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Development of Critical Experiments to Provide Validation Data for Multiphysics Coupling Methods (Final Report)

Computational simulation has become one of the most important tools in the modern toolbox for nuclear reactor design. Reactor simulations, like the reactors themselves, involve multiple physical processes including neutronics, fluid flow and heat transfer (thermal-hydraulics), thermo-mechanics, fuel behavior, chemistry, and balance of plant. Each process can affect the behavior of the others, and advanced computational tools have been developed that couple separate physics models together to simulate the feedback effects. The objective of this work is to generate experimental data to support the validation of multi-physics reactor codes. It specifically targets the SHARP toolset from the NEAMS Reactor Product Line, but it is intended to be useful in any set of coded that couples thermal-hydraulics with neutronics simulations. The project takes advantage of the inherent flexibility of the RPI Reactor Critical Facility (RCF), a low power open-pool research reactor. The standard configuration of the RCF is used to explore the effects of moderator temperature on neutronic behavior and reactivity. Because the low power of the reactor generates no appreciable temperature change in the moderator, the moderator temperature is artificially changed with two 18 kW electric immersion heaters. The temperature feedback effects can be observed by recording the change in the reactor power as the reactor goes from a supercritical state, to critical, to a subcritical state. To expand the temperature range and temperature rate of change that can be investigated, an experimental apparatus consisting of a heated water loop was designed and installed in the RCF. In this setup, water from a heated reservoir tank is pumped through a pipe placed through the center of the reactor core. The water in the reservoir can be heated to around 70 °C and pumped through the system. The pump has a variable flow rate and electronic control, so a number of scenarios can be developed. A slug of water can be pushed through the system to generate a reasonably fast change in reactivity. The pump speed can be increased or decreased over the course of a measurement, or even oscillated at different periods, to observe the response of the reactor. To complement the experimental data generated by the RCF, a set of computational models have been developed. They are intended to illustrate the usefulness of the experimental data generated in validating coupled multi-physics simulations. A model previously constructed in MCNP has been used in conjunction with safety analysis at the RCF for many years and was modified to support the design of the heated water loop experiment. This model was translated into Serpent 2, a similar Monte Carlo code, which provided the added advantage of being able to produce collapsed cross-section data files for use in the deterministic neutron transport codes that are part of the SHARP toolset. A complete reconstruction of the RCF model, both with and without the heated fluid loop experiment, were necessary for use with the SHARP codes, PROTEUS (neutronics) and Nek5000 (thermal hydraulics), as these require an unstructured mesh format to operate. The computational requirements for fully coupled three dimensional simulations are significant, and challenges to full implementation and comparison with RCF experiments remain. A wide variety of experiments have been conducted for eventual benchmarking and validation of multi-physics reactor codes. A complete database of detailed time- and temperature-dependent measurements have been generated and stored. Several examples of the experimental results are presented here, with refinement and analysis of experiments ongoing. While these experiments still only address a finite range of operating conditions, in particular being limited to water in the sub-boiling regime, they represent a unique (to date) look at the feedback between temperature and neutronic behavior suited for validation of the coupling routines in multi-physics codes. It is hoped that these will be the foundation of future benchmarks that will provide confidence in the tools that will be used to develop the next generation of nuclear reactor systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Reliability‐based layout optimization in offshore wind energy systems

Abstract Existing methods for optimizing wind array layouts typically use power or cost objectives and rarely consider reliability‐based objectives. Component and system failure rates, however, are dependent on location‐specific wind conditions, are influenced by array layout and wake interactions, and have a direct and significant impact on capital costs, operational costs, and power production. Although wind power plant models exist that calculate wind loads with sufficient resolution to capture component loading dynamics from wind conditions, they are computationally expensive and thus not suitable for research applications requiring many evaluations, particularly optimization. This study describes the development of computationally efficient, reliability‐based layout optimization methods, enabling us to explore the relationship between component reliability and layout optimization. These methods include the surrogate modeling of the planet bearing life based on varying wind conditions simulated in FAST.Farm and the formulation of reliability‐based objectives based on failure cost and power production models. Through demonstration of this method, we explore how wind conditions, objective functions, and capacity density influence reliability‐based layout optimization. Results indicate that considering reliability alongside power production can reduce failure costs associated with replacement costs and downtime while maintaining or improving power production. Our conclusions highlight the opportunity for wind power plant developers to integrate reliability and operational expenditures alongside performance and capital expenditure objectives in plant design and development to improve plant performance and costs.

17 WIND ENERGY↗

Selection function of clusters in Dark Energy Survey year 3 data from cross-matching with South Pole Telescope detections

Context. Galaxy clusters selected based on overdensities of galaxies in photometric surveys provide the largest cluster samples. However, modeling the selection function of such samples is complicated by noncluster members projected along the line of sight (projection effects) and the potential detection of unvirialized objects (contamination). Aims. We empirically constrained the magnitude of these effects by cross-matching galaxy clusters selected in the Dark Energy Survey data with the redMaPPer algorithm with significant detections in three South Pole Telescope surveys (SZ, pol-ECS, pol-500d). Methods. For matched clusters, we augmented the redMaPPer catalog with the SPT detection significance. For unmatched objects we used the SPT detection threshold as an upper limit on the SZe signature. Using a Bayesian population model applied to the collected multiwavelength data, we explored various physically motivated models to describe the relationship between observed richness and halo mass. Results. Our analysis reveals a clear preference for models with an additional skewed scatter component associated with projection effects over a purely log-normal scatter model. We rule out significant contamination by unvirialized objects at the high-richness end of the sample. While dedicated simulations offer a well-fitting calibration of projection effects, our findings suggest the presence of redshift-dependent trends that these simulations may not have captured. Our findings highlight that modeling the selection function of optically detected clusters remains a complicated challenge that requires a combination of simulation and data-driven approaches.

79 ASTRONOMY AND ASTROPHYSICS↗

A stochastic perturbation method to generate inflow turbulence in large-eddy simulation models: Application to neutrally stratified atmospheric boundary layers

Despite the variety of existing methods, efficient generation of turbulent inflow conditions for large-eddy simulation (LES) models remains a challenging and active research area. Herein, we extend our previous research on the cell perturbation method, which uses a novel stochastic approach based upon finite amplitude perturbations of the potential temperature field applied within a region near the inflow boundaries of the LES domain [Muñoz-Esparza et al., “Bridging the transition from mesoscale to microscale turbulence in numerical weather prediction models,” Boundary-Layer Meteorol., 153, 409–440 (2014)]. The objective was twofold: (i) to identify the governing parameters of the method and their optimum values and (ii) to generalize the results over a broad range of atmospheric large-scale forcing conditions, U{sub g} = 5 − 25 m s{sup −1}, where U{sub g} is the geostrophic wind. We identified the perturbation Eckert number, Ec=U{sub g}{sup 2}/ρc{sub p}θ{sup ~}{sub pm}, to be the parameter governing the flow transition to turbulence in neutrally stratified boundary layers. Here, θ{sup ~}{sub pm} is the maximum perturbation amplitude applied, c{sub p} is the specific heat capacity at constant pressure, and ρ is the density. The optimal Eckert number was found for nonlinear perturbations allowed by Ec ≈ 0.16, which instigate formation of hairpin-like vortices that most rapidly transition to a developed turbulent state. Larger Ec numbers (linear small-amplitude perturbations) result in streaky structures requiring larger fetches to reach the quasi-equilibrium solution, while smaller Ec numbers lead to buoyancy dominated perturbations exhibiting difficulties for hairpin-like vortices to emerge. Cell perturbations with wavelengths within the inertial range of three-dimensional turbulence achieved identical quasi-equilibrium values of resolved turbulent kinetic energy, q, and Reynolds-shear stress, . In contrast, large-scale perturbations acting at the production range exhibited reduced levels of , due to the formation of coherent streamwise structures, while q was maintained, requiring larger fetches for the turbulent solution to stabilize. Additionally, the cell perturbation method was compared to a synthetic turbulence generator. The proposed stochastic approach provided at least the same efficiency in developing realistic turbulence, while accelerating the formation of large-scales associated with production of turbulent kinetic energy. Also, it is computationally inexpensive and does not require any turbulent information.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Assessment of Potential Impact of Electromagnetic Fields from Undersea Cable on Migratory Fish Behavior

The US Department of Energy and US Department of the Interior, Bureau of Ocean Energy Management commissioned this study to address the limited scientific data on the impacts of high voltage direct current cables on aquatic biota, in particular migratory species within the San Francisco Bay. Empirical evidence exists that marine animals perceive and orient to local distortions in the earth’s main geomagnetic field magnetic field. The electromagnetic fields (EMF) generated by the cables that carry electricity from hydrokinetic energy sources to shore-based power stations may produce similar local distortions in the earth’s main field. Concern exists that animals that migrate along the continental shelves might orient to the EMF from the cables, and move either inshore or offshore away from their normal path. The Trans Bay Cable (TBC) is a ±200-kilovolt (kV), 400 MW 85-km long High Voltage Direct Current (DC) buried transmission line linking Pittsburg, CA with San Francisco, CA (SF) through the San Francisco Bay. The study addresses the following specific questions based on measurements and projections of the EMF produced by an existing marine cable, the TBC, in San Francisco Bay. Specifically, does the presence of EMF from an operating power cable alter the behavior and path of bony fishes and sharks along a migratory corridor? Does the EMF from an operating power cable guide migratory movements or pose an obstacle to movement? To meet the main study objectives several activities needed to be carried out: 1) modeling of the magnetic fields produced by the TBC, 2) assessing the migratory impacts on Chinook salmon smolts (Oncorhynchus tshawytscha) and green sturgeon (Acipenser medirostris) as a result of local magnetic field distortions produced by bridge structures and 3) analyzing behavioral responses by migratory Chinook salmon and green sturgeon to a high-voltage power cable. To meet the first objective, magnetic field measurements were made using two submerged Geometrics magnetometers towed behind a survey vessel in four locations in the San Francisco estuary along profiles crossing the cable path. We applied basic formulas to describe magnetic field from a DC cable summed vectorially with the background geomagnetic field (in the absence of other sources that would perturb the ambient field) to derive characteristics of the cable not immediately or otherwise observable. The magnetic field profiles of 76 survey lines were regressed against the measured fields, representing eight days of measurement. Many profiles were dominated by field distortions caused by bridge structures or other submerged objects, and the cable contribution to the field was not detectable. The regressions based on fundamental principles (Biot Savart law) and the vectorial summation of cable and geomagnetic fields provide estimates of cable characteristics consistent with plausible expectations. For the second objective, detailed gradiometer survey were examined. Distortions in the earth’s main field produced by bridges across the estuary were much greater than those from the TBC. The former anomalies exceeded the latter by an order of magnitude or more. Significant numbers of tagged Chinook salmon smolts migrated past bridges, which produced strong magnetic anomalies, to the Golden Gate Bridge, where they were recorded by dual arrays of acoustic tag-detecting monitors moored in lines across the mouth of the bay. Adult green sturgeon successfully swam upstream and downstream through the estuary on the way to and from their spawning grounds. Hence, the large anomalies produced by the bridges that run perpendicular to these migration routes do not appear to present a strong barrier to the natural seasonal movement patterns of salmonid smolts and adult green sturgeon. Finally, to assess the behavioral responses by migratory Chinook salmon and green sturgeon to a high- voltage power cable - the potential impacts effect of the TBC on fishes migrating through the San Francisco Estuary were examined. These included late-fall run Chinook salmon smolts (Oncorhynchus tshawytscha) that migrate downstream through the San Francisco Estuary to the Pacific Ocean and adult green sturgeon (Acipenser medirostris), which migrate upstream from the ocean through the estuary to their spawning habitat in the upper Sacramento River and return to the ocean after spawning occurs. Our results indicate Chinook salmon smolts may be attracted to the cable after activation (more cable location crossings, more detections at Bay Bridge, high importance of distance to cable in predicting fish location), but are not impeded from successfully migrating through the San Francisco Bay (similar proportions of successful exits, faster transit rates). Cable activity had opposite effects on outbound and inbound green sturgeon migrations: outbound migrations had significantly longer transit times while inbound migrations had significantly shorter migration times. However, the proportion of green sturgeon that successfully migrated through the San Francisco Bay was not strongly impacted after cable activation for either migration type. Based on the work, we provide the following conclusions: 1) calculations of magnetic fields for assessment of marine life can be performed; however, local anomalies in the fields resulting from submerged structures require validation of such calculations through collection of ambient DC magnetic field data, 2) the large anomalies produced by the bridges that run perpendicular to these migration routes do not appear to present a strong barrier to the natural seasonal movement patterns of salmonid smolts and adult green sturgeon and 3) Chinook salmon smolts may be attracted to the activated cable based on analysis of cable crossing, misdirections, and first presence at the array data, however, the cable activation does not appear to change the proportion of smolts that successfully migrate through the San Francisco Bay. Cable activation impacts inbound and outbound migrating adult green sturgeon: travel time was increased for outbound migrations but decreased for inbound migrations. However, cable activation did not appear to impact the success of either migration type in this species.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Comparing Numerical Models of the TALOS Wave Energy Converter

In this study, we present the development of a numerical model of the TALOS Wave Energy Converter (WEC) in WEC-Sim and compare it with existing numerical in-house models from Lancaster and results from DNV's Sesam code. The objective of this work is to validate the performance of the TALOS WEC using WEC-Sim and compare the results with those obtained from other numerical models. The TALOS WEC is a promising technology for the generation of clean, renewable energy from ocean waves. The development of a reliable numerical model for the TALOS WEC is crucial for its design and optimization. To achieve this, we have implemented the TALOS WEC in WEC-Sim and compared the results to in-house models from Lancaster and to results from DNV's Sesam code. Our results show good agreement with the results from Lancaster and DNV, demonstrating the accuracy and reliability of the numerical model developed in WEC-Sim. This work advances the field of wave energy conversion by providing a verified numerical model of the TALOS WEC, which can be used for further optimization and design studies.

CFD↗

Prioritizing Countries by Concern Regarding Access to Weapons of Mass Destruction Materials

This article presents a global prioritization methodology that evaluates the relative risks of non-state actor acquisition of materials that could be used in chemical, biological, radiological, nuclear and high explosive Weapons of Mass Destruction (WMD) from the country’s relevant infrastructure. Prioritization is based on three domains: 1. Assessing relative scale of materials in each country, 2. The country’s corresponding security posture, and 3. The presence of threat actors. The output is a list of countries prioritized from greatest risk to least. Rather than providing an overall 1 to N ranking, however, the results are placed into tiers based upon their natural groupings within the three domains. The countries in the highest tiers are flagged as potential US national security concern; those scoring in the middle and at the bottom are flagged as posing lower US national security concern. A systematic approach assesses each country by leveraging many disciplines, such as risk and decision analysis, as well as expert judgement. A quantitative value model based on Multi-Attribute Value Theory (MAVT) organizes the objectives scoring criteria into a value tree using lessons learned from previous studies, published literature, and expert judgement. The article presents the prioritization categories and corresponding value model scoring criteria to include measurement type, weight, range, and value preference. Country names and data are notional in order to share the details on the underlying methodology and model without identification of actual security risks. A deliberative process addresses factors external to the model and scrutinizes inputs, methodology, model, and results.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Survey of gravitationally lensed objects in HSC imaging (SuGOHI) – X. Strong lens finding in the HSC-SSP using convolutional neural networks

ABSTRACT We apply a novel model based on convolutional neural networks (CNN) to identify gravitationally lensed galaxies in multiband imaging of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a parent sample of 2350 061 galaxies selected from the $\sim$ 800 deg$^2$ Wide area of the HSC-SSP Public Data Release 2. The galaxies in HSC Wide are selected based on stringent pre-selection criteria, such as multiband magnitudes, stellar mass, star formation rate, extendedness limit, photometric redshift range, etc. The trained CNN assigns a score from 0 to 1, with 1 representing lenses and 0 representing non-lenses. Initially, the CNN selects a total of 20 241 cutouts with a score greater than 0.9, but this number is subsequently reduced to 1522 cutouts after removing definite non-lenses for further visual inspection. We discover 43 grade A (definite) and 269 grade B (probable) strong lens candidates, of which 97 are completely new. In addition, we also discover 880 grade C (possible) lens candidates, 289 of which are known systems in the literature. We identify 143 candidates from the known systems of grade C that had higher confidence in previous searches. Our model can also recover 285 candidate galaxy-scale lenses from the Survey of Gravitationally lensed Objects in HSC Imaging (SuGOHI), where a single foreground galaxy acts as the deflector. Even though group-scale and cluster-scale lens systems are not included in the training, a sample of 32 SuGOHI-c (i.e. group/cluster-scale systems) lens candidates is retrieved. Our discoveries will be useful for ongoing and planned spectroscopic surveys, such as the Subaru Prime Focus Spectrograph project, to measure lens and source redshifts in order to enable detailed lens modelling.

Jaelani, Anton T. (ORCID:0000000162825778)↗

A Multi-Year Plan for Enhancing Turbulence Modeling in Hydra-TH

The purpose of this milestone report is to document a multi-year plan for enhancing turbulence modeling in Hydra-TH. In Phase II of the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, Hydra-TH is being developed to the meet the high-fidelity, high-Reynolds number CFD based thermal hydraulic simulation needs of the program. This work will be conducted within the thermal hydraulics methods (THM) focus area. This objective will be met by; maturation of recently added models, strategic design/development of new models and systematic and rigorous testing of existing and new models and model extensions. This report will also serve to meet the requirements of CASL level three milestone, L3:THM.CFD.P10.02, scheduled for completion March 31, 2015.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A new and inexpensive non-bit-for-bit solution reproducibility test based on time step convergence (TSC1.0)

A test procedure is proposed for identifying numerically significant solution changes in evolution equations used in atmospheric models. The test issues a fail signal when any code modifications or computing environment changes lead to solution differences that exceed the known time step sensitivity of the reference model. Initial evidence is provided using the Community Atmosphere Model (CAM) version 5.3 that the proposed procedure can be used to distinguish rounding-level solution changes from impacts of compiler optimization or parameter perturbation, which are known to cause substantial differences in the simulated climate. The test is not exhaustive since it does not detect issues associated with diagnostic calculations that do not feedback to the model state variables. Nevertheless, it provides a practical and objective way to assess the significance of solution changes. The short simulation length implies low computational cost. The independence between ensemble members allows for parallel execution of all simulations, thus facilitating fast turnaround. The new method is simple to implement since it does not require any code modifications. We expect that the same methodology can be used for any geophysical model to which the concept of time step convergence is applicable.

54 ENVIRONMENTAL SCIENCES↗

A Parameterized Life Cycle Model for Rapid Quantification of Bioenergy Sustainability Metrics

Life cycle assessment (LCA) is a method for assessing all environmental impacts associated with provisioning a good or service. A life cycle encompasses the system which directly produces a good, as well as all systems and processes on which that system is dependent. The objective of this work is to develop a flexible, parameterized model representing a superstructure of life cycles for advanced biofuel production. Parameterizing the model allows users to define a variety of biofuel production scenarios and assess key sustainability metrics, without needing to acquire additional data or perform separate life cycle assessments. Within the model, parameters will include feedstock species and phenotype, a range of farming and harvest practices, feedstock pre-processing, and operating conditions within the biomass conversion process. The model will be used to identify major impact drivers within bioenergy life cycles and aid CBI researchers and leadership in targeting areas where additional R&D efforts will have the most beneficial impacts.

09 BIOMASS FUELS↗

Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework

In this report, a robust machine-learning-based computational framework that couples multi-layer neural network (MLNN) proxies and a multi-objective particle swarm optimizer (MOPSO) to design water-alternating-carbon dioxide injection (CO 2 -WAG) projects is presented. The proposed optimization protocol considers various objectives, including oil recovery and CO 2 storage volume. Expert MLNN systems are trained and employed as surrogate models of the high-fidelity compositional simulator in the optimization workflow. When multiple objective functions are considered, two approaches are employed to treat the objectives: the weighted sum method and the Pareto-front-based scheme. A field-scale implementation focusing on tertiary recovery in the Morrow B formation at Farnsworth Unit (FWU) is presented. The developed Pareto-optimal solutions indicate the maximal available oil production can be 1.64 × 10 7 barrels and maximal carbon storage can achieve 2.35 × 10 7 tons. Trade-offs factor is defined to divide the constructed Pareto front into 4 sections with the trade-off factors’ value ranges from 0.35 to 49.9. This work also compares the optimum solution found by the aggregative objective function and the solution repository covered by the Pareto front that considers the physical and operational constraints and reduces uncertainties involved by the multi-objective optimization process. Our comparison indicates multiple solutions exist to satisfy the objective criteria of the WAG design, and these results cannot be found using the traditional weighted sum method. The Pareto front solution can provide more options for project designers, but decisions regarding necessary trade-offs must be made using the solution repository to balance the project economics and CO 2 storage amount.

10 SYNTHETIC FUELS↗

Validation of Material Models For Automotive Carbon Fiber Composite Structures Via Physical And Crash Testing (VMM Composites Project)

As automotive fuel economy requirements increase, the push for reducing overall vehicle weight will likely include the consideration of materials that have not previously been part of mainstream vehicle design and manufacturing, including carbon fiber composites. Vehicle manufacturers currently rely on computer-aided engineering (CAE) methods as part of the design and development process, so going forward, the ability to accurately and predictably model carbon fiber composites will be necessary. If composites are to be used for structural components, this need applies to both, crash and quasi-static modeling. This final report covers the results of a five-year, $6.89M, 50% cost-shared research project between Department of Energy (DOE) and the US Advanced Materials Partnership (USAMP) under Cooperative Agreement DE-EE-0005661 known as “Validation of Material Models for Automotive Carbon Fiber Composite Structures Via Physical and Crash Testing (VMM).” The objective of the VMM Composites Project was to validate and assess the ability of physics-based material models to predict crash performance of automotive primary load-carrying carbon fiber composite structures. Simulation material models that were evaluated included micro-mechanics based meso-scale models developed by the University of Michigan (UM) and micro-plane models by Northwestern University (NWU) under previous collaborations with the DOE and Automotive Composites Consortium/USAMP, as well as five commercial crash codes: LS-DYNA, RADIOSS, VPS/PAM-CRASH, Abaqus, and GENOA-MCQ. CAE predictions obtained from seven organizations were compared with experimental results from quasi-static testing and dynamic crash testing of a thermoset carbon fiber composite front-bumper and crush-can (FBCC) system gathered under multiple loading conditions. This FBCC design was developed to demonstrate progressive crush, virtual simulation, tooling, fabrication, assembly, non-destructive evaluation and crash testing advances in order to assess the correlation of the predicted results to the physical tests. The FBCC was developed to meet a goal of 30-35% mass reduction while aiming for equivalent energy absorption as a steel component for which baseline experimental results were obtained from testing in the same crash modes. The project also evaluated crash performance of thermoplastic composite structures fabricated from commercial prepreg materials and low cost carbon fiber sourced from Oak Ridge National Laboratory. The VMM Project determined that no set of predictions from a CAE supplier were found to be universally accurate among all the six crash modes evaluated. In general, crash modes that were most dependent on the properties of the prepreg were more accurate than those that were dependent on the behavior of the joints. The project found that current CAE modeling methods or best practices for carbon fiber composites have not achieved standardization, and accuracy of CAE is highly reliant on the experience of its users. Coupon tests alone are not sufficient to develop an accurate material model, but it is necessary to bridge the gap between the coupon data and performance of the actual structure with a series of subcomponent level tests. Much of the unreliability of the predictions can be attributed to shortcomings in our ability to mathematically link the effects of manufacturing and material variability into the material models. This is a subject of ongoing research in the industry. The final report is organized by key technical tasks to describe how the validation project developed, modeled and compared crash data obtained on the composite FBCC to the multiple sets of CAE predictions. Highlights of the report include a discussion of the quantitative comparison between predictions and experimental data, as well as an in-depth discussion of remaining technological gaps that exist in the industry, which are intended to spur innovations and improvements in CAE technology.

36 MATERIALS SCIENCE↗

Implementing and Improving CBMZ-MAM3 Chemistry and Aerosol Modules in the Regional Climate Model WRF-CAM5: An Evaluation over the Western US and Eastern North Pacific

The representation of aerosols in climate-chemistry models is important for air quality and climate change research, but it can require significant computational resources. The objective of this study was to improve the representation of aerosols in climate–chemistry models, specifically in the carbon bond mechanism, version Z (CBMZ), and modal aerosol modules with three lognormal modes (MAM3) in the WRF-CAM5 model. The study aimed to enhance the model’s chemistry capabilities by incorporating biomass burning emissions, establishing a conversion mechanism between volatile organic compounds (VOCs) and secondary organic carbons (SOCs), and evaluating its performance against observational benchmarks. The results of the study demonstrated the effectiveness of the enhanced chemistry capabilities in the WRF-CAM5 model. Six simulations were conducted over the western U.S. and northeastern Pacific region, comparing the model’s performance with observational benchmarks such as reanalysis, ground-based, and satellite data. The findings revealed a significant reduction in root-mean-square errors (RMSE) for surface concentrations of black carbon (BC) and organic carbon (OC). Specifically, the model exhibited a 31% reduction in RMSE for BC concentrations and a 58% reduction in RMSE for OC concentrations. These outcomes underscored the importance of accurate aerosol representation in climate-chemistry models and emphasized the potential for improving simulation accuracy and reducing errors through the incorporation of enhanced chemistry modules in such models.

54 ENVIRONMENTAL SCIENCES↗

Measurement of Nuclear Power Plant Construction Performance Using EVMS Model

The Earned Value Management System (EVMS) method integrates three critical elements of project management: scope, cost and time management. It requires the periodic monitoring of actual expenditures and physical scope accomplishments and allows calculation of cost and schedule variances along with performance indices. It allows forecasting of project cost and schedule at completion and highlights the possible need for corrective action. Application of earned value management techniques is scalable to individual projects as determined by their size and complexity. Effective management of quality, cost, and time is the utmost objective for any type of construction project. An EVMS model provides an advanced systematic method of controlling these three performance measures in an integrated way. However, the additional management effort required to develop and maintain an effective Work Breakdown Structure (WBS) has been highlighted as a major barrier to application of this concept. This paper examines the influencing attributes that would facilitate effective EVMS implementation including a restructuring of the WBS for nuclear power plant construction.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Using Machine Learning to Understand Electric and Hybrid Vehicles Ownership in Burdened and Nonburdened Communities

Transitioning to electric and hybrid vehicles (EHVs) for all communities is a pivotal step toward sustainable transportation and environmental conservation. This paper aims to understand the adoption of EHVs, focusing on burdened communities (BCs) in the United States. The EHV ownership-based analysis combines two datasets—behavioral data from the Puget Sound Regional Travel Survey integrated with BCs (Justice40) data covering transportation insecurity, environmental burden, social vulnerability, health vulnerability, and climate and disaster risk burden. After creating this unique database, descriptive analysis and modeling are used to analyze the data and predict EHV ownership in the future. Specifically, we use a new method that combines particle swarm optimization (PSO) with a stacking model named PSO-Stacking, which incorporates heterogeneous base learners of machine learning and deep learning. PSO applies a customized objective function to select the optimal hyperparameters for heterogeneous learners within the stacking model, effectively addressing challenges such as multicollinearity, data imbalance, nonlinearity, and overfitting. The proposed solution covers more accurate results than standard benchmark models for EHV ownership in BCs and non-BCs. In addition, the results of the PSO-Stacking method are explained using the local interpretable model-agnostic explanations technique. Results show a negative correlation between the BCs indicators, that is, higher transportation insecurity associated with lower EHV ownership. Furthermore, BCs have higher future climate risk scores, diesel particulate matter levels, and PM2.5 in the air than non-BCs because of higher conventional vehicle ownership. These communities are at higher risk and can benefit from electrification, EV infrastructure, and EV policies to address environmental challenges.

Aslam, Zeeshan [ORNL]↗

CONSTRAINTS ON THE INTERGALACTIC MAGNETIC FIELD WITH GAMMA-RAY OBSERVATIONS OF BLAZARS

Distant BL Lacertae objects emit γ-rays that interact with the extragalactic background light (EBL), creating electron–positron pairs, and reducing the flux measured by ground-based imaging atmospheric Cherenkov telescopes (IACTs) at very-high energies (VHE). These pairs can Compton-scatter the cosmic microwave background, creating a γ-ray signature at slightly lower energies that is observable by the Fermi Large Area Telescope (LAT). This signal is strongly dependent on the intergalactic magnetic field (IGMF) strength (B) and its coherence length (L{sub B}). We use IACT spectra taken from the literature for 5 VHE-detected BL Lac objects and combine them with LAT spectra for these sources to constrain these IGMF parameters. Low B values can be ruled out by the constraint that the cascade flux cannot exceed that observed by the LAT. High values of B can be ruled out from the constraint that the EBL-deabsorbed IACT spectrum cannot be greater than the LAT spectrum extrapolated into the VHE band, unless the cascade spectrum contributes a sizable fraction of the LAT flux. We rule out low B values (B ≲ 10{sup −19} G for L{sub B} ≥ 1 Mpc) at >5σ in all trials with different EBL models and data selection, except when using >1 GeV spectra and the lowest EBL models. We were not able to constrain high values of B.

79 ASTRONOMY AND ASTROPHYSICS↗

CHEMICAL ANALYSIS OF SIMULATED HIGH LEVEL WASTE GLASSES TO SUPPORT SULFATE SOLUBILITY MODELING

The U.S. Department of Energy (DOE), Office of Environmental Management (EM) is sponsoring an international, collaborative project to develop a fundamental model for sulfate solubility in nuclear waste glass. The solubility of sulfate has a significant impact on the achievable waste loading for nuclear waste forms both within the DOE complex and to some extent at U.K. sites. The development of enhanced borosilicate glass compositions with improved sulfate solubility will allow for higher waste loadings and accelerated cleanup missions. Much of the previous work on improving sulfate retention in waste glasses has been done on an empirical basis, making it difficult to apply the findings to future waste compositions despite the large number of glass systems studied. A more fundamental, rather than empirical, model of sulfate solubility in glass, under development at Sheffield Hallam University (SHU), could provide a solution to the issues of sulfate solubility. The model uses the normalized cation field strength index as a function of glass composition to predict sulfate capacity, and has shown early success for some glass systems. The objective of the current scope is to mature the sulfate solubility model to the point where it can be used to guide glass composition development for DOE waste vitrification efforts, allowing for enhanced waste loadings and waste throughput. A series of targeted glass compositions was selected to resolve data gaps in the current model. SHU fabricated these glasses and sent samples to the Savannah River National Laboratory (SRNL) for chemical composition analysis. SHU will use the resulting data to enhance the sulfate solubility model and resolve any deficiencies. In this report, SRNL provides chemical analyses for simulated waste glasses fabricated SHU in support of sulfate solubility model development. A review of the measured compositions revealed that there are issues with the B{sub 2}O{sub 3} and Fe{sub 2}O{sub 3} concentrations missing their targeted values by a significant amount for several of the study glasses. SHU is reviewing the fabrication of these glasses and the chemicals used in batching them to identify the source of these issues. The measured sulfate concentrations were all below their targeted values. This is expected, as the targeted concentrations likely exceeded the solubility limit for sulfate in these glass compositions. Some volatilization of sulfate may also have occurred during fabrication of the glasses. Measurements of the other oxides in the study glasses were reasonably close to their targeted values

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗