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DOE OSTI2018

Supercritical Brayton Power Conversion with a Direct Cooled Reactor for Space Power

To achieve future goals in space exploration a long life, compact power system will be necessary, and nuclear power sources are a promising option. The goal of this project is to achieve mass optimization with a supercritical Brayton Cycle coupled to a direct-cooled nuclear reactor. It is critical to minimize the total mass of this system because of space launch costs. The total mass involves both the components’ masses as well as the fuel mass which is related to system efficiency. This paper discusses a project in which a detailed reactor model is integrated with a carefully constructed cycle model in order to simultaneously optimize the design of these two aspects of the system. Component models are discussed as well as an initial optimization study. A robust, simple recuperated Brayton cycle model is complete and is in the process of integration with a developing reactor model. Preliminary observations of the cycle model have led to the conclusion that there will be an optimum point between a large recuperator and small reactor with high system efficiency, and a large reactor and small recuperator with low recuperator mass for any given radiater size. Once the reactor model is integrated into the cycle optimization, the tradeoffs between the sizes of the radiator, recuperator, and reactor will be further investigated and an optimum system mass will be apparent.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2018

Supercritical Brayton Power Conversion with a Direct Cooled Reactor for Space Power

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Simulation of flame acceleration and deflagration-to-detonation transition with heat transfer in HE product and fractured HE

A simple heat transfer model has been developed for high explosives. For the gaseous high explosive (HE) product, the Smargorinsky eddy viscosity model has been adopted for estimating the turbulent thermal conductivity. Convective heat transfer in the fractured solid HE is modeled as the effective thermal conduction in the porous media, which is equivalent to the enthalpy flux carried by the velocity determined by Darcy’s law with Forchheimer term.Other features of the model include a multi-reaction chain, equation-of-state for each species involved, and a two-phase hotspot model. Test calculations are performed with various initial disturbances. Onset and progress of flame acceleration (FA) and chemical reactions are strongly affected by the heat transfer and initial disturbance. Staged development of FA also affirms the necessity of modeling based on a multi-reaction chain. When conditions warrant,e.g., stronger initial disturbance, FA evolves to deflagration-to-detonation transition (DDT),demonstrating automatic capture of the DDT.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

Electrification of Pakistan's Transport System: Modeling Electric Vehicle Penetration and Energy Supply Chain Impacts

Initial analysis of the National Electric Vehicle Policy (NEVP) of Pakistan was undertaken by an integrated energy planning team from November 2019 through August 2020. This technical reference document seeks to present the background, inputs and assumptions, methodology, and results of the policy analysis in detail. The intended audience is the technical modeler, analyst, or reviewer who seeks to understand specifically the modeling effort within this initial analytical phase, with the end-goal of interpreting, re-producing, or modifying the simulations or extending the models to conduct follow-on studies subsequently. These studies may examine in greater detail the energy sector, impacts to emissions, charging station infrastructure needs, and overall benefits-cost trade of the policy, among other areas of interest.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

DECOVALEX-2023: An international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

The DECOVALEX initiative is an international research collaboration (www.decovalex.org), initiated in 1992, for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. DECOVALEX stands for “DEvelopment of COupled Models and VALidation against EXperiments”. The creation of this international initiative was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of the complex perturbations and coupled processes in geologic repositories and how these impact long-term performance predictions. The most recent phase of the DECOVALEX Project, here referred to as DECOVALEX-2023, started in early 2020 and ended in late 2023. More than fifty research teams associated with 17 international DECOVALEX partner organizations participated in the comparative evaluation of eight modeling tasks covering a wide range of spatial and temporal scales, geological formations, and coupled processes. This Virtual Special Issue on DECOVALEX-2023 provides an in-depth overview of these collaborative research efforts and how these have advanced the state-of-the-art of understanding and modeling coupled THMC processes. While primarily focused on radioactive waste, much of the work included here has wider application to many geoengineering topics.

Coupled processes↗

DOE OSTI2018

Influence of Hydrological Perturbations and Riverbed Sediment Characteristics on Hyporheic Zone Respiration of CO 2 and N 2

Rivers in climatic zones characterized by dry and wet seasons often experience periodic transitions between losing and gaining conditions across the river-aquifer continuum. Infiltration shifts can stimulate hyporheic microbial biomass growth and cycling of riverine carbon and nitrogen leading to major exports of biogenic CO 2 and N 2 to rivers. In this study, we develop and test a numerical model that simulates biological-physical feedback in the hyporheic zone. We used the model to explore different initial conditions in terms of dissolved organic carbon availability, sediment characteristics, and stochastic variability in aerobic and anaerobic conditions from water table fluctuations. Our results show that while highly losing rivers have greater hyporheic CO 2 and N 2 production, gaining rivers allowed the greatest fraction of CO 2 and N 2 production to return to the river. Hyporheic aerobic respiration and denitrification contributed 0.1–2 g/m 2 /d of CO 2 and 0.01–0.2 g/m 2 /d of N 2 ; however, the suite of potential microbial behaviors varied greatly among sediment characteristics. We found that losing rivers that consistently lacked an exit pathway can store up to 100% of the entering C/N as subsurface biomass and dissolved gas. Finally, our results demonstrate the importance of subsurface feedbacks whereby microbes and hydrology jointly control fate of C and N and are strongly linked to wet-season control of initial sediment conditions and hydrologic control of seepage direction. These results provide a new understanding of hydrobiological and sediment-based controls on hyporheic zone respiration, including a new explanation for the occurrence of anoxic microzones and large denitrification rates in gravelly riverbeds.

58 GEOSCIENCES↗

DOE OSTI2026

Impact of Salt Chemistry and Interlayer Architecture on Solid Electrolyte Interphase Composition and Performance

Reversible lithium metal anodes require interphases that are chemically stable, mechanically robust, and compatible with scalable processing. Here, we use slot-die-coated, salt-rich PEO interlayers to design SEI nanolayers on Cu current collectors and isolate how salt anion chemistry controls interphase composition and lithium plating/stripping behavior in architectures relevant to Li plating and anode-free cells. Mesoscale modeling shows that dendrite initiation at SEI defects is governed by a tradeoff among interphase thickness, ionic conductivity, and stiffness through defect-driven current focusing, motivating controlled formation from thin precursor layers. Using UHV-transferred XPS and ToF-SIMS depth profiling after controlled Li deposition, we find that fluorinated sulfonylimide salts (LiTFSI, LiFSI) form mixed inorganic/organic interphases containing LiF and PEO-derived alkoxides, with LiFSI producing a more LiF-dominant Li-facing surface than LiTFSI under identical conditions. In contrast, LiNO 3 -containing interlayers yield a comparatively thick nitrate-derived interphase that reduces upon Li contact to an N-rich inorganic layer (Li–N/N 3− , LiN x O y ). In Cu| |Li cells, these designed interlayers reduce interfacial resistance and improve Coulombic efficiency (CE) and critical current density (CCD) relative to uncoated controls, with LiFSI- and LiNO 3 -based interlayers providing the highest CE/CCD. Overall, the results demonstrate a manufacturing-relevant approach to engineer SEI nanolayers by salt chemistry, providing pathways to improve reversible lithium metal anodes while reducing reliance on LiTFSI.

anion chemistry↗

DOE OSTI2024

Measurement of prompt D + and ${D}_s^{+}$ production in p Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

The production of prompt D + and $D^+_s$ mesons is studied in proton-lead collisions at a centre-of-mass energy of $\sqrt{^{S}NN}$ = 5.02 TeV. The data sample corresponding to an integrated luminosity of (1.58 ± 0.02)nb –1 is collected by the LHCb experiment at the LHC. The differential production cross-sections are measured using D + and $D^+_s$ candidates with transverse momentum in the range of 0 < p T < 14 GeV/c and rapidities in the ranges of 1.5 < y* < 4.0 and –5.0 < y* < –2.5 in the nucleon-nucleon centre-of-mass system. For both particles, the nuclear modification factor and the forward-backward production ratio are determined. These results are compared with theoretical models that include initial-state nuclear effects. In addition, measurements of the cross-section ratios between D + , $D^+_s$ and D 0 mesons are presented, providing a baseline for studying the charm hadronization in lead-lead collisions at LHC energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Assessing mean climate change signals in the global CORDEX-CORE ensemble

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25 $\,\mathrm {km}$ (0.22 $^{\circ }$ /jats:inline-formula>) versus 50 $\,\mathrm {km}$ (0.44 $^{\circ }$ )) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Transition in ICF Capsule Implosions

Longstanding design and reproducibility challenges in inertial confinement fusion (ICF) capsule implosion experiments involve recognizing the need for appropriately characterized and modeled three-dimensional initial conditions and high-fidelity simulation capabilities to predict transitional flow approaching turbulence, material mixing characteristics, and late-time quantities of interest—e.g., fusion yield. We build on previous coarse graining simulations of the indirect-drive national ignition facility (NIF) cryogenic capsule N170601 experiment-a precursor of N221205 which resulted in net energy gain. We apply effectively combined initialization aspects and multiphysics coupling in conjunction with newly available hydrodynamics simulation methods, including directional unsplit algorithms and low Mach-number correction-key advances enabling high fidelity coarse grained simulations of radiation-hydrodynamics driven transition. Our presentation includes discussion of the capsule initialization and implosion dynamics, analysis of the vorticity production budget, transition signatures, quantities of interest—late-time ion temperature and fusion-neutron yield, numerical uncertainty quantification, and comparisons with NIF data.

42 ENGINEERING↗

DOE OSTI2022

Analytical methods for superresolution dislocation identification in dark-field X-ray microscopy

In this work, we develop several inference methods to estimate the position of dislocations from images generated using dark-field X-ray microscopy (DFXM)—achieving superresolution accuracy and principled uncertainty quantification. Using the framework of Bayesian inference, we incorporate models of the DFXM contrast mechanism and detector measurement noise, along with initial position estimates, into a statistical model coupling DFXM images with the dislocation position of interest. We motivate several position estimation and uncertainty quantification algorithms based on this model. We then demonstrate the accuracy of our primary estimation algorithm on synthetic realistic DFXM images of edge dislocations in single-crystal aluminum. We conclude with a discussion of our methods’ impact on future dislocation studies and possible future research avenues.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Iron Ore Reduction by Hydrogen Using a Laboratory Scale Fluidized Bed Reactor: Kinetic Investigation—Experimental Setup and Method for Determination

The reduction kinetics of hematite iron ore fines to metallic iron by hydrogen using a laboratory fluidized bed reactor were investigated in a temperature range between 873 K and 1073 K, by measuring the weight change of the sample portion during reduction. The fluidization conditions were checked regarding plausibility within the Grace diagram and the measured pressure drop across the material during experiments. The apparent activation energy of the reduction was determined against the degree of reduction and varied along an estimated two-peak curve between 11 and 55 kJ mol{sup −1}. Conventional kinetic analysis for the reduction of FeO to metallic iron, using typical models to describe gas–solid reactions, does not show results with high accuracy. Multistep kinetic analysis, using the Johnson–Mehl–Avrami model, shows that the initial stage of reduction from Fe{sub 2}O{sub 3} to Fe{sub 3}O{sub 4}, and partly to FeO, is controlled by diffusion and chemical reaction, depending on the temperature. Further reduction can be described by a combination of nucleation and chemical reaction, whereby the influence of nucleation increases with an increasing reduction temperature. The results of the kinetical analysis were linked to the shape of the curve from apparent activation energy against the degree of reduction.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Establishing a neutronics design and equilibrium cycle analysis for the I 2 S-LWR reactor with UO 2 and U 3 Si 2 Fuel

The Integral Inherently Safe (I 2 S-LWR) reactor was developed not only to enhance passive reactor safety performance, but also to improve reactor economics. This paper describes the steady-state and depletion analysis of the I 2 S-LWR core using both UO 2 and U 3 Si 2 fuel designs. The development and validation of the core models are described, to include the generation of HELIOS cross sections and comparison with the WEC lattice code PARAGON and the Monte Carlo code SERPENT. The few group homogenized cross sections were then prepared for the U.S. NRC PARCS core simulator using the GenPMAXS code. The multicycle capability in PARCS was used to determine the equilibrium core condition for three batch cores loaded with the UO 2 and then with the U 3 Si 2 fuel designs. Comparing the results from the WEC code ANC at beginning, middle, and end of cycle showed good agreement. Core conditions at beginning and end of cycle were then used to determine the converged steady-state conditions of a coupled RELAP5/PARCS model, which provided the initial condition for various transient accident simulations which are reported in a companion paper.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Electrophysiological interrogation of asymmetric droplet interface bilayers reveals surface-bound alamethicin induces lipid flip-flop

The droplet interface bilayer (DIB) method offers simple control over initial leaflet compositions in model membranes, enabling an experimental path to filling gaps in our knowledge about the interplay between compositional lipid asymmetry, membrane properties, and the behaviors of membrane-active species. Yet, the stability of lipid leaflet asymmetry in DIBs has received very little attention, particularly in the presence of peptides and ion channels that are often studied in DIBs. Herein, we demonstrate for the first time parallel, capacitance-based measurements of intramembrane potential with arrays of asymmetric DIBs assembled in a microfluidic device to characterize the stability of leaflet asymmetry over many hours in the presence and absence of membrane-active peptides. DIBs assembled from opposing monolayers of the ester (DPhPC) and ether (DOPhPC) forms of diphytanoyl-phosphatidylcholine yielded asymmetric bilayers with leaflet compositions that were stable for at least 18 has indicated by a stable |137 mV| intramembrane potential. In contrast, the addition of surface-bound alamethicin peptides caused a gradual, concentration-dependent decrease in the magnitude of the dipole potential difference. Intermittent current-voltage measurements revealed that alamethicin in asymmetric DIBs also shifts the threshold voltage required to drive peptide insertion and ion channel formation. These outcomes take place over the course of 1 to 5 h after membrane formation, and suggest that alamethicin peptides promote lipid flip-flop, even in the un-inserted, surface-bound state, by disordering lipids in the monolayer to which they bind. Furthermore, this methodology establishes the use of parallel electrophysiology for efficiently studying membrane asymmetry in arrays of DIBs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Pollen Cell Wall Patterns Form from Modulated Phases

The ornately geometric walls of pollen grains have inspired scientists for decades. Here, we show that the evolved diversity of these patterns is entirely recapitulated by a biophysical model in which an initially uniform polysaccharide layer in the extracellular space, mechanically coupled to the cell membrane, phase separates to a spatially modulated state. Experiments reveal this process occurring in living cells. We observe that in ~10% of extant species, this phase separation reaches equilibrium during development such that individual pollen grains are identical and perfectly reproducible. About 90% of species undergo an arrest of this process prior to equilibrium such that individual grains are similar but inexact copies. Equilibrium patterns have appeared multiple times during the evolution of seed plants, but selection does not favor these states. This framework for pattern development provides a route to rationalizing the surface textures of other secreted structures, such as cell walls and insect cuticle.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

The use of digital thread for reconstruction of local fiber orientation in a compression molded pin bracket via deep learning

A deep convolutional neural network (DCNN) was used for microstructure reconstruction using artificial intelligence (MR-AI) by predicting local average fiber orientation distributions (FOD) in a 3D prepreg platelet molded composite (PPMC) pin bracket. To train the MR-AI model, surface strain fields from residual stresses simulated in PPMC plates were used as the input to the DCNN. A training dataset included PPMC plates with various degrees of global fiber alignment, based on the information obtained from high-fidelity flow simulation of a pin bracket. Further, the MR-AI model was then deployed to analyze FOD in the 3D pin bracket by conducting thermo-elastic residual stress analysis. Initially, the MR-AI model was established entirely on the synthetic simulation data. Then, a μCT scan of a physically molded pin bracket was used to create a finite element model that provided data for additional validation of the DCNN model. For the μCT scan finite element pin bracket the MR-AI model predicted the distribution of fiber orientation tensor components with MAE of 0.10 indicating a global prediction error of 10%. For the flow simulated pin bracket, the MR-AI model predicted the distribution of fiber orientation tensor components with a global prediction error of 11%. The MR-AI model showed the ability to predict regions of varying alignment in the base and flange of the pin bracket. The proposed MR-AI methodology allows for rapid prediction of FOD in geometrically complex parts and offers a promising path to detecting unique fiber orientation states in molded components.

42 ENGINEERING↗

DOE OSTI2025

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Formation of helices with controllable chirality in gel-fiber composites

While microscale helices with specified chirality are pervasive in biological systems, driving purely synthetic materials to self-organize into such useful structures remains a significant challenge. Through theory and simulations, we model the behavior of initially flat ribbons of gel-fiber composites and show that these materials self-organize into three-dimensional helices with the application of heat. We specifically focus on thermo-responsive gels, which shrink when heated to a point near the lower critical solubility temperature (LCST). Within the composite, regions of the LCST gel that lie far from the fibers can readily shrink in response to the increased temperature; however, near the fibers the network is inhibited from undergoing the heat-induced collapse. This competition between the constrained and the unconstrained regions of the heated sample plays a vital role in the structural evolution of the material. Additionally, we find that this dynamic process can be controlled through the careful placement of the fibers on the outer surface of the gel. We specifically identify fiber arrangements that lead to the formation of helical structures with controlled chirality. Moreover, we isolate scenarios where constraining the movement of one or both the free ends of the sample promotes and stabilizes the formation of helical structures with specified handedness. Such structurally tailored composites are useful for creating mechanically robust actuators, and “appendages” for soft robots that can controllably curl and uncurl with variations in temperature.

36 MATERIALS SCIENCE↗