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With the goal of advancing criticality safety with neutron localization, the following tasks were successful: (1) demonstrated neutron source localization using a NoMAD detector and ML; and (2) developed a real-time system for streaming in data from NoMAD, verifying that the system works in experimental settings.
At the initiation of the Used Fuel Disposition (UFD) R&D campaign, international geologic disposal programs and past work in the U.S. were surveyed to identify viable disposal concepts for crystalline, clay/shale, and salt host media (Hardin et al., 2012). Concepts for disposal of commercial spent nuclear fuel (SNF) and high-level waste (HLW) from reprocessing are relatively advanced in countries such as Finland, France, and Sweden. The UFD work quickly showed that these international concepts are all “enclosed,” whereby waste packages are emplaced in direct or close contact with natural or engineered materials . Alternative “open” modes (emplacement tunnels are kept open after emplacement for extended ventilation) have been limited to the Yucca Mountain License Application Design (CRWMS M&O, 1999). Thermal analysis showed that, if “enclosed” concepts are constrained by peak package/buffer temperature, waste package capacity is limited to 4 PWR assemblies (or 9-BWR) in all media except salt. This information motivated separate studies: 1) extend the peak temperature tolerance of backfill materials, which is ongoing; and 2) develop small canisters (up to 4-PWR size) that can be grouped in larger multi-pack units for convenience of storage, transportation, and possibly disposal (should the disposal concept permit larger packages). A recent result from the second line of investigation is the Task Order 18 report: Generic Design for Small Standardized Transportation, Aging and Disposal Canister Systems (EnergySolution, 2015). This report identifies disposal concepts for the small canisters (4-PWR size) drawing heavily on previous work, and for the multi-pack (16-PWR or 36-BWR).
In the immediate aftermath of the common-cause seismic and tsunami events that triggered the Fukushima Daiichi nuclear accident on March 11, 2011, the nuclear regulator, the Canadian Nuclear Safety Commission (CNSC), requested that all Cass I nuclear facilities re-examine the safety cases for their nuclear facilities. Lessons-learned task forces were established by the CNSC, and the nuclear utilities, Ontario Power Generation (OPG), Bruce Power (BP), and New Brunswick Power (NBP). The purposes of these independent task forces was to develop relevant lessons learned issues for the Candu nuclear power plants operating in Canada and to identify actions that could enhance safety. Subsequently, a CNSC Integrated Action Plan was developed to address the recommendations arising from the CNSC Task Force Report, and the licensees aligned their actions with this plan. The actions were grouped into four categories, as follows. 1. Strengthening defence in depth; Actions included re-assessment of a site-specific external hazards using PSA; physical plant changes to add further cooling water make-up capability to heat sinks; development of new Canadian standards and updated regulatory documents that address requirements for Beyond Design Basis Accidents (BDBA), Probabilistic Safety Assessment (PSA) and Period Safety Review (PSR); development of a new and novel methodology for assessing multi-unit risk that is consistent with the IAEA construct of defence-in-depth (including a safety goal hierarchy and complementary risk analysis methods that address 'Black Swan' events); enhanced management of hydrogen combustion challenges; and enhanced Severe Accident Management Guidelines (SAMG). 2. Enhancing emergency response; Actions included provision of Emergency Mitigation Equipment (EME) such as transportable diesel-driven pumps or fire engines, transportable diesel generators for AC and instrument power; pre-installed connections to in-plant equipment via easily accessible and protected quick-connect points for water and electrical power; upgraded emergency response centres; enhanced communication systems and protocols; and enhanced emergency response programs, training and exercises. 3. Improving the regulatory framework and processes; 4. Enhancing international collaboration. Actions assigned under categories 3 and 4 were placed upon the regulator. This presentation will focus on the assigned actions in categories 1 and 2. The underlying motivation, objectives, and safety benefits associated with the actions will be described within the context of broader aspects of severe accident mitigation in water-cooled reactors. (author)
Power outages cost American industries and businesses billions of dollars and jeopardize the lives of hospital patients. The losses can be greatly reduced with a fast, reliable, and flexible self-healing tool. This paper is aimed to tackle the challenging task of developing an adaptive restoration decision support system (RDSS). The proposed RDSS determines restoration actions both in planning and real-time phases and adapts to constantly changing system conditions. The comprehensive formulation encompasses practical constraints including ac power flow, dynamic reserve, and load modeling. Here, the combinatorial problem is decomposed into a two-stage formulation solved by an integer L-shaped algorithm. The two stages are then executed online in the RDSS framework employing a sliding window method. The IEEE 39-bus system has been studied under normal and contingency conditions to demonstrate the effectiveness and efficiency of the proposed online RDSS.
The Atlantic Ocean covers approximately 25% of Earth’s surface and the atmosphere above it is home to a complex array of clouds and aerosols that have important influences on regional and global weather and climate. These influences must be accurately depicted in short range, medium range, seasonal, and climate forecast models. Conditions over the tropical Atlantic are particularly complex due to continental scale plumes of dust from the Sahara Desert and smoke from agricultural burning in Africa that drift across the Atlantic Ocean basin toward the Americas. These plumes are often found meandering in the lower atmosphere above shallow tropical clouds that form above the ocean surface, presumably mingling with these clouds on occasion due to convective mixing processes. Elevated dust and smoke particles absorb incoming sunlight and substantially warm the marine atmosphere in the layer in which they are present. This warming may alter the thermal stability of the marine atmosphere and may throttle or enhance the development of clouds, change their internal structure and the rate at which they precipitate. Alternatively, it may isolate the lower atmosphere from drier layers above enabling water vapor to accumulate near the ocean surface potentially leading to the development of deeper convection. Our study was organized around the principal concept of determining the impact of African smoke and dust plumes upon cloud development at ASI and understanding how a popular shallow convection parameterization used in models responds to the presence of this aerosol. We analyzed observations collected during the US Department of Energy (DOE) Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign using the Atmospheric Radiation Measurement Program’s Mobile Facility #1 (AMF-1), which was deployed to Ascension Island (ASI) in Southeastern Atlantic for a one-year period. Ascension Island is immediately downwind from an African source of these plumes, but far enough removed to enable the lower atmosphere to have reacted to their presence. A main goal of our study was to compute radiative heating rate profiles over Ascension Island and along the trajectory from the biomass burning regions along coastal Africa to Ascension Island. To compute the radiative heating rate due to aerosols and clouds, we employed observed profiles of temperature, humidity, and clouds from LASIC alongside aerosol optical properties from the Modern-era Retrospective analysis for Research and Applications Version 2 (MERRA-2), as input for the Rapid Radiation Transfer Model (RRTM). Radiative heating was also assessed across the southeast Atlantic Ocean using an ensemble of back trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We were successful in this effort and the resulting publication is already being cited despite its relatively short lifetime in the literature. The second part of our study involved the process-level representation of the clouds observed over the Southeastern Atlantic in models. Our initial task, upon which the balance of this portion of the study depended, was to evaluate the representativeness of the clouds observed by AMF-1. What orographic influence did Ascension Island have on the measured cloud structure? We set out to answer this question by trying to separate observations that were clearly indicative of orographic forcing from those that were representative of open ocean. The siting of AMF-1, which was 340-m above sea-level on the slope of a steep escarpment, proved demonstrably problematic for cloud process measurements. Despite considerable effort using multiple approaches including artificial intelligence (AI), we were unable to successfully compensate for the orographic forcing present at the AMF-1 site on ASI and, hence, produce process-level summaries of the convective mass flux representative of open ocean over the Southeastern Atlantic. Even though the project has officially ended, we are making a final attempt using two new types of clustering algorithm (i.e., AI) on the recommendation of a former student, who is an expert in this area. Since we have only recently begun to test these new AI schemes, the recommendations from the second part of our project outlined below are based on our experience at the time of this report.
The University of Alaska Fairbanks (UAF) Alaska Hydrokinetic Energy Research Center was tasked with developing a real-time data telemetry / remote power generation system to monitor frazil ice conditions in the Kvichak River in support of the U.S. Department of Energy funded "Next Generation MHK River Power System Optimized for Performance, Durability and Survivability" project. A real-time telemetry system was requested because of the short time span between the end of the frazil ice season when the instruments would be recovered, limited vessel availability and the project end-date. To meet the project objectives, UAF designed and assembled a remote power/real-time data telemetry system that included an auto start propane generator, a small PV array, a small battery bank and line-of-sight radios as well as two sonar systems to monitor river velocity and water column acoustic backscatter strength. Both sonars included internal batteries for powering the instruments in case of failure of the shore based power system. The sonars, deployed in ~5 m of water on the bed of the Kvichak River, adjacent to the Village of Igiugig, Alaska were tethered to shore via a waterproof armored cable that conveyed power to the subsurface instruments and data from the instruments to the shore based telemetry system. The instruments were programmed to record data internally as well as to transmit data serially over the cables to the shore based system. The system was in-place between November, 2016 and June, 2017. While the real-time data telemetry system was not successful and the remote power generation power system was only partially successful, the system design included sufficient redundant power in the form of internal instrument batteries to enable the collection of nearly three months of overlapping velocity and backscatter data (from November through February) and a record of acoustic backscatter strength spanning the entire ~150 day frazil ice season between November, 2016 and ~April, 2017. This submission includes the overwinter ice study plan, raw data, and report.
DOE manages over 300 types of SNF, most of which are located at the INL site. “Road-ready dry storage” is a management concept where SNF is packaged into dry, sealed canisters, which are then placed in on-site storage in anticipation of later removal. The Idaho Cleanup Project and INL are collaborating on the Road-Ready Capability Demonstration Project, which will develop and demonstrate the designs, technology, processes, and regulatory framework for packaging DOE SNF for road-ready dry storage. In support of establishing a large-scale road-ready dry storage program at the INL site, the demonstration will package a select amount of DOE-managed SNF into DOE Standard Canisters. The closure process for the DOE Standard Canisters will include fuel and basket loading, welding, inspection, leak testing, and if needed, repair. As a follow-up to previous discussion on the design of the DOE Closure Leak Test Assembly, this report describes recent fabrication and testing efforts performed at INL. DOE Standard Canisters are sealed by two sequential gas tungsten arc welds. Both are performed by remotely operated and semi-autonomous welding systems. The first weld is a circumferential pipe weld that completes assembly of the canister body and lid assembly. The second and final closure weld connects the vent plug to the vent port with an identical butt joint to the circumferential pipe weld. After the second weld is performed on the vent port, these welds are helium leak tested using an inside-out technique. In addition to the commercially available vacuum and leak detector systems, the DOE Standard Canister Closure Leak Test Assembly was designed for both remote and manual operation. This report describes fabrication and performance testing associated with the inside-out technique. INL staff designed and tested systems to accomplish these tasks. Hardware fabrication occurred at INL facilities. Forthcoming work includes design optimization, integration to existing systems, and implementation to packaging demonstration operations.
As part of the Light Water Reactor Sustainability program, an ongoing research effort is being conducted on technical specifications surveillance interval extension of digital equipment in nuclear power plants. The research team is led by Idaho National Laboratory and includes Pacific Northwest National Laboratory, Technology Resources, and Oak Ridge National Laboratory. This research focuses on developing methods for applying the U.S. Nuclear Regulatory Commission (NRC)–approved guidance to implement a licensee-controlled, risk-informed surveillance frequency change program in digital instrumentation and control (I&C) systems that include self-diagnostics and online monitoring (OLM) capabilities. Although approved methods exist for extending technical specifications (TS) surveillance test intervals (STIs) for general equipment, including analog I&C equipment, gaps remain in technology and guidance on crediting newer digital equipment’s internal self-diagnostics and OLM characteristics. Previous research described a general methodology for crediting internal self-diagnostics for extending surveillance test intervals. The methodology used self-diagnostics to detect—and credited recovery from—failure. Self-diagnostics were also applied for performance monitoring during the extended surveillance interval. This report discusses the status of recent activities to evaluate the previously developed methodology using a pilot study. Although both a utility partner for a pilot study and a specific digital asset were identified in FY2020, delays in obtaining proprietary information resulted in a limited ability to fully evaluate the methodology, and further interactions were complicated by the COVID pandemic. Therefore, at that time, the use of public-domain information—along with current processes for surveillance interval extension through a surveillance frequency control program—identified the need to fully assess diagnostic coverage as part of the pilot study. Furthermore, self-diagnostics were also identified as a potential option to replace the drift analyses conducted as part of current STI extension procedures. In FY2022, the project was reconstituted with the industry partner, and information and data were made available by the industry partner to the research team for review. The shared information included failure event descriptions and data for a digital I&C system since its implementation, as well as recent STI extension interval reports developed by the utility partner on that digital I&C system. This report presents an evaluation of this information and data and describes an application of the proposed methodology cited above. The methodology seeks to take advantage of the self-diagnostics and OLM capabilities to reduce risk or reduce the level of qualitative monitoring assessment needed to perform a risk-informed STI extension using existing NRC approved guidance or both. Addressing these issues of STI extension by crediting self-diagnostics is likely to result in benefits for current and future nuclear power plant (NPP) operations, including lowering the barriers to adoption of digital I&C systems and increasing cost savings by deferring or eliminating unneeded preventive maintenance (tasks or checks or activities). Specifically, self-diagnostic and OLM capabilities of newer digital equipment being installed in non-safety and safety applications are designed to detect failures, provide early warning of potential failures, and notify plant operators to take appropriate action to reduce out of service (OOS) time thus protecting safety margins. Moreover, the equipment is expected to provide information that time-related operational degradation is identified early to ensure timely and planned corrective actions instead of a reactive and unplanned approach ahead of an extended-surveillance interval.
Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and execution strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.
The Rad-NESHAP program takes samples at major point sources to track how much of select nuclides are being emitted out of the stack. Samples are taken at the site where the radiological operations are being performed. The samples are then sent to analytical laboratories for analysis to determine what nuclides exist in the sample. However, due to the sensitivity of the instruments, false positives are often reported. To reduce the number of false positives, the results reported from the analytical labs are compared to set detection limits. Anything below the set detection limit is considered part of the background while anything above the limit is considered a positive hit. Therefore, the detection limit must be set low enough that any false negatives do not result in a significant dose missed at the end of the year but high enough that there are not enough false positives to skew the annual dose being reported. All detection limits listed in this section for the analyses below were designed to meet the stated equivalent emissions rate and subsequent off-site doses. These minimum detectable activities (MDAs) were developed in the 1990s and documented in the memo cited for each analysis below. These limits and memos are all currently referenced in the Quality Assurance Project Plan (QAPP) for the Rad-NESHAP Compliance Task, which is being updated to a Project Implementation Plan (PIP) concurrently with this document. As part of this update process, the original MDAs defined in this section needed to be verified that they were still conservative and meet the off-site dose levels stated.
SF-26-086 CodeScribe introduces a structured, multi-stage pipeline that combines deterministic program analysis with LLM-powered translation to enable incremental, testable Fortran-to-C++ migration. First, `code-scribe index` traverses the project directory tree and produces `scribe.yaml` metadata files recording all modules, subroutines, and functions at each level, giving the LLM accurate structural context instead of a hallucinated codebase model. Second, `code-scribe draft` performs the deterministic portion of translation — converting Fortran types to C++ equivalents, replacing `use` statements with `#include` and `using namespace` directives, and detecting constructs requiring special handling — while embedding`scribe-prompt` annotations that guide the LLM through non-trivial cases such as statement-function-to-lambda conversions and `extern "C"` wrapper generation. Third, `code-scribe translate` applies project-specific TOML-based few-shot prompt templates and submits the composed prompt to a pluggable LLM backend (OpenAI, Anthropic, Argonne ARGO, any OpenAI-compatible endpoint, or local Hugging Face checkpoints), producing a C++ source file, a header, and a Fortran-C++ interface file for each translated routine so the codebase compiles and runs correctly throughout the migration. Beyond translation, CodeScribe includes a tool-using coding agent (`code-scribe agent`) with read, bash, edit, and write capabilities, and a bounded loop mode (`code-scribe loop`) that runs repeated stateless agent sessions over a task file with restricted tool access — enabling sustained, auditable software development workflows for broader scientific computing tasks.
Measurements in Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors, such as the MicroBooNE detector at Fermilab, feature large, high fidelity event images. Deep learning techniques have been extremely successful in classification tasks of photographs, but their application to LArTPC event images is challenging, due to the large size of the events. Events in these detectors are typically two orders of magnitude larger than images found in classical challenges, like recognition of handwritten digits contained in the MNIST database or object recognition in the ImageNet database. Ideally, training would occur on many instances of the entire event data, instead of many instances of cropped regions of interest from the event data. However, such efforts lead to extremely long training cycles, which slow down the exploration of new network architectures and hyperparameter scans to improve the classification performance. We present studies of scaling a LArTPC classification problem on multiple architectures, spanning multiple nodes. The studies are carried out on simulated events in the MicroBooNE detector. We emphasize that it is beyond the scope of this study to optimize networks or extract the physics from any results here. Institutional computing at Pacific Northwest National Laboratory and the SummitDev machine at Oak Ridge National Laboratory’s Leadership Computing Facility have been used. To our knowledge, this is the first use of state-of-the-art Convolutional Neural Networks for particle physics and their attendant compute techniques onto the DOE Leadership Class Facilities. We expect benefits to accrue particularly to the Deep Underground Neutrino Experiment (DUNE) LArTPC program, the flagship US High Energy Physics (HEP) program for the coming decades.
High-energy physics requires the generation of large numbers of simulated data samples from complex but analytically tractable distributions called matrix elements. Surrogate models, such as normalizing flows, are gaining popularity for this task due to their computational efficiency. We adopt an approach based on flow annealed importance sampling bootstrap (FAB) that evaluates the differentiable target density during training and helps avoid the costly generation of training data in advance. We show that FAB reaches higher sampling efficiency with fewer target evaluations in high dimensions in comparison to other methods.
The Illinois Express Quantum Network (IEQNET) is a program to realize metro-scale quantum networking over deployed optical fiber using currently available technology. IEQNET consists of multiple sites that are geographically dispersed in the Chicago metropolitan area. Each site has one or more quantum nodes (Qnodes) representing the communication parties in a quantum network. Q-nodes generate or measure quantum signals such as entangled photons and communicate the results via standard, classical, means. The entangled photons in IEQNET nodes are generated at multiple wavelengths, and are selectively distributed to the desired users via optical switches. Here we describe the network architecture of IEQNET, including the Internet-inspired layered hierarchy that leverages software-defined-networking (SDN) technology to perform traditional wavelength routing and assignment between the Q-nodes. Specifically, SDN decouples the control and data planes, with the control plane being entirely classical. Issues associated with synchronization, calibration, network monitoring, and scheduling will be discussed. An important goal of IEQNET is demonstrating the extent to which the control plane can coexist with the data plane using the same fiber lines. This goal is furthered by the use of tunable narrow-band optical filtering at the receivers and, at least in some cases, a wide wavelength separation between the quantum and classical channels. We envision IEQNET to aid in developing robust and practical quantum networks by demonstrating metro-scale quantum communication tasks such as entanglement distribution and quantum-state teleportation.
The integration of additive manufacturing (AM) capabilities on Computer Numerical Control (CNC) systems allows for the expansion of additive manufacturing to a wide range of part and tool repair operations. This multi-tasking integration, termed hybrid manufacturing, has been researched by others in the past, and Autodesk has been critical in developing process planning and toolpath algorithms for hybrid systems. Objectives and Tasks: Hybrid manufacturing systems enable both additive and subtractive capabilities in a single manufacturing workcell. These systems have the potential to impact a variety of industries, including the tool and die industry due to their repair, refurbishment, and complex geometry manufacturing capabilities. While there has been significant development of toolpath planning for both subtractive and additive processes independently, there has been little, if any, development of hybrid toolpath planning to integrate both processes during the manufacturing design and toolpath generation stage of a product’s lifecycle. Furthermore, additive toolpath planning has been limited to planar manufacturing, but this limitation could be overcome as hybrid CNC machines have multi-axis control. The objectives of this research include: - Development and demonstration of independent three-, four-, and five-axis toolpath generation algorithms for both additive and subtractive processes, and - Development, demonstration, and integration of three-, four-, and five-axis hybrid process planning and toolpath generation algorithms for hybrid additive and subtractive processes. The team will leverage the widely used Autodesk Fusion 360 product design and manufacturing (CAD/CAM) platform to achieve these objectives. Autodesk will provide the expertise in CAD tools, as well as access to their new CAD/CAM manufacturing tools (3-, 4-, and 5-axis milling, additive toolpath generation). ORNL will provide expertise in additive manufacturing toolpath generation, process planning, and manufacturing validation. By the end of the program, the team will have developed and validated multi-axis milling, additive manufacturing, and hybrid manufacturing on an industrial hybrid CNC system (Mazak 500-VC).
Expansion of the power grid in the USA is essential to fulfilling the rising energy demand of the country. In particular, the transmission grid, a network of electrical energy corridors that enable the flow of large amounts of energy from the point of generation to the point of consumption, needs significant expansion to cater to this growth of electrification. The current infrastructure is also dated, and any new transmission corridor should be based on a vision of building a modern infrastructure that is futureproof. High voltage DC (HVDC) transmission technology falls in this category: it is the most economical way to build large transmission lines and relies on sophisticated electronics and flexible controls, rather than just passive components like switchgear and transformers. This project is aimed at establishing the technical and economic feasibility of a network of HVDC lines that are interconnected to form a multi-terminal DC network. HVDC transmission is not a new technology and United States has a number of such lines; however, these are point to point transmissions and do not form a DC grid. Modeling and analyzing DC grids is challenging since there are no established modeling tools and the traditional ways of modeling AC grids fall short of providing the fidelity required the fast dynamics of the DC grid. This project aims to build a software-in-the-loop simulator for a multi-terminal HVDC grid, called MULTISIM and, establish new control and protection algorithms to operate such a connected DC system. NLR, a key partner, established the core framework of the MULTISIM simulator and validated its functionality. The GE Vernova team, created a full-scale model of a four-terminal HVDC network using PSCAD (Power Systems Computer Aided Design) software and established the baseline performance of the system during normal and fault operation. The project was started on 10/12024 with a kick-off meeting held on 12/11/2024 and ran through two quarters till termination. All the tasks, milestones and deliverables during this period were met. Several interim reports detailing the various tasks were submitted. The following sections provide details on the completed tasks till the project pause and termination after Q2.
Destructive analytical measurements establish a nuclear facility’s nuclear material inventory and inventory differences for Nuclear Material Accountancy and Control. A nuclear laboratory’s ability to perform accurate high-precision analytical measurements is key for tracking large inventories within a facility’s material balance areas and during production to track material movement through dynamic processes. For uranium, these measurements are made by using several established high-precision measurement protocols. These include isotope dilution mass spectrometry, gravimetry, and potentiometric titrations. Whatever measurement technique a nuclear lab chooses to use, reference materials (RMs) with certified attributes and accompanying uncertainties are used to calibrate measurement systems, and are the cornerstone for accurate results. In addition to calibration, RMs provide for metrological traceability, are used for method development and validation, and thus provide critical evaluations of the appropriateness and performance of analytical processes used. Evaluations may include validation that a method is fit-for-purpose, quantification of systematic and random biases, and the evaluation of long-term and short-term performance metrics. High-precision measurement techniques require that measured attributes be certified to a high degree of precision in the RMs used—ultimately, to a higher degree than that of the measurement technique itself. The US authority on the production of special nuclear material Certified Reference Materials is the NBL Program Office (NBLPO), formally known as New Brunswick Laboratory (NBL). The NBLPO is responsible for the sales and distribution of existing NBL certified reference materials (CRMs) and for the production of the next generation of nuclear RMs. To accomplish its mission, NBLPO is establishing key base capabilities within the DOE laboratory complex that formerly existed at the NBL laboratory. The Nuclear Analytical Chemistry (NAC) section within the Chemical Sciences Division (CSD) at Oak Ridge National Laboratory (ORNL) is currently working with NBLPO to set up laboratory and measurement capabilities to provide measurements and capabilities for production and/or recertification of existing and future CRMs for uranium assay. The NBL-developed high-precision titration (HPT) method is a critically-evaluated, extremely precise and accurate primary method utilized for the determination of uranium content in a variety of uranium materials. The HPT method, combined with detailed balance weighing protocols, provides for an analytical methodology that is unsurpassed in precision and one in which all sources of error have been evaluated, a requirement of CRM certification. HPT capability within the United States was lost with the closure of the labs at NBL. The NAC has been collaborating with NBLPO to stand up and demonstrate the capability to perform uranium assay via HPT at ORNL. HPT can produce results with an expanded uncertainty of approximately 0.01% for pure uranium compounds, with typical precisions of <0.006%. The major tasks required to stand up the method at ORNL were the refurbishment of a dedicated lab and equipment setup, procedure development, analyst training, establishing method-specific quality assurance, and qualification of an analyst to perform the method. This report summarizes these tasks, outlines the documents drafted, and gives the outcome of the qualification titrations.
The North American Board of Certified Energy Practitioners (NABCEP) is the most respected, well-established, and widely recognized national certification organization for professionals in the field of renewable energy. NABCEP’s certifications were created to facilitate consumer protection, improve quality assurance, and help employers judge the skills of existing or potential employees. The certifications also allow individuals to differentiate themselves from others in their field and advance their careers while fostering increased recognition of the profession. Since NABCEP’s founding in 2002, all of its certification exams have been administered in paper-and-pencil format twice per year at 30 exam sites around the United States. The biannual test administration and relatively low number of exam sites make it challenging for many qualified renewable energy professionals to take NABCEP’s certification exams. The rigorous nature of the exam, which leads to many candidates failing the exam on their first and sometimes second attempts, combined with the low number of annual test administrations means that anyone who fails will need to wait another six months for the chance to retake the exam. These factors limited the potential growth of NABCEP’s certification programs and the resultant quality assurance within the renewable energy industry. Thanks to a generous grant by the Department of Energy’s Solar Training and Education for Professional (STEP) program, NABCEP recently began updating its Photovoltaic (PV) Installation Professional Exam and developing three new specialty certifications in PV design, PV installation, and PV commissioning & maintenance. One of the primary objectives of this STEP-funded project was to develop the exams using a computer-based testing (CBT) model to increase the number of exam administrations and available exam sites for NABCEP’s certification exams. To successfully complete this project, NABCEP partnered with Castle Worldwide, Inc. With more than 25 years of experience in test development, test administration, analysis of examinations, and has a staff of 70 experienced personnel, NABCEP was confident that Castle’s team was more than qualified to help NABCEP make the transition to CBT examinations. NABCEP and Castle Worldwide jointly developed a project management plan that included key deliverables, scope management, a work breakdown structure, roles and responsibilities, and a project schedule with milestones. The project schedule was carefully monitored to ensure that activities along the critical path were not delayed and, when deemed necessary, the project was crashed to add resources so that activities could occur in parallel. NABCEP and Castle Worldwide staff met weekly to discuss any potential schedule variances and activities which might delay the closing of the project. NABCEP also recruited 46 subject matter experts (SMEs) to work with Castle’s staff on this project. NABCEP staff, SME’s, and Castle staff worked together to develop the Job Task Analyses that form the basis for the certification exams, create new examination forms, conduct passing score studies, and complete a psychometrical analysis of potential exam items. NABCEP’s SMEs utilized Castle’s item development platform during face-to-face meetings, webinars, and remote item authoring to write, review, and approve exam items. Castle also used their software to psychometrically analyze existing exam items to confirm the reliability and validity of the NABCEP’s certification exams. On January 3rd, 2018, NABCEP’s began offering its PV Installation Professional certification exam via CBT. The exam was available at Castle’s nearly 600 exam sites in the United States. A large number of sites will help to ensure better access for solar professionals in rural and remote areas, which drives down the implicit costs of taking the certification exams. Thanks to the STEP grant and the robust partnership between NABCEP and Castle Worldwide, Inc., personnel certifications will be much more accessible and affordable for renewable energy professionals.