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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

MONKES: a fast neoclassical code for the evaluation of monoenergetic transport coefficients in stellarator plasmas

Abstract MONKES is a new neoclassical code for the evaluation of monoenergetic transport coefficients in stellarators. By means of a convergence study and benchmarks with other codes, it is shown that MONKES is accurate and efficient. The combination of spectral discretization in spatial and velocity coordinates with block sparsity allows MONKES to compute monoenergetic coefficients at low collisionality, in a single core, in approximately one minute. MONKES is sufficiently fast to be integrated into stellarator optimization codes for direct optimization of the bootstrap current and to be included in predictive transport suites. The code and data from this paper are available at https://github.com/JavierEscoto/MONKES/ .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1993

Circulation and rainfall climatology of a 10-year (1979 - 1988) integration with the Goddard Laboratory for atmospheres general circulation model

A 10-year (1979-1988) integration of Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) under Atmospheric Model Intercomparison Project (AMIP) is analyzed and compared with observation. The first momentum fields of circulation variables and also hydrological variables including precipitation, evaporation, and soil moisture are presented. Our goals are (1) to produce a benchmark documentation of the GLA GCM for future model improvements; (2) to examine systematic errors between the simulated and the observed circulation, precipitation, and hydrologic cycle; (3) to examine the interannual variability of the simulated atmosphere and compare it with observation; and (4) to examine the ability of the model to capture the major climate anomalies in response to events such as El Nino and La Nina. The 10-year mean seasonal and annual simulated circulation is quite reasonable compared to the analyzed circulation, except the polar regions and area of high orography. Precipitation over tropics are quite well simulated, and the signal of El Nino/La Nina episodes can be easily identified. The time series of evaporation and soil moisture in the 12 biomes of the biosphere also show reasonable patterns compared to the estimated evaporation and soil moisture.

Kim, J.-H.↗
NASA NTRSDate not supplied

QuAIL Tools for Benchmarking, Analysis and Quantum Algorithm Development

HybridQ and PySA are open-source tools developed by NASA to support benchmarking, analysis and quantum algorithm development in areas such as simulation, optimization and machine learning. These tools leverage classical hardware acceleration via high-performance computing CPU and GPU architectures and support high-performance computing. HybridQ is a highly extensible platform designed to provide a common framework to integrate multiple state-of-the-art techniques to simulate large scale quantum circuits. PySA is an extensible platform to optimize a classical cost function. We provide an outline of each of these open-source tools and highlight projects using each of these tools in contexts of simulation, optimization and machine learning.

Quantum Computing↗
DOE OSTI2016

V and V of the HTR Code Package (HCP) as a comprehensive HTR steady state and transient safety analysis framework - 18664

The HTR code package (HCP) allows for the simulation of several safety-related aspects of a High Temperature Reactor core in a highly integrated manner. HCP currently couples the thermo-fluid dynamics and time dependent neutronics code MGT, the spectrum code TRISHA, the burn up code TNT, the fuel management code SHUFLE and the fission product release code STACY. During its development, state-of-the-art programming techniques and standards are applied. The cross sections in HCP are generated by a 0D- or 1D solver featuring an innovative approach to treat the double heterogeneity of pebble fuel. Also major improvements have been made to optimize the nuclear data library based on ENDF/B-VII. Two advanced fuel management models are provided by the code module SHUFLE that go far beyond the capabilities of existing system codes like VSOP. The source term analysis code module STACY is coupled to HCP providing release rate calculations with a high spatial resolution making use of the nuclide densities provided by TNT. An outstanding new feature of HCP is the possibility to simulate long-term operation scenarios based on OTTO or MEDUL fuel shuffling schemes as well as selected transients in one integrated code package. Even alternating steady state/transient/steady state simulations are possible. So with HCP different fuel strategies and their influence on various kinds of accidents can be examined with one consistent reactor model. This paper provides an overview of the development status of the HCP and reports about selected benchmark results. It is demonstrated that the new system code HCP is capable to replace existing stand-alone codes like VSOP, TINTE/MGT, FRESCO or PANAMA while introducing new features, which so far to our knowledge were not available in the field of HTR safety research. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Transient MOC with frequency transform and DSA on unstructured mesh

We present an implementation of the transient method of characteristics (MOC) with isotropic time derivatives, accelerated by diffusion synthetic acceleration (DSA). The fully implicit frequency transform method is used to solve the transient problem with analytic precursor integration. The code works on meshes composed of almost any of the commonly used non-curvilinear finite element types, and can handle the deformation of geometry in time-dependent transport calculations. We present results of a continuous Fourier analysis for the transient multigroup DSA problem, and representative benchmarking results are presented for the C5G7-TD benchmark in 2D showing reasonable performance and agreement compared to other codes. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Absolute integral cross sections for the state-selected ion–molecule reaction N{sub 2}{sup +}(X{sup 2}Σ{sub g}{sup +}; v{sup +} = 0–2) + C{sub 2}H{sub 2} in the collision energy range of 0.03–10.00 eV

Using the vacuum ultraviolet laser pulsed field ionization-photoion source, together with the double-quadrupole–double-octopole mass spectrometer developed in our laboratory, we have investigated the state-selected ion–molecule reaction N{sub 2}{sup +}(X{sup 2}Σ{sub g}{sup +}; v {sup +} = 0–2, N{sup +} = 0–9) + C{sub 2}H{sub 2}, achieving high internal-state selectivity and high kinetic energy resolution for reactant N{sub 2}{sup +} ions. The charge transfer (CT) and hydrogen-atom transfer (HT) channels, which lead to the respective formation of product C{sub 2}H{sub 2}{sup +} and N{sub 2}H{sup +} ions, are observed. The vibrationally selected absolute integral cross sections for the CT [σ {sub CT}(v {sup +})] and HT [[σ {sub HT}(v {sup +})] channels obtained in the center-of-mass collision energy (E {sub cm}) range of 0.03–10.00 eV reveal opposite E {sub cm} dependences. The σ {sub CT}(v {sup +}) is found to increase as E {sub cm} is decreased, and is consistent with the long-range exothermic CT mechanism, whereas the E {sub cm} enhancement observed for the σ {sub HT}(v {sup +}) suggests effective coupling of kinetic energy to internal energy, enhancing the formation of N{sub 2}H{sup +}. The σ {sub HT}(v {sup +}) curve exhibits a step at E {sub cm} = 0.70–1.00 eV, suggesting the involvement of the excited C{sub 2}H{sub 2}{sup +}(A{sup 2}Σ{sub g}{sup +}) state in the HT reaction. Contrary to the strong E {sub cm} dependences for σ {sub CT}(v {sup +}) and σ {sub HT}(v {sup +}), the effect of vibrational excitation of N{sub 2}{sup +} on both the CT and HT channels is marginal. The branching ratios and cross sections for the CT and HT channels determined in the present study are useful for modeling the atmospheric compositions of Saturn's largest moon, Titan. These cross sections and branching ratios are also valuable for benchmarking theoretical calculations on chemical dynamics of the titled reaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Results from the US-German Benchmark Initiative for FY14

Sandia recently joined the third phase of and is a contributing partner to a U.S.-German “Joint Project” entitled “Comparison of current constitutive models and simulation procedures on the basis of model calculations of the thermo-mechanical behavior and healing of rock salt.” The first goal of the project is to check the ability of numerical modeling tools to correctly describe the relevant deformation phenomena in rock salt under various influences. Achieving this goal will lead to increased confidence in the results of numerical simulations related to the secure storage of radioactive wastes in rock salt, thereby enhancing the acceptance of the results. These results may ultimately be used to make various assertions regarding both the stability analysis of an underground repository in salt during the operating phase and the long-term integrity of the geological barrier against the release of harmful substances into the biosphere in the post-operating phase. Among the numerical modeling tools are constitutive models that are used in computer simulations for the description of the thermal, mechanical, and hydraulic behavior of the host rock under various influences and for the long-term prediction of this behavior into the future. A second goal of the project is to investigate and demonstrate the possibilities for further potential development and improvement of these constitutive models. This report summarizes the efforts undertaken during FY14 in support of these international benchmark calculations of field experiments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Completion of Critical Experiments with Molybdenum Sleeves at Sandia

Sandia National Laboratories (SNL) and the Institut de Radioprotection et de Sûreté Nucléaire (IRSN) have collaborated on the design and execution of a set of critical experiments that explore the effects of molybdenum in water moderated fuel-rod arrays. The molybdenum is included as sleeves (tubes) on some of the fuel rods in the arrays. The fuel used in the experiments is known at Sandia as the Seven Percent Critical Experiment (7uPCX) fuel. This fuel has been used is several published benchmark evaluations in including LEU-COMP-THERM-78 and LEU-COMP THERM-080.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Generation IV Benchmarking of TRISO Fuel Performance Models Under Accident Conditions Final Report

The Generation IV International Forum (GIF) is a co-operative international endeavor of fourteen members organized to carry out the research and development needed to establish the feasibility and performance capabilities of the next generation nuclear energy systems. GIF selected six reactor technologies, amongst which is the Very High Temperature Reactor (VHTR) that is primarily dedicated to the cogeneration of electricity and hydrogen. The technical basis for VHTR is the tristructural isotropic (TRISO)-coated particle fuel, the graphite as the core structure, helium coolant, as well as the dedicated core layout and lower power density to removal decay heat in a natural way. At the heart of safety features of the VHTR concept lie the TRISO fuel particles that are designed to keep their structural integrity and retain fission products at temperatures up to 1600°C. As part as the design and future operation of VHTRs, a key aspect is the accurate prediction of fuel performance under irradiation and accident conditions. Modeling and simulation allow prediction of TRISO fuel behavior when subject to neutron flux and in high temperature accident scenarios. The refinement of the fuel performance models and codes is performed by comparison to in-pile and out-of-pile experimental data that reproduce the expected irradiation conditions in high temperature gas-cooled reactors (HTGRs). Historically, the International Atomic Energy Agency (IAEA) developed a benchmark dedicated to the validation of predictive methods for fuel and fission product behavior through the Coordinated Research Program CRP-2 (IAEA, 1997). CRP-2 was later updated to cover fuel fabrication, quality assurance, irradiation performance, safety testing, and spent fuel. The scope of the resulting CRP-6 benchmarks focused on HTGR fuel performance and fission product release (IAEA, 2012). Taking advantage of additional TRISO fuel fabrication, irradiation, and safety testing campaigns, GIF launched a Generation IV Benchmarking of TRISO Fuel Performance Models under Accident Conditions in late 2015. This GIF benchmark is a three-year program steered by Idaho National Laboratory (INL, USA). The other participants include the Japan Atomic Energy Agency (JAEA, Japan) and the Korea Atomic Energy Research Institute (KAERI, Korea). The objectives of the benchmark are to: follow on the IAEA CRP benchmarks, (2) model fission product release under accident conditions, (3) compare results obtained by the fuel performance modeling codes of the benchmark participants, and (4) compare these code predictions to experimental data. Safety tests chosen for modeling include the first and second experiments of the Advanced Gas Reactor program (AGR-1 and AGR-2) and the High Flux Reactor (HFR) EU1bis experiment. This report presents the results obtained by the three research institutions using their respective fuel performance modeling codes. Comparisons of the corresponding fission product release predictions are made with experimental data from AGR-1, AGR-2, and HFR-EU1bis. The benchmark results show good agreements between all participants but also show a general trend of over-prediction of the experimental release data, which is mainly attributed to the use of over-estimated diffusion coefficients.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

A fully-integrated lattice Boltzmann method for fluid–structure interaction

Here we present a fully-integrated lattice Boltzmann (LB) method for fluid–structure interaction (FSI) simulations that efficiently models deformable solids in complex suspensions and active systems. Our Eulerian method (LBRMT) couples finite-strain solids to the LB fluid on the same fixed computational grid with the reference map technique (RMT). An integral part of the LBRMT is a new LB boundary condition for moving deformable interfaces across different densities. With this fully Eulerian solid–fluid coupling, the LBRMT is well-suited for parallelization and simulating multi-body contact without remeshing or extra meshes. We validate its accuracy via a benchmark of a deformable solid in a lid-driven cavity, then showcase its versatility through examples of soft solids rotating and settling. The LBRMT achieves a spatial convergence rate between first-order and second-order for FSI simulations and is designed for low to intermediate Reynolds number flows with finite inertia at small Mach numbers. With simulations of complex suspensions mixing, we highlight the potential of the LBRMT for studying collective behavior in soft matter and biofluid dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Autoregressive distributed lag-based dynamic uniformity modeling and monitoring approaches for superconductor manufacturing

High-temperature superconductors (HTS), known for their high efficiency and low energy loss, have found profound applications across various fields, driving the demand for long, uniformly performing tapes. However, ensuring uniform performance over extended lengths of HTS tapes, often characterized by the consistency of critical current, remains challenging due to fluctuations in growth conditions during manufacturing. Here, to elucidate the mechanisms underlying variations in tape uniformity and enable real-time monitoring of associated parameters, we propose an Autoregressive Distributed Lag (ADL)-based Dynamic Uniformity Modeling and Monitoring (ADUM2) approach. This method integrates uniformity measurement, the identification of critical process parameters and real-time monitoring within the manufacturing process. The ADUM2 approach is applied to the advanced metal organic chemical vapor deposition (A-MOCVD) process, a pilot-scale method for superconductor manufacturing. Our model demonstrates superior performance compared to benchmark methods, accounting for over 80% of the total variance in the data and identifying 13 key process parameters influencing the uniformity of HTS tapes. This study offers significant insights into the high-temperature superconductor manufacturing process and holds the potential to facilitate the production of cost-effective, uniformly performing long superconducting tapes in the future.

autoregressive distributed lag analysis↗
DOE OSTI2019

A Moving Target Defense Control Framework for Cyber-Physical Systems

This paper considers the problem of efficiently and securely controlling cyber-physical systems that are operating in uncertain, and adversarial environments. To mitigate sensor, actuator attacks, and performance loss due to such attacks, we formulate a secure control algorithm that consists of a proactive and a reactive defense mechanism. The proactive mechanism, which is based on the principles of moving target defense, utilizes a stochastic switching structure to dynamically and continuously alter the parameters of the system, while hindering the attacker's ability to conduct successful reconnaissance to the system. The unpredictability of the current actuator and sensor is optimized using an information entropy measure, which is induced by probabilistic switching. The reactive mechanism on the other side, detects potentially attacked components, namely sensors and actuators, by leveraging online data to compute an integral Bellman error. A rigorous mathematical framework is presented to guarantee the stability of the equilibrium point of the closed-loop system, and provide a quantified bound on the performance loss when utilizing both reactive and proactive mechanisms. Simulation results show the efficacy of the proposed approaches on a benchmark aircraft model.

42 ENGINEERING↗
DOE OSTI2013

Verification & Validation of High-Order Short-Characteristics-Based Deterministic Transport Methodology on Unstructured Grids

The research team has developed a practical, high-order, discrete-ordinates, short characteristics neutron transport code for three-dimensional configurations represented on unstructured tetrahedral grids that can be used for realistic reactor physics applications at both the assembly and core levels. This project will perform a comprehensive verification and validation of this new computational tool against both a continuous-energy Monte Carlo simulation (e.g. MCNP) and experimentally measured data, an essential prerequisite for its deployment in reactor core modeling. Verification is divided into three phases. The team will first conduct spatial mesh and expansion order refinement studies to monitor convergence of the numerical solution to reference solutions. This is quantified by convergence rates that are based on integral error norms computed from the cell-by-cell difference between the code’s numerical solution and its reference counterpart. The latter is either analytic or very fine- mesh numerical solutions from independent computational tools. For the second phase, the team will create a suite of code-independent benchmark configurations to enable testing the theoretical order of accuracy of any particular discretization of the discrete ordinates approximation of the transport equation. For each tested case (i.e. mesh and spatial approximation order), researchers will execute the code and compare the resulting numerical solution to the exact solution on a per cell basis to determine the distribution of the numerical error. The final activity comprises a comparison to continuous-energy Monte Carlo solutions for zero-power critical configuration measurements at Idaho National Laboratory’s Advanced Test Reactor (ATR). Results of this comparison will allow the investigators to distinguish between modeling errors and the above-listed discretization errors introduced by the deterministic method, and to separate the sources of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Verification and Validation of High-Fidelity Multi-Physics Simulation Codes for Advanced Nuclear Reactors (Year 2)

The project objective is to verify and validate a suite of high-fidelity multi-physics simulation methods and codes developed during the previous I-NERI projects, against Monte Carlo solutions and experimental measurements for LWR and VHTR cores. Using benchmark problems developed during the previous year, ANL and KAERI continued to work on verifying the neutronics code DeCART and associated cross section libraries. Initial progress was also made on validating the code against experimental data. KAERI focused on verifying the DeCART code against numerical benchmark problems such as a PMR200 2-D pin cell/core and a HTTR 2-D block/core as well as improving DeCART capabilities such as the cross-section library group structure optimization, the fundamental and generalized adjoint equation solver, cylindrical boundary treatment, improved ray tracing, and implementing the direct resonance integral table method for resonance treatment. Verification test results for the updated capabilities showed substantial improvements in the estimation of eigenvalue and reaction rates.

Lee, C. H.↗
NASA NTRS2013

Characterization of Fluorescent Polystyrene Microspheres for Advanced Flow Diagnostics

Fluorescent dye-doped polystyrene latex microspheres (PSLs) are being developed for velocimetry and scalar measurements in variable property flows. Two organic dyes, Rhodamine B (RhB) and dichlorofluorescence (DCF), are examined to assess laser-induced fluorescence (LIF) properties for flow imaging applications and single-shot temperature measurements. A major interest in the current research is the application of safe dyes, thus DCF is of particular interest, while RhB is used as a benchmark. Success is demonstrated for single-point laser Doppler velocimetry (LDV) and also imaging fluorescence, excited via a continuous wave 2 W laser beam, for exposures down to 10 ms. In contrast, when exciting with a pulsed Nd:YAG laser at 200 mJ/pulse, no fluorescence was detected, even when integrating tens of pulses. We show that this is due to saturation of the LIF signal at relatively low excitation intensities, 4-5 orders of magnitude lower than the pulsed laser intensity. A two-band LIF technique is applied in a heated jet, indicating that the technique effectively removes interfering inputs such as particle diameter variation. Temperature measurement uncertainties are estimated based upon the variance measured for the two-band LIF intensity ratio and the achievable dye temperature sensitivity, indicating that particles developed to date may provide about +/-12.5 C precision, while future improvements in dye temperature sensitivity and signal quality may enable single-shot temperature measurements with sub-degree precision.

Maisto, Pietro M. F.↗
NASA NTRS2024

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗
DOE OSTI2022

Bio-Optimized Technologies to Keep Thermoplastics out of Landfills and the Environment (BOTTLE)

Plastics have revolutionized modern life, but reliance on these fossil-based materials that persist for centuries is causing a pollution crisis and contributing to greenhouse gas (GHG) emissions. To develop new technologies to address this problem, the Bio-Optimized Technologies to keep Thermoplastics out of Landfills and the Environment (BOTTLE) Consortium will deliver selective, scalable technologies to enable cost-effective recycling, upcycling, and increased energy efficiency. BOTTLE is an interdisciplinary team of experts that aim to develop selective, scalable processes to deconstruct and upcycle today's plastics and thermosets, redesign tomorrow's plastics to be recyclable-by-design (RBD) and derived from both bio-based and plastic waste-based feedstocks, work with industrial partners across the value chain to catalyze the circular economy for plastics, and leverage AMO and BETO investments in analysis-guided R&D, integrated process development, chemical and biological catalysis, materials characterization, modeling, and data science. BOTTLE is guided by techno-economic analysis (TEA) and supply chain-based life-cycle assessment (LCA). BOTTLE comprises members from ten partner institutions. Primary outcomes to date include establishment of a full consortium, impactful, benchmarking analyses that will be important for the plastics recycling and upcycling community, and multiple impactful, high-impact publications across the breadth of our research portfolio.

bio-optimized↗