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At least 1,549 records · Page 86

Co-Generation Wastewater Treatment at Coal-Fired Energy Plants (Final Report)

Steam electric energy generation typically results in the discharge of one or more effluent streams. Coal-fired energy plant air quality regulations have had the effect of transferring pollutants previously in the flue gas to water by means of the flue gas desulfurization (FGD) system. Combined physical-chemical and biological treatment solutions are currently the most economical approach for treating FGD wastewater. Multi-effect evaporators are significantly higher cost but can meet potential upcoming regulations that are more stringent.

01 COAL, LIGNITE, AND PEAT↗

Collaborative Proposal: Fire, Dust, Air and Water: Improving Aerosol Biogeochemistry Interactions in ACME

This document describes results from a grant studying the role of fire in the Earth system, as a source of nutrients to land and marine ecosystems. Iron is a nutrient that often limits plant growth in the oceans. Wildfires, as well as the combustion when we are burning fossil fuels, releases iron to the atmosphere that can later be deposited on the oceans, fueling plant growth.

58 GEOSCIENCES↗

Fire Modeling of a Facility for Combustible Loading

The purpose of this project was to create a fire model of the facility. Results from the model will be used to establish standoff distances from combustible fuel packages in the facility, in order to protect material from a thermal event.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

AOI.1 Application of Artificial Intelligence techniques enabling coal fired power plants the ability to achieve higher efficiency, improved availability, and increased reliability of their operations (Final Report)

During this effort, SparkCognition with support from the Electric Power Research Institute (EPRI) was tasked with applying artificial intelligence (AI) to improve the reliability, efficiency, and safety of operations at a coal-fired plant. By implementing AI techniques, like machine learning (ML), it is believed that operators can leverage existing data sources to gain more insights such as advanced warning of machine degradation. With enough lead time, a reliability engineer can take action to minimize, or even avoid, impact to production. To complete this work effort, SparkCognition developed and refined an ML-based model using sensor data for a Steam Turbine unit at a host site. The models were deployed in an online, web-based solution that allows users to visualize model outputs and supporting data. The final solution, based on SparkCognition’s proprietary software platform called SparkPredict®, was shared with EPRI who completed an online evaluation of results to determine the solution’s ability to detect actionable events.

20 FOSSIL-FUELED POWER PLANTS↗

Los Alamos National Laboratory Floodplain Assessment for the Technical Area 72 Outdoor Live Fire Range Safety Upgrades Project

The National Nuclear Security Administration (NNSA), a semi-autonomous agency within the U.S. Department of Energy (DOE), is proposing new construction and upgrade activities in lower Sandia Canyon at Technical Area (TA) 72 at the Outdoor Live Fire Range facility at Los Alamos National Laboratory (LANL). The proposed upgrades are intended to improve range safety to help fulfill the mission requirements of maintaining a trained and qualified armed Protective Force.

54 ENVIRONMENTAL SCIENCES↗

Improving Coal-Fired Plant Performance Through Integrated Predictive and Condition-Based Monitoring Tools

The project demonstrated the ability to improve boiler performance and reliability through the integrated use of condition-based monitoring (CBM) and predictions of the impacts of coal quality on boiler operations at a full-scale coal-fired power plant. The advanced tool developed actively monitors and manages coal quality and overall boiler conditions that maximizes availability and maintains generating capacity while reducing cost. The tool is used to forecast and alert plant operators and engineers about poor boiler conditions which may occur as a result of incoming coal and/or current power plant operating conditions. The Combustion System Performance Indices (CSPI) and CoalTracker (CT) programs predicts fireside performance of the plant including slagging, fouling, erosion, slag flow, strength development (sintering/densification), and slag layer thickness based on the composition of delivered coal. CT program is tailored for each plant and is used to track the coal from the point of delivery to the burner. The most successful application of the CSPI-CT has been at plants where the coal composition is determined through the use of a full stream elemental analyzers based on prompt gamma neutron analysis (PGNAA). The CSPI-CT program information is used by coal procurement, coal mining and plant operations personnel to select and blend coal properties for the best plant performance.

01 COAL, LIGNITE, AND PEAT↗

Field Scale Testing of the Thermocatalytic Ethylene Production Process Using Ethane and Actual Coal Fired Flue Gas Co 2

This report provides a summary of the work performed and results obtained from a project supported by the US DOE (DE-FE0031713). In this study, Southern Research (SR) completed field-scale demonstration of a rationally designed novel nano-engineered catalyst driven thermochemical process to produce high yield of ethylene by using CO 2 derived from actual coal-fired flue gas and ethane. This process, referred to here as “CO 2 -ODH” due to CO 2 use via oxidative dehydrogenation (ODH) mechanism, follows a modified pathway to classical steam cracking (SC) process of ethylene production thus paving the way for significantly reduced CO 2 footprint, marginally improved thermodynamics, higher product selectivity and lower reaction temperatures.

01 COAL, LIGNITE, AND PEAT↗

Fission In R-process Elements (FIRE) - Quarterly Report (Q2FY22)

The goal of the FIRE topical collaboration in nuclear theory was to determine the astrophysical conditions of the rapid neutron capture process (r-process), which is responsible for the formation of heavy elements. This was be achieved by including in r-process simulations the most advanced models of fission (spontaneous, neutron-induced, β-delayed) that have been developed at LLNL and LANL. The collaboration was composed of LLNL (lead) and LANL for fission work, BNL for nuclear data management, and the university of Notre Dame and North Carolina State University for r-process simulations. Under DOE/NNSA agreement, both universities received funds from DOE Office of Science, while national laboratories receive funds directly from NA221.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fission In R-process Elements (FIRE)

The goal of the FIRE topical collaboration in nuclear theory was to determine the astrophysical conditions of the rapid neutron capture process (r-process), which is responsible for the formation of heavy elements. This was achieved by including in r-process simulations the most advanced models of fission (spontaneous, neutron-induced, β-delayed) that have been developed at LLNL and LANL. The collaboration was composed of LLNL (lead) and LANL for work on nuclear data (ground-state properties, fission, β-decay), BNL for nuclear data management, and the university of Notre Dame and North Carolina State University for r-process simulations. Under DOE/NNSA agreement, both universities received funds from the DOE Office of Science, while national laboratories received funds directly from NA221.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Fission In R-process Elements (FIRE)

The goal of the FIRE topical collaboration in nuclear theory was to determine the astrophysical conditions of the rapid neutron capture process (r-process), which is responsible for the formation of heavy elements. This was be achieved by including in r-process simulations the most advanced models of fission (spontaneous, neutron-induced, β-delayed) that have been developed at LLNL and LANL. The collaboration was composed of LLNL (lead) and LANL for fission work, BNL for nuclear data management, and the university of Notre Dame and North Carolina State University for r-process simulations. Under DOE/NNSA agreement, both universities received funds from DOE Office of Science, while national laboratories receive funds directly from NA221.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improving Reliability, Weight and Cost of Gas-Fired Absorption Heat Pumps

The objective of the project was to identify and verify a viable path for the use of aluminum tubes in evaporators for gas-fired ammonia-water absorption heat pumps (GAHP), via identification of a suitable alloy, coating, inhibitor, process, or combination, for the purpose of achieving weight and cost reduction.

03 NATURAL GAS↗

Los Alamos National Laboratory Floodplain Assessment for the Technical Area 72 Outdoor Live Fire Range Gate Installation Project

The National Nuclear Security Administration (NNSA), a semi-autonomous agency within the U.S. Department of Energy (DOE), is proposing new construction in lower Sandia Canyon at Technical Area (TA) 72 at the Outdoor Live Fire Range facility at Los Alamos National Laboratory (LANL). The proposed upgrades are intended to improve range safety.

54 ENVIRONMENTAL SCIENCES↗

Technology Maturation of Wireless Harsh Environment Sensors For Improved Condition Based Monitoring Of Coal Fired Power Generation

The overall goal of this project was to demonstrate and develop the usage of high-temperature (HT) harsh-environment (HE) wireless surface acoustic wave resonator (SAWR) sensor technology to promote reliable maintenance through condition-based maintenance (CBM) for field applications in harsh service conditions associated with power plant environments. The project aimed to advance the HT HE wireless SAWR sensor technology from TRL 5 to TRL 7. In addition to HT HE wireless temperature sensing, efforts were dedicated during this project to investigate, develop and increase the TRL from 3 to 5 for the following technologies: (a) HT HE strain sensors to address additional CBM monitoring needs, such as boiler tube mechanical / thermal stresses, which can provide early indications for boiler tube cracking and failure; and (b) HT aluminum nitride (AlN) and scandium aluminum nitride (ScAlN) based piezoelectric thin film fabrication and implementation of SAW sensors, with the goal of releasing the need to use single crystal piezoelectric materials for SAWRs and thus broaden possible technology applications to non-planar and harder to modify surfaces. To achieve the goals mentioned above, UMaine and its partner, Environetix Technologies Corporation, established partnerships with the following power plants: Longview Power (Maidsville, WV), a coal-fired power plant; Penobscot Energy Recovery Corp (PERC, Orrington, ME), a waste-to-energy power plant; and the UMaine Steam Plant (Orono, ME), an oil / natural gas power plant. To realize wireless HT HE SAWR sensor systems in these harsh service conditions, the University of Maine research team worked with Environetix and these power plants to define, design, fabricate, test and validate a mature prototype wireless temperature SAWR sensor system for boiler tube applications within the HT HE of the reheater pass damper chamber to directly and wirelessly monitor the temperature at eighteen independent boiler tube locations. The system included three levels, or “tiers”, of wireless communication to enable remote monitoring: Tier 1, the wireless link in the reheater pass damper chamber directly accessing the sensors on the boilers; Tier 2, the wireless local area network link, transmitting processed sensor information within the power plant to the Tier 3, a commercial wireless signal carrier company for secure remote data monitoring outside of the power plant. Regarding the wireless sensor system installed at Longview Power, temperature information from the boilers was continuously transmitted from the Longview boilers at Maidsville, WV, to Environetix headquarters, Orono, ME, over a 34 month period, when the system was finally decommissioned. Strain sensors and piezoelectric ScAlN thin film sensors were successfully installed on the exhaust duct at the UMaine Steam Power plant. The advances in wireless strain sensors and thin film piezoelectric film fabrication and testing were performed mostly in UMaine laboratories and field tested at the UMaine Steam Plant, due to its close proximity to UMaine/Environetix, access to the plant facility, and due to difficulties in accessing the other power plants during the COVID shut-down period. The project accomplished the TRL level increase of the targeted CBM technologies through the successful fabrication, installation, test, and validation of dedicated and commercial wireless sensor systems, utilizing the three different power plants. The outcomes of this project, including the wireless sensor data capability, are expected to yield an advance for CBM in harsh power plant environments. The reduction of maintenance costs, improved safety during plant operation, and increased power plant efficiency will lead to increased revenues (i.e., fewer forced outages) due to better process monitoring enabled by the wireless HT HE SAWR temperature sensor technology.

20 FOSSIL-FUELED POWER PLANTS↗

Fission In R-process Elements (FIRE) (NA-22 Quarterly Report, Q4FY22)

The goal of the FIRE topical collaboration in nuclear theory was to determine the astrophysical conditions of the rapid neutron capture process (r-process), which is responsible for the formation of heavy elements. This was be achieved by including in r-process simulations the most advanced models of fission (spontaneous, neutron-induced, β-delayed) that have been developed at LLNL and LANL. The collaboration was composed of LLNL (lead) and LANL for fission work, BNL for nuclear data management, and the university of Notre Dame and North Carolina State University for r-process simulations. Under DOE/NNSA agreement, both universities received funds from DOE Office of Science, while national laboratories receive funds directly from NA221.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Validation Analysis of Medium-Scale Methanol Pool Fire Simulated in SIERRA/Fuego [Slides]

Analysis of methanol pool fire conducted as part of validation study for SIERRA/Fuego. Results showed trends & errors consistent with related studies. Area validation metric provides way to quantify model form uncertainty. AVM shows that more work could be done to understand how model form uncertainty varies with mesh resolution. There is a possible atypical use of MAVM on time-series data. AVM shows mismatch between predicted flame height and experimental value less sensitive to variations in mixture fraction than temperature. Mismatch about experimental value also more symmetric for mixture fraction. Our analysis showed that mixture fraction is preferable for this application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of Radiative Heat Transfer and Flow Physics from Medium-scale Methanol Pool Fire Simulations [Slides]

Analysis of methanol pool fire conducted as part of validation study for SIERRA/Fuego. Radiation model was effectively calibrated by modifying radiation model parameters for methanol. Computing integrated buoyancy flux, entrainment rate, and turbulent kinetic energy allowed for evaluation of less typical quantities in this validation study. Quantities were compared with experimental data or correlations and generally showed agreement. TKE needed fine mesh to be computed accurately. Predicted flame height less sensitive to variations in mixture fraction than temperature. Mixture fraction is a preferable threshold variable for this application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗