceptance criteria and/or were within the range of previously tested fiberboard and baseline samples. The visual, microscopic and tensile testing results were consistent with previous O-ring and baseline Viton results. The lead shield surface was covered with corrosion product as observed on other shields but there was no evidence of excessive blistering, flaking, or spalling. Besides minor and expected corrosion, no evidence of a degraded condition was found in this package. Examination of the 9975-02731 corroborates existing evidence that the 9975 package is robust and the components can perform their expected functions.

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