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NASA NTRS1994

The Determination of Forces and Moments on a Gimballed SRM Nozzle Using a Cold Flow Model

The Solid Rocket Motor Air Flow Facility (SAF) at NASA Marshall Space Flight Center was used to characterize the flow in the critical aft end and nozzle of a solid propellant rocket motor (SRM) as part of the design phase of development. The SAF is a high pressure, blowdown facility which supplies a controlled flow of air to a subscale model of the internal port and nozzle of a SRM to enable measurement and evaluation of the flow field and surface pressure distributions. The ASRM Aft Section/Nozzle Model is an 8 percent scale model of the 19 second burn time aft port geometry and nozzle of the Advanced Solid Rocket Motor, the now canceled new generation space Shuttle Booster. It has the capability to simulate fixed nozzle gimbal angles of 0, 4, and 8 degrees. The model was tested at full scale motor Reynolds Numbers with extensive surface pressure instrumentation to enable detailed mapping of the surface pressure distributions over the nozzle interior surface, the exterior surface of the nozzle nose and the surface of the simulated propellant grain in the aft motor port. A mathematical analysis and associated numerical procedure were developed to integrate the measured surface pressure distributions to determine the lateral and axial forces on the moveable section of the nozzle, the effective model thrust and the effective aerodynamic thrust vector (as opposed to the geometric nozzle gimbal angle). The nozzle lateral and axial aerodynamic loads and moments about the pivot point are required for design purposes and require complex, three dimensional flow analyses. The alignment of the thrust vector with the nozzle geometric centerline is also a design requirement requiring three dimensional analyses which were supported by this experimental program. The model was tested with all three gimbal angles at three pressure levels to determine Reynolds number effects and reproducibility. This program was successful in demonstrating that a measured surface pressure distribution could be integrated to determine the lateral and axial loads, moments and thrust vector alignment for the scaled model of a large space booster nozzle. Numerical results were provided which are scaleable to the full scale rocket motor and can be used as benchmark data for 3-D CFD analyses.

Whitesides, R. Harold↗

DOE OSTI2019

The 2019 Edition of the IRPhEP Handbook

The International Reactor Physics Experiment Evaluation Project (IRPhEP) [1] was established to preserve and evaluate integral reactor physics experiment data, including separate or special effects measurements for nuclear energy and technology applications. Numerous international experiments have been performed over the past several decades to support reactor operations, safety, measurements, and design. Those experiments represent a significant investment of infrastructure, cost, and expertise that, in many instances, cannot be as easily reproduced. They represent valuable resources of data for present and future research, and provide the basis for recording, development, and validation of methods [2]. The primary focus of the IRPhEP is to provide an extensively peer-reviewed set of reactor physics integral data suitable for reactor designers and safety analysts to not just validate the analytical tools necessary to design next-generation nuclear reactors, but to establish the safety basis for their operation. Contributors worldwide collaborate to evaluate and review selected benchmark experiments for inclusion in the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook) [3]. More detailed discussion of the IRPhEP, including highlighted reactor physics benchmark evaluations, can be found in the November and December 2014 editions of Nuclear Science and Engineering [1]. Several new evaluations, and revisions to existing benchmarks have been prepared for inclusion in the 2019 edition of the IRPhEP Handbook (see Table I).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks

Hyperparameters employed by deep learning (DL) methods play a substantial role in the performance and reliability of these methods in practice. Unfortunately, finding performance-optimizing hyperparameter settings is a notoriously difficult task. Hyperparameter search methods typically have limited production-strength implementations or do not target scalability within a highly parallel machine, portability across different machines, experimental comparison between different methods, and tighter integration with workflow systems. In this paper, we present DeepHyper, a Python package that provides a common interface for the implementation and study of scalable hyperparameter search methods. It adopts the Balsam workflow system to hide the complexities of running large numbers of hyperparameter configurations in parallel on high-performance computing (HPC) systems. We implement and study asynchronous model-based search methods that consist of sampling a small number of input hyperparameter configurations and progressively fitting surrogate models over the input-output space until exhausting a user-defined budget of evaluations. We evaluate the efficacy of these methods relative to approaches such as random search, genetic algorithms, Bayesian optimization, and hyperband on DL benchmarks on CPU- and GPU-based HPC systems.

Balaprakash, Prasanna↗

DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗

DOE OSTI2025

Integration and Quantitative Comparison of Up-Scaled Molecular Observation Network Data with Existing Soil Databases

MONet provides novel soil molecular data to the research community for understanding biogeochemical processes and complementing other soil datasets. This study assesses MONet's ability to replicate known soil patterns via a comparative analysis of soil respiration (Rs), pH, and clay content against benchmark datasets. Results show moderate agreement for pH and clay content, highlighting MONet's strengths in capturing soil biogeochemical variation in underrepresented regions like urban areas. Rs data are marked by the appropriate trends relative to other datasets, but direct comparison is impractical due to methodological differences in underlying data. Strategic sampling is recommended to improve MONet's coverage and eventual utility in bridging molecular observations with global datasets.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

ABSOLUTE INTEGRAL CROSS SECTIONS AND PRODUCT BRANCHING RATIOS FOR THE VIBRATIONALLY SELECTED ION-MOLECULE REACTIONS: N{sub 2}{sup +}(X {sup 2}{Sigma}{sub g}{sup +}; v {sup +} = 0-2) + CH{sub 4}

Absolute vibrationally selected integral cross sections ({sigma}{sub v+}'s) for the ion-molecule reaction N{sub 2}{sup +}(X {sup 2}{Sigma}{sub g}{sup +}; v {sup +} = 0-2) + CH{sub 4} have been measured by using the newly developed vacuum ultraviolet (VUV) laser pulsed field ionization-photoion (PFI-PI) double-quadrupole-double-octopole ion guide apparatus. By employing a novel electric field pulsing scheme to the VUV laser PFI-PI source, we have been able to prepare reactant N{sub 2}{sup +} ions in single-vibrational quantum states with not only high intensity and high purity but also high kinetic energy resolution, allowing integral cross section measurements to be conducted in the center-of-mass kinetic energies (E{sub cm}'s) from 0.05 to 10.00 eV. Three primary product channels corresponding to the formations of CH{sub 3}{sup +}, CH{sub 2}{sup +}, and N{sub 2}H{sup +} were identified. After correcting for the secondary reactions involving CH{sub 3}{sup +} and CH{sub 2}{sup +}, we have determined the {sigma}{sub v+} values of the formation of these primary product ions, {sigma}{sub v+}(CH{sub 3}{sup +}), {sigma}{sub v+}(CH{sub 2}{sup +}), and {sigma}{sub v+}(N{sub 2}H{sup +}), and their branching ratios, [{sigma}{sub v+}(CH{sub 3}{sup +}): {sigma}{sub v+}(CH{sub 2}{sup +}): {sigma}{sub v+}(N{sub 2}H{sup +})]/{sigma}{sub v+}(CH{sub 3}{sup +} + CH{sub 2}{sup +} + N{sub 2}H{sup +}), v {sup +} = 0-2, in the E{sub cm} range of 0.05-10.00 eV, where {sigma}{sub v+}(CH{sub 3}{sup +} + CH{sub 2}{sup +} + N{sub 2}H{sup +}) = {sigma}{sub v+}(CH{sub 3}{sup +}) + {sigma}{sub v+}(CH{sub 2}{sup +}) + {sigma}{sub v+}(N{sub 2}H{sup +}). The branching ratios are found to be nearly independent of the v {sup +} state and E{sub cm}. Complex v {sup +}-state and E{sub cm} dependences for {sigma}{sub v+}(CH{sub 3}{sup +}), {sigma}{sub v+}(CH{sub 2}{sup +}), and {sigma}{sub v+}(N{sub 2}H{sup +}) along with vibrational inhibition for the formation of these product ions are observed. The vibrational effects on the {sigma}{sub v+} values are sufficiently large to warrant the inclusion of the vibrationally excited reactions N{sub 2}{sup +}(X {sup 2}{Sigma}{sub g}{sup +}; v {sup +} {>=} 1) + CH{sub 4} for a more realistic modeling of the ion and neutral densities observed in the atmosphere of Titan. The cross-sectional data obtained in the present study are also useful for benchmarking theoretical calculations on ion-neutral collision dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

Theoretical Approaches to Describing the Oxygen Reduction Reaction Activity of Single-Atom Catalysts

Single-atom catalysts have recently emerged as promising low-cost alternatives to Pt for the oxygen reduction reaction (ORR). Given the unique properties that distinguish these systems from traditional transition-metal electrocatalysts, it is essential to benchmark and establish appropriate computational approaches to study these novel materials. Herein, we employ multiple levels of theory, including wave function methods, density functional theory (DFT), and classical simulations, to investigate Cu-modified covalent triazine framework catalysts (Cu/CTF). We consider three major aspects of treating this system computationally. First, we present a step-wise approach to predict the ORR mechanism and adsorbate coverages on Cu/CTF. We then benchmark various DFT methods to coupled-cluster theory with the domain-based local pair natural orbital approximation, which indicates that HSE06 and PBE0 hybrid functionals most accurately describe the adsorption energies of ORR adsorbates on Cu/CTF. We finally employ thermodynamic integration and other techniques to consider solvation effects, which play significant roles in predicting the energies of reaction intermediates and the overall ORR pathway. Lastly, our findings indicate that accurate descriptions of both the electronic structure and solvation are necessary to understand the ORR activity of Cu/CTF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

The density matrix functional approach to electron correlation: Dynamic and nondynamic correlation along the full dissociation coordinate

For chemistry an accurate description of bond weakening and breaking is vital. The great advantage of density matrix functionals, as opposed to density functionals, is their ability to describe such processes since they naturally cover both nondynamical and dynamical correlation. This is obvious in the Löwdin-Shull functional, the exact natural orbital functional for two-electron systems. We present in this paper extensions of this functional for the breaking of a single electron pair bond in N-electron molecules, using LiH, BeH{sup +}, and Li{sub 2} molecules as prototypes. Attention is given to the proper formulation of the functional in terms of not just J and K integrals but also the two-electron L integrals (K integrals with a different distribution of the complex conjugation of the orbitals), which is crucial for the calculation of response functions. Accurate energy curves are obtained with extended Löwdin-Shull functionals along the complete dissociation coordinate using full CI calculations as benchmark.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Thermally generated magnonic spin currents in a polycrystalline gadolinium iron garnet thin film with perpendicular magnetic anisotropy

Rare-earth iron garnets (REIGs) are the benchmark systems for magnonics, including the longitudinal spin Seebeck effect (LSSE). While most research has focused on single-crystalline REIGs on complimentary garnet substrates, moving to more, cost-effective complementary metal-oxide semiconductor (CMOS)-compatible substrates is important to integrate REIG thin films with existing technology. In this regard, we grow a 130 nm-thick polycrystalline gadolinium iron garnet (GdIG) film on the Si/SiO2 substrate and investigate the temperature-dependent LSSE. Interestingly, the polycrystalline GdIG film exhibits perpendicular magnetic anisotropy (PMA) at room temperature which is induced by tensile in-plane (IP)-strain originating from the thermal-expansion mismatch between the GdIG film and the substrate during rapid thermal annealing. Further, a spin-reorientation transition from the out-of-plane IP direction below TS = 180 K is observed. Additionally, the film reveals a magnetic compensation temperature, TComp, of ≈240 K. The LSSE voltage not only demonstrates a sign-inversion around TComp, but also shows noticeable changes around TS. As compared to a single-crystalline GdIG film, the lower LSSE voltage for the polycrystalline GdIG is attributed to the higher effective magnetic anisotropy and enhanced magnon scattering at the grain boundaries. Our study not only paves the way for the cost-effective growth of CMOS-compatible REIG-based systems with PMA for magnonic memory and information processing applications, but also highlights the fact that the spincaloritronic and spin-insulatronic properties of the polycrystalline REIGs follow those of their single-crystalline counterparts with reduced spin-to-charge conversion efficiency through LSSE which can be tuned further by controlling the average gran size and interface engineering.

Physics↗

DOE OSTI2022

Anisotropic angular scattering models of elastic electron-neutral collisions for Monte Carlo plasma simulations

Many laboratory and industrial plasma applications require accurate modeling techniques to understand the interplay between microscopic and macroscopic processes. A prime example of this interplay is how particle and Monte Carlo (MC) simulation codes describe angular scattering of electrons following elastic scattering events. The forward peaked nature of high energy electron elastic scattering is relatively trivial to accurately describe in plasma simulations. However, for lower energy collisions, which produce near isotropic or backward peaked differential cross sections, there is not a strong consensus among the plasma modeling community on how to best describe these angular scattering trends. Here, in this study, we propose a systematic method to approximate the aforementioned non-trivial angular scattering behavior with a formula that can be readily implemented in particle-in-cell (PIC) and/or MC plasma simulation codes. The present approach is specifically applied to fusion relevant atomic hydrogen and helium, as well as for molecular hydrogen, and results are also applicable to the atomic isotopes and homonuclear molecular isotopologues of these species. Comparisons between the present angular distribution function and benchmark scattering data were used to validate the proposed models. In addition, two-term Boltzmann calculations and PIC direct simulation MC simulations revealed that the proposed angular distribution function is accurate, agreeing very well with benchmark convergent close-coupling scattering calculations, and electron transport measurements. These studies confirmed that the present angular distribution function model can be utilized without the need of renormalization to the momentum transfer cross section (as opposed to using the elastic scattering integrated cross section), which has been suggested by several studies in order to correct for deficient angular scattering models, and to agree with transport measurements. Hence, the present anisotropic angular scattering model can be utilized to accurately model the momentum transfer as well as the electron trajectories of elastic collisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Model-agnostic search for dijet resonances with anomalous jet substructure in proton–proton collisions at $\sqrt{s}$ = 13 TeV

This paper presents a model-agnostic search for narrow resonances in the dijet final state in the mass range 1.8-6 TeV. The signal is assumed to produce jets with substructure atypical of jets initiated by light quarks or gluons, with minimal additional assumptions. Search regions are obtained by utilizing multivariate machine-learning methods to select jets with anomalous substructure. A collection of complementary anomaly detection methods - based on unsupervised, weakly supervised, and semisupervised algorithms - are used in order to maximize the sensitivity to unknown new physics signatures. These algorithms are applied to data corresponding to an integrated luminosity of 138 fb -1 , recorded by the CMS experiment at the LHC, at a center-of-mass energy of 13 TeV. No significant excesses above background expectations are seen. Exclusion limits are derived on the production cross section of benchmark signal models varying in resonance mass, jet mass, and jet substructure. Many of these signatures have not been previously sought, making several of the limits reported on the corresponding benchmark models the first ever. When compared to benchmark inclusive and substructure-based search strategies, the anomaly detection methods are found to significantly enhance the sensitivity to a variety of models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates

Characterizing glycans and glycoconjugates in the context of three-dimensional structures is important in understanding their biological roles and developing efficient therapeutic agents. Computational modeling and molecular simulation have become an essential tool complementary to experimental methods. In this work, we present a computational tool, Glycan Modeler for in silico N–/O –glycosylation of the target protein and generation of carbohydrate-only systems. In our previous study, we developed Glycan Reader , a web-based tool for detecting carbohydrate molecules from a PDB structure and generation of simulation system and input files. As integrated into Glycan Reader in CHARMM-GUI, Glycan Modeler (Glycan Reader & Modeler) enables to generate the structures of glycans and glycoconjugates for given glycan sequences and glycosylation sites using PDB glycan template structures from Glycan Fragment Database (http://glycanstructure.org/fragment-db). Our benchmark tests demonstrate the universal applicability of Glycan Reader & Modeler to various glycan sequences and target proteins. We also investigated the structural properties of modeled glycan structures by running 2-μs molecular dynamics simulations of HIV envelope protein. The simulations show that the modeled glycan structures built by Glycan Reader & Modeler have the similar structural features compared to the ones solved by X-ray crystallography. We also describe the representative examples of glycoconjugate modeling with video demos to illustrate the practical applications of Glycan Reader & Modeler . Glycan Reader & Modeler is freely available at http://charmm-gui.org/input/glycan.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Impact of a midband gravitational wave experiment on detectability of cosmological stochastic gravitational wave backgrounds

In this report we make forecasts for the impact a future “midband” space-based gravitational wave experiment, most sensitive to 10 -2 - 10Hz,could have on potential detections of cosmological stochastic gravitational wave backgrounds (SGWBs). Specific proposed midband experiments considered are TianGo, B-DECIGO, and AEDGE. We propose a combined power-law integrated sensitivity (CPLS) curve combining GW experiments over different frequency bands, which shows the midband improves sensitivity to SGWBs by up to two orders of magnitude at 10 -2 - 10 Hz . We consider GW emission from cosmic strings and phase transitions as benchmark examples of cosmological SGWBs. We explicitly model various astrophysical SGWB sources, most importantly from unresolved black hole mergers. Using Markov Chain Monte Carlo, we demonstrated that midband experiments can, when combined with LIGO A+ and LISA, significantly improve sensitivities to cosmological SGWBs and better separate them from astrophysical SGWBs. In particular, we forecast that a midband experiment improves sensitivity to cosmic string tension G μ by up to a factor of 10, driven by improved component separation from astrophysical sources. For phase transitions, a midband experiment can detect signals peaking at 0.1–1 Hz, which for our fiducial model corresponds to early Universe temperatures of T * ~10 4 – 10 6 GeV , generally beyond the reach of LIGO and LISA. The midband closes an energy gap and better captures characteristic spectral shape information. It thus substantially improves measurement of the properties of phase transitions at lower energies of T * ~ O(10 3 ) GeV , potentially relevant to new physics at the electroweak scale, whereas in this energy range LISA alone will detect an excess but not effectively measure the phase transition parameters. Our modeling code and chains are publicly available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Enhancing Solar Power Forecasting with Regularized Constrained Quantile Regression Averaging and Bootstrapping Techniques

Probabilistic solar power forecasting (SPF) plays an essential role in optimizing power-grid operations by quantifying the forecast uncertainty. To improve the accuracy and robustness of probabilistic SPF, this paper introduces the regularized constrained quantile regression averaging (rCQRA) method to combine outputs from multiple PSPF models. In addition, a bootstrapping method was used to quantify model uncertainty, providing insights into the reliability and significance of each ensemble component. To evaluate its efficacy, the proposed rCQRA method is used to integrate four PSPF methods. The resulting SPF models are trained and validated using a real-world six-year dataset from a rooftop solar plant in the USA. The performance of the proposed rCQRA method is evaluated and compared with two benchmark methods under three categories of weather conditions. It is shown that the rCQRA method has superior performance in its forecast reliability, sharpness, and accuracy.

Ensemble learning, probabilistic solar power forec↗

DOE OSTI2015

A position-aware linear solid constitutive model for peridynamics

A position-aware linear solid (PALS) peridynamic constitutive model is proposed for isotropic elastic solids. The PALS model addresses problems that arise, in ordinary peridynamic material models such as the linear peridynamic solid (LPS), due to incomplete neighborhoods near the surface of a body. We improved model behavior in the vicinity of free surfaces through the application of two influence functions that correspond, respectively, to the volumetric and deviatoric parts of the deformation. Furthermore, the model is position-aware in that the influence functions vary over the body and reflect the proximity of each material point to free surfaces. Demonstration calculations on simple benchmark problems show a sharp reduction in error relative to the LPS model.

36 MATERIALS SCIENCE↗

DOE OSTI2018

The Multi-Plume Eddy-Diffusivity/Mass-Flux (EDMF) Unified Parameterization: Stratocumulus and the Transition to Cumulus Boundary Layers

The primary objective of this project is to mitigate inaccuracies and biases in subtropical boundary layer clouds, particularly in oceanic upwelling regions. Our approach began with developing a novel unified boundary layer and convection parameterization, utilizing the multi-plume Eddy-Diffusivity/Mass-Flux (EDMF) framework. We evaluated this advanced stochastic multi-plume EDMF parameterization in an independent single-column model (SCM), benchmarking it against Large-Eddy Simulation (LES) reference data and satellite observations. This version of the EDMF is designed to seamlessly represent a continuum of convective processes, from dry and cloudy boundary layer convection to deep moist convection. We progressed by integrating the stochastic multi-plume EDMF scheme into the Simple Cloud-Resolving E3SM (Energy Exascale Earth System Model) Atmosphere model (SCREAM), coupling it with the SHOC (Simplified Higher-Order Closure) turbulence and convection scheme. This combined approach was then evaluated against LES reference data for both maritime and continental shallow convection within the E3SM SCM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Bottom-up design of actinide materials from molecular clusters: Demonstration of a general-purpose simulation capability leveraging machine-learned atomic potentials

Actinide thin-film coatings such as uranium dioxide (UO 2 ) play an important role in nuclear reactors and other mission-relevant applications, but realization of their potential requires a deep fundamental understanding of the chemical vapor deposition (CVD) processes used for their growth. The slow experimental progress can be attributed, in part, to the standard safety guidelines associated with handling uranium byproducts, which are often corrosive, toxic, and radioactive. Accurate simulation techniques, when used in concert with experiment, can improve laboratory safety, material durability, and deliverable timeframes. However, state-of-the-art computational methods are either insufficiently accurate or intractably expensive. To remedy this situation, in this project we suggested a machine-learning (ML) accelerated workflow for simulating molecular clustering toward deposition. As a benchmark test case, we considered molecular clustering in steam and assessed independent components of our workflow by comparing with measured thermodynamic properties of water. After analyzing each component individually and finding no fundamental barrier to realization of the workflow, we attempted to integrate the ML component, a Sandia-developed tool called FitSNAP. As this was the first application of FitSNAP to atoms and molecules in the gas phase at Sandia, the method required more fitting data than was originally anticipated. Systematic improvements were made by including in the fit data diatomic potentials, molecular single-bond-breaking curves, and symmetry-constrained intermolecular potentials. We concluded that our strategy provides a feasible pathway toward modeling CVD and related processes, but that extensive training data must be generated before it can be of practical use.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Q3 Report for FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

This report describes the work and activities carried out towards the completion of each of the following milestones in FY25 Q3: 1. Demonstrate workflow for generating self-consistent CESOL plasma profiles + first wall and divertor loading prediction and generate the CAT plasma and neutron loading needed for further engineering analysis. • Benchmark between two first wall heat flux mapping methods, identify importance of various heat flux sources and physics impact of using fully coupled CESOL vs post-analysis evaluation. 2. Generate medium fidelity parametrized CAD. • Generate parametrized CAD components for the CAT example case via either user-defined modules called within the geometry generation or by defeatured/parametrized CAD, including DCLL blanket matched to divertor boundary and magnets. Define materials, labels, and boundary conditions for passing the mesh to CFD tools. 3. Demonstrate multiphysics magnet analysis. • Demonstrate magnet analysis workflow called from the FREDA workflow, and 4. Demonstrate nuclear analysis. • Add model to OpenFOAM and/or other codes possibly including Diablo to account for tritium diffusion in solids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗