Analysis of hard X-ray focusing by 2D diamond CRL
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Abstract not provided.
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We have designed and demonstrated a quantum cascade laser (QCL) based standoff system that utilizes an uncooled mercury cadmium telluride (MCT) detector with lock-in signal processing for chemical identification at a distance of 12.5 meters in indoor ambient light conditions. In the system, a tunable quad-QCL operating (1 MHz) in quasi-continuous wave mode between 8.45 and 10.03 μm (~1182 to 1000 cm –1 ) serves as the active mid-infrared source for remotely interrogating mineral, powder, and thin film oil samples including powder mixtures (6, 12.5, 25, and 50%) of crystalline quartz (SiO 2 ) in KBr. Light as reflected from a given sample is collected using a 10-inch (25.4 cm) Dall Kirkham telescope and coupled with ZnSe optics to an uncooled MCT detector. Furthermore, the mixture dependence of the highly transparent KBr and strongly absorbing quartz was found to fit a modified version of the Schatz reflectance model for compacted powder mixtures. All reflectance spectra reported are relative to an Au-coated diffuse reflector. A NIST traceable polystyrene standard reflector was also used to determine the QCL wavelength tuning range and calibration.
Under a DOE Nuclear Criticality Safety Program (NCSP) task involving Analytical Methods, three Laboratories collaborated in a comparison of results obtained from Sensitivity/Uncertainty (S/U) packages relevant to validation of transport codes. The task involves Institut de Radioprotection et de Sûreté Nucléaire (IRSN), Los Alamos National Laboratory (LANL), and Oak Ridge National Laboratory (ORNL) comparing results of MORET 5/MACSENS V3.0, MCNP6.2/Whisper-1.1, and SCALE 6.2.3/TSUNAMI/USLSTATS respectively. All Monte Carlo transport code results utilize ENDF/B-VII.1. Four cases from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook) were selected as application models: HEU-MET-FAST-013-001, HEU-SOL-THERM 001-008, PU-MET-FAST-022-001, and PU-SOL-THERM 001-001. Ultimately, comparison is made between Upper Subcritical Limits (USLs) obtained using each code package for each application case. Since differences exist in whether packages take into account margin of subcriticality (MOS), the USL may be computed using bias and bias uncertainty, also known as the calculational margin (CM) in ANSI/ANS 8.24. Application of portions of MOS to the USL for nuclear data uncertainty of and potential code margin is referred to as USL herein. In either case, additional MOS is considered for actual application cases.
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Three (3) items of errata are submitted for our recently published paper [ Opt. Express 28 , 36505 ( 2020 ) 10.1364/OE.405566 ]. One is a clarifying extension to the Fig. 3 caption. Two are typographical corrections. The scientific results and conclusions are unaffected.
Utility owners and operators of commercial nuclear power plants in the United States (U.S.) are and will be modernizing their nuclear power plants by performing a digital transformation involving design of an integrated set of systems that together enable a technology centric operating plant. The Plant Modernization Pathway of the U.S. Department of Energy Light Water Reactor Sustainability Program has a strategic action plan that lays the groundwork for a digital transformation of the nuclear industry. The model for this transformation is an advanced concept of operations, with an end point vision, “To achieve the maximum aggregate benefit enabled by this digital transformation.” To achieve this, the digital infrastructure for a nuclear plant must be designed as an integrated set of systems that together enable a technology centric operating model. The digital transformation process obviously needs to involve technology considerations and systems engineering, but it also needs to include human and organizational expertise. Thus, human and organizational factors, including sociotechnical systems methods and techniques (e.g., Cognitive Systems Engineering, Systems Theoretic Accident Modeling and Processes, human systems integration, and Macroergonomics) need to be considered for digital transformation projects in order to effectively integrate human and organizational expertise efforts into the new work system that results from nuclear power plant digital modernization. That is, the work system is the basic unit of sociotechnical systems analysis and contains three components: personnel, technical, and organization and management. These components should be jointly optimized with respect to the interdependence of systems performance criteria of effectiveness, efficiency and safety. Joint optimization can be achieved through the application of three human and organization functions: knowledge representation, knowledge elicitation, and cross-functional integration. This report provides a strategic framework for effective integration of human and organizational expertise within nuclear power plant digital modernization efforts.
The project's long-term goal is to assert and maintain an international scientific leadership position in the development of Earth system models that address the grand challenge of actionable predictions of Earth system variability and change, with an emphasis on the most critical scientific questions facing the nation and DOE. The grand challenge will be addressed by overcoming three major limitations: Pushing the high-resolution frontier of Earth system modeling through a combination of strategic model development and computational advances targeting exascale computers and beyond. Bridging the gap in scales and processes by developing a new class of models that couple the natural, managed, and man-made systems across scales to address energy sector vulnerability to variability and change. The project will achieve its goal through four intersecting project elements: A series of prediction and simulation experiments addressing scientific questions and mission needs; A well-documented and tested, continuously advancing, evolving, and improving system of model codes that comprise the E3SM Earth system model; The ability to use effectively leading (and “bleeding”) edge computational facilities soon after their deployment at DOE national laboratories; and An infrastructure to support code development, hypothesis testing, simulation execution, and analysis of results. To achieve the Grand Challenge of actionable Earth system predictions to address the most critical scientific questions facing our nation and DOE, the E3SM project defined its strategy in a fifteen-year roadmap with four intersecting project elements: A series of prediction and simulation experiments addressing scientific questions and mission needs; A well-documented and tested, continuously advancing, evolving, and improving system of model codes that comprise the E3SM Earth system model ; The ability to use effectively leading (and “bleeding”) edge computational facilities soon after their deployment at DOE national laboratories; and An infrastructure to support code development, hypothesis testing, simulation execution, and analysis of results. Figure 1 depicts the E3SM Project Roadmap, showing the relationships among the first three major project elements: the simulations, the modeling system to perform those simulations, and the machines on which they will be executed. Unlike the other three elements that have distinct but overlapping phases, the fourth element, the infrastructure, will evolve continuously based on the requirements imposed by project needs.
The configuration management process at Y-12 is a crucial process to ensure safe operations and compliance with Department of Energy (DOE) regulations and requirements. This process is evaluated utilizing systems-thinking methodology in order to understand the current operational flow, with the ultimate goal of building an easily understandable, representative model. This model offers insights on key areas of waste and provides a potential solution by modernizing rate limiting steps: a software implementation to update the traditional document management system and make it paperless. Stakeholders of the software implementation are identified in order to define characteristic requirements of an effective product and the anticipated benefit is evaluated. Ultimately, this project is an effort to increase the quality of life for all stakeholders, while improving the capacity, throughput, and effectiveness of a necessary process at Y-12.
The presentation includes various images to illustrate the analysis. Helios G4 Plasma FIB: Xe ion columns mills material 30 times faster than Ga; Options include: Energy Dispersive Spectroscopy (EDS), Wavelength Dispersive spectroscopy (WDS) Electron backscattered Diffraction (EBSD), Time of Flight Sims (ToF SIMS), Inert gas/vacuum sample transfer system; Excels at micromachining and collecting 3D datasets using various detection systems.
This report presents early results from a deployment of fuel cell electric buses (FCEBs) operated by SunLine Transit Agency in the Coachella Valley area of California. The five FCEBs, produced by New Flyer, feature an electric drive propulsion system powered by a Ballard fuel cell system. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The goal of this evaluation is to compare the FCEB performance to that of conventional technology and to track progress over time toward meeting the technical targets set by DOE and the Department of Transportation (DOT). The FCEBs were delivered beginning in mid-2019. The data period covers January 2020 through July 2020. NREL collects data on five 2019 model year compressed natural gas (CNG) buses as a baseline comparison at SunLine. These new CNG buses were phased into service beginning in April 2020.
This report documents work performed supporting US Department of Energy (DOE) Nuclear Energy Spent Fuel and Waste Disposition, Spent Fuel and Waste Science and Technology, under work breakdown structure element 1.08.01.03.04, “Inventory and Waste Form Characteristics and Performance.” In particular, this report fulfills the M3 milestone, M3SF-21OR010309072 "Draft Experimental Plan for Commercial SNF Degradation in Repository Environments” as described in work package SF-21OR01030907 "SNF Degradation Testing-ORNL".This experimental plan is a collaboration between ORNL, SNL, ANL, and PNNL. It is intended to support source term model development and spent fuel degradation testing in a range of generic repository conditions. Potential testing and experiments to support validation of the Fuel Matrix Dissolution Model (FMDM) and the overall development/validation of repository source term modeling are discussed.
Abstract not provided.
Abstract not provided.
Further work for this milestone confirmed that using ECP Gitlab CI does not work with PR based work flow used by the Open MPI.