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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 379 records · Page 21

A LEAN SYSTEMS APPROACH TO IMPROVING MAINTENANCE OUTPUT AND CONFIGURATION MANAGEMENT

The purpose of this capstone paper is to apply a lean systems approach to the current maintenance planning program in the Assembly/Disassembly Organization. This capstone will take a two-pronged approach to address both output rate in maintenance planning and accurate configuration management resulting from maintenance work orders. In short, the current system suffers from waste in the planning process due lack of procedures to address varying maintenance packages, including maintenance packages which include changes to configuration managed systems. The capstone will detail a lean systems approach to proper characterization of maintenance jobs and integration of change management into the maintenance process in order to retain proper control of the systems used to produce in this nuclear facility.

99 GENERAL AND MISCELLANEOUS↗

Data Based Shock Test Specification

It is vital that avionic packages used for testing and certifying the reliability and safety of U.S. nuclear weapons with platform aircraft survive exposure to shock environments during transportation and delivery. The objective of this research was to characterize the response to these transportation shock environments delivering accurate shock test specifications in order to set laboratory programming material and device certification rigor. Responses to shock events were analyzed in the frequency domain via the Shock Response Spectrum (SRS). Shocks were then grouped based on respective behavior of maximum response accelerations which were pseudorandomly resampled and compared to test data to form test specifications based on the MinerPalmgren hypothesis. In addition to discovering significant over testing in current shock specifications, a new systematic, data-driven approach to designing shock specifications was formulated.

42 ENGINEERING↗

Q-Fibre Quarterly Performance Progress Report

The project titled Quantitative Strain Monitoring for Well and Seal Integrity through Wellbore Fiber Optic Cable s, or Q-Fibre in short, is a multi-national collaborative project under the Clean Energy Transitional Partnership (CETP) program. The lead organization of the project is the Norwegian Geotechnical Institute (NGI), and the LLNL team joins as a beneficiary member. The LLNL team receives the funding from the U.S. Department of Energy with the amount of $\$$1 million across three years, and the budget is primarily allocated to Work Package 3 (WP3) of the project, which focuses on Numerical Modeling of Fiber Optic Cable Data . Figure 1 presents all work packages involved in the project and corresponding lead organization for each work package. The LLNL team leads WP3.

42 ENGINEERING↗

Achieving 50% Energy Savings in Chicago Homes: A Case Study for Advancing Equity and Climate Goals

Since 2019, the National Renewable Energy Laboratory (NREL) and Elevate have collaborated to identify pathways to deep energy retrofits in Chicago's housing stock, document equity implications and co-benefits of this transition, and validate the findings by implementing retrofits in real Chicago homes. This document summarizes our analysis process to model advanced retrofit packages that lead to greater than 50% energy savings in Chicago homes. Based on these findings, we have also developed a roadmap with the City to guide implementation, and are deploying the recommended retrofit packages in real Chicago homes to realize these energy savings. This work was developed in collaboration with two key stakeholders - the City of Chicago and Commonwealth Edison (ComEd) - and funded by the U.S. Department of Energy (DOE). NREL's Residential Buildings team maintains the best-in-class ResStock™ energy model of the U.S. residential building stock. For this work, we calibrated ResStock to Chicago's unique local housing stock to accurately simulate energy use in Chicago homes both for current conditions and with various retrofit scenarios. We simulated a wide range of potential building retrofits covering all aspects of residential energy use and then grouped these into packages based on energy and utility bill savings. ResStock can model diverse building types and housing characteristics, so we're able to observe the range of outcomes that might occur when these upgrades are deployed across the entire housing stock. We can then estimate potential energy savings from an advanced retrofit program on Chicago's housing stock by comparing the modeled energy use before versus after a retrofit. This novel version of ResStock, calibrated to Chicago with data from Elevate, can help City officials, ComEd, and other partners plan for community-scale decarbonization via residential retrofits. Specifically, this work contributes the following project goals: Develop a building retrofit prioritization strategy for Chicago single-family and 2- to 4-unit buildings; Identify neighborhoods and home types that have the highest potential for savings from electrification; and Assess the impact of advanced building retrofits on energy use, utility bills, and CO2 emissions at the city and building level. Although this study is specific to Chicago, its methods and learnings are applicable across the United States. These findings are especially notable for heat pumps and electrification retrofits in cold climates.

building energy modeling↗

EXCHANGE Campaign 1: A Community-Driven Baseline Characterization of Soils, Sediments, and Water Across Coastal Gradients

The EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) program is a consortium of scientists working together to improve our understanding of how the two-way exchange of water between estuaries or large lake lacustuaries and the terrestrial landscape influence the state and function of ecosystems across the coastal interface. EXCHANGE Campaign 1 (EC1) focuses on the spatial variation in biogeochemical structure and function at the coastal terrestrial-aquatic interface (TAI). In the Fall of 2021, the EXCHANGE Consortium gathered samples from 52 TAIs. Samples collected from EC1 were analyzed for bulk geochemical parameters, bulk physicochemical parameters, organic matter characteristics, and redox-sensitive elements.Please download ec1_README.pdf for a complete list of available data in each .zip folder, package version history, and detailed information about the project. This README will serve as the central place for EC1 Data Package updates. Experimental setup and v1 methods are documented in Myers-Pigg and Pennington et al., 2023 (https://doi.org/10.1038/s41597-023-02548-7).EC1 Data Package Structure:ec1_README.pdfec1_methods.pdfec1_metadata_v3.zip...ec1_dd.csv...ec1_flmd.csv...ec1_sample_catalog.csv...ec1_metadata_kitlevel.csv...ec1_metadata_collectionlevel.csv...ec1_data_collectionlevel.csv...ec1_igsn_metadata.csvec1_soil_v3.zipec1_sediment_v3.zipec1_water_v3.zipec1_processingscripts_v3.zipThis data package is on v3 and was originally published May 2023 (v1). Subsequent updates will be published here with new version numbers. Please see the Change History section in ec1_README.pdf for detailed changes.---Acknowledging EXCHANGE: General Support and Data Product UseWe ask that users of EXCHANGE data add the following acknowledgement when publishing data in scholarly articles and data repositories:"This research is based on work supported by COMPASS-FME, a multi-institutional project supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Environmental System Science Program."

54 ENVIRONMENTAL SCIENCES↗

Refinery Integration Analysis: Pathways, Challenges, and Opportunities

Integrating biomass-derived intermediates into traditional petroleum refineries presents unique challenges and opportunities, requiring innovative analysis approaches that account for biofuel producers and refiners. Consequently, teams within the National Renewable Energy Laboratory (NREL) have developed a comprehensive refinery integration analysis framework that combines experimental data, detailed techno-economic analyses of bio-conversion pathways, and economic projections within refinery linear programming (LP) optimization models. These models enable the identification of promising bio-integration strategies tailored to specific refinery configurations, economic conditions, and production goals. They also capture upstream and downstream impacts, highlighting critical bottlenecks and research opportunities for increasing the share of biogenic feedstocks in traditional refining operations. Refinery models are also packaged into a broader bio-economy optimization framework which enables biofuel supply chain optimization with standalone biofuel production and refinery co-processing/repurposing options. This presentation discusses promising refinery bio-integration strategies along with key challenges and opportunities identified using NREL's refinery and bio-economy optimization frameworks.

09 BIOMASS FUELS↗

Preliminary Analysis of Advanced Reactor Spent Nuclear Fuel Storage, Transportation, and Disposal

Due to increased interest in advanced reactor deployment and their associated potential new fuel cycles, the U.S. Department of Energy (DOE) Spent Fuel and Waste Science and Technology (SFWST) program has begun to evaluate the possible implications of long term management and final disposition of the spent nuclear fuel (SNF) generated. Safely managing and dispositioning this SNF, along with any other associated radioactive waste, is the primary focus of this initial preliminary assessment. This paper summarizes efforts to evaluate the characteristics and packaging options for three types of advanced reactor SNF forms: (1) tristructural isotropic (TRISO), (2) metallic, and (3) irradiated fuel salt presented in the report titled “Storage, Transportation, and Disposal of Advanced Reactor Spent Nuclear Fuel and High-Level Waste”. TRISO and metallic SNF and their associated waste streams were emphasized because of the near-term anticipated demonstrations of X-energy’s Xe-100 and TerraPower and GE Hitachi’s Natrium advanced reactors. Preliminary information on spent fuel salts discharged from molten-salt reactors (MSRs) was also examined to provide a baseline for future efforts. All calculations and assumptions were based on publicly available information. This paper identifies several different reactors that produce either TRISO or metallic SNF as well as a few of the reactor and fuel characteristics used for the assessments. Based on these characteristics, calculations were performed to determine the applicability of packaging SNF into existing canister designs. The evaluations included geometric (e.g., dimension, volume) and mass/weight considerations, known operational approaches and loading procedures, physical and chemical considerations/conditions for storage environments, and as-loaded radiation, thermal, and criticality analyses to identify constraints on storage, transportation, and disposal. Gaps in publicly available data pertaining to reactor operation and/or fuel composition provide increased uncertainty in some evaluations. Additionally, uncertainty in packaging and SNF management operations provide additional uncertainty. However, preliminary conclusions can still be assessed through this work and are presented in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 1: assessing E3SM aerosol predictions using aircraft, ship, and surface measurements

Abstract. An Earth system model (ESM) aerosol–cloud diagnostics package is developed to facilitate the routine evaluation of aerosols, clouds, and aerosol–cloud interactions simulated by the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). The first version focuses on comparing simulated aerosol properties with aircraft, ship, and surface measurements, which are mostly measured in situ. The diagnostics currently cover six field campaigns in four geographical regions: eastern North Atlantic (ENA), central US (CUS), northeastern Pacific (NEP), and Southern Ocean (SO). These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the Atmospheric Radiation Measurement (ARM) program and other agencies. Various types of diagnostics and metrics are performed for aerosol number, size distribution, chemical composition, cloud condensation nuclei (CCN) concentration, and various meteorological quantities to assess how well E3SM represents observed aerosol properties across spatial scales. Overall, E3SM qualitatively reproduces the observed aerosol number concentration, size distribution, and chemical composition reasonably well, but it overestimates Aitken-mode aerosols and underestimates accumulation-mode aerosols over the CUS and ENA regions, suggesting that processes related to particle growth or coagulation might be too weak in the model. The current version of E3SM struggles to reproduce the new particle formation events frequently observed over both the CUS and ENA regions, indicating missing processes in current parameterizations. The diagnostics package is coded and organized in a way that can be extended to other field campaign datasets and adapted to higher-resolution model simulations.

54 ENVIRONMENTAL SCIENCES↗

Summary of BISON Milestones: NEAMS FY2020 Report

This summary report contains an overview of work performed under the work package entitled "FY2020 NEAMS Advanced Fuels Performance'', which is focused on the development and support of the fuel performance code BISON. The second chapter lists FY20 milestones titles, completion schedule, and milestone level. Subsequent chapters summarize and demonstrate completion of the milestones. The last chapter outlines FY21 proposed future work. In FY20, the NEAMS program emphasized development of BISON for its application to advanced reactors. While there are a variety of advanced fuel concepts, based on interaction with industry and the Nuclear Regulatory Commission, the fuel types we chose to develop were metallic fast reactor, UN/UC and particle fuels. The last chapter of this report documents proposed work for FY21. We plan to continue work on metallic and particle fuel in terms of developing/calibrating models and to begin rigorous validation/assessment for both fuel types. Due to the merger of the NEAMS and CASL programs, FY21 will see a return to light water reactor model development and simulation; this time focused on advanced technology fuels. Additionally, we seek to improve BISON, fundamentally. As such, we plan improvements to BISON and MOOSE in terms of algorithmic robustness, performance, ease-of-use, and quality assurance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Research and Development Studies for Reactor Neutrino Experiments in Turkey (RNET)

The program of the Reactor Neutrino Experiments of Turkey includes a small portable Water-based liquid scintillator detector to detect neutrinos from the Akkuyu nuclear power plant, planned to begin operating in 2023. The small near-field detector will weigh about 2-3 tons and will be placed less than 100 meters from the reactor cores. The Reactor Neutrino Experiments of Turkey program also includes a medium-size 30-ton Water-based liquid scintillator detector, which will be placed 1-2 km away from the reactor cores and will be used as a far detector. Both detectors and their responses to neutrino interactions were simulated using a GEANT4-based RAT-PAC simulation package. Here, we will share the technical and physical details of both detectors, and discuss the ongoing R&D effort for neutrino studies in Turkey.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Investigation of INL Site Implementation of ARG-US

The Packaging Certification and Life Cycle Management department at Argonne National Laboratory (ANL) developed a suite of monitoring systems collectively referred to here as ARG-US. ARG-US is used to provide necessary data for nuclear facility and system operation and maintenance. ARG-US has been previously demonstrated in hot cells, radioactive material (RAM) storage areas, and RAM shipment trucks. It has also been installed directly on RAM storage and shipment containers. ARG-US offers some unique advantages over other commercially available systems by using wireless data connections, battery power supplies, and customizable monitoring methods. Idaho National Laboratory (INL) has been tasked with investigating applications for ARG-US at INL site facilities, which are operated by several different contractors. The initial investigation scope centered on CPP-603 Wet & Dry Fuel Storage Facility in relation to the upcoming DOE Spent (SNF) Packaging Demonstration. The investigation has been led by the Used Fuel Management Department in the Nuclear Science and Technology Directorate. This investigation is expected to recommend processes or facilities at the INL site at which to implement ARG-US systems. INL has engaged local site technical and oversite representatives, security, nuclear safeguards, and program management to identify good candidates for ARG-US test implementations. INL has identified high-level goals for any INL site implementation of ARG-US: provide unique testing environments, prompt development of new monitoring methods/techniques for the ARG-US suite, and acquire useful monitoring for the user facility. To these ends, INL suggests 3 program areas for further investigation: CPP-603 Fuel Handling Cave (FHC), legacy mixed waste storage systems at Idaho Nuclear Technology & Engineering Center (INTEC) known as the “tank farm”, and periodic and emergency environmental monitoring. This progress report relates activities undertaken in this investigation, describes the preliminary areas of interest for limited scope ARG-US testing or implementation, and relays expected actions needed to complete the task scope. This report offers an opportunity to the program sponsor, technical leads at ANL, and INL site representatives to give feedback on the initial assessment and make recommendations on the forthcoming activities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Diverging climate response of corn yield and carbon use efficiency across the U.S.

Abstract In this paper, we developed an open-source package to analyze the overall trend and responses of both carbon use efficiency (CUE) and corn yield to climate factors for the contiguous United States. Our algorithm enables automatic retrieval of remote sensing data through the Google Earth Engine (GEE) and U.S. Department of Agriculture (USDA) agricultural production data at the county level through application programming interface (API). Firstly, we integrated satellite products of net primary productivity and gross primary productivity based on the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, and climatic variables from the European Centre for Medium-Range Weather Forecasts. Secondly, we calculated CUE and commonly used climate metrics. Thirdly, we investigated the spatial heterogeneity of these variables. We applied a random forest algorithm to identify the key climate drivers of CUE and crop yield, and estimated the responses of CUE and yield to climate variability using the spatial moving window regression across the U.S. Our results show that growing degree days (GDD) has the highest predictive power for both CUE and yield, while extreme degree days (EDD) is the least important explanatory variable. Moreover, we observed that in most areas of the U.S., yield increases or stays the same with higher GDD and precipitation. However, CUE decreases with higher GDD in the north and shows more mixed and fragmented interactions in the south. Notably, there are some exceptions where yield is negatively correlated with precipitation in the Missouri and Mississippi River Valleys. As global warming continues, we anticipate a decrease in CUE throughout the vast northern part of the country, despite the possibility of yield remaining stable or increasing.

54 ENVIRONMENTAL SCIENCES↗

2017 Puerto Rico G-LiHT Metadata

This data package contains metadata for data acquired for sample transects across Puerto Rico using NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager in March 2017. Flights specifically targeted sites with coincident field data collection for NGEE-Tropics, existing forest inventory plots from the USDA-Forest Service Forest Inventory & Analysis (FIA) program and university collaborators, and other research installations (e.g., NEON).

54 ENVIRONMENTAL SCIENCES↗

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Computational design of non-porous pH-responsive antibody nanoparticles

Abstract Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.

Biochemistry & Molecular Biology↗

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

Anions↗

The Dark Energy Survey Supernova Program: Corrections on Photometry Due to Wavelength-dependent Atmospheric Effects

Abstract Wavelength-dependent atmospheric effects impact photometric supernova flux measurements for ground-based observations. We present corrections on supernova flux measurements from the Dark Energy Survey Supernova Program’s 5YR sample (DES-SN5YR) for differential chromatic refraction (DCR) and wavelength-dependent seeing, and we show their impact on the cosmological parameters w and Ω m . We use g − i colors of Type Ia supernovae to quantify astrometric offsets caused by DCR and simulate point-spread functions (PSFs) using the GalSIM package to predict the shapes of the PSFs with DCR and wavelength-dependent seeing. We calculate the magnitude corrections and apply them to the magnitudes computed by the DES-SN5YR photometric pipeline. We find that for the DES-SN5YR analysis, not accounting for the astrometric offsets and changes in the PSF shape cause an average bias of +0.2 mmag and −0.3 mmag, respectively, with standard deviations of 0.7 mmag and 2.7 mmag across all DES observing bands ( griz ) throughout all redshifts. When the DCR and seeing effects are not accounted for, we find that w and Ω m are lower by less than 0.004 ± 0.02 and 0.001 ± 0.01, respectively, with 0.02 and 0.01 being the 1 σ statistical uncertainties. Although we find that these biases do not limit the constraints of the DES-SN5YR sample, future surveys with much higher statistics, lower systematics, and especially those that observe in the u band will require these corrections as wavelength-dependent atmospheric effects are larger at shorter wavelengths. We also discuss limitations of our method and how they can be better accounted for in future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Report on FY 2021 Fabrication and Testing of Qualified Alloy 709 Welds at ORNL

Alloy 709 is a candidate construction material for the Sodium Fast Reactor (SFR). As part of the Alloy 709 ASME Code Case development team under the Advanced Reactor Technologies (ART) Program, this work covers the development of the technical basis for weld fabrication and weld qualification of Alloy 709. This report summarizes the research conducted in FY 2021 and relevant results from previous reporting periods, aimed at welding commercial heat of Alloy 709 plates of relatively high phosphorous (P) level in support of ASME code case data package. Welding, code qualification tests, and associated microstructure characterization were carried out in determining the effect of P levels of weld wire on the weldability of the high P commercial heat of Alloy 709. The Alloy 709 weld creep strength was evaluated though preliminary creep testing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗