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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Flammable Gas Generation and Control at the Idaho Completion Project Legacy Combustible Gas Generation - 20191

On April 11, 2018, four drums containing transuranic waste at the Idaho National Laboratory underwent over-pressurization, ejecting their lids and spreading radiological waste within a facility. An investigation has found that waste in the drums generated methane gas, which contributed to the event. Subsequent to the investigation, the potential for drums to have methane and other flammable analytes whose concentrations could approach or exceed the lower flammability limit (LFL) and the adequacy of the controls to prevent or mitigate a possible deflagration was evaluated. An extensive review of the historical records was performed to determine how many drums exceed the LFL. The historical record identified a small quantity of drums that exceeded the LFL for xylene, hydrogen, and methane. The primary codified applicable code or standard for handling drums is 29 CFR 1910.120 (j) 'Handling Drums and Containers.' It is used throughout the commercial and government sector. This code is integrated throughout the Fluor Idaho safety management programs and procedures to control the Standard Industrial Hazards (SIHs) associated with drum and container handling. Example requirements include: - Drums and containers are inspected, and their integrity assured prior to being moved. - Site operations are organized to minimize the amount of drum or container movement. - When there is a reasonable possibility of flammable atmospheres being present, material handling equipment and hand tools are of the type to prevent sources of ignition. Drums and containers under pressure, as evidenced by bulging or swelling, are not moved until the cause for excess pressure is determined and appropriate containment procedures have been implemented to protect employees from explosive relief of the drum. Drums which exceed the WIPP FGA limit have NCRs associated with them. Once a drum fails flammable gas sampling, an NCR is initiated. The NCR drives placement into NCR dense pack rows. A standing order drives placement of the FGA failures to a single planer segregation location. These drums are not allowed for further processing or shipment until the NCR has been cleared. Once in the single planer rows, follow-up FGA testing is performed by CCP. The NCR is dispositioned by follow-up sampling occurring after adequate time has been provided for the gas to diffuse through the filter assembly, or, in some cases, the drums are repackaged into additional drums to reduce the source term. To date, the ICP project has performed approximately 1.5 million drums moves without a deflagration event due to combustible gas generation. Flammable gas generation in a transuranic waste drum is not unique to the ICP but is common across the DOE complex. Based on the experience at Idaho, application of industry standards is sufficient to control the risk of drum deflagration due to drum movements. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Idaho National Laboratory Annual Report for Permit to Construct P-2015.0023 for Calendar Year 2020

The U.S. Department of Energy (DOE) Idaho National Laboratory (INL) Site operates facilities with potential emissions criteria and hazardous air pollutants. This report documents the calendar year 2020 criteria and hazardous air pollutants emissions and has been prepared to comply with permit to construct (PTC) P-2015-0023, Condition 2.9 and Idaho Administrative Procedures Act (IDAPA) 58.01.01.178, Standard Contents of Permits Establishing a Facility Emissions Cap (FEC). IDAPA 58.01.01.178.04 requires that all permits establishing a FEC shall include sufficient reporting to assure compliance with the permit establishing the FEC. Total hazardous air pollutant (HAP) emissions for the year were 0.59 tons in aggregate and the maximum individual HAP was hydrochloric acid at 0.35 tons. Criteria pollutant emissions were 1.23 tons for sulfur dioxide, 40.96 tons for oxides of nitrogen, 11.7 tons of carbon monoxide, 3.01 tons of total particulate matter and 1.98 tons of volatile organic compounds (VOC).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Annual FEC-PTC Report - CDRL F.70

The U.S. Department of Energy (DOE) Idaho National Laboratory (INL) Site operates facilities with potential emissions of criteria and hazardous air pollutants. This report documents the calendar year 2021 criteria and hazardous air pollutants emissions and has been prepared to comply with permit to construct (PTC) P-2015.0023 for the period of 1-1-2021 up to the effective date of PTC P 2020.0045 (1-29-2021), and PTC P-2020.0045 for the period from 1-29-2021 through 12-31-2021. The Idaho Administrative Procedures Act (IDAPA) 58.01.01.178, Standard Contents of Permits Establishing a Facility Emissions Cap (FEC) requires that all permits establishing a FEC shall include sufficient reporting to assure compliance with the permit establishing the FEC. Total hazardous air pollutant (HAP) emissions for the year were 0.10 tons in aggregate and the maximum individual HAP was toluene at 0.04 tons. Criteria pollutant emissions were 0.75 tons for sulfur dioxide, 24.33 tons for oxides of nitrogen, 6.07 tons of carbon monoxide, 2.53 tons of total particulate matter and 0.99 tons of volatile organic compounds (VOC).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Use of Multi-Attribute Utility Analyses to Assess Transportation Routes from ISFSIs - 20535

With two consolidated interim storage facilities for used nuclear fuel (UNF) having applied for storage licenses, there is the potential need to transport UNF in the U.S. from shutdown reactor sites to complete the site cleanup and from operating reactor sites who may be running out of storage options (e.g., spent fuel pools are nearly full and dry storage facilities are reaching licensed capacity). At some of the shutdown reactor sites, only the independent spent fuel storage installation (ISFSI) exists and often there remains a degraded transportation infrastructure for performing shipments from these sites. At other sites (e.g., operating reactor plants), the existing transportation infrastructure on the site is unchanged and sufficient for moving UNF, but the environment around the route may have changed (e.g., what was once a rural setting has transformed into a more urban setting) and/or local stakeholders want their input taken into consideration in UNF transportation activities. So, although preliminary evaluations have been performed to identify viable modes of transport from these sites using rail, barge, and/or heavy haul truck, if multiple options exist for moving the UNF from the site (e.g., multiple truck routes or a truck and a barge route both exist) then an evaluation that takes input from multiple stakeholders should be considered to identified the preference (e.g., ranking) of routes from a site. Orano has supported the development of several studies examining the viable routes for removing UNF from some of these sites and has utilized a multi-attribute utility analysis (MUA) to establish a ranking of routes and associated modes to move the UNF from the ISFSIs to a Class I rail carrier. The ultimate result from the MUA is a list(s) of the most to the least favored/preferred routes from the site. This paper provides an overview of the MUA methodology and provides an example of its application to a site with a shutdown reactor. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Predicting wind farm operations with machine learning and the P2D‐RANS model: A case study for an AWAKEN site

Abstract The power performance and the wind velocity field of an onshore wind farm are predicted with machine learning models and the pseudo‐2D RANS model, then assessed against SCADA data. The wind farm under investigation is one of the sites involved with the American WAKE experimeNt (AWAKEN). The performed simulations enable predictions of the power capture at the farm and turbine levels while providing insights into the effects on power capture associated with wake interactions that operating upstream turbines induce, as well as the variability caused by atmospheric stability. The machine learning models show improved accuracy compared to the pseudo‐2D RANS model in the predictions of turbine power capture and farm power capture with roughly half the normalized error. The machine learning models also entail lower computational costs upon training. Further, the machine learning models provide predictions of the wind turbulence intensity at the turbine level for different wind and atmospheric conditions with very good accuracy, which is difficult to achieve through RANS modeling. Additionally, farm‐to‐farm interactions are noted, with adverse impacts on power predictions from both models.

17 WIND ENERGY↗