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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Particle Method for the Multispecies Landau Equation

Abstract The multispecies Landau collision operator describes the two-particle, small scattering angle or grazing collisions in a plasma made up of different species of particles such as electrons and ions. Recently, a structure preserving deterministic particle method (Carrillo et al. in J. Comput. Phys. 7:100066, 2020) has been developed for the single species spatially homogeneous Landau equation. This method relies on a regularization of the Landau collision operator so that an approximate solution, which is a linear combination of Dirac delta distributions, is well-defined. Based on a weak form of the regularized Landau equation, the time dependent locations of the Dirac delta functions satisfy a system of ordinary differential equations. In this work, we extend this particle method to the multispecies case, and examine its conservation of mass, momentum, and energy, and decay of entropy properties. We show that the equilibrium distribution of the regularized multispecies Landau equation is a Maxwellian distribution, and state a critical condition on the regularization parameters that guarantees a species independent equilibrium temperature. A convergence study comparing an exact multispecies Bobylev-Krook-Wu (BKW) solution to the particle solution shows approximately 2nd order accuracy. Important physical properties such as conservation, decay of entropy, and equilibrium distribution of the particle method are demonstrated with several numerical examples.

Mathematics↗
DOE OSTI2024

The liquid-conduction, vapor-flow heat pipe model in Sockeye

A single-phase heat pipe flow model implemented in the heat pipe application Sockeye is described. This model solves one-dimensional, compressible flow equations for the vapor phase in the center of a heat pipe, which are coupled to the two-dimensional heat conduction equation for the wick, liquid, and cladding, as well as to an ordinary differential equation tracking the working fluid inventory in the evaporator section of the heat pipe. This model is demonstrated with several test problems, including comparisons to analytic solutions for the vapor flow fields, analytic curves for sonic and capillary limitations of heat pipe operation, and some experimental data. The numerical solution gives excellent agreement for verification problems and good agreement with experimental results. Also, demonstrations show that the model is very robust, allowing for full simulations of heat pipe transients, including frozen startup, sonic-limited (supersonic) flow, and heat pipe shutdown.

42 ENGINEERING↗
DOE OSTI2026

Identification of Common Types of Plastics by Vibrational Spectroscopic Techniques

Polyethylene Terephthalate (PET), High-Density Polyethylene (HDPE), Polyvinyl Chloride (PVC), Low-Density Polyethylene (LDPE), Polypropylene (PP), and Polystyrene (PS) account for most plastic use worldwide, with production nearing 380 million tons annually. A considerable portion enters municipal solid waste and landfills, creating long-term environmental concerns. Scaling recycling operations requires automated sorting technologies, with spectroscopy and machine learning offering promising solutions. In this study, a six-class convolutional neural network (CNN) was developed for plastic identification using vibrational spectroscopies. Raman Scattering (RS) spectra collected from recycling samples enabled accurate chemical differentiation while assessing the influence of visible features such as color. A CNN trained on RS data achieved 100% classification accuracy. To strengthen field applicability, Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy was incorporated, achieving 95% accuracy with a similar CNN model. These findings demonstrate the potential of integrating spectroscopy with deep learning for reliable plastic classification, advancing development of scalable, field-ready recycling technologies.

Garcia Tovar, Maria P.↗
DOE OSTI2024

Pure-Water-Fed Forward-Bias Bipolar Membrane CO 2 Electrolyzer

Coupling renewable electricity to reduce carbon dioxide (CO 2 ) electrochemically into carbon feedstocks offers a promising pathway to produce chemical fuels sustainably. While there has been success in developing materials and theory for CO 2 reduction, the widespread deployment of CO 2 electrolyzers has been hindered by challenges in the reactor design and operational stability due to CO 2 crossover and (bi)carbonate salt precipitation. Herein, we design asymmetrical bipolar membranes assembled into a zero-gap CO 2 electrolyzer fed with pure water, solving both challenges. By investigating and optimizing the anion-exchangelayer thickness, cathode differential pressure, and cell temperature, the forward-bias bipolar membrane CO 2 electrolyzer achieves a CO faradic efficiency over 80% with a partial current density over 200 mA cm –2 at less than 3.0 V with negligible CO 2 crossover. In addition, this electrolyzer achieves 0.61 and 2.1 mV h –1 decay rates at 150 and 300 mA cm –2 for 200 and 100 h, respectively. Postmortem analysis indicates that the deterioration of catalyst/polymer– electrolyte interfaces resulted from catalyst structural change, and ionomer degradation at reductive potential shows the decay mechanism. Furthermore, all these results point to the future research direction and show a promising pathway to deploy CO 2 electrolyzers at scale for industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Filtration Performance of Simulated 200 West Area Waste Feeds

This report describes the scaled experimental system and approach used to examine dead-end filtration performance of representative 200W waste feeds. The scaled system, which was originally designed and assembled to test Tank Side Cesium Removal (TSCR) system performance with higher-than-expected solid loadings in 2021 (Schonewill et al. 2021), was repurposed to conduct the current experiments at ~1/145 of full scale (based on throughput). Six experimental runs were conducted with five different 200W waste feed simulants: three using a DEF module scaled for TSCR and three using a DEF module scaled for the 200W process modules (based on the current design for the Advanced Modular Pretreatment System). Each experiment was run continuously for multiple days with an operating approach prototypic of the full-scale system. Staff performing the experimental runs monitored performance, obtained data from calibrated process instruments, and collected samples for observation and analysis. The measured data are presented with a focus on assessing DEF performance – specifically, the filters’ differential pressure response to the five waste simulants, frequency and efficacy of backwashing, and baseline recovery between experimental runs; data related to ion exchange column performance are also discussed in cases where the opportunity arose. The experimental campaign demonstrated that the DEFs satisfied their primary function of protecting the ion exchange column from solid intrusion for all the representative simulants used. The filters readily handled solids loadings of =500 ppm (and even greater), especially the modules scaled to the 200W process modules. Adjustments to the processing flow rate and reductions in feed temperature were observed to affect the rate of differential pressure increase on the filters, but neither adversely affected the ability of the DEFs to perform their primary function. Backflushing reliably recovered filter performance in all runs, although it did not prevent irreversible fouling for one simulant. The run that exhibited irreversible fouling established that both the quantity and the nature of the solids being filtered need to be considered when projecting filter performance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Dualities among massive, partially massless and shift symmetric fields on (A)dS

We catalog all the electromagnetic-like dualities that exist between free dynamical bosonic fields of arbitrary symmetry type and mass on (anti-) de Sitter space in all dimensions, including dualities among the partially massless and shift symmetric fields. This generalizes to all these field types the well known fact that a massless p-form is dual to a massless (D − p − 2)-form in D spacetime dimensions. In the process, we describe the structure of the Weyl modules (the spaces of local operators linear in the fields and their derivative relations) for all the massive, partially massless and shift symmetric fields.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Quantum Algorithm for Linear Non-unitary Dynamics with Near-Optimal Dependence on All Parameters

We introduce a family of identities that express general linear non-unitary evolution operators as a linear combination of unitary evolution operators, each solving a Hamiltonian simulation problem. This formulation can exponentially enhance the accuracy of the recently introduced linear combination of Hamiltonian simulation (LCHS) method [An, Liu, and Lin, Physical Review Letters, 2023]. For the first time, this approach enables quantum algorithms to solve linear differential equations with both optimal state preparation cost and near-optimal scaling in matrix queries on all parameters.

Applied Dynamical Systems↗
DOE OSTI2026

A mathematical framework for thermodynamic computing with applications to chemical reaction networks

The widespread adoption of energy-intensive computing applications has led to a growing need for energy-efficient computing approaches. Thermodynamic computing offers a promising approach for low-energy computation by leveraging the intrinsic computational capabilities of physical, chemical, or biological systems. However, the mathematical foundations of thermodynamic computing require further development to fully realize the potential energy efficiencies, as well as to assess factors like noise and operational speed. In this paper, we establish a mathematical framework for utilizing thermodynamic processes to perform fundamental operations, including addition, subtraction, multiplication, and division. We highlight the use of chemical reactions as potential computational units and explore synthetic chemical and biochemical systems as practical implementations. Additionally, we demonstrate how these principles can be applied to solving complex mathematical problems, such as ordinary differential equations (ODEs) and suggest the necessary components to implement the thermodynamic computing framework using chemical reactions based in a microfluidic device. This work enhances our understanding of thermodynamic processes for natural computing as a basis for scalable, energy-efficient computation in paradigm disruptive next-generation systems.

Cannon, William R. [Pacific Northwest National Lab↗
DOE OSTI2025

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Measurement of muon neutrino charged-current quasielasticlike cross section using off-axis NuMI beam at ICARUS

This paper presents the first neutrino cross-section measurement from the ICARUS detector at Fermilab, using Neutrinos at the Main Injector (NuMI) beam data collected from two beam operation periods corresponding to 2.5 × 10 20 protons-on-target in neutrino beam mode. The signal is defined by events with no pions produced in the final state, a topology dominated by charged-current quasielasticlike signatures. The measurement is reported as flux-averaged differential cross sections as functions of kinematic variables that provide sensitivity to the complex nuclear effects that often dominate the systematic uncertainty budgets of neutrino oscillation measurements. Specifically, this work reports cross sections in two angular variables—the angle of the outgoing lepton and the opening angle between the lepton and leading proton—and two variables characterizing the kinematic imbalance between the muon and proton in the plane transverse to the incoming neutrino. These results are compared against predictions from a variety of neutrino event generators, with p values calculated between the extracted cross sections and each prediction. Overall, the predictions agree with the data; however, the current budget of uncertainties does not yet provide sufficient discriminating power to favor a specific model.

Abd Alrahman, F. [Houston U.]↗
DOE OSTI2025

Thermal mechanical assessment of a SiC-SiC-composite clad fuel pin concept in a light water reactor environment

Accident Tolerant Fuels (ATFs) are designed to increase coping time following an accident scenario while preserving or improving current steady state reactor operational performance. A potential ATF concept is SiC-SiC composite claddings. Fuel performance simulations were conducted on a SiC-SiC based cladding concept utilizing a multilayered approach for improved performance. This cladding concept referred to as the Duplex concept is a duplex structure composed of a monolithic SiC layer placed on the outside of a SiC-SiC composite. A liquid metal is added to fuel-cladding gap for improved heat dissipation from the fuel. The monolithic SiC layer is used to improve the coolant corrosion characteristics and protect the SiC-SiC composite layer from exposure to the coolant. The fuel performance code BISON was used to conduct fuel performance simulations on the cladding concepts. Comparisons are made with a current prototypic fuel rod design (UO 2 fuel enclosed in Zircaloy-4 cladding). Representative steady-state cases were considered for normal power and two cycle power histories. Additionally, a PCI ramp case was simulated to analyze potential anticipated operational occurrences. Transient response during a Loss of Coolant Accident and a Reactivity Initiated Accident were also simulated. This computational study demonstrated that for normal operating conditions, the SiC concept cladding performed as well as the baseline for the standard power cases evaluated. The ramping evaluations indicate potential fracturing of the SiC-SiC composite of the composite cladding compared to the Zircaloy-4 cladding due to the temperature gradient and the subsequent differential thermal conductivity degradation and swelling across the composite thickness. In conclusion, the rod fails early at low enthalpy for RIA but survives a LOCA with minimal material loss due to high temperature steam corrosion.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Numerical simulation of RHIC polarized proton run 17 spin flipper experiments

RHIC nine-magnet spin flipper has been operated successfully during RHIC polarized proton Run 17, with 97% spin flip efficiency achieved. The results show the importance of mirror resonance removal, small spin tune spread, and proper spin flipper driving tune sweep speed. Detailed spin tracking simulations, based on a Lorentz force and Thomas-BMT differential equation numerical solver code for accuracy, have been carried out to understand the experimental results. Agreement within measurement accuracy is obtained at injection energy, 23.8 GeV. It is not as tight at 255 GeV, reasons for that are exposed. These measurements and numerical studies allow to determine the sensitivity of spin-flip efficiency to the dispersion slopes at the two Siberian snakes and to the ac dipole frequency sweep speed. They also provide guidance for future developments at BNL’s electron-ion collider. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

HdsaLib

HdsaLib performs hyper-differential sensitivity analysis in optimization problems that are constrained by partial differential equation problems. The software aids researchers in understanding the impact of uncertainties on their optimization models. The tool has been applied for use in ice sheet modeling, fluid flow modeling, atmospheric tracer transport modeling, and subsurface flow modeling. 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.

van Bloemen Waanders, Bart [Sandia National Lab. (↗
DOE OSTI2025

Acceleration of Power System Dynamic Simulations Using a Deep Equilibrium Layer and Neural ODE Surrogate

The dominant paradigm for power system dynamic simulation is to build system-level simulations by combining physics-based models of individual components. The sheer size of the system along with the rapid integration of inverter-based resources exacerbates the computational burden of running time domain simulations. Here, in this paper, we propose a data-driven surrogate model based on implicit machine learningspecifically deep equilibrium layers and neural ordinary differential equationsto learn a reduced order model of a portion of the full underlying system. The data-driven surrogate achieves similar accuracy and reduction in simulation time compared to a physics-based surrogate, without the constraint of requiring detailed knowledge of the underlying dynamic models. This work also establishes key requirements needed to integrate the surrogate into existing simulation workflows; the proposed surrogate is initialized to a steady state operating point that matches the power flow solution by design.

Neural ordinary differential equations↗
DOE OSTI2026

Simulations of grain growth in tungsten armor materials under ARC plasma edge operation conditions using an integrated plasma-edge/materials model

An integrated model of grain growth deuterium-exposed tungsten polycrystals, consisting of a two-dimensional vertex dynamics model fitted to atomistic data, has been developed to assess the grain growth kinetics of deuterium-exposed polycrystalline tungsten (W). The model tracks the motion of grain boundaries under the effect of driving forces stemming from grain boundary curvature and differential deuterium concentration accumulation. Here, we apply the model to experimentally synthesized tungsten polycrystals under deuterium-saturated conditions relevant to the ARC concept design. The results indicate rapid grain growth kinetics in the near-surface region adjacent to the plasma, where the temperature reaches 1400 K, whereas the microstructure remains stable deeper in the material with the lower temperature of 1000 K. The combined modeling and analysis further reveal that monolithic tungsten produced via conventional fabrication routes is highly susceptible to grain coarsening at temperatures exceeding 1000 K, largely independent of the magnitude of the applied driving force. Moreover, the accumulation of deuterium near grain boundaries has a pronounced inhibitory effect on grain boundary migration. High-angle grain boundaries ( > 50°) contribute more significantly to the overall grain growth process.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Inclusive and differential cross-section measurements of $ t\overline{t}Z$ production in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector, including EFT and spin-correlation interpretations

Measurements of both the inclusive and differential production cross sections of a top-quark-top-antiquark pair in association with a Z boson ($t\overline{t}Z$) are presented. Final states with two, three or four isolated leptons (electrons or muons) are targeted. The measurements use the data recorded by the ATLAS detector in pp collisions at $\sqrt{s}$ = 13 TeV at the Large Hadron Collider during the years 2015–2018, corresponding to an integrated luminosity of 140 fb -1 . The inclusive cross section is measured to be ${\sigma}_{t\overline{t}Z}$ = 0.86 ± 0.04 (stat.) ± 0.04 (syst.) pb and found to be in agreement with the most advanced Standard Model predictions. The differential measurements are presented as a function of a number of observables that probe the kinematics of the $t\overline{t}Z$ system. Both the absolute and normalised differential cross-section measurements are performed at particle level and parton level for specific fiducial volumes, and are compared with NLO+NNLL theoretical predictions. The results are interpreted in the framework of Standard Model effective field theory and used to set limits on a large number of dimension-6 operators involving the top quark. The first measurement of spin correlations in $t\overline{t}Z$ events is presented: the results are in agreement with the Standard Model expectations, and the null hypothesis of no spin correlations is disfavoured with a significance of 1.8 standard deviations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Evaluating the feasibility of using downwind methods to quantify point source oil and gas emissions using continuously monitoring fence-line sensors

The dependable reporting of methane (CH 4 ) emissions from point sources, such as fugitive leaks from oil and gas infrastructure, is important for profit maximization (retaining more hydrocarbons), evaluating climate impacts, assessing CH 4 fees for regulatory programs, and validating CH 4 intensity in differentiated gas programs. Currently, there are disagreements between emissions reported by different quantification techniques for the same sources. It has been suggested that downwind CH 4 quantification methods using CH 4 measurements on the fence line of production facilities could be used to generate emission estimates from oil and gas operations at the site level, but it is currently unclear how accurate the quantified emissions are. To investigate the accuracy of downwind methods, this study uses fence-line simulated data collected during controlled-release experiments as input for a non-standard closed-path eddy covariance (EC), the Gaussian plume inverse model (GPIM), and the backward Lagrangian stochastic (bLs) model in a range of atmospheric conditions. This study's EC attempt was unsuccessful due to data collection and instrumentation issues, resulting in invalid results characterized by underestimated emissions, large negative fluxes, and cospectra/ogives that deviated from their ideal shapes. Consequently, the EC results could not be compared with the GPIM and bLS model. The bLs model demonstrated the highest accuracy for single-release single-point emissions, though it exhibited greater uncertainty than GPIM under multi-release conditions. Across the GPIM and bLs model, the most reliable quantification was achieved with 15 min averaging and a narrow 5° wind sector range. Although EC was limited in this context, future studies should consider employing a standard EC system and further optimizing GPIM and bLs approaches – particularly for complex multi-source scenarios – to enhance quantification accuracy and reduce uncertainty.

03 NATURAL GAS↗