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The purpose of this course is to give you an orientation to DOE O 426.2, Personnel Selection, Training, Qualification, and Certification Requirements for DOE Nuclear Facilities.
This document describes the training and qualification requirements for the Project Engineer (PE) position at the Los Alamos National Laboratory (LANL). Analysis indicates that the Project Engineer position is not required to meet the requirements of DOE Order 426.2, Personnel Selection, Training, Qualification, and Certification Requirements for DOE Nuclear Facilities for “Technical Staff” positions. However, Engineering Services Division (ESD) has decided to hold their Project Engineers to a higher professional standard by developing a qualification program for the PEs.
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.
The Biden Administration's issuance of Executive Orders directly addressing and accelerating Federal fleet electrification places an onus on both fleet and facility managers. This panel will help fleet and facility personnel understand how to select EVSE infrastructure in terms of implementation, energy management, and costs of procurement, installation/deployment, and electricity. The panel will cover technology aspects to include managed EVSE, bi-directional charging, implications on local electrical systems and storage needs in certain cases to buffer power demand. Discussion will include various considerations relevant to ensuring adequate EVSE, balancing infrastructure needs, and upgrades with fleet needs. The panelists will discuss how to provide sufficient infrastructure support, including which stakeholders to involve, procurement impediments, easement locations, and requirements that arise during the design and implementation process.
In the domain of cybersecurity, there are a wide variety of education and training courses offered by a variety of training providers (commercial vendors, governmental, and academic institutions). Unfortunately, a comprehensive cross-provider mapping of the body of course offerings does not currently exist. Furthermore, although individual providers have made efforts, an accepted cross-provider mapping of education and training courses (or categories) to an accepted framework of work-roles by cybersecurity work-role and competency level has not yet been developed. The inability to compare training courses by topic or cybersecurity work-role and the level of difficulty (competency level) affects all organizations in identifying and selecting potential training opportunities for their personnel performing cybersecurity duties. In this work, we report on our application of Machine Learning (ML) Text Classification and Natural Language Processing (NLP) methodologies to begin to create a process to organize an accurate and thorough catalog of course offerings by work-role and competency level. Through the analysis of text-based course attributes (description, learning objectives, prerequisites, etc.) along with the text-based attributes for identified cybersecurity work-roles, our ML efforts examined methods to determine the work-role "best-fit" for each course as well as the competency level through action-verb text comparison.
Integrated Operations for Nuclear: Work Reduction Opportunity Demonstration The DI BCA document also identifies specific, digitally enabled WRO categories for further study. These were selected as most relevant by Reference Plant personnel from a larger list of WRO areas identified across the nuclear industry as captured INL/RPT-21-64134, “Process for Significant Nuclear Work Function Innovation Based on Integrated Operations Concepts.” This ION WRO demonstration report was developed to provide illustrative, specific, and actionable direction for intertwined PTPG changes associated with digital modernization efforts. The coordinated changes in these areas are intended to maximize safe plant operational and economic performance. This includes enabling WROs associated with detailed configuration, implementation, and use of digital systems and how they are supported over their lifecycle. Illustrating this direction through a minimum set of advanced technology examples establishes a model PTPG framework that can be leveraged across the spectrum of nuclear plant digital modernization efforts going forward. This document addresses many related concepts. To promote an integrated understanding of the topics that make up this work, this document contains an extensive set of internal hyperlinks. This set includes hyperlinks to page numbers in the table of contents, section numbers, items in lists, figures, tables, and references to other documents within the report. When hovering the cursor above hyperlinked text in Adobe, the cursor will change from “ ” to “ .” When the “ ” appears, a left mouse click will take the reader to the referenced location in the document. To return to the original location in the document, the reader need only press and hold the “alt” button on the keyboard and then simultaneously press the “<” directional key on the keyboard.
This dataset from Lawrence Livermore National Laboratory (LLNL) consists of four raw X-ray diffraction (XRD) scans and preliminary results of quantitative XRD analysis. The scanned samples were prepared from four subcores, which came from various depths of the FORGE well 16A(78)-32 core. Desired core lengths were selected from available core photos (on GDR), provided by FORGE personnel, and subcored at LLNL. The XRD scans were collected in May 2023 at LLNL as pre-experimental characterization data for these subcores, which will be used in core-flooding experiments at LLNL and in triaxial direct shear experiments at Los Alamos National Laboratory as part of DOE Project 5-2428. XRD scans are in RAW file format (e.g., FORGE-5477-full.raw) and are suitable for viewing and analysis using open-source quantitative XRD software (e.g., Profex; www.profex-xrd.org ) and/or other proprietary instrument software.
LaserNetUS Collaborative Network established in 2018 is a network of high-power laser facilities supported by the Department of Energy (DOE) Office of Fusion Energy Sciences (FES) and operating effectively as a user facility. Its mission is to advance and promote intense laser science and applications by providing scientists and students with broad access to unique facilities and enabling technologies, advancing the frontiers of laser-science research, and fostering collaboration among researchers and networks from around the world. Users who submit proposals through an annual call are selected by an external and independent proposal review panel (PRP) not involving personnel from any of the facilities. Besides the Omega Laser Facility at the University of Rochester’s Laboratory for Laser Energetics (UR/LLE), the network during this project period includes high-intensity laser facilities from six other universities and three national laboratories, namely, the Colorado State University (CSU), the University of Michigan (UM), the University of Nebraska at Lincoln (UNL), The Ohio State University (OSU), Université du Québec, the University of Texas at Austin (UT Austin), Lawrence Berkeley National Laboratory (LBNL), SLAC National Accelerator Laboratory (SLAC) and Lawrence Livermore National Laboratory (LLNL), respectively. The network facilities span a wide range in laser pulse energy, pulse duration, repetition rate, and experimental diagnostic equipment enabling innovative research in a variety of exciting areas. Details of the LaserNetUS facilities, organization and committees, events, and accomplishments can be found at the network website (https://lasernetus.org/). A very important role that the LaserNetUS fulfills is the training of students and young scientists who will be key for the future development of laser-plasma science and high-power laser technology itself. The network provides these students not only with access to the most advanced instrumentation and laser facilities, but also the opportunities to interact and collaborate with students from other institutions and with a large group of experienced scientists. As the largest university-based laser users’ facility in the world, the Omega Laser Facility at the UR/LLE has served the high-energy-density physics (HEDP) and inertial fusion science community for nearly 40 years. The multi-beam multi-kJ OMEGA EP Laser System brings unique capabilities to the LaserNetUS network. The combination of high intensity and high energy in short- and long-pulse operation together with solid or gas-jet targets and externally applied magnetic fields provides users a wide domain of experimental conditions. This award provides a total of eight shot days on OMEGA EP for LaserNetUS users. During the award period of performance (June 2019–November 2021), seven teams have fully utilized the eight shot days for their unique science experiments on OMEGA EP with a total of 83 target shots. These experiments involve 13 graduate students, two undergraduate students and six postdoctoral researchers. Results have been widely disseminated at international conferences including LaserNetUS annual meeting (~20 presentations including three invited), and in peer-reviewed journal publications (three published with several manuscripts in preparation).
LaserNetUS Collaborative Network established in 2018 is a network of high-power laser facilities supported by the Department of Energy (DOE) Office of Fusion Energy Sciences (FES) and operating effectively as a user facility. Its mission is to advance and promote intense laser science and applications by providing scientists and students with broad access to unique facilities and enabling technologies, advancing the frontiers of laser-science research, and fostering collaboration among researchers and networks from around the world. Users who submit proposals through an annual call are selected by an external and independent proposal review panel (PRP) not involving personnel from any of the facilities.
Navistar presents the SuperTruck II (ST II) Final Report to the Unites States Department of Energy (US DOE), which covers the five Budget Periods (BPs) from 10-1-2016 through 6-30-2022. For ST II, Navistar built on the achievements of the SuperTruck I (ST I) Program as a catalyst to continue critical research, design and development, testing, and operations to reach the ambitious goals of the ST II project. This approach allowed Navistar to continue contributing to the essential needs of our nation for safe, efficient, and cost-effective delivery of goods and services, as we reduced negative environmental effects and improved operational productivity. This document contains information specified in DOE F 4600.2, Final Scientific/Technical Report DOE F 241.3, B. SCIENTIFIC/TECHNICAL REPORTS, explaining how we met and exceeded program requirements. Throughout this Final Report, Navistar extracted information from documents prepared during the project that represent our management, design and development, building, and testing efforts to meet and exceed SuperTruck II project goals. Navistar followed Plan requirements to achieve / exceed Project Objectives: a) >100% improvement in vehicle freight efficiency (FE) (on ton-MPG basis) relative to 2009 baseline with stretch goal of 140% improvement [actual: 170%); b) >55% engine brake thermal efficiency (BTE) demonstrated in operational engine at a 65-mph cruise point on a dynamometer – ≥31% increase from 2009 baseline [actual: 55.20% of combined BTE) ; and c) development and implementation of commercially cost effective technologies (in terms of a simple payback). Technology selection / development path focused on developing technologies applicable for production within 3-year approach, while ensuring technology readiness and cost of ownership for end users. The Program was organized into five budget periods: Requirements / Technology Assessment and Initial Hardware Testing; Technology Development and Concept Readiness Demonstration; Technology Finalization and Validation Tractor / Trailer Fabrication, Integration and Commissioning Demonstration; and Fuel Economy (FE) and Brake Thermal Efficiency (BTE) and Program Completion. Leadership was provided by DOE, with tasks performed by laboratories (Argonne National Laboratory, Lawrence Livermore National Laboratory); partners at Bosch, TPI, Dana, and J.B. Hunt; , and support from University of Michigan and Clemson University. Navistar lead this team with Principal Investigator / Contracting Officer; Project Manager (PM); Vehicle, Engine, and Aftertreatment Engineers; Finance Manager, Technical Program Leads, and Legal/IP; and other key personnel. Work also included personnel in risk management; funding / budget / finance. Work involved analysis, development, testing, and down selection of individual/system engine, aftertreatment, and vehicle technologies, with integration of selected technologies into a prototype vehicle for demonstration of fuel-efficiency gain. Work also included component/integrated system level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. As ST II progressed, Navistar performed computer-based modeling / simulations of technologies focused on the primary operational areas: Engine, Aftertreatment, and Vehicle. During the ST II Program, the COVID Virus outbreak unexpectedly challenged by the effects of, which affected staffing, scheduling, design, supplies, availability of materials, production procedures, and testing. The DOE responded by extending the program by three quarters to ensure that project tasks were completed for this vital project. Focus continued on analyzing, developing, testing, and down selecting individual-/system-level engine and vehicle technologies for integration of the final selected technologies into a prototype vehicle that would demonstrate fuel-efficiency gains made possible through these technologies. This included component/integrated system-level development of truck and trailer aerodynamics, base engine efficiency, advanced aftertreatment, combustion efficiency, waste heat recovery, solar power, distributed and intelligent vehicle power, hybrid powertrain, reduced rolling resistance, weight reduction, idle reduction, and driver feedback. Throughout the program, function, reliability, and performance at all levels were ensured through testing. Proof of this approach was demonstrated in multiple, on-road demonstrations: Scenario A (Flatland) Fuel Economy, Scenario B (Hilly) Fuel Economy, and City Cycle Tests. Other benefits derived from ST II included new/improved products, publications, patents, and next-step capabilities related to electric/hydrogen vehicles and autonomous driving.
An earlier report described a procedure for optimal sensor set selection and its implementation on a computational cluster. This new and innovative capability was developed to facilitate a reduction in operations staffing levels to improve plant economics. By automating surveillance and maintenance tasks through early detection of degrading sensors and equipment, staff can be more efficiently deployed. The method uses automated reasoning and domain knowledge in the form of the conservation equations to infer from plant measurements the state of equipment health. Inclusion of domain knowledge addresses the problem that exists with pure data-driven methods that there are no rigorous guidelines for determining what constitutes an adequate sensor set. Formalizing the procedure for sensor set selection as we have done results in a more reliable and explainable diagnosis of plant equipment health. Importantly, from the standpoint of the plant owner, personnel are provided with an early and explicit diagnosis of an equipment problem. That in principle automates the process and eliminates having to send personnel into the plant to find the cause as typically occurs when a data-driven method detects an anomaly. In this report we describe first results obtained using a computational cluster to solve the sensor set selection problem as framed above. The case described addresses the problem of equipment health monitoring in the high-pressure (HP) feedwater system of a pressurized light water reactor as seen through the eyes of our collaborating utility partner. Maintenance of this system can amount to millions of dollars per year if equipment health issues go undiagnosed and lead to loss of function. On examining the potential that is inherent in the installed sensor set for diagnosing equipment health degradation, it was found that greater fault resolution capability can be achieved using a sensor set that is 20 percent fewer in number. The take-away is that compared to the installed sensor set there exists a more strategic assignment of sensors that will furnish better health monitoring capability and with fewer sensors. Where the problem defies solution by manual inspection, as is the case here, one can be found by an algorithm. The solution was obtained in four hours using 30 computational cores. The HP feedwater problem as posed above illustrates the added value of approaching the sensor selection problem as one amenable to algorithmic solution. This problem is of interest to advanced reactor designers and to utilities that are setting up remote monitoring and diagnostic centers.
Given the mismatch between the large volume of data archived for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and limited personnel and computational resources for downscaling, only a small fraction of the CMIP6 archive can be downscaled. In this work, we develop an approach to robustly sample projected hydroclimate states in CMIP6 for downscaling to test whether the selection of a single initial condition (IC) ensemble member from each CMIP6 model is sufficient to span the range of modeled hydroclimate over the conterminous United States (CONUS) and CONUS sub-regions. We calculate the pattern-centered root mean square difference of IC ensemble member anomalies relative to each model’s historical climatology for shared socioeconomic pathway (SSP) projections over 30-year time periods and compare the ratio of inter-model to intra-model variability for this metric. Regardless of SSP, inter-model variability is generally much greater than intra-model variability at the scales of the CONUS as a whole, as well as for most CONUS sub-regions. However, for some variables and scenarios, inter- and intra-model variability are similar at sub-CONUS scales, indicating that selecting a single IC ensemble member per model may be sufficient to sample the range of projected hydroclimate states in the 21st Century across CONUS, but for specific regions and variables, more careful selection of ensemble members may be necessary. Regionally resolved Taylor diagrams identify where more IC ensemble member downscaling efforts should be focused if resources are available to do so. Our results suggest that, with parsimonious sampling, the requisite computational expense of downscaling temperature and precipitation fields over the CONUS for subsequent CMIP activities may increase only marginally despite the great increase in data volumes with each successive CMIP phase.
Heavy duty vehicle platooning under highway operating conditions has been projected to provide significant fuel economy gains based on aerodynamic drag improvements of the platooning vehicles. Realizing these benefits and the economic viability under real-world operating conditions presents several challenges. The objective of this paper (the third as part of a series) is to analytically quantify the payback and profitability of heavy-duty vehicles platooning across the U.S. Interstate highway system. In this paper, a rigorous assessment of several factors that influence the platooning system payback for an end-user as well as the revenue potential for suppliers who may be utilizing an equipment lease model dependent on end-user savings, is presented. In this assessment key interactions explored include market adoption rates, platooning velocities, platoon-able daily mileage, platooning likelihood, variations in baseline powertrain fuel economy (diesel or electric), price of fuel (diesel or electricity), platooning fuel economy benefits, price of the added technology, and the impact of natural platooning due to traffic interactions. Further, the paper explores the economic impact of higher levels of vehicle automation for the trailing vehicles in the platoon, where extending the driver Hours of Service (HoS) may provide additional financial benefits. While the approach makes use of a limited fidelity vehicle analytical model for longitudinal dynamics and operations economics, the narrative provides application decision personnel with a mechanism and well-defined set of impact factors to consider as part of their architectural selection process.
On April 14, 1954, Laboratory employees were formally notified by a “Special Bulletin to All Employees” (Appendix A) that the Atomic Energy Commission had convened a Personnel Security Board, at the request of J. Robert Oppenheimer, to investigate “substantial derogatory information” about their former director. Long on procedural detail and short on specifics, the Bulletin served primarily as an announcement that “A board was accordingly established for the purpose of hearing the case and advising the Commission as to whether or not suspension of clearance of Dr. Oppenheimer should be made permanent.”
Heavy duty (HD) vehicles platooning under highway operating conditions, have been projected to provide significant fuel economy (FE) gains based on aerodynamic drag reduction of the platooning vehicles. Realizing these benefits under real-world operating conditions have several challenges. This paper (the second as part of series) quantifies the minimum admissible separation distance between platooning vehicles in HD commercial vehicle (CV) applications. This distance must be set up such that no collision occurs with leading vehicles under all deceleration conditions. In this paper key interactions to characterize this distance are demonstrated. These include, road surface conditions, grade, inter-vehicle communication delays, air-brake lag time, vehicle speed, weight, and aerodynamic drag. It is seen that characterizing the vehicle and road dynamics will be critical in establishing required deceleration or stopping distances for each vehicle in a platoon. The results of the study also necessitate vehicle control systems that can dynamically adjust not only the separation distances but also the braking reference points based on road conditions. The narrative provides application decision personnel with a well-defined set of admissible separation distance impact factors to consider as part of their architecture selection process.
Robust solar industry growth is creating a shortage of U.S. workers who are knowledgeable in emerging Distributed Energy Resource (DER) technologies including networking, operational software, smart advanced inverters, smart advanced PV modules, and cybersecurity. Retraining military veterans and other qualified individuals to fill workforce gaps in those technologies is the project focus. The project leverages the experience and contributions of DER and cybersecurity experts, educational organizations offering accreditation, and groups serving our nation’s veterans to meet its goals. To bridge this workforce skills gap, the Cyberguardians and STEM Warriors project will establish a complete learning and career advancement system for veterans, transitioning military personnel and other qualified individuals into the DER workforce. The project will guide participants successfully through the process of program/vocation selection, curriculum enrollment, academic mentoring, degree or certificate attainment, job board enrollment, introduction to hiring managers at DER companies, and successful job acquisition. This webinar was used to promote the Cyberguardians program and to ensure ample news coverage to reach veterans, employers, and others that would benefit from this program.
Heavy duty vehicle platooning under highway operating conditions, has been projected to provide significant fuel economy gains based on aerodynamic drag improvements of the platooning vehicles. Realizing these benefits under real-world operating conditions presents several challenges. This paper (the first as part of series) provides a framework to quantify the fuel economy benefits of both conventional and electrified powertrains operating across the U.S. Interstate highway system. In addition to the powertrain, key interactions that are explored include the vehicle separation distance, baseline vehicle aerodynamic properties, vehicle weight, number of vehicles in the platoon, excursions from road speed limits, and particular traffic interactions. While the approach makes use of a limited fidelity vehicle model for longitudinal dynamics, the narrative provides application decision personnel with a mechanism and well-defined set of fuel economy impact factors to consider as part of their architecture selection process.
Department 00635, Performance Assurance, assessments reveal risks and opportunities for improvement Labs-wide. This assessment was conducted to identify opportunities for improving the Department 00635 Assessment Program. This evaluation was conducted to identify opportunities for improving the Center 00600 assessment process by reviewing the quality of assessments completed by Environment Safety and Health (ES&H) personnel in fiscal year (FY) 2018. Approximately 20 percent of the Center 00600 assessments completed in FY18 were reviewed. One assessment was selected from each Center 00600 department contingent on availability in the Assurance Information System (AIS).