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At least 811 records · Page 45
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DOE OSTI2020

Lawrence Livermore National Laboratory Annual Environmental Report 2019

The purposes of the Lawrence Livermore National Laboratory (LLNL) Environmental Report 2019 are to record LLNL's compliance with environmental standards and requirements, describe LLNL’s environmental protection and remediation programs, and present the results of environmental monitoring at the two LLNL sites—the Livermore Site and Site 300. The report is prepared for the U.S. Department of Energy (DOE) by LLNL’s Environmental Functional Area. Submittal of the report satisfies requirements under DOE Order 231.1B, “Environment, Safety and Health Reporting,” and DOE Order 458.1, “Radiation Protection of the Public and Environment.” The report begins with an executive summary, which provides the purpose of the report and an overview of LLNL’s compliance and monitoring results. The first three chapters provide background information: Chapter 1 is an overview of the location, meteorology, and hydrogeology of the two LLNL sites; Chapter 2 is a summary of LLNL’s compliance with environmental regulations; and Chapter 3 is a description of LLNL’s environmental programs with an emphasis on the Environmental Management System including pollution prevention. The majority of the report covers LLNL’s environmental monitoring programs and monitoring data for 2019: effluent and ambient air monitoring and dose assessment (Chapter 4); waters, including wastewater, storm water runoff, surface water, rain, and groundwater (Chapter 5); and terrestrial, including soil, sediment, vegetation, foodstuff, ambient radiation, and special status wildlife and plants (Chapter 6). The remaining two chapters discuss LLNL’s groundwater remediation program (Chapter 7), and quality assurance for the environmental monitoring programs (Chapter 8). Complete monitoring data, which are summarized in the body of the report, are provided in Appendix A.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

West Valley Demonstration Project Annual Site Environmental Report (CY2019)

The report, prepared for the U.S. Department of Energy West Valley Demonstration Project office (DOE-WVDP), summarizes the environmental protection program at the WVDP for calendar year (CY) 2019. Monitoring and surveillance of the facilities used by the DOE are conducted to verify protection of public health and safety and the environment. The report is a key component of DOE’s effort to keep the public informed of environmental conditions at the WVDP. The quality assurance protocols applied to the environmental monitoring program ensure the validity and accuracy of the monitoring data. In addition to demonstrating compliance with environmental laws, regulations, and directives, evaluation of data collected in 2019 continued to indicate that WVDP activities pose no threat to public health or safety, or to the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Fleet Compliance Annual Report (MY 2018, FY2019)

The U.S. Department of Energy (DOE) regulates covered state government and alternative fuel provider fleets, pursuant to the Energy Policy Act of 1992 (EPAct), as amended. For model year (MY) 2018, the compliance rate with this program for the more than 311 reporting fleets was 100%. Fleets used either Standard Compliance or Alternative Compliance reporting methods.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Annual Site Environmental Report (CY2019)

The primary purpose of this report is to summarize the performance of Ames Laboratory’s environmental programs, present highlights of significant environmental activities, and confirm compliance with environmental regulations and requirements for calendar year 2019. This report is a working requirement of Department of Energy Order 231.1B, Environment, Safety and Health Reporting. It includes descriptions of the Laboratory’s site, mission, the status of its compliance with applicable environmental regulations, its planning and activities to maintain compliance, and a comprehensive review of its environmental protection, surveillance and monitoring activities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

2021 Stewardship Science Academic Programs Annual

I am a staff scientist at Sandia National Laboratories (SNL). I work on multiple fundamental-science projects and lead modeling/data-analysis for the stellar opacity experiments. I also work with theorists to refine plasma material-property calculations to make NNSA simulations more predictable. These are challenging and important problems for national security. In fact, our experiments raised questions about “opacity”, the property of matter that controls energy transport inside stars. This work was published by Nature due to its serious implication over broad applications, and our team received NNSA Defense Program Award of Excellence, both in 2015. Work at SNL is collegial and full of learning through interactions with the world’s finest experimentalists and theorists. When I started my Ph.D. program, working at a national lab was a dream position. Today, I collaborate with top scientists to solve mission-critical problems. The Stewardship Science Academic Programs (SSAP) and National Laser Users’ Facility (NLUF) played a vital role in the efficient learning and seamless transition to SNL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials (Second Annual Progress Report)

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer, and through reconstruction of data obtained from experimental measurements. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and Inconel 718 plate produced with laser powder bed fusion (LPBF) method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBH’s have the same sizes as the imprinted defects in the LPBF specimens, but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects, and allow for estimation of their sizes and locations. Detection sensitivity of TT is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, we investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Mixed Waste Landfill Annual Long-Term Monitoring & Maintenance Report (Apr 2015-Mar 2016)

Sandia National Laboratories (SNL) is a multi-purpose engineering and science laboratory owned by the U.S. Department of Energy (DOE)/National Nuclear Security Administration. SNL is managed and operated by Sandia Corporation (Sandia), a wholly-owned subsidiary of Lockheed Martin Corporation. Sandia National Laboratories, New Mexico (SNL/NM) is located within the boundaries of Kirtland Air Force Base (KAFB), southeast of the City of Albuquerque in Bernalillo County, New Mexico. The Mixed Waste Landfill (MWL) is located 4 miles south of SNL/NM central facilities and 5 miles southeast of Albuquerque International Sunport, in the north-central portion of Technical Area (TA)-III. The MWL disposal area comprises 2.6 acres. During operations, the MWL accepted containerized and other low-level radioactive waste and minor amounts of mixed waste from SNL/NM research facilities and off-site DOE and U.S. Department of Defense generators from March 1959 to December 1988. More specific information regarding the MWL inventory and past disposal practices is presented in the MWL Phase 2 RCRA Facility Investigation Report (Peace et al. September 2002) and the extensive MWL Administrative Record.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Data Transfer Tool (HPC Annual Report V.3.1)

Sandia has been developing and supporting data transfer tools for over 20 years and has the expertise to take DOE into the Extreme Scale era. In looking at Exascale and beyond (Extreme Scale Computing), data sets can be thousands of 500TBs in size, a single file can be in the 100TB range, and billions of files are expected. Huge bursts of data need to be transferred, even today. While data archiving is often not thought about, it is an integral part of the full data management path when data is generated on HPC systems. In order to move generated data to its final resting place (data archive) or to transfer between file systems, a capable data transfer tool is required.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Carnac for Emulytics (HPC Annual Report V.1.0)

Carnac, located at Sandia's California site, is an institutional cluster for Emulytics that provides security researchers with resources to model enterprise computer networks and evaluate how resilient they are from attacks. While multiple Emulytics cluster computers have been built at Sandia, Carnac is the first system that was developed as an institutional resource that can be shared among different groups with disparate requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Microcalorimeters for IAEA NML (Annual Report FY2020)

Based on input from Andrey Bosko (IAEA NML) during a visit to LLNL October 17-18, 2019, the project focused on adapting magnetic microcalorimeters (MMCs) for high-resolution decay energy (Q) spectroscopy of actinides. This included fabricating an MMC detector suitable for MeV signals, testing different approaches on how to embed an alpha source inside an absorber, and demonstrating Q-spectroscopy with MMCs.

42 ENGINEERING↗
DOE OSTI2021

Arroyo Seco Improvement Program Annual Report for 2020

The Arroyo Seco Improvement Program is being carried out at Sandia National Laboratories, California in order to address erosion and other streambed instability issues in the Arroyo Seco as it crosses the Sandia National Laboratories, California. The work involves both repair of existing eroded areas, and habitat enhancement. This work is being carried out under the requirements of Army Corps of Engineers permit 2006-400195S and California Regional Water Quality Control Board, San Francisco Bay Region Water Quality Certification Site No. 02-01-C0987.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Heavy-Duty Low-Temperature and Diesel Combustion & Heavy-Duty Combustion Modeling (FY 2018 Annual Progress Report)

Regulatory drivers and market demands for lower pollutant emissions, lower carbon dioxide emissions, and lower fuel consumption motivate the development of clean and fuel-efficient engine operating strategies. Most current production engines use a combination of both in-cylinder and exhaust emission control strategies to achieve these goals. The emissions and efficiency performance of in-cylinder strategies depend strongly on flow and mixing processes associated with fuel injection. Both heavy- and light-duty engine/vehicle manufacturers use multiple-injection strategies to reduce noise, emissions, and fuel consumption. For both conventional and low-temperature diesel combustion, the state of knowledge and modeling tools for multiple injections are far less advanced than for single-injection strategies. Engine efficiency is limited to some degree by tradeoffs that must be accepted to meet particulate matter (including soot) emissions limits. Recent work on this project has filled some knowledge gaps on soot oxidation with multiple injections, and the current work for Fiscal Year (FY) 2018 addresses knowledge gaps on soot formation for multiple injections. While total in-cylinder soot is readily measured, discerning formation from oxidation is difficult. The FY 2018 experiments are designed to create in-cylinder conditions at the threshold of soot formation, where processes that affect soot formation can be more readily discerned. Soot formation pathways under such conditions are fraught with uncertainties, and soot models significantly overpredict polyaromatic hydrocarbon (PAH) and soot, so experimental data at these conditions will provide much needed data for improvements to PAH and soot models.

02 PETROLEUM↗
DOE OSTI2020

2020 Vehicle Technology Office Annual Progress Report from Jianchao Ye

Traditional batteries are composed of two-dimensional films that are stacked and/or rolled. Thin film batteries display high power density while their thick film counterparts show good energy density, but it has proven difficult to concurrently achieve both within these planar form factors. In addition, conventional Li-ion batteries based on liquid organic electrolytes or gel polymer electrolytes have raised severe safety concerns due to the intrinsic flammable properties of the organic electrolytes.

25 ENERGY STORAGE↗