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At least 163 records · Page 9

Elucidating bonding preferences in tetrakis(imido)uranate(VI) dianions

Actinyl species, [AnO 2 ] 2+ , are well-known derivatives of the f-block because of their natural occurrence and essential roles in the nuclear fuel cycle. Along with their nitrogen analogues, [An(NR) 2 ] 2+ , actinyls are characterized by their two strong trans-An–element multiple bonds, a consequence of the inverse trans influence. We report that these robust bonds can be weakened significantly by increasing the number of multiple bonds to uranium, as demonstrated by a family of uranium(VI) dianions bearing four U–N multiple bonds, [M] 2 [U(NR) 4 ] (M = Li, Na, K, Rb, Cs). Their geometry is dictated by cation coordination and sterics rather than by electronic factors. Multiple bond weakening by the addition of strong π donors has the potential for applications in the processing of high-valent actinyls, commonly found in environmental pollutants and spent nuclear fuels.

Anderson, Nickolas H.↗

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required to represent the ejected foam. The exponents were evaluated by least squares method from experimental data. The equation is used and it can represent multiple factors in other problems as well; for example, evaluation of fatigue life, creep life, fracture toughness, and structural fracture, as well as optimization functions. The software is rather simplistic. Required inputs are initial value, final value, and an exponent for each factor. The number of factors is open-ended. The value is updated as each factor is evaluated. If a factor goes to zero, the previous value is used in the evaluation.

Abumeri, Galib H.↗

Hybrid super homogenization and discontinuity factor method for continuous finite element diffusion

This paper presents a novel homogenization equivalence technique aiming to simultaneously leveragethe simplicity of the Super Homogenization (SPH) method to reproduce reference reaction rates andthe ability to preserve reference leakage rates at desired surfaces through Discontinuity Factors (DF).The need for this new class of methods arises from the inability of the current state-of-the-art SPH technology to properly reproduce the reactor multiplication factor for problems with significant leakage. This work shows that this defect lies in the use of normalization factors in the SPH algorithm: while they are necessary with purely reflecting problems to ensure uniqueness of the solution, they introduce homogenization inconsistencies if at least one vacuum boundary condition is present. Two solutions to this problem are presented in this work: (i) to simply remove the normalization factor or (ii) to introduce additional degrees of freedom in the form of DFs in such a way that the normalization factors can still constrain the problem. While the former clearly offers unrivaled simplicity and can lead to very satisfactory results for leakage-dominated cores or if spatial restriction of the SPH regions is applied – as demonstrated for the High Temperature Test Reactor, the latter is more robust and does not require to scale the fission terms with the reference eigenvalue.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

CORSICA modelling of ITER hybrid operation scenarios

The hybrid operating mode observed in several tokamaks is characterized by further enhancement over the high plasma confinement (H-mode) associated with reduced magneto-hydro-dynamic (MHD) instabilities linked to a stationary flat safety factor ($q$ ) profile in the core region. The proposed ITER hybrid operation is currently aiming at operating for a long burn duration (>1000 s) with a moderate fusion power multiplication factor, $Q$ , of at least 5. This paper presents here candidate ITER hybrid operation scenarios developed using a free-boundary transport modelling code, CORSICA, taking all relevant physics and engineering constraints into account. The ITER hybrid operation scenarios have been developed by tailoring the 15 MA baseline ITER inductive H-mode scenario. Accessible operation conditions for ITER hybrid operation and achievable range of plasma parameters have been investigated considering uncertainties on the plasma confinement and transport. ITER operation capability for avoiding the poloidal field coil current, field and force limits has been examined by applying different current ramp rates, flat-top plasma currents and densities, and pre-magnetization of the poloidal field coils. Various combinations of heating and current drive (H&CD) schemes have been applied to study several physics issues, such as the plasma current density profile tailoring, enhancement of the plasma energy confinement and fusion power generation. A parameterized edge pedestal model based on EPED1 added to the CORSICA code has been applied to hybrid operation scenarios. Finally, fully self-consistent free-boundary transport simulations have been performed to provide information on the poloidal field coil voltage demands and to study the controllability with the ITER controllers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

LANDSCAPE MANAGEMENT FOR SUSTAINABLE SUPPLIES OF BIOENERGY FEEDSTOCK AND ENHANCED SOIL QUALITY

Agriculture can simultaneously address global food, feed, fiber, and energy challenges provided our soil, water, and air resources are not compromised in doing so. As we embark on the 19th Triennial Conference of the International Soil and Tillage Research Organization (ISTRO), I am pleased to proclaim that our members are well poised to lead these endeavors because of our comprehensive understanding of soil, water, agricultural and bio-systems engineering processes. The concept of landscape management, as an approach for integrating multiple bioenergy feedstock sources, including biomass residuals, into current crop production systems, is used as the focal point to show how these ever-increasing global challenges can be met in a sustainable manner. Starting with the 2005 Billion Ton Study (BTS) goals, research and technology transfer activities leading to the 2011 U.S. Department of Energy (DOE) Revised Billion Ton Study (BT2) and development of a residue management tool to guide sustainable crop residue harvest will be reviewed. Multi-location USDA-Agricultural Research Service (ARS) Renewable Energy Assessment Project (REAP) team research and on-going partnerships between public and private sector groups will be shared to show the development of landscape management strategies that can simultaneously address the multiple factors that must be balanced to meet the global challenges. Effective landscape management strategies recognize the importance of nature’s diversity and strive to emulate those conditions to sustain multiple critical ecosystem services. To illustrate those services, the soil quality impact of harvesting crop residues are presented to show how careful, comprehensive monitoring of soil, water and air resources must be an integral part of sustainable bioenergy feedstock production systems. Preliminary analyses suggest that to sustain soil resources within the U.S. Corn Belt, corn (Zea mays L.) stover should not be harvested if average grain yields are less than 11 Mg ha-1 (175 bu ac-1) unless more intensive landscape management practices are implemented. Furthermore, although non-irrigated corn grain yields east and west of the primary Corn Belt may not consistently achieve the 11 Mg ha-1 yield levels, corn can still be part of an overall landscape approach for sustainable feedstock production. Another option for producers with consistently high yields (> 12.6 Mg ha-1 or 200 bu ac-1) that may enable them to sustainably harvest even more stover is to decrease their tillage intensity which will reduce fuel use, preserve rhizosphere carbon, and/or help maintain soil structure and soil quality benefits often attributed to no-till production systems. In conclusion, I challenge all ISTRO scientists to critically ask if your research is contributing to improved soil and crop management strategies that effectively address the complexity associated with sustainable food, feed, fiber and fuel production throughout the world.

09 BIOMASS FUELS↗

Neutronics and activation analysis of lithium-based ternary alloys in IFE blankets

Here we report that an attractive feature of using liquid lithium as the breeder and coolant in fusion blankets is that it has very high tritium solubility and results in very low levels of tritium permeation throughout the facility infrastructure. However, lithium metal vigorously reacts with air and water and presents plant safety concerns. The Lawrence Livermore National Laboratory is carrying an effort to develop a lithium-based alloy that maintains the beneficial properties of lithium (e.g. high tritium breeding and solubility) and at the same time reduces overall flammability concerns. This study evaluates the neutronics performance of lithium-based alloys in the blanket of an inertial fusion energy chamber in order to inform such development. 3-D Monte Carlo calculations were performed to evaluate two main neutronics performance parameters for the blanket: tritium breeding ratio (TBR), and the fusion energy multiplication factor (EMF). It was found that elements that exhibit low absorption cross sections and higher q-values such as lead, tin, and strontium, perform well with those that have high neutron multiplication such as lead and bismuth. These elements meet TBR constrains ranging from 1.02 to 1.1. However, most alloys do not reach EMFs greater than 1.15. Additionally, it was found that enriching lithium significantly increases the TBR and decreases the minimum lithium concentration by more than 60%. The amount of enrichment depends on how much total lithium is in the alloy to begin with. Alloys that performed well in the TBR and EMF calculations were considered for activation analysis. Activation simulations were executed with 50 years of irradiation and 300 years of cooling. It was discovered that bismuth is a poor choice due to achieving the highest decay heat, contact dose rates, and accident doses. In addition, it does not meet the waste disposal ratings (WDR). Some of the activation results for alloys with tin, zinc, and gallium were in the higher end and should be considered secondary to elements such as strontium and barium that had overall better results. The results of this study along with other considerations such as thermodynamics, and chemical reactivity will help down select a preferred lithium ternary alloy.

36 MATERIALS SCIENCE↗

BOSS quasar outflows traced by C iv

ABSTRACT We investigate possible factors that drive fast quasar outflows using a sample of 39 249 quasars at median redshift 〈z〉 ≈ 2.17. Unique to this study, the quasar redshifts are re-measured based on the Mg ii emission line, and explore unprecedented outflow velocities (>6000 km s−1), while maintaining statistical significance. We measure reliable C iv blueshifts for 1178 quasars with velocities >2500 km s−1. From those, 255(13) quasars have blueshifts above 4000(6000) km s−1, with the highest C iv velocity ≈7000 km s−1. Several correlations are observed, where higher C iv blueshifts in general are in quasars with broader, weaker C iv emission profiles, weak He ii emission, larger Eddington ratios, and bluer ultraviolet (UV) continuum slope across the rest-frame UV to near-infrared. Analysis reveals two primary factors contributing to faster outflows: higher Eddington ratios, and softer far-UV continuum (hν >24.6 eV). We find supporting evidence that radiative line driving may generate extreme outflow velocities, influenced by multiple factors as suggested by the aforementioned correlations. This evidence highlights the importance of considering a multidimensional parameter space in future studies when analyzing large C iv blueshifts to determine the fundamental causes of outflows.

Gillette, Jarred (ORCID:0000000185284839)↗

Uncertainty Quantification in Vibro-Acoustics Diagnosis of Alkali-Silica Reaction Degradation in Medium-Sized Concrete Samples

The objectives of this ongoing research project focus on health monitoring and data analytics of concrete slabs containing reactive aggregates and thus subjected to degradation due to alkali-silica reaction (ASR). A controlled concrete slab with four pockets of reactive aggregates (pure silica, wells, placitas, and spratt) was cast at Vanderbilt University and cured in representative conditions to accelerate degradation due to ASR. A set of four concrete samples were also cast and cured at the University of Alabama for ASR testing. Of these four samples, two slabs contained reactive aggregates while the other two had the non-reactive aggregate counterparts mixed throughout the samples. Vibro-acoustic testing was used on these slabs to locate ASR damage within the reactive samples. Vibro-acoustic modulation (VAM) is a vibration-based NDE method that utilizes signatures of nonlinear dynamic interactions on contact surfaces of crack or delamination damage to detect and localize the damage. VAM analysis was conducted on both the Vanderbilt and Alabama samples using multiple variables for damage detection and localization. The results from the data analysis of the vibro-acoustic testing on concrete slabs cured at Vanderbilt University and the University of Alabama are discussed in detail in this report. Results for damage localization are dependent on multiple variables used in the vibro-acoustic modulation experiments. A major focus of this report is to quantify the uncertainty in the diagnosis due to multiple factors and uncertainty sources. The uncertainty quantification methodology presented in this report was applied to VAM-based diagnosis and prognosis. However, the methodology is general, and is capable of being applied to multiple technique that collect spatially distributed data. Future work needs to investigate the incorporation of uncertainty quantification in developing a robust Prognostics and Health Management framework. Digital image correlation is a three-dimensional, full-field, optical NDE technique to measure contour, deformation, vibration, and strain. The application of the digital image correlation technique to study ASR-related degradation on a large concrete specimen at the University of Tennessee is discussed and observations are presented in this report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Postoperative Stereotactic Radiosurgery Without Whole-Brain Radiation Therapy for Brain Metastases: Potential Role of Preoperative Tumor Size

Purpose: Radiation therapy following resection of a brain metastasis increases the probability of disease control at the surgical site. We analyzed our experience with postoperative stereotactic radiosurgery (SRS) as an alternative to whole-brain radiotherapy (WBRT), with an emphasis on identifying factors that might predict intracranial disease control and overall survival (OS). Methods and Materials: We retrospectively reviewed all patients through December 2008, who, after surgical resection, underwent SRS to the tumor bed, deferring WBRT. Multiple factors were analyzed for time to intracranial recurrence (ICR), whether local recurrence (LR) at the surgical bed or “distant” recurrence (DR) in the brain, for time to WBRT, and for OS. Results: A total of 49 lesions in 47 patients were treated with postoperative SRS. With median follow-up of 9.3 months (range, 1.1-61.4 months), local control rates at the resection cavity were 85.5% at 1 year and 66.9% at 2 years. OS rates at 1 and 2 years were 52.5% and 31.7%, respectively. On univariate analysis (preoperative) tumors larger than 3.0 cm exhibited a significantly shorter time to LR. At a cutoff of 2.0 cm, larger tumors resulted in significantly shorter times not only for LR but also for DR, ICR, and salvage WBRT. While multivariate Cox regressions showed preoperative size to be significant for times to DR, ICR, and WBRT, in similar multivariate analysis for OS, only the graded prognostic assessment proved to be significant. However, the number of intracranial metastases at presentation was not significantly associated with OS nor with other outcome variables. Conclusions: Larger tumor size was associated with shorter time to recurrence and with shorter time to salvage WBRT; however, larger tumors were not associated with decrements in OS, suggesting successful salvage. SRS to the tumor bed without WBRT is an effective treatment for resected brain metastases, achieving local control particularly for tumors up to 3.0 cm diameter.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Wind Turbine Sound Setbacks and Supply Curves: Ordinances and Extrapolated Trends, 110 Hub Height, 130 Rotor Diameter

This dataset provides a comprehensive set of wind turbine sound setbacks from every residential structure in the contiguous United States (CONUS). A sound setback is defined as the minimum required distance between a residential structure and a hypothetical turbine installation site to ensure that modeled sound levels received at the residence do not exceed local sound ordinances, which are commonly expressed in A-weighted decibels (dBA). Therefore, sound setbacks are a local spatial assessment combining multiple factors, including the sound pressure curve as a function of the observer location (distance and direction) relative to the turbine, local sound regulations, and the geographical distribution of residential structures. The dataset is organized into multiple scenario-based products, detailed as follows: 1. Existing and extrapolated sound setbacks. An existing scenario characterizes sound setbacks only in states or counties that have implemented sound regulations as of 2022. The extrapolated scenarios extend a constant sound threshold to counties that lack explicit sound regulations, with thresholds ranging from 35 to 60 dBA, in 5-dBA increments reflecting the variation observed in current sound ordinances. 2. Sound setbacks in directional and worst scenarios. The directional scenario accounts for the distance and orientation of residential structures relative to a hypothetical turbine location, utilizing the turbine's sound emissions in that specific direction. In contrast, the worst scenario takes loudest sound level at each distance step from the turbine, irrespective of directional considerations, which aligns with current industry practice. 3. Supply curves for Open and Reference Access scenarios. This dataset includes supply curves generated by the reV model, which integrates each of the above sound setbacks into both Open and Reference siting scenarios. In addition, two Open and Reference baselines scenarios were included which do not consider sound setbacks for comparative analysis. All sound setback data are stored in TIF files, with partial maps of the data provided in PNG format. The values in the sound setback raster range from 0 to 1, representing the fraction of developable land within a 90 meter by 90 meter pixel due to sound ordinances. A value of 0 indicates areas where wind energy development is prohibited, while a value of 1 signifies areas fully permissible. The wind turbine parameters used in the sound modeling are based on the land-based turbine from International Energy Agency (IEA), featuring a rated electrical power of 3.4 MW, a rotor diameter of 130 meters, and a hub height of 110 meters. The atmospheric conditions, including wind speed/direction, turbulence, air temperature, relative humidity, and air pressure, that drive the sound generation are obtained from the WIND Toolkit dataset.

Array↗

Exploring the determinants of organic matter bioavailability through substrate-explicit thermodynamic modeling

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations in previous studies, these assumptions may not be universally valid because OM degradation is a complex process governed by multiple factors. To identify key drivers of OM respiration, we performed a comprehensive analysis of diverse river systems using Fourier-transform ion cyclotron resonance mass spectrometry OM data and associated respiration measurements collected by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. In support of our argument, we found that the incorporation of all compounds detected in the samples into the SXTM resulted in a poor correlation between the predicted and measured respiration rates. The data-model consistency was significantly improved by the selective use of a small subset (i.e., only about 5%) of organic compounds identified using an optimization method. Through a subsequent comparative analysis of the subset of compounds (which we presume as bioavailable) against the full set of compounds, we identified three major traits that potentially determine OM bioavailability, including: (1) thermodynamic favorability of aerobic respiration, (2) the number of C atoms contained in compounds, and (2) carbon/nitrogen (C/N) ratio. We found that all three factors serve as “filters” in that the compounds with undesirable properties in any of these traits are strictly excluded from the bioavailable fraction. This work highlights the importance of accounting for the complex interplay among multiple key traits to increase the predictive power of biogeochemical and ecosystem models.

59 BASIC BIOLOGICAL SCIENCES↗

Best Practices for Smart Grid-Interactive Efficient Building Ready Performance Contracts

Grid-interactive efficient building (GEB) measures reduce costs and optimize energy use for additional grid services by coordinating building energy loads and providing continuous demand management. Incorporating GEB energy conservation measures (ECMs) in performance contracts is reliant upon multiple factors. These factors include site selection with utility tariffs and incentives favorable to GEB, the identification of GEB as a priority in the initial stages of the contracting process, integration of GEB within comprehensive performance contracts with multiple other ECMs, and careful consideration of GEB measurement and verification (M&V) for energy savings performance contracts (ESPCs) and performance assurance for utility energy service contracts (UESCs).

building energy loads↗

Analysis and Burnup Modeling of the GEM*STAR Accelerator-Driven System

The purpose of this paper is to evaluate the neutronics and fuel burnup of the GEM*STAR accelerator-driven reactor design. The GEM*STAR design uses a molten salt fuel, with graphite moderation in a subcritical configuration with supplemental neutrons provided by an acceleratordriven proton spallation source. This allows for very safe operation since no criticality accidents are possible. A continuous extraction of spent fuel and addition of fresh fuel allows for the reactor to run at an equilibrium state of power and isotopic concentrations. Further, the liquid fuel and subcritical nature allow for higher burnup and more flexible fueling options. In previous analysis of the reactor, several simplifying assumptions were made about the neutronics modeling. In this study, these assumptions are eliminated, and a more detailed study is performed using MCNP6, Monteburns, and CINDER90 for neutronics and burnup calculation. Although there are some differences between the old and new analyses, equilibrium isotopic concentrations are within 10%, while electric multiplication factors are within 20%. Burnup analysis shows that the approach to equilibrium takes approximately two years for natural uranium fuel. By decreasing the fuel feed rate, the burnup can be increased at the cost of slightly lower electric multiplication. The performance of several feed materials are examined including natural uranium, LWR spent fuel and plutonium.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Estimating List-Mode Data Sensitivities to Nuclear Data with MCNP6

Nuclear data are a vital component of predictive simulations used in applications like experiment design, stockpile stewardship, nuclear nonproliferation/safeguards, health physics, and criticality safety. A singular simulation requires the coalescence of different areas of nuclear data such as cross sections, angular distributions, and energy distributions of emitted neutrons for different materials and energy ranges. Improving nuclear data and thus reducing the uncertainty in simulated parameters could enable smaller, better-informed safety factors and ultimately reduce operational and procedural costs. There is a constant effort to garner a better understanding of the physical quantities represented by nuclear data through experiments. Integral experiment benchmarks use simulated and measured results to validate current nuclear data values. In the past, benchmarks primarily focused on the effective multiplication factor (k eff ); however, this limited scope has caused compensating errors and areas of nuclear data that lack validation. Compensating errors are inaccuracies in nuclear data that are obfuscated by cancellation when observing integrated values such as k eff . Diverse integral benchmark experiments that look for quantities of interest other than k eff and include multiple responses minimize the possibility of compensating errors and provides validation to areas of nuclear data previously lacking experimental validation. Benchmark experiments can be optimized during the design process to be highly dependent on specific areas of nuclear data. The dependence of a response in an experiment to a specific area/type of nuclear data is defined as sensitivity. A larger sensitivity means that nuclear data uncertainties will play a larger role in the response(s) resulting in larger bias. Currently, the sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®1 ) transport code are limited to responses of k eff and tallied values (e.g., flux, surface current). As a part of the EUCLID project, this work explores estimating list-mode nuclear data sensitivities that can be used to design experiments aimed to constrain and reduce compensating errors in nuclear data by focusing on responses other than k eff . Tallied values are ideal quantities that are estimated with detectors during experiments. List-mode data (a list of neutron collection times) are the direct output of detector systems in subcritical neutron noise experiments. Expanding MCNP sensitivity capabilities to include the sensitivity of responses estimated from list-mode data, such as the prompt neutron decay constant (α) and multiplicity estimates (S and D), enables more direct comparison of simulated and measured experimental quantities. Additionally, deterministic tools such as SENSMG are capable of obtaining sensitivities to a wide variety of responses; however, these tools cannot handle complex geometries due to the assumptions made in discretizing the phase-space variables of the Boltzman transport equation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An Evaluation of Energy Storage Options for Nuclear Power

Energy supply, distribution, and demand are continuing to evolve as new generation sources come online and new appliances are installed. A larger percentage of the United States (U.S.) energy mix is provided by variable energy sources such as wind and solar each year, and distributed generation is becoming more common. In parallel, an evolution in consumer products such as electrical vehicles, information technology devices for residential and industrial applications, and appliances is changing how energy is consumed. As a result of these trends, nuclear power plants (NPPs) are being called upon to operate more flexibly than ever before. Furthermore, advanced nuclear power plants (A-NPPs) might operate as part of an electricity system that looks very different than when the current NPP fleet was constructed. A-NPPs face the possibility that they will need to operate in an environment where flexibility (e.g., fast ramping) is more highly valued than stability (e.g., baseload generation for conventional demand curves). The current fleet of NPPs is struggling to remain economical in competitive markets in an era of historically low natural gas prices and renewable sources with very low marginal costs. These factors, overlaid with an ambiguous national policy related to nuclear energy and a decision-making context that struggles with multi-decade capital investments, raise key questions and present significant challenges to the economics of nuclear power in the evolving grid. Multiple factors could improve the economics of A-NPPs, including: (1) minimizing the need for active safety systems, (2) minimizing adoption of one-off reactor designs, (3) establishing policies that credit low carbon emitting technologies, and (4) integrating energy storage technologies that increase revenue and reduce costs through a combination of ancillary services, market hedging, and reduced costs via stable operation. This report focuses on Item (4), containing an overview, synthesis, and examination of energy storage options that could be integrated with nuclear generation. Figure 1 provides an overview of the 2015 energy mix by sector, which shows that NPPs are currently used exclusively for electricity generation that is ultimately consumed in the residential, commercial, and industrial sectors. Some areas for NPP energy growth in the future include power generation for electrified transportation and thermal generation for storage and industrial applications. Currently, most industrial thermal energy users combust fossil resources (i.e., coal or natural gas) to meet the energy needs of the processes, but heat from nuclear operations could also be used in certain specific applications.

25 ENERGY STORAGE↗

An Evaluation of Energy Storage Options for Nuclear Power

Energy supply, distribution, and demand are continuing to evolve as new generation sources come online and new appliances are installed. A larger percentage of the United States (U.S.) energy mix is provided by variable energy sources such as wind and solar each year, and distributed generation is becoming more common. In parallel, an evolution in consumer products such as electrical vehicles, information technology devices for residential and industrial applications, and appliances is changing how energy is consumed. As a result of these trends, nuclear power plants (NPPs) are being called upon to operate more flexibly than ever before. Furthermore, advanced nuclear power plants (A-NPPs) might operate as part of an electricity system that looks very different than when the current NPP fleet was constructed. A-NPPs face the possibility that they will need to operate in an environment where flexibility (e.g., fast ramping) is more highly valued than stability (e.g., baseload generation for conventional demand curves). The current fleet of NPPs is struggling to remain economical in competitive markets in an era of historically low natural gas prices and renewable sources with very low marginal costs. These factors, overlaid with an ambiguous national policy related to nuclear energy and a decision-making context that struggles with multi-decade capital investments, raise key questions and present significant challenges to the economics of nuclear power in the evolving grid. Multiple factors could improve the economics of A-NPPs, including: (1) minimizing the need for active safety systems, (2) minimizing adoption of one-off reactor designs, (3) establishing policies that credit low carbon emitting technologies, and (4) integrating energy storage technologies that increase revenue and reduce costs through a combination of ancillary services, market hedging, and reduced costs via stable operation. This report focuses on Item (4), containing an overview, synthesis, and examination of energy storage options that could be integrated with nuclear generation. Figure 1 provides an overview of the 2015 energy mix by sector, which shows that NPPs are currently used exclusively for electricity generation that is ultimately consumed in the residential, commercial, and industrial sectors. Some areas for NPP energy growth in the future include power generation for electrified transportation and thermal generation for storage and industrial applications. Currently, most industrial thermal energy users combust fossil resources (i.e., coal or natural gas) to meet the energy needs of the processes, but heat from nuclear operations could also be used in certain specific applications.

25 ENERGY STORAGE↗

Quantum Key Distribution Applicability to Smart Grid Cybersecurity Systems

To meet the increasing demand for electricity and to have a more reliable and resilient electric grid against conventional and extreme events, grid modernization is more crucial now than ever before. This will require the development and deployment of devices that provide advanced communication capabilities. The overall efficiency, reliability, and resilience of the smart grid will be inextricably linked to the exchange of information between these devices. Unfortunately, the increased information flow will increase the potential attack surface and introduce new vulnerabilities. While a smarter grid will depend critically on information flow, these benefits will be accrued only if that information can be protected. Nowadays, information is secured in smart grids primarily through cryptography. However, with the increasing number of sophisticated attacks as well as the increasing computational power, the security of the “classical” cryptographic algorithms is threatened. Quantum information science offers solutions to this problem, specifically quantum key distribution (QKD), which provides a means for the generation and secure distribution of symmetric cryptographic keys. The security of QKD stems ultimately from the very nature of quantum physics. In this paper, we investigate the applicability of QKD to the various smart grid sectors and specific use cases. We have identified 18 smart grid use cases of interest for QKD suitability together with 7 QKD factors used for the assessment of the various use cases. For each use case, the impact to security of the loss of confidentiality, integrity, and/or availability is specified. In addition, the suitability of QKD is assessed for each use case with respect to multiple factors.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Including Chi-Nu 235 U PFNS Experimental Data into an ENDF/B-VIII.1 Release Candidate Evaluation

This report documents an evaluation of 235 U prompt fission neutron spectra (PFNS) that is a release candidate for the upcoming U.S. nuclear data library, ENDF/B-VIII.1. This evaluation differs from its predecessor, ENDF/B-VIII.0, mainly by the inclusion of 235 U PFNS measured by the Chi-Nu team of LANL and LLNL. This data set is the first one that covers the 235 U PFNS for continuous incident-neutron energies of 1⁻20 MeV and outgoing-neutron energies from 10 keV⁻10 MeV with high precision. Previous data sets were either measured in a limited energy range or with less precision. Hence, these new Chi-Nu data provide decisive information for the evaluation. The resulting evaluated data correspond well to the new experimental PFNS. The evaluated PFNS also produce average mean energies and 239 Pu/ 235 U PFNS in agreement with associated Chi-Nu data. If one uses the new evaluated data to predict the neutron multiplication factor, k eff , of selected ICSBEP critical assemblies, the differences of simulated values compared to those using ENDF/B-VIII.0 is modest (less than 55 pcm). This difference in k eff can be easily accommodated by changes in the 235 U average prompt fission neutron multiplicity that is currently being re-evaluated. In addition to that, the new PFNS predict on average 235 U LLNL pulsed-sphere neutron-leakage spectra better than ENDF/B-VIIII.0 PFNS.

235U↗