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This ECAR serves to demonstrate the compatibility of MARVEL Reactor materials in contact with the two molten metal coolants, sodium potassium eutectic and lead. Operational requirements are determined, and recommendations for material treatment or replacement are presented.
Many public and private entities such as government agencies and private foundations have missions related to the improvement, protection, and sustainability of the environment. In pursuit of their missions, they fund projects with related outcomes. Typically, the funding scene consists of scarce funding dollars for the many project requests. In light of funding limitations and funder's search for innovative funding schemes, a method to support the allocation of scarce dollars among project components is presented. The proposed scheme has similarities to methods in the project selection literature but differs in its focus on project components and its connection to and enumeration of the universe of funding possibilities. The value of having access to the universe is demonstrated with illustrations. The presentation includes Excel implementations that should appeal to a broad spectrum of project evaluators and reviewers. Access to the space of funding possibilities facilitates a rich analysis of funding alternatives. - Highlights: • Method is given for allocating scarce funding dollars among competing projects. • Allocations are made to fund parts of projects • Proposed method provides access to the universe of funding possibilities. • Proposed method facilitates a rich analysis of funding possibilities. • Excel spreadsheet implementations are provided.
The purpose of this report is to discuss the projects implemented, utilizing Department of Energy grant funds, to support the use and understanding of renewable energy in Orange County, Florida and the Greater Orlando Area. Orange County is located in the State of Florida and is most popularly referred to as Orlando. The greater Orlando area’s current population is 1,225,267 and in 2015 was the first destination to surpass 60 million visitors. Orange County utilized grant funds to add to the growing demand for access to charging stations by installing one level 2 dual NovaCharge CT4021 electric vehicle charging station at the Orange County/University of Florida Cooperative Extension Center. The charging station is considered a “smart” charger connected to a central network operated by a third party. Data collected includes the number of charging sessions, session start and end times, the electricity usage, greenhouse gases saved and other pertinent data used for reporting purposes. Orange County continues to support the use of electric vehicles in Metro Orlando and this project continues to bring awareness to our public regarding using alternative vehicles. Additionally, we offer all visitors to the Orange County/University of Florida Cooperative Extension Center free charges for their electric vehicles 24 hours a day. Since the operation of the charging station there have been 52 unique driver users, a total of 532.2258 kg of greenhouse gas savings and 159.03 gallons of gasoline savings. The installation of the additional electric vehicle charging station is part of a county-wide goal of promoting implementation of renewable energy technologies as well as supporting the use of electric vehicles including the Drive Electric Orlando & Florida programs. http://driveelectricorlando.com/ & ; http://www.driveelectricflorida.org/ . Grant funds were also used for Outreach and Educational efforts. Educational efforts about renewable energy were accomplished through the continued support as well as a proposed expansion and potential relocation of the Climate Change Education Center. The growth of the Climate Change Education Center focused on 2 educational subsectors. The first educational sector focused on an apprenticeship with university students. The second sector Orange County partnered with a hospitality college that held seminars to educate students in sustainability best practices that would influence the industry as a whole as students take jobs around the U.S. and other parts of the world. Orange County completed five of the originally proposed six educational seminars. The first seminar focused on community based social marketing techniques for driving sustainable behavior changes. The second seminar held was a green team workshop. The third seminar focused on urban sustainability planning. The fourth and fifth seminars held were Florida Energy Code workshops for building inspectors. A sixth transit oriented development seminar in partnership with Rollins College was explored, but was not conducted because the proposed on campus venue was not accessible for an extended period of time due to renovations. Additionally, an ENERGY STAR training program was conducted with students from the University of Central Florida; three of the five buildings assessed received ENERGY STAR ratings; one student completed the training and received their certification as an ENERGY STAR Specialist. Background: Location: Orange County is located in the central region of the State of Florida and is most popularly known for including the City of Orlando. The greater Orlando area’s current population is 1,225,267 and is home to large corporations such as Walt Disney World, Universal Studios Orlando, Ritz Carlton, Darden Restaurants, and the nation’s second largest convention center. Opportunities Identified: Encouraging Sustainability in Major Sectors: The Central Florida economy is largely dependent on the hospitality industry and in 2015 it was the first destination to surpass 60 million visitors. With over 60 million visitors each year, 120,000 hotel rooms, 4,000 restaurants, and 75 theme parks and attractions, the local hospitality industry provided a wealth of opportunity to reduce greenhouse gas emissions through building energy efficiency and renewable energy. Accordingly, Central Florida is an ideal training ground for teaching best practices for sustainability focused on the hospitality industry. Meeting the Growing Demand for Electric Vehicle Infrastructure: According to the 2014 U.S Clean Tech Leadership Index Report, nationwide electric vehicle ownership in the top 50 largest metro areas increased sharply in 2013; the Orlando Metro Area was ranked #5 in the nation in in terms of electric vehicle charging stations per one million people. Additionally, the Orange County 2014-2015 Annual Sustainable Orange County Report indicated there are 300 electric vehicle charging stations in Central Florida (roughly 300 charging stations within ~70 mile radius available to our residents of Orange County). By increasing and improving access to charging stations, Orange County supports the growing demand for renewable energy technologies. Project Achievements/Accomplishments: Installed an Electric Charging Station: Orange County utilized grant funds to install one level 2 dual NovaCharge CT4021 electric vehicle charging station at the Orange County/University of Florida Cooperative Extension Center. The charging station is considered a “smart” charger connected to a central network operated by a third party that monitors the number of charging sessions, session start and end times, the electricity usage, greenhouse gases saved and other pertinent data. During the six months of operation of the charging station there have been 52 unique driver users of the charging station; a total of 532.2258 kg of greenhouse gas savings and 159.03 gallons of gasoline savings. Operation and Potential Relocation of the Orange County Climate Change Education Center: The Climate Change Education Center, originally located within the Orange County Convention Center, served as a central place to inform and educate commercial and residential sectors of environmental, health, and economic benefits of renewable energy, energy efficiency, and greenhouse gas emission reductions. Grant funds were used to pay for the rent required to maintain a lease at the Convention Center, conduct five educational workshops, and for planned upgrades to the Center displays highlighting a number of energy efficiency and renewable energy projects implemented at the Orange County Convention Center and Downtown Orange County. An initial design concept for an upgraded Climate Change Education Center and educational displays was proposed. However, after the Convention Center determined the space occupied by the Climate Change Education Center; a feasibility study for relocation to the proposed area was conducted in October 2013. In December 2013, it was determined that the desired location of the for the Climate Change Education Center at the Orange County Extension Education Center provided too many construction challenges for relocation with too many building retrofits and access problems, including lack of access for loading and unloading exhibits as well as roof drainage relocations and sewer service connection issues. Another suitable location for relocating the Climate Change Education Center could not be located so the project was terminated. The Climate Change Education Center is no longer in existence in Orange County and has been eliminated. Grant funds were used to pay for marketing services for a state wide marketing program including solar & other renewable energy technologies for rebranding and developing marketing materials including web site design and updating. A website was maintained and updated the www.PowerUpGreenEnergy.com website (no longer in service). Sustainability Training for the Hospitality Industry and Major Sectors: To introduce energy efficiency and renewable energy concepts to the hospitality industry, Orange County partnered with a hospitality college that held seminars to educate students in sustainability best practices that would influence the industry as a whole as students take jobs around the U.S. and other parts of the world. Orange County completed five of the originally proposed six education seminars. Seminar topics included: driving sustainable behavior change through community based social marketing; green team programs; urban sustainability planning; and Florida Energy Code workshops for building inspectors. In partnership with Rollins College, a sixth seminar focused on transit-oriented development was explored, but was not conducted due to extended renovations at the proposed on-campus venue. Green Job Training Development: To promote green industry development and on-the-job training in occupations that encourage energy efficiency and resource reduction, Orange County piloted an ENERGY STAR training and apprenticeship program with students from the University of Central Florida; three students applied for the program; one student completed the training and received their certification as an ENERGY STAR specialist; three of the five buildings assessed received ENERGY STAR Ratings.
In this work, we present a relativistic quantum embedding formalism capable of variationally treating relativistic effects, including scalar-relativity and spin–orbit coupling. We extend density functional theory (DFT)-in-DFT projection-based quantum embedding to a relativistic two-component formalism, where the full spin magnetization vector form is retained throughout the embedding treatment. To benchmark various relativistic embedding schemes, spin–orbit splitting of the nominally t 2g valence manifold of W(CO) 6 , exchange coupling of [(H 3 N) 4 Cr(OH) 2 Cr(NH 3 ) 4 ] 4+ , and the dissociation potential curve of WF 6 are investigated. The relativistic embedding formalism introduced in this work is well suited for efficient modeling of open-shell systems containing late transition metal, lanthanide, and actinide molecular complexes.
In recent years, the cost of small wind turbines for homes, farms, and small businesses has decreased dramatically thanks to advances in American technology made possible by research and development support from the U.S. Department of Energy. But further reductions are needed to realize the gigawatt-scale potential of distributed wind energy to help electrify rural America, reduce carbon emissions, and create jobs. Currently, for residential- and farm-scale wind turbines with direct-drive, permanent-magnet alternators, the alternator is the highest-cost component of the wind turbine (excluding the tower). The Bergey Windpower Excel 15 wind turbine incorporates advanced technology in its rotor and controls and will soon incorporate advanced power electronics - but its alternator is based on technology that is more than a decade old. To help reduce capital expenditures of the Excel 15 wind turbine, Bergey Windpower is developing an advanced, lower- cost, permanent-magnet alternator.
The goal of the Assessment of Heavy-Duty Fueling Methods and Components project was to comprehensively assess heavy-duty (HD) fuel cell electric vehicle fueling protocols and their effects on techno-economic assessments (TEA) and total cost of ownership (TCO). The project leveraged and built upon ongoing international HD fueling protocols and fueling component development activities to deliver component performance assessments, modeling tools and methods evaluations, TEA of industry-selected protocol structures, and experimental validations of the strategies at the station scale. The effects of the protocols on the fueling times, station costs, and TCO were explored. Fueling time, which was influenced by temperature and protocol selection, had a large impact on the station cost due to component sizing and satisfying hourly demand. As the fleet size increased, the station cost was shown to exponentially decrease by achieving economies of scale. Technology year and fuel economy were the largest contributors to the TCO; however, the choice of fueling protocol had a minor impact on the TCO.
ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.
A statistical model is formulated to compute exotic rotational correlations that arise as inertial frames and causal structure emerge on large scales from entangled Planck scale quantum systems. Noncommutative quantum dynamics are represented by random transverse displacements that respect causal symmetry. Entanglement is represented by covariance of these displacements in Planck scale intervals defined by future null cones of events on an observer's world line. Light that propagates in a nonradial direction inherits a projected component of the exotic rotational correlation that accumulates as a random walk in phase. A calculation of the projection and accumulation leads to exact predictions for statistical properties of exotic Planck scale correlations in an interferometer of any configuration. The cross-covariance for two nearly co-located interferometers is shown to depart only slightly from the autocovariance. Specific examples are computed for configurations that approximate realistic experiments, and show that the model can be rigorously tested.
Numerous cutting-edge scientific technologies originate at the laboratory scale, but transitioning them to practical industry applications is a formidable challenge. Traditional pilot projects at intermediate scales are costly and time-consuming. An alternative, the pilot-scale model, relies on high-fidelity numerical simulations, but even these simulations can be computationally prohibitive at larger scales. To overcome these limitations, we propose a scalable, physics-constrained reduced order model (ROM) method. The ROM identifies critical physics modes from small-scale unit components, projecting governing equations onto these modes to create a reduced model that retains essential physics details. We also employ Discontinuous Galerkin Domain Decomposition (DG-DD) to apply ROM to unit components and interfaces, enabling the construction of large-scale global systems without data at such large scales. Here this method is demonstrated on the Poisson and Stokes flow equations, showing that it can solve equations about 15–40 times faster with only ~1% relative error. Furthermore, ROM takes one order of magnitude less memory than the full order model, enabling larger scale predictions at a given memory limitation.
This paper discusses the hardware and software components of the Grid Computing system used to implement the Locus Algorithm to identify optimum pointings for differential photometry of 61,662,376 stars and 23,799 quasars. The scale of the data, together with initial operational assessments demanded a High Performance Computing (HPC) system to complete the data analysis. Grid computing was chosen as the HPC solution as the optimum choice available within this project. The physical and logical structure of the National Grid computing Infrastructure informed the approach that was taken. That approach was one of layered separation of the different project components to enable maximum flexibility and extensibility.
Abstract. In recent decades, three major volcanic eruptions of different intensity have occurred (Mount Agung in 1963, El Chichón in 1982 and Mount Pinatubo in 1991), with reported climate impacts on seasonal to decadal timescales that could have been potentially predicted with accurate and timely estimates of the associated stratospheric aerosol loads. The Decadal Climate Prediction Project component C (DCPP-C) includes a protocol to investigate the impact of volcanic aerosols on the climate experienced during the years that followed those eruptions through the use of decadal predictions. The interest of conducting this exercise with climate predictions is that, thanks to the initialisation, they start from the observed climate conditions at the time of the eruptions, which helps to disentangle the climatic changes due to the initial conditions and internal variability from the volcanic forcing. The protocol consists of repeating the retrospective predictions that are initialised just before the last three major volcanic eruptions but without the inclusion of their volcanic forcing, which are then compared with the baseline predictions to disentangle the simulated volcanic effects upon climate. We present the results from six Coupled Model Intercomparison Project Phase 6 (CMIP6) decadal prediction systems. These systems show strong agreement in predicting the well-known post-volcanic radiative effects following the three eruptions, which induce a long-lasting cooling in the ocean. Furthermore, the multi-model multi-eruption composite is consistent with previous work reporting an acceleration of the Northern Hemisphere polar vortex and the development of El Niño conditions the first year after the eruption, followed by a strengthening of the Atlantic Meridional Overturning Circulation the subsequent years. Our analysis reveals that all these dynamical responses are both model- and eruption-dependent. A novel aspect of this study is that we also assess whether the volcanic forcing improves the realism of the predictions. Comparing the predicted surface temperature anomalies in the two sets of hindcasts (with and without volcanic forcing) with observations we show that, overall, including the volcanic forcing results in better predictions. The volcanic forcing is found to be particularly relevant for reproducing the observed sea surface temperature (SST) variability in the North Atlantic Ocean following the 1991 eruption of Pinatubo.
Final technical report summarizes the program progress and technical accomplishments of the Laser Direct Manufacturing (LDM) for Nuclear Power Components project. A series of experiments varying build process parameters (scan speed and laser power) were conducted at the outset to establish the optimal build conditions for each of the alloys. Fabrication was completed in collaboration with Quad City Manufacturing Laboratory (QCML). The density of all sample specimens was measured and compared to literature values. Optimal build process conditions giving fabricated part densities close to literature values were chosen for making mechanical test coupons. Test coupons whose principal axis is on the x-y plane (perpendicular to build direction) and on the z plane (parallel to build direction) were built and tested as part of the experimental build matrix to understand the impact of the anisotropic nature of the process.. Investigations are described 316L SS, Inconel 600, 718 and 800 and oxide dispersion strengthed 316L SS (Yttria) alloys.
Body-Centered Cubic (BCC) metals exhibit anomalous mechanical properties such as twinning/anti-twinning and tension/compression asymmetry, which are attributed to asymmetric behavior of screw dislocations. Unlike Face-Centered Cubic (FCC) metals, the Critical Resolved Shear Stress (CRSS) of BCC metals deviates from the Schmid law. Here, we use a mesoscale modeling approach called Phase Field Dislocation Dynamics (PFDD) to understand the critical factors that control this non-Schmid behavior and reproduce atomistic predictions of the CRSS (Peierls stress). All inputs to the PFDD model are obtained from Molecular Statics (MS) simulations. Multiple pathways for modeling the non-Schmid behavior are investigated by incorporating the representative dislocation properties into different energy terms in the PFDD model. One way to understand non-Schmid behavior is to incorporate stress components projected on inclined planes into the external energy term within PFDD. Alternatively, we propose that non-Schmid behavior can also be accounted for by considering the variation of the {110} unstable stacking fault energy and the dislocation core width as a function of the applied tensorial stress field. The CRSS predicted using PFDD modeling is in excellent agreement with MS predictions.
Monsoons affect the economy, agriculture, and human health of two thirds of the world’s population. Therefore, predicting variations in monsoon precipitation is societally important. We explore the ability of climate models from the sixth phase of the Climate Model Intercomparison Project to predict summer monsoon precipitation variability by using hindcasts from the Decadal Climate Prediction Project (Component A). The multi-model ensemble-mean shows significant skill at predicting summer monsoon precipitation from one year to 6–9 years ahead. However, this skill is dependent on the model, monsoon domain, and lead-time. In general, the skill of the multi-model ensemble-mean prediction is low in year 1 but increases for longer-lead times and is largely consistent with externally forced changes. The best captured region is northern Africa for the 2–5 and 6–9 year forecast lead times. In contrast, there is no significant skill using the ensemble-mean over East and South Asia and, furthermore, there is significant spread in skill among models for these domains. By sub-sampling the ensemble we show that the difference in skill between models is tied to the simulation of the externally forced response over East and South Asia, with models with a more skilful forced response capable of better predictions. A further contribution is from skilful prediction of Pacific Ocean temperatures for the South Asian summer monsoon at longer lead-times. Therefore, these results indicate that predictions of the East and South Asian monsoons could be significantly improved.
Multi-Agent Consensus Equilibrium (MACE) formulates an inverse imaging problem as a balance among multiple update agents such as data-fitting terms and denoisers. However, each such agent operates on a separate copy of the full image, leading to redundant memory use and slow convergence when each agent affects only a small subset of the full image. In this article, we extend MACE to Projected Multi-Agent Consensus Equilibrium (PMACE), in which each agent updates only a projected component of the full image, thus greatly reducing memory use for some applications. We describe PMACE in terms of an equilibrium problem and an equivalent fixed-point problem and show that in most cases the PMACE equilibrium is not the solution of an optimization problem. To demonstrate the value of PMACE, we apply it to the problem of ptychography, in which a sample is reconstructed from the diffraction patterns resulting from coherent X-ray illumination at multiple overlapping spots. In our PMACE formulation, each spot corresponds to a separate data-fitting agent, with the final solution found as an equilibrium among all the agents. In conclusion, our results demonstrate that the PMACE reconstruction algorithm generates more accurate reconstructions at a lower computational cost than existing ptychography algorithms when the spots are sparsely sampled.
The online monitoring of active components project, under the Advanced Instrumentation, Information, and Control Technologies Pathway of the Light Water Reactor Sustainability Program, researched diagnostic and prognostic models for alternating current induction motors (IM). Idaho National Laboratory (INL) worked with the Electric Power Research Institute (EPRI) to augment and revise the fault signatures previously implemented in the Asset Fault Signature Database of EPRI’s Fleet Wide Prognostic and Health Management (FW PHM) Suite software. Induction Motor diagnostic models were researched using the experimental data collected by Idaho State University. Prognostic models were explored in the set of literature and through a limited experiment with 40HP to seek the Remaining Useful Life Database of the FW PHM Suite.
The U.S. Department of Energy, Office of Nuclear Energy is laying the groundwork for implementing interim storage of spent nuclear fuel (SNF) pursuant to the Administration's Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste. This effort includes planning to address technical and logistical aspects of transporting SNF to an interim storage facility. A key project component is the development and utilization of a decision-support tool to evaluate transportation routing options and emergency preparedness. START (Stakeholder Tool for Assessing Radioactive Transportation) is a web-based application that utilizes geographic information systems (GIS) technology to represent transportation network operations as well as proximate features, such as tribal lands, emergency response capability, schools and environmentally-sensitive areas. Modes and routes between shipment origins and destinations designated by the user can be evaluated according to multiple routing criteria, and users can impose constraints that require the route to pass through or avoid specified locations. Considerable information is produced describing route efficiency, safety, security and environmental exposure that enable stakeholders to understand the implications of alternative route options. This paper describes START's capabilities and illustrates its use. (authors)