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At least 433 records · Page 24

ecode - Electron Transport Algorithm Testing v. 1.0

ecode is a Monte Carlo code used for testing algorithms related to electron transport. The code can read basic physics parameters, such as energy-dependent stopping powers and screening parameters. The code permits simple planar geometries of slabs or cubes. Parallelization consists of domain replication, with work distributed at the start of the calculation and statistical results gathered at the end of the calculation. Some basic routines (such as input parsing, random number generation, and statistics processing) are shared with the Integrated Tiger Series codes. A variety of algorithms for uncertainty propagation are incorporated based on the stochastic collocation and stochastic Galerkin methods. These permit uncertainty only in the total and angular scattering cross sections. The code contains algorithms for simulating stochastic mixtures of two materials. The physics is approximate, ranging from mono-energetic and isotropic scattering to screened Rutherford angular scattering and Rutherford energy-loss scattering (simple electron transport models). No production of secondary particles is implemented, and no photon physics is implemented.

Franke, Brian C.↗

ARM Radiosondes for National Polar-Orbiting Operational Environmental Satellite System Preparatory Project Validation Field Campaign Report

This IOP has been a coordinated effort involving the U.S. Department of Energy (DOE) Atmospheric Radiation (ARM) Climate Research Facility, the University of Wisconsin (UW)-Madison, and the JPSS project to validate SNPP NOAA Unique Combined Atmospheric Processing System (NUCAPS) temperature and moisture sounding products from the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). In this arrangement, funding for radiosondes was provided by the JPSS project to ARM. These radiosondes were launched coincident with the SNPP satellite overpasses (OP) at four of the ARM field sites beginning in July 2012 and running through September 2017. Combined with other ARM data, an assessment of the radiosonde data quality was performed and post-processing corrections applied producing an ARM site Best Estimate (BE) product. The SNPP targeted radiosondes were integrated into the NOAA Products Validation System (NPROVS+) system, which collocated the radiosondes with satellite products (NOAA, National Aeronautics and Space Administration [NASA], European Organisation for the Exploitation of Meteorological Satellites [EUMETSAT], Geostationary Operational Environmental Satellite [GOES], Constellation Observing System for Meteorology, Ionosphere, and Climate [COSMIC]) and Numerical Weather Prediction (NWP forecasts for use in product assessment and algorithm development. This work was a fundamental, integral, and cost-effective part of the SNPP validation effort and provided critical accuracy assessments of the SNPP temperature and water vapor soundings.

54 ENVIRONMENTAL SCIENCES↗

Joint UAS-Balloon Activities (JUBA) Field Campaign Report

Using internal investment funds within Sandia National Laboratories’ (SNL) Division 6000, the Joint UAS-Balloon Activity (JUBA) was a collaborative exercise between SNL Organizations 6533 and 6913 (later 8863) to demonstrate simultaneous flights of tethered balloons and unmanned aerial systems (UAS) on the North Slope of Alaska. JUBA UAS and tethered balloon flights were conducted within the Restricted Airspace associated with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility third ARM Mobile Facility (AMF3) site at Oliktok Point, Alaska. The Restricted Airspace occupies a two-nautical-mile radius around Oliktok Point. JUBA was conducted at the Sandia Arctic Site, which is approximately 2 km east-southeast of the AMF3. JUBA activities occurred from 08/08/17 and 08/10/17. Atmospheric measurements from tethered balloons can occur for a long duration, but offer limited spatial variation. Measurements from UAS could offer increased spatial variability. To understand how balloon and UAS activities could occur together, JUBA activities included the following: Developing aviation safety plans for the simultaneous, collocated operation of tethered balloons and UAS Adapting tethered balloon-based fiber optic distributed temperature sensing (DTS) measurements to a UAS platform Creating solutions to technical challenges such as: Developing a motor system to match the fiber deployment rate with the ascent/descent rate of the UAS Evaluating methods of identifying the surface in the DTS temperature profile Correlating simultaneous balloon and UAS DTS temperature measurements Assessing the effects of a fiber optic rotary joint on the DTS temperature measurements Determining what UAS-based sensors provided the best calibration source for the DTS temperature data.

North Slope of Alaska, arctic processes, unmanned ↗

Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.

Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted ℓ 2 -norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Air Pollutant Emissions and Regulatory Implications of a Biorefinery Co-Processing Bio-Oil in a Petroleum Refinery: Preprint

Pyrolysis oil, often referred to as bio-oil when derived from biomass through a fast pyrolysis process, has attracted considerable attention because of the high carbonaceous matter and high heating value compared to the original biomass. Pyrolysis oil provides a viable link between the agriculture/forestry and (petro-) chemical industry. Utilizing existing fossil fuel infrastructure by introducing bio-oil in petroleum refineries to produce renewable hydrocarbon fuels (i.e., repurposing existing assets) is appealing due to its relatively low capital requirement. Our analysis examined the air pollutant emissions for a biorefinery utilizing an ex situ catalytic fast pyrolysis process to produce raw bio-oil, with a design capacity of 2,000 dry metric tons of biomass per day. Such a biorefinery is capable of providing sufficient bio-oil to a 4,200 barrels per day capacity of fluidized catalytic cracking unit if the bio-oil is co-processed at 5% (by volume) feed rate. This research is focused on understanding the potential air pollutant regulatory and permitting implications for a refinery co-processing 5% bio-oil with 95% vacuum gas oil in a fluidized catalytic cracking unit for two scenarios: the first case assumes that an ex situ biorefinery is collocated with a petroleum refinery, and the second one assumes that a petroleum refinery will receive bio-oil from a stand-alone biorefinery. We estimated the potential-to-emit values for 4 biorefinery and FCC sizes and assessed technically feasible emission control options that could help to avoid being subject to prevention of significant deterioration requirements due to petroleum refinery modifications to co-process bio-oil. This research fills gaps and overcomes barriers related to air permitting requirements for co-processing bio-oil in existing refineries for various stakeholders. The insights gained from this analysis can facilitate decision making and help expedite permitting processes for petroleum refineries, which seek opportunities to produce lower carbon fuels in their existing infrastructure.

09 BIOMASS FUELS↗

Air Pollutant Emissions and Regulatory Implications of a Biorefinery Co-Processing Bio-Oil in a Petroleum Refinery

Pyrolysis oil, often referred to as bio-oil when derived from biomass through a fast pyrolysis process, has attracted considerable attention because of the high carbonaceous matter and high heating value compared to the original biomass. Pyrolysis oil provides a viable link between the agriculture/forestry and (petro-) chemical industry. Utilizing existing fossil fuel infrastructure by introducing bio-oil in petroleum refineries to produce renewable hydrocarbon fuels (i.e., repurposing existing assets) is appealing due to its relatively low capital requirement. Our analysis examined the air pollutant emissions for a biorefinery utilizing an ex situ catalytic fast pyrolysis process to produce raw bio-oil, with a design capacity of 2,000 dry metric tons of biomass per day. Such a biorefinery is capable of providing sufficient bio-oil to a 4,200 barrels per day capacity of fluidized catalytic cracking unit if the bio-oil is co-processed at 5% (by volume) feed rate. This research is focused on understanding the potential air pollutant regulatory and permitting implications for a refinery co-processing 5% bio-oil with 95% vacuum gas oil in a fluidized catalytic cracking unit for two scenarios: the first case assumes that an ex situ biorefinery is collocated with a petroleum refinery, and the second one assumes that a petroleum refinery will receive bio-oil from a stand-alone biorefinery. We estimated the potential-to-emit values for 4 biorefinery and FCC sizes and assessed technically feasible emission control options that could help to avoid being subject to prevention of significant deterioration requirements due to petroleum refinery modifications to co-process bio-oil. This research fills gaps and overcomes barriers related to air permitting requirements for co-processing bio-oil in existing refineries for various stakeholders. The insights gained from this analysis can facilitate decision making and help expedite permitting processes for petroleum refineries, which seek opportunities to produce lower carbon fuels in their existing infrastructure.

09 BIOMASS FUELS↗

Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models

We use a conditional Karhunen-Lo` eve (KL) model to quantify and reduce uncertainty in a stochastic partial differential equation (SPDE) problem with partially-known space-dependent coefficient, Y (x). We assume that a small number of Y (x) measurements are available and model Y (x) with a KL expansion. We achieve reduction in uncertainty by conditioning the KL expansion coefficients on measurements. We consider two approaches for conditioning the KL expansion: In Approach 1, we condition the KL model first and then truncate it. In Approach 2, we first truncate the KL expansion and then condition it. We employ the conditional KL expansion together with Monte Carlo and sparse grid collocation methods to compute the moments of the solution of the SPDE problem. Uncertainty of the problem is further reduced by adaptively selecting additional observation locations using two active learning methods. Method 1 minimizes the variance of the PDE coefficient, while Method 2 minimizes the variance of the solution of the PDE. We demonstrate that conditioning leads to dimension reduction of the KL representation of Y (x). For a linear diffusion SPDE with uncertain log-normal coefficient, we show that Approach 1 provides a more accurate approximation of the conditional log-normal coefficient and solution of the SPDE than Approach 2 for the same number of random dimensions in a conditional KL expansion. Furthermore, Approach 2 provides a good estimate for the number of terms of the truncated KL expansion of the conditional field of Approach 1. Finally, we demonstrate that active learning based on Method 2 is more efficient for uncertainty reduction in the SPDE’s states (i.e., it leads to a larger reduction of the variance) than active learning using Method 2.

Conditioned Karhunen-Lo` eve expanion, machine lea↗

Vectoring into Potential Blind Geothermal Systems in the Granite Springs Valley Area, Western Nevada: Application of the Play Fairway Analysis at Multiple Scales

The Great Basin region of the western USA is capable of generating much greater amounts of geothermal energy than currently produced. Most geothermal resources in this region are blind, and thus the favorable characteristics for geothermal activity must be synthesized and methodologies developed to discover new commercial-grade systems. The geothermal play fairway concept involves integration of multiple parameters indicative of geothermal activity as a means of identifying promising areas for new development. In the Nevada play fairway project, nine geologic, geochemical, and geophysical parameters were initially synthesized to produce a new geothermal potential map of 96,000 km2. Granite Springs Valley in western Nevada is a particularly promising site selected for detailed study. It contains several favorable structural settings, including terminations of major Quaternary normal faults and fault intersections. Geologic, geophysical, and geochemical techniques were employed to define the most likely sites for high permeability and select drilling targets for temperature-gradient holes. Local and intermediate permeability models were revised to reflect results of detailed analyses and generate new detailed play fairway maps of the area. The most promising site lies in the northeastern part of the basin directly east of Adobe Flat, where the horse-tailing termination of a major normal fault (as revealed by new gravity data), opaline sinter deposits, warm shallow wells, and a low-resistivity anomaly are collocated. Geothermometry suggests a blind system with temperatures as high as ~130°C in this area. Four new temperature-gradient holes document temperatures of ~80°C at ~150 m depth. Lessons learned in the detailed studies of this project include: 1) initially identified sites commonly include multiple favorable settings at a finer scale; 2) promising sites in Cenozoic basins cannot be well defined without detailed geophysical surveys; and 3) play fairway analysis is critical at multiple scales, providing a means to select regional prospects as well as vectoring into drilling targets at individual sites.

15 GEOTHERMAL ENERGY↗

Discovery and analysis of a blind geothermal system in southeastern Gabbs Valley, Western Nevada

This study assessed the potential for high-temperature (≥130°C) blind geothermal systems in southeastern Gabbs Valley by employing a geothermal play fairway analysis approach involving integration of geologic, geophysical, and geochemical datasets. Gabbs Valley is a complex, tectonically active basin within the Great Basin on the boundary between the transtensional central Walker Lane domain and extensional Basin and Range province. The termination of the Petrified Springs fault, a major dextral fault of the central Walker Lane, in an array of normal faults indicates that southeastern Gabbs Valley occupies a displacement transfer zone, which is a favorable structural setting for geothermal activity. The displacement transfer zone is a structurally complicated area with many faults of varying geometries, kinematics, and ages. A substantial northwest-trending gravity high within the south-central part of southeastern Gabbs Valley is produced from offsets along concealed northwest-striking dextral-normal faults that intersect strands of north-northeast-to east-northeast-striking normal faults. This area of tightly spaced faults and fault intersections is a particularly favorable structural setting within the broader-scale displacement transfer zone. Multiple lines of direct and indirect evidence suggest the presence of a relatively high-temperature (≥130°C) blind geothermal system in this area, including collocated intersecting gravity gradients, magnetic-low, low-resistivity, and 2-m temperature anomaly. Potentially related, water samples from agricultural wells ~7 km northwest of the 2-m anomaly yield geothermometers indicating subsurface fluid temperatures of 130-140°C. Six temperature-gradient holes were drilled to target the extent of the shallow-temperature and geophysical anomalies to define the geothermal system in southeastern Gabbs Valley. Two wells contained high temperatures exceeding boiling with bottom-hole temperatures ii of 114.5°C and 124.9°C, respectively, and the remaining wells displayed elevated to background temperatures ranging from 79.2°C to 28.7°C. The observed temperature gradients for the two hottest drill holes necessitate drill-hole intercepts of convecting hydrothermal fluids. The 2-m survey is spatially and thermally consistent with the temperature-gradient holes and constrains the core of upflow at a shallow depth interval (<250m) to an area <0.5-1 km west-southwest of the hottest drill hole. The zone of inferred upwelling occupies the area corresponding to the center of the magnetic-low. This project has several significant implications. The newly discovered blind geothermal system in southeastern Gabbs Valley may be capable of supporting a binary-type geothermal power plant. This detailed study provides an initial validation of the play fairway approach to geothermal exploration. It also demonstrates both the broad applicability of the play fairway exploration strategy and the large untapped potential for commercial-grade blind geothermal systems in many of the basins in the Great Basin region.

15 GEOTHERMAL ENERGY↗

Summary of Phase 1 and Plans for Phase 2 of the Washington State Geothermal Play-Fairway Analysis

A geothermal play fairway is constituted by the collocation of heat, permeability, and saturated porosity in sufficient volume that provide adequate heat exchange at depths accessible by modern drilling technologies. The focus of Phase 1 of the Washington State play-fairway analysis (PFA) was to develop and apply a methodology to integrate detailed models of heat and permeability potential for each play (study area). The goal is to minimize risk associated with investments in geothermal exploration of greenfield projects by rigorously analyzing available data, applying favorability modeling concepts that have been successfully used at known geothermal systems, and addressing data quality and model sensitivity. The integrated results indicate locations where commercial geothermal potential is highest, based on available data. Here, these results also reveal where new data are needed to increase resolution and reduce uncertainty to minimize risk (work conducted in Phase 2), and thus successfully identify sites for exploration wells (in Phase 3).

geothermal favorability↗

Phyto-screening for Volatile Organic Compounds in a Clay-based Glacial Till at the Niagara Falls Storage Site, New York - 17372

The Niagara Falls Storage Site (NFSS) and associated vicinity properties (VPs) occupy approximately 607 hectares (1,500 acres) of the original 3,035-hectare (7,500-acre) Lake Ontario Ordnance Works (LOOW). The NFSS was used to store radioactive materials, residues and waste from uranium ore processing between 1944 and 1952. The waste-handling practices produced an array of groundwater impacts throughout the site. Although the groundwater at the NFSS is naturally high in total dissolved solids that preclude untreated consumption, the groundwater contaminant levels in some areas of the site are very high and may pose risk to a Construction Worker receptor, as well as limit the options for future site re-use. Volatile organic compound (VOC) impacted soil in the northern portion of the site has produced a groundwater plume with significant concentrations of tetrachloroethene (PCE) and associated daughter compounds. Active groundwater remediation is impractical due to the clayey soils, as evident from adjacent property owners who have unsuccessfully attempted active remediation of their VOC plumes. Consequently, the Buffalo District may evaluate excavation options, with secondary phyto-remediative approaches as passive alternatives to lessen the groundwater impacts during the project's life cycle. A preliminary field-study in the VOC plume area sampled the interior of a Black Locust (Robinia pseudoacacia) tree using a Haglof tree corer. Detectable levels of tetrachloroethene (PCE), trichloroethene (TCE), and cis-1,2,-dichloroethene (cis-DCE) were found in the woody interior of the tree. Subsequent sampling and analyses were performed on proximal trees of varying species in and around the currently delineated VOC plume. The results indicate that poplar and native cottonwood variants preferentially contain the VOCs, whereas collocated hardwood trees produced non-detectable results. Additional sampling of Cottonwoods in the VOC-impacted area promoted further delineations of the impacts. The tree-sampling data can be considered a broad surrogate for soil sampling to optimally delineate the VOC plume without performing additional invasive sampling of the subsurface (e.g., drilling). The results also will be used to determine which native tree species preferentially uptake the VOCs from soil and groundwater. These species, and possibly other hybrid species known for VOC uptake and transpiration, would be propagated to promote interim phyto-extraction of the VOCs during the maintenance period between decision-document completion and likely remedial action under the Formerly Utilized Sites Remedial Action Program (FUSRAP). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Evaluation of the MARVEL Reactor Inhalation Dose Consequences

A dose consequence analysis was performed to support the preliminary Microreactor Applications Research Validation and Evaluation Project (MARVEL) design effort. The purpose of the MARVEL project is to develop a nuclear microreactor applications test bed at Idaho National Laboratory (INL) to perform research and development on various operational features of microreactors to ultimately improve integration of microreactors to end-user applications. The MARVEL concept is a 100 kilowatt (kW) thermal (kWth) and approximately 20-kW electric (kWe) generating microreactor. The MARVEL system will be located in the INL TREAT facility in the north high-bay equipment pit. The analysis considers the bounding release fractions of the MARVEL reactor concept and documents the dose consequences to the public and collocated worker.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

High Angle Remediation Antimony, Mercury, and Pu-239/240 Contaminated Soil at LANL near Los Alamos Town Site - 18579

The Manhattan Project and early Cold War era operations at Los Alamos National Laboratory (LANL) left behind soil contaminated with antimony, mercury, and Pu-239/240. TerranearPMC (TPMC) successfully completed a phased three-year high-angle legacy cleanup project to excavate contaminated soil from a steep, difficult-to-access canyon wall in the Upper Los Alamos Canyon Aggregate Area bordering Los Alamos town site. The first and third phases of the project (years 2015 and 2017) utilized a Menzi Muck (spider excavator) in concert with a 275 US ton telescoping crane to remove ∼158 cubic yards (cy) of mercury-contaminated rock and soil (i.e. media) from one solid waste management unit (SWMU) in 2015; and ∼70 cy of antimony contaminated media, and ∼65 cy of collocated mercury and Pu-239/240 contaminated media from two SWMUs in 2017. All soil excavated from the site was containerized in soft-sided 1.0 cy, 1.77 cy, and 3.5 cy IP-1 containers and shipped to an approved, licensed, off-site disposal facility. The crane was also used to move the spider excavator, field personnel, tools, the packaged waste, and restoration materials into and out of the canyon. In 2016, conventional but miniaturized excavation equipment was used to remove about 133 cy of Pu-239/240 contaminated media from four SWMUs west of both the 2015 and 2017 excavations. A total of 398 soil screening, waste composite, characterization/bounding, and confirmation samples were collected during the project. Media that was left in place after the excavation was sampled to confirm that human health concerns and environmental risk issues had been mitigated. This proven technical approach was the preferred method for cleaning up ∼426 cy of contaminated media from steep, difficult-to-access legacy waste sites within the Upper Los Alamos Canyon Aggregate Area between 2015 and 2017. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Cost saving opportunities in emergency planning at nuclear power plants - 18819

This paper identifies generalized offsite emergency planning costs for 2014 covering twenty different commercial nuclear plant locations in the U.S. This information was analyzed to quantify the potential cost savings associated with reduction in offsite emergency planning zone size as a function of sixteen offsite emergency planning standards contained in 10 CFR 50.47(b). Mean annual operating and maintenance costs and startup costs for a typical offsite nuclear power plant emergency planning program were $2.25 M and $10 M, respectively. However, if a reactor design technical basis were developed that allowed for a reduction in offsite plume emergency planning zone (EPZ) size from the nominal 10 mile standard currently used, collocation of that EPZ with the site plant boundary could produce programmatic savings in excess of 90% over a typical 40 year plant life. Lesser, but still potentially significant savings, are possible if the plume EPZ were resized to five and two miles. Negligible potential cost savings were identified with reductions in the ingestion pathway EPZ size which has been typically set at 50 miles. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Quantifying the Uncertainty in Deterministic Phonon Transport Calculations of Thermal Conductivity using Polynomial Chaos Expansions

The nature of computational simulations requires the inclusion of an uncertainty analysis, as we have limited knowledge of all physically determined input parameters for a computationally simulated problem. We rely on uncertainty quantification (UQ) to characterize our confidence in the outcomes. Quantifying uncertainty can provide a basis for certifications in high-consequence decisions, such as nuclear reactor design, and is a fundamental component of model validation. We employ a previously developed method of uncertainty quantification, polynomial chaos expansion with stochastic collocation (PCE-SC), applied to deterministic phonon transport simulations. In these simulations, we use the neutron transport code Rattlesnake, which solves the Self-Adjoint Angular Flux (SAAF) formulation of the transport equation with a continuous finite element (CFEM) spatial discretization and discrete ordinates, spherical harmonics angular discretizations. Rattlesnake was developed in the multi-physics object oriented simulation environment (MOOSE) framework. We have previously shown Rattlesnake to be effective in simulating phonon transport. We aim to provide a deterministic phonon transport framework for heterogeneous nuclear fuel with fission product defects to predict thermal conductivity (?). A first principles, physics-based calculation of thermal conductivity must involve factors such as the microstructure of nuclear fuel, which constantly changes during the fission process through the formation of isotopic decay products. Heat transport in oxide nuclear fuels is dominated by phonon transport. Impurities in the bulk material influence the transport of energy at the fundamental level, altering the scattering behavior of phonons and electrons. Conventionally, heat transport follows classical physics based on the heat equation derived from Fourier's law q = -k∇T, where q is heat flux, k is thermal conductivity and ∇T is a temperature gradient. However, Fourier's law is a macroscopic empirical law in which the thermal conductivity? does not have a mechanistic connection to the underpinning heat transport processes. Thermal conductivity of a material depends both on the material's intrinsic ability to transport heat and a variety of resistive effects caused by defects in the material. Thus ab initio prediction of the macroscopic conductivity - the property of interest for safe reactor operation - requires simulating detailed processes of heat transport, and then determining the effective thermal conductivity of the simulated material from the resulting heat flux under the imposed temperature difference. The thermal conductivity of a bulk, homogeneous, dielectric material can be well estimated by the mechanistically derived expression: k{sub bulk} = 1/3 C{sub ν}νgλ (2), where C{sub ν}, νg, and λ are the volumetric specific heat, phonon speed, and phonon mean free path, respectively. In these problems the relevant parameter is the material's acoustic thickness, its characteristic distance L relative to the phonon mean free path λ. In Eq. (2) the largest source of uncertainty is λ. While propagating uncertainty in λ to uncertainty in k through Eq. (2) is trivial, systems with extrinsic scattering require more sophisticated approaches. At the microscopic level, uncertainty in λ changes both a material's intrinsic thermal conductivity. Our goal is to propagate the uncertainty in λ through the deterministic transport computation of k. Because there are a small number of uncertain input quantities, we use the method of polynomial chaos expansion (PCE), which expresses solutions in the form of spectral expansions of an uncertain variable. This approach combines both intrusive and nonintrusive methods of uncertainty propagation techniques and results in a unique formulation which is very effective and efficient for problems with few uncertain parameters. Uncertainty Quantification and Sensitivity Analysis We use PCE-SC to measure propagation of uncertainty in a 3-D phonon transport problem of homogeneous silicon, to compute the mean and variance in temperature, heat flux and thermal conductivity. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Time-Dependent Sensitivity Analysis of OECD Benchmark using BISON and RAVEN

Developments in uncertainty quantification for nuclear simulations have decreased the computational cost required to perform accurate sensitivity analysis. This work demonstrates implementation of these methods in the RAVEN framework, allowing for time-dependent sensitivity analysis. By demonstration we consider an OECD benchmark case. We propagate uncertainties using RAVEN operating on the BISON fuels performance code. We then consider the time-evolution of output response sensitivity to uncertain inputs. We perform sensitivity analysis using time-based stochastic collocation for generalized polynomial chaos (SCgPC) and high-dimension model reduction (HDMR). While uncertainty quantification applied to end-of-cycle statistics is useful, we demonstrate that dominant sources of uncertainty for figures of merit may fluctuate throughout the simulation. Time-dependent sensitivity analysis allows more insight on key design parameters for fuel. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Error Convergence Characterization for Stochastic Transport Methods

There has been increased interest in reliably and efficiently solving engineering systems involving uncertainty in recent years. Characterization of the convergence of errors within the problem, including statistical and bias errors, increases confidence that chosen solution methods are appropriate for a particular problem and quantity of interest (QoI), that implementation errors have not been made, and can aid users or algorithms in solving problems within a tolerance efficiently. We demonstrate a method for characterizing error convergence in a simple stochastic transport problem. Though the approach is applicable to problems with more complicated physics, our simple problem enables analytic QoI solutions so that error convergence behavior and the identification of limiting errors can be presented with high precision. A one-dimensional, two-material, neutral-particle, and absorption-only transport problem involving uniformly distributed uncertain total cross sections is presented. Random sampling (RS) and stochastic collocation (SC) are used as stochastic solvers which sample from the uncertain space and Monte Carlo (MC) transport is employed to solve transport results on the resulting realizations. Probability density functions (PDFs) are created using either RS solutions or samples taken from a polynomial chaos expansion (PCE) constructed with SC solutions. The convergence of each solver is characterized with respect to the QoI against analytic solutions, convergence behavior is used to efficiently solve a QoI within a tolerance, and convergence plots are used to identify dominant solution errors.

42 ENGINEERING↗

Demonstrating Advanced Nuclear Energy Solutions for Net Zero

Background/Objectives. The aggressive goals being set by nation states, communities, and private industry for decarbonization of grid electricity, industrial heat sources, and transportation around the world are imperative to mitigating the devastating effects that we are seeing from climate change. Although many of these goals focus on accomplishments by 2035 or 2050, the decisions that we make today won’t just impact the landscape of energy systems for the next 20 or 30 years—they will shape the world’s environment for centuries to come. That means that we can’t just focus on technologies that will get us to 2050, but technologies that will withstand our energy demands over that long-ranging future. Success will require us to utilize all of the clean energy resources that we have available to meet demands for electricity, heat, and steam, and we will need energy carriers such as hydrogen that do not emit additional greenhouse gases at the point of use. Nuclear energy, ranging from technologies in service today to advanced, higher temperature and modular systems that will be in service this decade, will provide a robust complement to renewable energy resources that operate variably. Researchers across the U.S. Department of Energy laboratory complex are working to advance multiple aspects of these clean energy solutions, with many focusing on integrated energy system solutions that leverage all available clean energy assets to meet wide-ranging energy demands. Approach/Activities. Nuclear energy is a proven, zero-emission option during operation that can provide consistent, dispatchable power to meet electricity demands while also providing high-quality heat that can meet energy demands beyond the electricity sector. Energy system design should seek to maximize these assets. As a dispatchable energy source with a small land utilization footprint, nuclear energy can be collocated with renewable resources, and the smaller systems that will be deployed this decade (ranging from a few megawatts to hundreds of megawatts) can be installed right where that energy is needed. Integrated nuclear and renewable systems will enhance power grid reliability and resilience, and they will help stabilize the grid through their increasingly flexible operation. Licensing, installation, and broad adoption of these advanced nuclear energy systems are expected to progress significantly in the 2020s, but this may be longer than desired by some stakeholders wishing to implement impactful clean energy decisions today. However, one must recall that nuclear energy systems will operate for 80 or more years, as is being demonstrated by current fleet nuclear systems. The nuclear community is extremely thorough in reviewing these systems with regard to safety and security; these efforts ensure that the deployed systems will continue to provide reliable, resilient energy over that operational lifetime. That investment of time up front will ensure that we can support energy demands over the centuries to come. While advanced nuclear technologies move through this process, communities and private industry may choose to install renewable generation systems that can later be coupled to the complementary nuclear systems as they become available—thus moving closer to the net zero goals in the near term. Choosing technologies and deployment configurations that allow small modular nuclear powerhouses to be added to these “energy parks” as they become available will ensure that advanced technologies can be readily adopted to support growing demands for clean energy. Results/Lessons Learned. The primary focus of integrated energy systems (IES) research is to assess the technical and economic potential of novel multi-input, multioutput solutions that are expected to enhance energy system flexibility, reliability, and resilience as we pursue a clean energy transition. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. In early FY23 Idaho National Laboratory (INL) will commission thermal energy generation systems that emulate nuclear fission energy input using electric heating and will allow for integrated system testing with thermal energy storage, hydrogen production via high temperature electrolysis (HTE), and power systems hardware to demonstrate operation of a clean energy park within a microgrid or larger grid infrastructure, supporting up to 450 kW of heat input via electric heating and demonstrating operation of HTE systems at the multi-hundred kW scale. This presentation will highlight the wide array of RD&D being conducted at INL and partner laboratories to develop and deploy nuclear and renewable-based IES that will be key to achieving our net zero goals, including both computational and experimental demonstrations. By working with key collaborators in industry, analytical st

08 HYDROGEN↗