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A reduced model for the ITER divertor based on SOLPS solutions for ITER Q = 10 baseline conditions: A. identifying options for the control parameters*

Edge codes such as SOLPS coupled to neutral codes such as EIRENE have become so comprehensive and sophisticated that they now constitute, in effect, 'code-experiments' that, as for actual experiments, can benefit from interpretation using simple models and conceptual frameworks, i.e. reduced models. The first task is the identification of options for the reduced model control parameters that are best suited for control of the action of the divertor, i.e. for control of target power loading and sputter-erosion, primarily. A strong correlation between the electron temperature at the divertor target, T e,t , and the neutral deuterium D 2 density at the target, n D2,t , flux-tube resolved, has recently been reported for a number of code studies including SOLPS-4.3 modeling of a set of ~50 ITER baseline cases: Q DT = 10, q 95 = 3, P SOL = 100 MW, metallic walls, and Ne seeding. This part A of the present study reports new results for largely the same ITER cases, confirming the strong correlations reported earlier between local values of T e,t , and (i) n D2,t , and (ii) normalized volumetric losses of power and pressure in the divertor. Strong correlations have now also been found, and are reported here for the first time, between T e,t and all of the divertor target quantities of practical interest. A physical explanation for this surprising result has not been fully identified; nevertheless it has encouraging implications for reduced modeling of the ITER divertor. For such ITER conditions, (i) the global Ne injection rate, Inj Ne [Ne/s], and (ii) the electron temperature at the location on the target where the peak power deposition occurs, T e,t @q ⊥,pk (eV), are found to be promising reduced model control parameters. In the companion report, part B, a reduced model for the ITER divertor is developed and described in detail, based on reversed-direction 2 point modelling, Rev2PM. The input to the reduced model is a value of the variable pair (T et @q ⟂,pk ,Inj Ne ) and the output are values of the various target as well as divertor-entrance quantities of practical interest, e.g. q ⊥,pk , n e,Xpt (the electron density at the poloidal location of the X-point), etc. In part B the reduced model is quantitatively characterized using one half of the code cases; it is then used to successfully predict (replicate) the code values of e.g. n e,Xpt for the other half of the cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Surrogate Hessian accelerated structural optimization for stochastic electronic structure theories

In this work, we present an efficient energy-based method for structural optimization with stochastic electronic structure theories, such as diffusion quantum Monte Carlo (DMC). This method is based on robust line-search energy minimization in reduced parameter space, exploiting approximate but accurate Hessian information from a surrogate theory, such as density functional theory. The surrogate theory is also used to characterize the potential energy surface, allowing for simple but reliable ways to maximize statistical efficiency while retaining controllable accuracy. We demonstrate the method by finding the minimum DMC energy structures of the selected flake-like aromatic molecules, such as benzene, coronene, and ovalene, represented by 2, 6, and 19 structural parameters, respectively. In each case, the energy minimum is found within two parallel line-search iterations. The method is near-optimal for a line-search technique and suitable for a broad range of applications. It is easily generalized to any electronic structure method where forces and stresses are still under active development and implementation, such as diffusion Monte Carlo, auxiliary-field Monte Carlo, and stochastic configuration interaction, as well as deterministic approaches such as the random-phase approximation. Accurate and efficient means of geometry optimization could shed light on a broad class of materials and molecules, showing high sensitivity of induced properties to structural variables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Microstructure Variability in Vapor-Deposited Energetic Materials by Using Phase-Field Methods

Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.

36 MATERIALS SCIENCE↗

A Lagrangian discontinuous Galerkin hydrodynamic method

Here, we present a new Lagrangian discontinuous Galerkin (DG) hydrodynamic method for solving the two-dimensional gas dynamic equations on unstructured hybrid meshes. The physical conservation laws for the momentum and total energy are discretized using a DG method based on linear Taylor expansions. Three different approaches are investigated for calculating the density variation over the element. The first approach evolves a Taylor expansion of the specific volume field. The second approach follows certain finite element methods and uses the strong mass conservation to calculate the density field at a location inside the element or on the element surface. The third approach evolves a Taylor expansion of the density field. The nodal velocity, and the corresponding forces, are explicitly calculated by solving a multidirectional approximate Riemann problem. An effective limiting strategy is presented that ensures monotonicity of the primitive variables. This new Lagrangian DG hydrodynamic method conserves mass, momentum, and total energy. Results from a suite of test problems are presented to demonstrate the robustness and expected second-order accuracy of this new method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Co-optimization of fuel properties, combustion system geometry, and injection strategy for conventional diesel fuel

Here, studies have shown that fuel properties can impact an engine’s operation in several ways, including ignition delay, sooting tendency, mixture formation, and combustion temperature. In mixing-controlled compression ignition (MCCI) engines, the fuel system design and piston bowl geometry significantly affect combustion performance and emissions. Based on current information, it is difficult to draw conclusions about fuel property effects and sensitivities. The central fuel hypothesis approach used in the US Department of Energy Co-Optima program has worked well for spark ignition fuels: identifying critical fuel property ranges is sufficient to screen fuel blends that are expected to maximize efficiency and reduce pollutant emissions. However, for MCCI-relevant fuels, the information gained from past studies is not sufficient to build such a merit function or to allow for performing a similar screening of fuel blends. It is hypothesized that a co-optimization of a fuel’s physical and chemical properties, combustion system geometry, and injection strategy could leverage synergies between the effects of the fuel properties and geometries, resulting in improved performance over state-of-the-art. A machine learning–assisted unconstrained global optimization algorithm was used to explore a design space comprising 23 independent variables. The results show that physical property effects were minimal even for large variations in fuel properties, and the only interaction effect that was observed was the effect of varied fuel density parameters on fuel/air mixture formation. Nevertheless, these interactions were not sufficient in magnitude to significantly affect optimization results. Therefore, analysis of the results suggests that fuel physical properties cannot be leveraged in a co-optimization context to increase engine efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Sensing ultrashort electronic coherent beating at conical intersections by single-electron pulses

In a theoretical study, we present an ultrafast technique for probing time-dependent molecular charge densities. An ultrafast optical pump first brings the molecule into an electronic nonstationary state. This is followed by coherent inelastic scattering of a broadband single-electron probe pulse with a variable delay T, which is detected spectrally. The technique is applied to reveal phase-sensitive background-free coherent electron beating in the conical intersection passage in uracil and reveals the otherwise elusive coherent beating of strongly coupled electrons and nuclei.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evidence for GeV cosmic rays from white dwarfs in the local cosmic ray spectra and in the gamma-ray emissivity of the inner Galaxy

Here, recent observations found that electrons are accelerated to ~10 GeV and emit synchrotron hard X-rays in two magnetic white dwarfs (WDs), also known as cataclysmic variables (CVs). In nova outbursts of WDs, multi-GeV gamma-rays were detected, implying that protons are accelerated to 100 GeV or higher. In recent optical surveys, the WD density is found to be higher near the Sun than in the Galactic disk by a factor ~2.5. The cosmic rays (CRs) produced by local CVs and novae will accumulate in the local bubble for 10 6 –10 7 yr. On these findings, we search for CRs from historic CVs and novae in the observed CR spectra. We model the CR spectra at the heliopause as sums of Galactic and local components based on observational data as much as possible. The initial Galactic CR electron and proton spectra are deduced from the gamma-ray emissivity, the local electron spectrum from the hard X-ray spectra at the CVs, and the local proton spectrum from gamma-ray spectra at novae. These spectral shapes are then expressed in a simple set of polynomial functions of CR energy and regressively fitted until the high-energy (>100 GeV) CR spectra near Earth and the Voyager-1 spectra at the heliopause are reproduced. We then extend the modeling to nuclear CR spectra and find that one spectral shape fits all local nuclear CRs, and that the apparent hardening of the nuclear CR spectra is caused by the roll-down of local nuclear spectra around 100–200 GeV. All local CR spectra populate a limited energy band below 100–200 GeV and enhance gamma-ray emissivity below ~10 GeV. Such an enhancement is observed in the inner Galaxy, suggesting the CR fluxes from CVs and novae are substantially higher there.

79 ASTRONOMY AND ASTROPHYSICS↗

HiFiPDV2 v. 2

SAND2024-01061O The HiFiPDV-2 software is similar to other photonic Doppler velocimetry (PDV) analysis codes in that it converts signals from intensity-time space to frequency-time space using a short-time Fourier transform (STFT). It then analyzes peaks of the resulting power spectral density information to extract the velocity-time history. The unique aspects of HiFiPDV and HiFiPDV-2 are that this reduction process is repeated for an array of reasonable STFT input variables. The resulting population distribution of output velocity-time histories is evaluated to determine the most likely velocity history and its associated uncertainty. This uncertainty is defined as the systematic uncertainty of the PDV signal as it is a function of input values to the reduction process. The HiFiPDV-2 program brings new functionality and efficiency to these calculations—most notably significant reductions in memory usage and calculation times, the ability to evaluate frequency-shifted signals, and the ability to filter out baseline signals. Developers recommend that users have at least 2 GB of RAM per CPU core in their system. 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.

Voorhees, Travis↗

Effects of forest degradation classification on the uncertainty of aboveground carbon estimates in the Amazon

Tropical forests are critical for the global carbon budget, yet they have been threatened by deforestation and forest degradation by fire, selective logging, and fragmentation. Existing uncertainties on land cover classification and in biomass estimates hinder accurate attribution of carbon emissions to specific forest classes. In this study, we used textural metrics derived from PlanetScope images to implement a probabilistic classification framework to identify intact, logged and burned forests in three Amazonian sites. We also estimated biomass for these forest classes using airborne lidar and compared biomass uncertainties using the lidar-derived estimates only to biomass uncertainties considering the forest degradation classification as well. Our classification approach reached overall accuracy of 0.86, with accuracy at individual sites varying from 0.69 to 0.93. Logged forests showed variable biomass changes, while burned forests showed an average carbon loss of 35%. We found that including uncertainty in forest degradation classification significantly increased uncertainty and decreased estimates of mean carbon density in two of the three test sites. Our findings indicate that the attribution of biomass changes to forest degradation classes needs to account for the uncertainty in forest degradation classification. By combining very high-resolution images with lidar data, we could attribute carbon stock changes to specific pathways of forest degradation. This approach also allows quantifying uncertainties of carbon emissions associated with forest degradation through logging and fire. Both the attribution and uncertainty quantification provide critical information for national greenhouse gas inventories.

54 ENVIRONMENTAL SCIENCES↗

Converging towards atomic and nuclear pressures (Final Report)

his report details the development of transformational tools and techniques, allowing the accurate characterization of matter at the most extreme conditions yet studied in the high energy density (HED) domain. Before this work, most experiments quantitatively mapping the nature of matter in the HED realm were performed using planar geometry, which allows for the isolation and measurement of variables in a single thermodynamic state. Such measurements include equation of state variables, optical conductivity, heat transport and more. However, due to a variety of plasma processes, such experiments are limited to below ~10 TPa (100 Mbar) pressures. To achieve higher pressures, convergent experiments are needed. Historically, convergent experiments have not been used for benchmark data because they are integral measurements. That is each part of a convergent target undergoes a time dependent wide range of states, making it difficult to accurately isolate any particular quantity for a given thermodynamic state. This effort developed innovative convergent HED platforms and techniques enabling the exploration of matter from atomic to nuclear scale pressures. This effort also performed pioneering experiments that yielded the first rigorous benchmark data at these extreme conditions. This funding award began with the overarching goal to understand the behavior of matter at extreme (atomic-to-nuclear scale) pressures. The motivation for these goals lie in the fact that every time scientists explore matter beyond the threshold of an atomic unit, there is a fundamental shift in science. The atomic unit for energy, mass, charge, length, and time have each been explored, and each time such a threshold was crossed, a new sequence of discoveries was made resulting in significant awards such as the Nobel Prize. The only unexplored atomic unit is pressure, and this effort set the course for exploring matter at and beyond such pressures. That most of the recently discovered extrasolar planets and stars, as well as matter in the late implosion stages of inertial fusion targets, have deep internal pressures at and beyond atomic pressures amplifies the importance of this effort. Much of the initial work in developing techniques to create these atomic-to-nuclear pressures already existed within the HED community, predominantly at large scale laser facilities such as the National Ignition Facility (NIF) and the Omega60 laser the University of Rochester and although these experiments were routinely performed the ability to extract information about the underlying physical states and processes remained elusive due to the complexity of the experiments, extreme scales in both time and space, and the integrated nature of all the measurements. This work built a rigorous framework so such measurements can routinely be made. This was done in part through the introduction of Bayesian inference techniques into the field of HED science. These techniques allow for the self-consistent extraction of the relevant variables and their explicit and implicit correlations, so as to make use of integrated experimental data to constrain physical models and provide accurate uncertainty bounds for the data. The techniques developed here are fully transparent and proved immediately useful providing quantitative rigorous benchmarks for physical states and processes at some of the most extreme conditions yet explored on Earth. This funding is directly or partly responsible for 7 publications in major peer-reviewed scientific journals, a doctoral thesis, 3 invited talks at major conferences, and the training of a post-doc, 2 graduate students, and 1 undergraduate student. Beyond the effort supported by this award launched the introduction of Bayesian inference into the HED physics community and helped push the usage if modern data-science techniques within the physics community at large.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Variability in the Position of the IBEX Ribbon over Nine Years: More Observational Evidence for a Secondary ENA Source

The ribbon of enhanced energetic neutral atom flux, discovered by the Interstellar Boundary Explorer (IBEX) in 2009, has redefined our understanding of the heliosphere's interaction with the local interstellar medium (LISM). Yet, its origin continues to be a topic of scientific debate. The ribbon is circular and traces the region where the putative LISM magnetic field (B LISM ) is perpendicular to the radial direction from the Sun. Using nine years of IBEX-Hi observations, we investigate the ribbon circularity and location as functions of time and energy. We provide updated locations of the ribbon center at five energy passbands (centered at 0.7, 1.1, 1.7, 2.7, and 4.3 keV) in ecliptic coordinates [longitude, latitude]: [217$_˙^°$dg41 ± 0$_˙^°$dg95, 44$_˙^°$dg36 ± 0$_˙^°$dg93], [219$_˙^°$dg72 ± 0$_˙^°$dg95, 41$_˙^°$dg50 ± 0$_˙^°$dg87], [220$_˙^°$dg51 ± 1$_˙^°$dg19, 39$_˙^°$dg96 ± 1$_˙^°$dg00], [218$_˙^°$dg08 ± 1$_˙^°$dg66, 38$_˙^°$dg44 ± 1$_˙^°$dg24], and [214$_˙^°$dg68 ± 1$_˙^°$dg48, 34$_˙^°$dg13 ± 1$_˙^°$dg19] respectively. The weighted mean center location over all energies and all years is [218$_˙^°$dg33 ± 0$_˙^°$dg68, 40$_˙^°$dg38 ± 0$_˙^°$dg88] and its radius is 74$_˙^°$dg81 ± 0$_˙^°$dg65. As viewed by IBEX at 1 au, we find that (1) the ribbon is stable over time, with distinct centers at each energy; (2) ribbon centers exhibit small temporal variations, likely caused by the solar wind (SW) speed and density variations; and (3) ribbon location in the sky appears to be driven by (i) the inherent alignment of the ribbon centers along the plane connecting the presumed B LISM and the heliospheric upwind direction, and (ii) the variable SW structure along the heliographic meridian, further emphasizing that the ribbon source is outside the heliosphere.

79 ASTRONOMY AND ASTROPHYSICS↗

Ground Motion and Intraevent Variability from 3D Deterministic Broadband (0-7.5 Hz) Simulations along a Nonplanar Strike-Slip Fault

In the article, we model deterministic broadband (-7.5 Hz) ground motion from an M w 7.1 bilateral strike-slip earthquake scenario with dynamic rupture propagation along a rough-fault topography embedded in a medium including small-scale velocity and density perturbations. Spectral accelerations (SAs) at periods 0.2-3 s and Arias intensity durations show a similar distance decay (at the level of 1-2 interevent standard deviations above the median) when compared to Next Generation Attenuation-West2 (NGA)-West2 ground-motion prediction equations (GMPEs) using a Q(f) power-law exponent of 0.6-0.8 above 1 Hz in models with a minimum V S of 750 m/s. With a trade-off from Q(f), the median ground motion is slightly increased by scattering from statistical models of small-scale heterogeneity with standard deviation (σ) of the perturbations at the lower end of the observed range (5%) but reduced by scattering attenuation at the upper end (10%) when using a realistic 3D background velocity model. The ground-motion variability is strongly affected by the addition of small-scale media heterogeneity, reducing otherwise large values of intraevent standard deviation closer to those of empirical observations. These simulations generally have intraevent standard deviations for SAs lower than the GMPEs for the modeled bandwidth, with an increasing trend with distance (most pronounced in low-to-moderate scattering media) near the level of observations at distances greater than 35 km from the fault. Durations for the models follow the same increasing trend with distance, in which σ~5% produces the best match to GMPE values. We find that a 3D background-velocity model reduces the pulse period into the expected range by breaking up coherent waves from directivity, generating a lognormal distribution of ground-motion residuals. These results indicate that a strongly heterogeneous medium is needed to produce realistic deterministic broadband ground motions. Finally, the addition of a thin surficial layer with low, frequency-independent Q in the model (with a minimum V S of 750 m/s) controls the high-frequency decay in energy, as measured by the parameter κ, that may be necessary to include as simulations continue to extend to higher frequencies.

Geochemistry & Geophysics↗

A robust and efficient finite volume method for compressible inviscid and viscous two-phase flows [A robust and efficient finite volume method for compressible viscous two-phase flows]

A robust and efficient density-based finite volume method is developed for solving the six-equation single pressure system of two-phase flows at all speeds on hybrid unstructured grids. Unlike conventional approaches where an expensive exact Riemann solver is normally required for computing numerical fluxes at the two-phase interfaces in addition to AUSM-type fluxes for single-phase interfaces in order to maintain stability and robustness in cases involving interactions of strong pressure and void-fraction discontinuities, a volume-fraction coupling term for the AUSM + -up fluxes is introduced in this work to impart the required robustness without the need of the exact Riemann solver. The resulting method is significantly less expensive in regions where otherwise the Riemann solver would be invoked. A transformation from conservative variables to primitive variables is presented and the primitive variables are then solved in the implicit method in order for the current finite volume method to be able to solve, effectively and efficiently, low Mach number flows in traditional multiphase applications, which otherwise is a great challenge for the standard density-based algorithms. Here, a number of benchmark test cases are presented to assess the performance and robustness of the developed finite volume method for both inviscid and viscous two-phase flow problems. The numerical results indicate that the current density-based method provides an attractive and viable alternative to its pressure-based counterpart for compressible two-phase flows at all speeds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Novel PCB Winding Transformer with Controllable Leakage Integration for a 6.6kW 500kHz High Efficiency High Density Bi-Directional On-Board Charger

Printed Circuit Board (PCB) transformer has been widely used in low power applications. Compared with conventional litz-wire transformer, the manufacture process is greatly simplified and the parasitic is much easier to control. However, in high power applications like on-board charger for electric vehicle, no one has ever done it due to the limitation of high winding loss and high multi-layer PCB cost. The emerging wideband- gap devices provide the opportunity to adopt PCB transformer in high power applications. In addition, the low inductance requirement brought by high frequency also makes it possible to realize magnetic integration in PCB transformer. In this paper, by using a two stage variable DC-link voltage structure, a novel 6-layer only PCB winding transformer structure is proposed for the second stage of the 6.6kW on-board charger, of which leakage inductance is controllable without sacrificing winding loss. A 6.6kW 500kHz prototype with almost 98% efficiency and 130W/in3 power density is built to verify the feasibility of the proposed PCB winding transformer.

42 ENGINEERING↗

Introducing the GeoRePORT Resource Size Tool: Reporting on Geothermal Resource Size Estimations Using the Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT): Preprint

The Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) was developed with funding from the U.S. Department of Energy Geothermal Technologies Office to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. The assessment protocols used in GeoRePORT allow for comparison of project attributes across locations and geological settings to understand the feasibility of geothermal development. This work introduces the Resource Size Tool, a new feature within the GeoRePORT package that compiles two independent methods for estimating geothermal resource size in terms of energy capacity in MW. Energy production potential for twenty-three case studies was estimated with the Resource Size Tool in order to 1) generate a reasonable range of resource size estimates for a particular geothermal field; 2) illustrate the advantages and limitations of each methodology (such as data input requirements, estimate accuracy and precision, and the appropriate circumstances of use); and 3) test the ability of the resource size tool to provide useful and accurate information for geothermal stakeholders. The tool employs two methods widely used in the geothermal industry: (1) USGS Volumetric and (2) Power Density. Results from our case studies show general overlap between these two methods in terms of resource size estimates; however, they also reveal key differences between the two approaches that should be considered when using such estimates to drive development. First, the two methods rely on different input parameters and therefore one method may be more appropriate and/or accurate for a given project than the other. Second, the Power Density method was found to generate wider ranges of resource size predictions, more consistently aligning with actual power production of the field but with larger scales of error; whereas the USGS Volumetric method predicts narrower ranges but tends to overestimate when compared to current MW production. Future work will refine variables used in the methods with input data from other sections of GeoRePORT and modify uncertainty levels based on the particular datasets used for a given project.

geological↗

A reduced model for the ITER divertor based on SOLPS solutions for ITER Q = 10 baseline conditions: B. A reduced model based on reversed-direction two point modeling

Edge codes such as SOLPS coupled to neutral codes such as EIRENE have become so comprehensive and sophisticated that they now constitute, in effect, 'code-experiments' that, as for actual experiments, can benefit from interpretation using simple models and conceptual frameworks, i.e. reduced models. The first task is the identification of options for the reduced model control parameters that are best suited for control of the action of the divertor, i.e. for control of target power loading and sputter–erosion, primarily. A strong correlation between the electron temperature at the divertor target, T e,t , and the neutral deuterium D 2 density at the target, n D2,t , flux-tube resolved, has recently been reported for a number of code studies including SOLPS-4.3 modeling of a set of ~50 ITER baseline cases: Q DT = 10, q 95 = 3, P SOL = 100 MW, metallic walls, and Ne seeding (Pitts et al 2019). Part A of the present study reports new results for largely the same ITER cases, confirming the strong correlation reported earlier between local values of T e,t , and (i) n D2,t , and (ii) normalized volumetric losses of power and pressure in the divertor. Strong correlations have now also been found, and are reported here for the first time, between T e,t and all of the divertor target quantities of practical interest. A physical explanation for this surprising result has not as yet been fully identified; nevertheless it has encouraging implications for reduced modeling of the ITER divertor. For such ITER conditions, (i) the global Ne injection rate, Inj Ne (Ne s –1 ), and (ii) the electron temperature at the location on the target where the peak power deposition occurs, T e,t @q ⊥,pk (eV), are found to be promising reduced model control parameters. In this part B, a reduced model for the ITER divertor is developed and described in detail, based on reversed-direction two point modeling, Rev2PM. The input to the reduced model is a value of the variable pair (T e,t @q ⊥,pk , Inj Ne )for a chosen case and the output are values of the various target as well as divertor-entrance quantities of practical interest, e.g. q ⊥,pk , the electron density at the X-point, n e,Xpt , etc. The reduced model was quantitatively characterized using one half of the code cases; it was then used to successfully predict (replicate) the code values of e.g. n e,Xpt for the other half.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A priori filtered chemical source term modeling for LES of high Karlovitz number premixed flames

Assumptions behind closure models for the filtered source term are studied a priori using results from DNS of turbulent n-heptane/air premixed flames at varying Karlovitz numbers. Simulations with both detailed chemistry and tabulated chemistry, as well as unity and non-unity Lewis numbers, are used to determine if finite-rate chemistry and differential diffusion effects affect the filtered chemical source terms. While the unfiltered source term shows large fluctuations, the filtered source terms from detailed chemistry and tabulated chemistry are in good agreement at sufficiently large filter widths (Δ ≳ l F ). Using the concept of optimal estimators, it is shown that a tabulation approach using the filtered progress variable and its variance can predict accurately the filtered chemical source terms. Finally, the filtered source terms from the DNS are compared to predictions from two commonly assumed sub-filter probability density function models. Both models show deviations from the filtered DNS source terms but predict accurately the mean turbulent flame speed. In conclusion, the results illustrate the potential of using simple tabulated chemistry approaches based on presumed PDFs for LES of premixed flames in the thin and distributed reaction zones regimes.

33 ADVANCED PROPULSION SYSTEMS↗

Controlling extrapolations of nuclear properties with feature selection

Predictions of nuclear properties far from measured data are inherently inaccurate because of uncertainties in our knowledge of nuclear forces and in our treatment of quantum many-body effects in strongly-interacting systems. While the model bias can be directly calculated when experimental data is available, only an estimate can be made in the absence of such measurements. Current approaches to compute the estimated bias quickly lose predictive power when their input variables are taken far from the training region, resulting in uncontrolled uncertainties in applications such as nucleosynthesis simulations. In this letter, we present a novel technique to identify the input variables of machine learning algorithms that can provide robust estimates of model bias. Our process is based on selecting input variables, or features, based on their probability distribution functions across the entire nuclear chart. We illustrate our approach on the problem of quantifying the model bias in nuclear binding energies calculated with Density Functional Theory (DFT). We prove that building model biases with only Z and N as features leads to highly unreliable extrapolations. Conversely, we show that proper feature selection can systematically improve theoretical predictions without increasing uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗