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The project was focused on the implementation of support in Analyst for computing beam-loaded Qs of modes in a 3D klystron gun or circuit.
Fusion design projects that reach the stage of design reviews typically require reliability, availability, maintainability and inspectability (RAMI) assessments. While many kinds of reliability and maintainability data are needed for a wide variety of fusion components to quantify a RAMI assessment, one of the types of components requiring data is the passive mechanical component. Passive mechanical components can be items such as metal plates, rods, shafts, brackets, bolts, and other items. Generally these passive components tend to have low failure rates since they are simple designs, have no or few moving parts, and do not need control signals to perform their design function. However, there are no widely recognized datasets for such components, so analysts must use multiple datasets and judgment for failure rates. This report gives recommended failure rates for various failure modes of these components, and gives suggested failure rate multipliers to apply to these failure rates if they reside in harsh environments. If the component resides far from the tokamak then typical industrial failure rates would suffice. Components near the tokamak find conditions can be demanding; similar to those in a fission reactor containment building. Some component failure rates can be modified if the components reside inside the tokamak.
PLTEMP/ANL V4.3 is a program that obtains a steady-state flow and temperature solution for a nuclear reactor core, or for a single fuel assembly. It is based on an evolutionary sequence of codes originally used for plate temperatures, hence “PLTEMP”, developed at Argonne National Laboratory over several decades. Fueled and non-fueled regions are modeled. Each fuel assembly consists of one or more plates or tubes separated by coolant channels. The fuel plates may have one to five layers of different materials, each with heat generation. The width of a fuel plate may be divided into multiple longitudinal stripes, each with its own axial power shape. Depending upon the heat transfer method selected, the temperature solution is effectively 2-dimensional or 3-dimensional (Appendix XV). It begins with a solution across all coolant channels and fuel plates or tubes within a given fuel assembly, at the entrance to the assembly. The temperature solution is repeated for each axial node along the length of the fuel assembly. The geometry may be either slab or radial, corresponding to fuel assemblies made of a series of flat (or slightly curved) plates, or of nested tubes. A variety of thermal-hydraulic correlations are available to determine safety margins such as onset-of-nucleate boiling ratio(ONBR), departure from nucleate boiling ratio (DNBR), and onset of flow instability ratio (OFIR). Coolant properties for either light or heavy water are obtained from FORTRAN functions rather than from tables. The code is intended for thermal-hydraulic analysis of research reactor performance in the sub-cooled boiling regime. Both turbulent and laminar flow regimes can be modeled. Options to calculate both forced flow and natural circulation are available. A general search capability is available (Appendix XII) to greatly reduce the reactor analyst’s time.
The goal of this project was to qualitatively evaluate the efficacy of using plasma cleaning to remove PDMS from vacuum systems. Silicon containing compounds are notorious for interfering with vacuum system techniques such as x-ray photoelectron spectroscopy (XPS), Auger Electron Spectroscopy (AES) and Secondary lon Mass Spectrometry (SIMS). Finding a way to remotely and rapidly remove contaminants from a system saves time and money for analysts using vacuum analytical techniques.
This Quick Start Guide is an abbreviated version of the Contingency Contractor Optimization Phase 3, User Manual for the Contingency Contractor Optimization Tool engineering prototype. It focuses on providing quick access instructions to the core activities of the two main user roles: Planning Manager and Analyst. Based on an electronic storyboard prototype developed in Phase 2, the Contingency Contractor Optimization Tool engineering prototype was refined in Phase 3 of the OSD ATL Contingency Contractor Optimization to support strategic planning for contingency contractors. The tool uses a model to optimize the total workforce mix by minimizing the combined total costs for the selected mission scenarios. The model will optimize the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet the mission requirements as effectively as possible, based on risk, cost, and other requirements.
Rapidly gaining understanding of an executable file is an extremely hard problem, yet one that is critical to support realistic network defense. Without a strong understanding of what programs do, there is no way that defenders can determine whether the presence of a given program is appropriate or not. This research effort was focused on developing ways to allow a human analyst to rapidly build understanding of the content of executable files.
This Quick Start Guide is an abbreviated version of the Contingency Contractor Optimization Phase 3, User Manual for the Contingency Contractor Optimization Tool engineering prototype. It focuses on providing quick access instructions to the core activities of the two main user roles: Planning Manager and Analyst. Based on an electronic storyboard prototype developed in Phase 2, the Contingency Contractor Optimization Tool engineering prototype was refined in Phase 3 of the OSD ATL Contingency Contractor Optimization to support strategic planning for contingency contractors. The tool uses a model to optimize the total workforce mix by minimizing the combined total costs for the selected mission scenarios. The model will optimize the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet the mission requirements as effectively as possible, based on risk, cost, and other requirements.
This report analyzes the power purchase agreements (PPAs) between Massachusetts electric distribution utilities (EDC) and Vineyard Wind LLC filed on July 31, 2018, and derives insights for estimating cost of U.S. offshore wind systems and broader cost modeling activities. The documented price for delivery of offshore wind generation and renewable energy certificates under the Vineyard Wind/electric distribution utilities PPA is 74 $/megawatt-hour (MWh) (2022$) for facility 1 (400 MW) and 65 $/MWh (2023$) for facility 2 (400 MW). However, this PPA price does not comprise the complete set of expected revenue sources and tax benefits available to the Vineyard Wind LLC project. A comprehensive accounting of expected revenue sources inclusive of those that are exogenous to the reported PPA is conducted in this study to estimate the project's levelized revenue of energy (LROE). This allows for a more equivalent comparison of the PPA pricing with bottom-up modeled (unsubsidized) levelized cost of energy (LCOE) estimates. LROE from the Vineyard LLC/EDC PPA is estimated to be 98$/MWh (2018$). This LROE estimate for the first commercial-scale offshore wind project in the United States appears to be within the range of LROE estimated for offshore wind projects recently tendered in Northern Europe with a start of commercial operation by the early 2020s. This suggests that a cost and risk premium for the initial set of U.S. offshore wind projects may be less pronounced than anticipated by many industry observers and analysts.
To address a variety of difficulties surrounding the use of finite element analysis (FEA) in product development at Sandia, this research explored a 'designerly' insertion of FEA into the design-build-test product development cycle. Designerly FEA is characterized by the use of simplified FEA models, designer-friendly FEA software, an FEA analyst embedded in the product design team, relative comparisons of design options, and a deliberate leveraging of routine prototype testing to collect model validation data. Two case study projects were used to explore the impact of this approach on the product development teams' thinking and perceptions of FEA. The case study data was collected using mixed methods and analyzed using a theory-building approach. The results were synthesized into a framework describing how the use of FEA to build confidence in a product design is related to the process by which product development teams gain or lose confidence in FEA itself. The implications may extend to other organizations that desire to increase the impact of simulation technologies in their product development process.
The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence (NSDD) has facilitated the installation of more than 3,728 radiation portal monitors (RPMs) at 660 sites in 63 countries. This collection of RPMs represents the world’s largest network of radiation detectors and provides one element of the defense-in-depth approach that supports the Global Nuclear Detection Architecture. These systems support NSDD’s mission to build partner country capability to deter, detect, and interdict the illicit transport of radiological and fissile material through strategic points of entry and exit at seaports, airports, and border crossings.NSDD works collaboratively with partner countries and international organizations to optimize the operation of these RPMs. The large amount of data provided by NSDD partner countries (summarized in the banner to the right) highlights the close cooperation and partnerships NSDD has built with 63 countries around the world. Thirty-two of these countries shared at least some RPM-related data with NSDD in fiscal year (FY) 2018. This significant level of data sharing is a key element that distinguishes the NSDD office as unique among nuclear nonproliferation programs and initiatives: NSDD can provide specific, objective, data-driven decisions and support for sustaining the radiation detection systems it helped deploy. This data analysis report summarizes and aggregates the RPM data provided to the NSDD office for analysis and review in FY 2018.The data can be used to describe RPM performance and characterize the wide diversity of NSDD deployment sites. For example, NSDD deploys detector systems across sites with natural background radiation levels that can vary by a factor of up to nine from site to site. Some RPM lanes have few occupancies, whereas others have up to approximately 8,000 occupancies per day, and the different types of cargo traveling through a site can result in site-wide alarm rates that range from near 0% at some sites to above 3% at others. Based on the data received, the global average uptime for NSDD RPMs was 97% for FY 2018. NSDD takes all these factors into account in making recommendations to partner countries on how to most effectively manage and maintain site operations. NSDD utilizes reports and other information products created by ORNL Radiation Inspection Systems Team (RIST) data analysts to efficiently allocate the resources needed to detect and ultimately interdict illicit nuclear and radiological material.
The fifth Source Physics Experiment test (SPE-5) was conducted in Nevada on April 26, 2016, at 20:49:00 Coordinated Universal Time (UTC). The explosive source was 4,288.7 kilograms (kg) of polymer-bonded explosive (PBXN) –110, equivalent to 5,035 kg of trinitrotoluene (TNT) detonated at a depth of 76.5 meters (m). The sixth Source Physics Experiment test (SPE-6) was conducted in Nevada on October 12, 2016 at 18:36:00 UTC. The explosive source was 1,982.2 kg of PBXC-141, equivalent to 2,240.2 kg of TNT detonated at the depth of 31.4 m. Both tests were recorded by an extensive set of instrumentation that includes sensors both at near-field (less than 100 m) and far-field (100 m or greater) distances. The near-field instruments consisted of three-component accelerometers installed at various depths ranging from 4 to 99 m below ground surface in boreholes positioned around the shot, and a set of single-component vertical accelerometers on the surface. The far-field network was composed of a variety of seismic and acoustic sensors, including short-period geophones, broadband seismometers, and three-component accelerometers at distances of 100 m to 400 kilometers. In addition, both explosions were recorded in a temporary array of 996 geophones arranged in a densely spaced grid pattern (“large N”). This report coincides with the release of these data for analysts and organizations that are not participants in this program. This report describes the fifth and sixth Source Physics Experiment tests and the various types of near-field and far-field data that are available.
This paper draws on a survey of wind industry professionals to clarify trends in the operational expenditures (OpEx) of U.S. land-based wind power plants. The paper also highlights key drivers of those trends. We find that average all-in lifetime OpEx has declined from approximately $\$$80/kW-yr ($\$$35/MWh) for projects built in the late 1990s to a level that is approaching $\$$40/kW-yr ($\$$11/MWh) for projects under construction in 2018. Turbine operations and maintenance (O&M) costs—inclusive of scheduled and unscheduled maintenance—represent the single largest component of overall OpEx and the primary source of cost reductions over the last decade. We observe wide ranges of OpEx over time; for example, survey respondents cite a range in average expected costs for projects commissioned between 2015 and 2018 from $\$$33/kW-yr to $\$$59/kW-yr. Notably, these broad ranges include high levels of variability in both turbine O&M costs and non-turbine OpEx. Potential technical and strategic drivers of this variability are highlighted. We also use historical OpEx learning rates, showing a 9% OpEx reduction for each doubling of global installed wind capacity, to project a further $\$$5–$\$$8/kW-yr (12%–18%) OpEx reduction from 2018 to 2040. When compared with the broader literature, these findings suggest that continued OpEx reductions may contribute 10% or more of the expected reductions in land-based wind’s levelized cost of energy. Moreover, these estimates may understate the importance of OpEx owing to the multiplicative effects through which operational advancements influence not only O&M costs but also component reliability, performance, and plant-level availability—thereby affecting levelized costs though OpEx reduction and by enhancing annual energy production and plant lifetimes. Given the limited quantity and comparability of previously available OpEx data, the data and trends reported here may usefully inform OpEx assumptions used by electric system planners, analysts, modelers, and research and development managers. The results may also provide useful benchmarks to the wind industry, helping developers and asset owners compare their OpEx expectations with historical experience and other industry projections.
The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.
The SNL Sierra Mechanics code suite is designed to enable simulation of complex multi-physics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.
This document describes the methodology used to analyze plutonium (Pu) materials for isotopic composition, radioactive daughters, and stable impurities by Inductively-Coupled Plasma Mass Spectrometry (ICPMS). Analysts need extensive skill in traditional analytical wet chemistry techniques, experience in ICPMS measurements, and an understanding of its limitations.
The U.S. Department of Energy (DOE) and the Sun Grant Initiative began the Regional Feedstock Partnership (RFP) in 2007 primarily to address information gaps associated with sustainably and reliably producing a billion-tons of biomass annually by the year 2030 for the U.S. bioenergy industry. The culmination of these efforts were reported in the Sun Grant/DOE Regional Feedstock Partnership Final Technical Report. The same biomass resources used to support these yield and sustainability efforts included analytical characterization data representing biomass quality. Considerable effort has been put into collection, harmonization, and archival of the analytical data, metadata, and physical samples associated with the thousands of samples collected from the RFP field trials. This data provides a unique opportunity to understand the impacts of agronomic and forest production practices, as well as environmental factors, on biomass material attributes relevant to bioenergy production. To more efficiently develop these relationships, this workshop was held to bring together the experts who conducted the RFP field trials and the biomass attribute data analysts. The objectives of the workshop included the following: • Enable face-to-face interactions with field trial experts, allowing for insights into the species and field trials themselves that are not obvious looking at data alone • Fill in metadata and analytical gaps from the RFP for future analyses • Share results from analysis of RFP biomass properties for each species along with associated field experiment observations/results • Discuss the potential to develop biomass quality maps • Discuss preparation of peer-reviewed publications for each species • Discuss outlines for a comprehensive summary report on the evaluation of RFP biomass material attributes for quality determination, focusing on the results of peer-reviewed publications and analysis of compiled RFP biomass attribute datasets
Radioisotope power systems (RPSs) convert decay heat from radioactive materials to electrical power. The National Aeronautics and Space Administration (NASA) uses RPSs for certain orbiters, landers, rovers, and probes that cannot rely on solar or chemical power. Most of the emitted charged particles in RPS fuels are locally absorbed, and the particles’ kinetic energy is converted into thermal energy as they slow down in the surrounding materials. This heat is subsequently converted into electricity through some form of energy conversion process (e.g., thermoelectric, heat engine, thermionic). While nearly all the charged particles are stopped locally, a non-trivial portion of the emitted neutral particles (neutrons and photons) escape the fuel and are free to interact with surrounding materials. This escaping radiation field can be operationally problematic for certain instruments, materials, electronics, etc., and can cause problems during terrestrial shipping, integration, testing for personnel, instrumentation, etc. Furthermore, the fuel’s emission spectrum evolves over time as the parent isotopes decay away and daughter products accumulate. This changing fuel composition alters characteristics of the ambient radiation field over time, which is further affected by RPS orientation and the surrounding environment. Tools that can rapidly estimate the radiation characteristics of RPSs with various fuel compositions, fuel ages, various RPS orientations, and in/on different spaceflight and planetary scenarios provide researchers with an opportunity to quickly estimate the radiation implications of a given RPS scenario. The RPS dose estimation tool (RPS-DET) provides engineers, scientists and analysts who are not trained in the art of particle transport software with a solution for quickly building, simulating, and analyzing the radiation impacts of various RPS designs in relevant spaceflight and terrestrial environments.
The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.