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DOE OSTI2023

DOE ART Graphite Program Intro Status 2023

General description of the ART Graphite Program with Status for 2023. This includes list of staff members, and brief description of behavior models, licensing & code, graphite R&D, As-Fab'd Properties, Machanism and Analysis, Irradiation. Also detail FY23 Activites, with AGC Update, Oxidation Activiteis, Baseline STatus, ASME Code Development, VIC Project Update, Molten salt studies. Slide included to highlight each employee contributions for work and papers and NEUPs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Versatile stochastic model for predictive KMC simulation of fcc metal nanostructure evolution with realistic kinetics

Stochastic lattice-gas models provide the natural framework for analysis of the surface diffusion-mediated evolution of crystalline metal nanostructures on the appropriate time scale (often 10 1 –10 4 s) and length scale. Model behavior can be precisely assessed by kinetic Monte Carlo simulation, typically incorporating a rejection-free algorithm to efficiently handle the broad range of Arrhenius rates for hopping of surface atoms. The model should realistically prescribe these rates, or the associated barriers, for a diversity of local surface environments. However, commonly used generic choices for barriers fail, even qualitatively, to simultaneously describe diffusion for different low-index facets, for terrace vs step edge diffusion, etc. We introduce an alternative Unconventional Interaction–Conventional Interaction formalism to prescribe these barriers, which, even with few parameters, can realistically capture most aspects of behavior. Here, the model is illustrated for single-component fcc metal systems, mainly for the case of Ag. It is quite versatile and can be applied to describe both the post-deposition evolution of 2D nanostructures in homoepitaxial thin films (e.g., reshaping and coalescence of 2D islands) and the post-synthesis evolution of 3D nanocrystals (e.g., reshaping of nanocrystals synthesized with various faceted non-equilibrium shapes back to 3D equilibrium Wulff shapes).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Electric Vehicle and Infrastructure Systems Modeling in Washington D.C. and Baltimore

This report documents the Argonne-Exelon effort to develop and utilize an agent-based model (ATEAM) of charging demand and infrastructure expansion applicable to the Washington, DC–Baltimore, MD consolidated metropolitan area. This study extends the ATEAM model time horizon to 10 years (from 2020 to 2030), expands agent behavior modeling capabilities, incorporates more granular and extensive empirical data on charging behavior, and analyzes charging needs for a much larger population of PEVs, in keeping with regional goals for significant adoption of ZEVs. With given targets for annual BEV adoption, five scenarios were developed to examine public infrastructure needs and resulting charging load, considering different home charging availabilities, as well as different PEV consumer profiles and public charging infrastructure deployment strategies. Scenario results show that if new chargers (both L2 and DCFC) are spread more widely (as with ubiquitous deployment strategies), there will be less variation in the number of chargers added to each census tract in the study area. More importantly, widespread public charging infrastructure with ubiquitous deployment strategies reduces unmet charging demand and improves charging success, even with heavy reliance on public charging. About 80 percent of BEV drivers can charge on their first attempt in scenarios with ubiquitous deployment strategies. Moreover, widespread public charging infrastructure better meets the demand for more charging, and in return, increases BEV adoption. Low home charging availability produces higher charging loads in public locations, especially during the early morning (around 8:00 a.m.) and late afternoon (around 6:00 p.m.). The evening peak load indicates that drivers are taking advantage of public charging before heading home. Study results also indicate that even with 20 percent home charging availability in 2030, just 20 percent of drivers attempt to charge on a given day. With their relatively high electric range (200+ miles), the BEVs expected to be on the road in 2030 can handle daily commutes without re-charging for a couple of days.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Effect of hydrophobic ionic liquids aqueous solubility on metal extraction from hydrochloric acid media: Mathematical modelling and trivalent thallium behavior

A mathematical model to explain cations’ solubility of both protic and aprotic ionic liquids in a wide range of hydrochloric acid solutions has been developed. The concept of this model is based on an assumption of the mineral acid extraction into the organic phase, formation of a salt there between an ionic liquid cation and chloride-anion due to ions recombination and partial salt back-extraction. The proposed approach allows estimating corresponding extraction constants. Comparison of calculated and experimentally measured solubility product constants shows that they are in good agreement. It has been determined also that the more the hydrophilicity of the ionic liquids’ cation the more hydrochloric acid is extracted. Furthermore, this model has been utilized to facilitate analysis of thallium transfer into hydrophobic ionic liquids providing insights into the mechanism of metal extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Quantum Drude oscillators coupled with Coulomb potential as an efficient model for bonded and non-covalent interactions in atomic dimers

The quantum Drude oscillator (QDO) model has been widely used as an efficient surrogate to describe the electric response properties of matter as well as long-range interactions in molecules and materials. Most commonly, QDOs are coupled within the dipole approximation so that the Hamiltonian can be exactly diagonalized, which forms the basis for the many-body dispersion method [Phys. Rev. Lett. 108, 236402 (2012)]. The dipole coupling is efficient and allows us to study non-covalent many-body effects in systems with thousands of atoms. However, there are two limitations: (i) the need to regularize the interaction at short distances with empirical damping functions and (ii) the lack of multipolar effects in the coupling potential. In this work, we convincingly address both limitations of the dipole-coupled QDO model by presenting a numerically exact solution of the Coulomb-coupled QDO model by means of quantum Monte Carlo methods. We calculate the potential-energy surfaces of homogeneous QDO dimers, analyzing their properties as a function of the three tunable parameters: frequency, reduced mass, and charge. We study the coupled-QDO model behavior at short distances and show how to parameterize this model to enable an effective description of chemical bonds, such as the covalent bond in the H2 molecule.

Chemistry↗

DOE OSTI2023

On the applicability of various levels of detail for occupant behavior representation and modeling in building performance simulation

Occupant behavior (OB) is one of the significant sources of uncertainty in building performance simulation. While OB modeling has received increased attention in the past decade, research on the degree of granularity or level of detail (LoD) required for representing occupants is still in the nascent stages. This paper analyzes the modeling and applicability of three LoDs to represent occupants in building performance assessment. A medium-sized prototype office building located in Chicago, Illinois is used as the simulation case study. Ten occupant-centric attributes are adopted to develop the LoDs for OB representation. We first demonstrate the different modeling approaches required for simulating the three fidelity levels. Later, we illustrate the suitability of the developed LoDs in supporting six building performance use cases across different lifecycle stages. Furthermore, this study intends to provide guidance for the building simulation community on appropriate OB representation to support various use cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

One Stomatal Model to Rule Them All? Toward Improved Representation of Carbon and Water Exchange in Global Models

Abstract Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr −1 . We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Functionally Assembled Terrestrial Ecosystem Simulator (FATES) for Hurricane Disturbance and Recovery

Tropical cyclones are an important cause of forest disturbance, and major storms caused severe structural damage and elevated tree mortality in coastal tropical forests. Model capabilities that can be used to understand post-hurricane forest recovery are still limited. We use a vegetation demography model, the Functionally Assembled Terrestrial Ecosystem Simulator, coupled with the Energy Exascale Earth System Model Land Model (ELM-FATES) to study the processes and the key factors regulating post-hurricane forest recovery. We implemented hurricane-induced forest damage, including defoliation, structural biomass reduction, and tree mortality, performed ensemble model simulations, and used random forest feature importance. For the simulation in the Luquillo Experimental Forest, Puerto Rico, we identified factors controlling the post-hurricane forest recovery, and quantified the sensitivity of key model parameters to the post-hurricane forest recovery. The results indicate a tendency for the Bisley forests to shift toward the light demanding plant functional type (PFT) when the pre-hurricane biomass between the light demanding and shade tolerant PFTs is nearly equal and forests experience hurricane disturbance with mortality >60% for both the two PFTs. Under more realistic conditions where the shade tolerant PFT is initially dominant, mortality >80% is required for a shift toward dominance of the light demanding PFT at Bisley. Hurricane mortality and background mortality are the two major factors regulating post-hurricane forest recovery in simulations. This research improves understanding of the ELM-FATES model behavior associated with hurricane disturbance and provides guidance for dynamic vegetation model development in representing hurricane induced forest damage with varied intensities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Process model for multilayer slide coating of polymer electrolyte membrane fuel cells

Slide coating is a precision method suitable for depositing multiple liquid-film layers simultaneously. Originally developed in the photographic film industry, it has been deployed for manufacturing of other products that benefit from multilayer coatings. One emerging application is the manufacture of polymer electrolyte membrane fuel cells (PEMFCs), which are used to produce electricity through electrochemical reactions of hydrogen and oxygen gas. The membrane-electrode assembly (MEA), in which key electrochemical reactions occur, consists of three layers that are typically deposited separately in serial fashion and then laminated together to form the three-layer MEA, i.e., three sequential steps of coat and dry. Adapting the process to simultaneous, multilayer slide coating of all three layers will save equipment cost and space while minimizing possible exposure to contaminants during transition between the steps. We are developing a three-layer slide coating model to aid the manufacturing process design of PEMFC. The model accounts for rheology of each layer, which typically exhibit shear thinning behavior. Model predictions are used to investigate simultaneous coatability of catalyst inks and to determine the best layer-by-layer ink selection.

25 ENERGY STORAGE↗

DOE OSTI2022

Report on Data Quality Required for Modeling an MSR

Calculations were performed to assess how uncertainties in molten salt property values impact the results of behavior models of molten salt reactor systems under steady-state conditions. The thermophysical and thermochemical properties of salt mixtures being considered for use in molten salt reactors are not yet well characterized and methods used to measure property values to molten salts are not yet well established. The limited property data for salts of interest that are available in the literature are inconsistent and unreliable. Many methods used to measure property values remain developmental in the sense that not all variables affecting measured values have been identified or controlled during the measurement and not all aspects of the measurements affecting data quality are calibrated. A prior report described the repeatability of measurements made at Argonne and the reproducibility of measurements made with the same salts at several institutions is being evaluated. There is significant uncertainty in measured property values due to instrumental limitations and the effects of contaminants in the salts used to make the measurements that impacts predictions of salt behavior in a reactor. Most salts of interest are multicomponent eutectic or near-eutectic mixtures and both uncertainty in the salt composition and uncertainty in measured values. Furthermore, the salt composition evolves over time due to the uptake of impurities from the atmosphere and corrosion of containment vessels. More significantly, fission products will accumulate during operation that change the salt compositions and property values. MSR developers need to understand how this uncertainty in the basic property data of the fuel will impact modeling predictions for normal reactor operation as well was in transient scenarios that will impact the safety basis. The calculations and analyses in this report address the impact of uncertainty in measured property values under steady-state conditions through a generalized parametric study. The pooled uncertainty from contributions by a number of factors were considered and quantified, including varying composition due to impurities and fission products, imprecision in the measured values, and uncontrolled aspects of the measurement. In this way, we can begin to gain an understanding of the magnitude of the impact uncertainty will have in modeling MSR systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Parameter extraction for a SPICE model of an hTron superconducting thermal switch

Efficiently simulating large circuits is crucial to the development of superconducting nanowire-based electronics. However, current simulation tools for this technology are not adapted to the scaling of circuit size and complexity. We focus on the multilayered heater-nanocryotron (hTron), a promising superconducting nanowire-based switch used in applications such as superconducting nanowire single-photon detector readout. Previously, the hTron was modeled using traditional finite-element methods, which fall short in simulating systems at a larger scale. An empirical-based method would be better adapted to this task, enhancing both simulation speed and agreement with experimental data. In this work, we perform switching current and activation delay measurements on 17 hTron devices. We then develop a method for extracting physical fitting parameters used to characterize the devices. We build a SPICE behavioral model that reproduces the static and transient device behavior using these parameters, and validate it by comparing its performance to a model developed in prior work, showing an improvement in simulation time by several orders of magnitude. Furthermore, our model provides circuit designers with a tool to help understand the hTron’s behavior during all design stages, thus enabling broader use of the hTron across various new areas of application.

Caloritronics↗

DOE OSTI2023

Development and application of sorption mass transfer models for fission product transport in TRISO fuel systems using BISON

Fission product mass transfer within and between TRISO particle and compact layers is an important phenomenon. It directly impacts fission product release predictions, which are used as source terms for safety and licensing calculations. Modeling fission product transport within layers and across bonded interfaces is relatively straightforward under the assumptions of isotropic Fickian diffusion, concentration continuity, and flux continuity. Modeling fission product transport across gaps and debonded layers is more difficult. Gaps are known to form between the buffer and inner PyC (IPyC), and debonding may occur between the IPyC and silicon carbide (SiC). A new mass transfer model was developed to provide a more accurate and robust fission product release calculation by accounting for interlayer sorptivity. One importance of the new model is to account for temperature and material changes across the gap based on sorption isotherm. This work presents the development of the sorption behavioral model and a fission product trapping model, and analyses the subsequent fission product diffusion behavior, specifically cesium, through TRISO particles and compact materials using the BISON fuel performance code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Integrated assessment model diagnostics: key indicators and model evolution

Integrated assessment models (IAMs) form a prime tool in informing climate mitigation strategies. Diagnostic indicators that allow to compare these models can help to describe and explain differences in model projections. This also increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler et al., 2015). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index (RAI), emission reduction type index (ERT), inertia timescale (IT), fossil fuel reduction (FFR), transformation index (TI) and cost per abatement value (CAV). We apply the approach to 17 IAMs, including both older version as well as their latest versions, as applied in the IPCC 6th Assessment Report (AR6). The study shows that the approach can be easily applied and allows for comparison of model versions in time. The indicators and their trends can often be explained in terms of model characteristics and changes. We show that together, the set of six indicators can provide an useful indication of the main traits of the model and can roughly indicate the general model behavior. The results also show that there is often a considerable spread across the models. Interestingly, the diagnostic values often change for different model versions, but there does not seem to be a distinct trend across the different models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Impact of Lateral Flow on Surface Water and Energy Budgets over the Southern Great Plains – A Modeling Study

As we see the horizontal grid spacing decrease, treatment of hydrologic processes in land surface models, such as the lateral flow of surface and subsurface flow, need to be explicitly represented. Unlike previous studies that mainly focused on the mountainous regions, in this study the offline WRF-Hydro model is employed to study the impact of lateral flow on soil moisture and energy fluxes over the relatively flat southern Great Plains (SGP). The vast amount of measurements over the SGP provide an unique opportunity to assess the model behavior. In addition, newly developed land surface properties and input forcing are ingested into the model, in an attempt to reduce uncertainties associated with the initial and boundary forcing and help to identify model deficiencies. Our results show that the more realistic inputs (parameters, soil types, forcing) lead to larger underestimation of latent heat flux and dry bias, indicating the existence of model structural uncertainty (embedded errors) in WRF-Hydro that need to be characterized to inform future model development efforts. Including lateral flow processes partly mitigates the model deficiencies in representing hydrologic processes and alleviates the dry bias. In particular, both surface and subsurface lateral flow increase soil moisture mainly over the lower elevations, except that subsurface flow also affects soil moisture over steeper terrains. Additional simulations are performed to assess the effect of routing resolution on model results. When LSM resolution is high, noticeable differences in soil moisture are produced between different routing resolutions especially over steep terrain. Whereas when LSM resolution is coarse, differences between routing resolutions become negligible, especially over flat terrain.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.0

HyRAM+ is a software toolkit for conducting quantitative risk assessment (QRA) and consequence modeling for hydrogen and other alternative fuels infrastructure and transportation systems. HyRAM+ contains validated, simplified release behavior models, a standardized QRA approach, and engineering models and generic data relevant to hydrogen installations. HyRAM (hydrogen-only) versions 1.0 to 3.1 were developed by Sandia for the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office (HFTO). The U.S. DOE Vehicle Technologies Office (VTO) and U.S. Department of Transportation (DOT) Pipeline and Hazardous Material Safety Administration (PHMSA) contributed to the development of HyRAM+ version 4.0 regarding the addition of methane (natural gas) and propane models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-10862 O

Groth, Katrina↗

DOE OSTI2022

HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.4.1.1

Groth, Katrina↗