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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Thermal conductivity of crack-containing media: A numerical study

The present study aims to evaluate the effective thermal conduction behavior of crack-containing media through micromechanical modeling. Numerical analyses were performed using the finite element method, first using periodic arrays of elliptical pores and then reducing the elliptical minor axis to reach the crack limit. This parametric approach was seen to be able to capture the effect of discontinuity across the crack face in a straightforward manner. The overall thermal conductivity of the model structures, encompassing a range of crack densities and spatial distributions, was investigated. It was found that, for cracks with mixed orientations, the effective thermal conductivity is insensitive to the actual crack alignment and can be uniquely represented by the crack density. The mixed-orientation periodic crack configurations are also representative of random sizes, orientations, and spatial distributions of cracks, thus exhibiting a high degree of generality. The modeling analyses can also be used to determine simple empirical expressions for two- and three-dimensional media containing random cracks.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Validation of a CFD Model Predicting the Effect of High Level Lateral Acceleration Sloshing on the Heat Transfer and Pressure Drop in a Small-Scale Tank in Normal Gravity

A two-phase CFD model is developed to study the effects of sloshing with high level lateral acceleration on the heat transfer and pressure drop in a small scale tank. Computational results are compared to the data provided by a non-isothermal sloshing experiment without phase change conducted by T. Himeno et al. at the University of Tokyo and JAXA in 2011. The results of the current model are, also, compared to CFD predictions reported by Himeno et al. A step change in lateral acceleration was applied in the experiment. Different levels of lateral acceleration amplitude, varying between 0G and 0.5G, were considered. CFD results for interface movement and tank pressure are presented and compared in this paper to the experimental data for the case in which the value of lateral acceleration was set to 0.5G. The effects of initial and boundary conditions and turbulence modeling approach on the tank pressure change during sloshing are discussed in detail. The effect of conjugate heat transfer in the tank wall is also studied to show its important role in determining the tank pressure evolution. The results of the Reynolds Averaged Navier Stokes (RANS) models are compared to the results of the Large Eddy Simulation model (LES) to underscore the importance of correctly capturing the effects of turbulence for high fidelity predictions.

multiphase flow↗
NASA NTRS2018

Validation of A CFD Model Predicting the Effect of High Level Lateral Acceleration Sloshing on the Heat Transfer and Pressure Drop in A Small-Scale Tank in Normal Gravity

A two-phase CFD model is developed to study the effects of sloshing with high level lateral acceleration on the heat transfer and pressure drop in a small scale tank. Computational results are compared to the data provided by a non-isothermal sloshing experiment without phase change conducted by T. Himeno et al. at the University of Tokyo and JAXA in 2011 [1]. The results of the current model are, also, compared to CFD predictions reported by Himeno et al. [2]. A step change in lateral acceleration was applied in the experiment. Different levels of lateral acceleration amplitude, varying between 0G and 0.5G, were considered. CFD results for interface movement and tank pressure are presented and compared in this paper to the experimental data for the case in which the value of lateral acceleration was set to 0.5G. The effects of initial and boundary conditions and turbulence modeling approach on the tank pressure change during sloshing are discussed in detail. The effect of conjugate heat transfer in the tank wall is also studied to show its important role in determining the tank pressure evolution. The results of the Reynolds Averaged Navier Stokes (RANS) models are compared to the results of the Large Eddy Simulation model (LES) to underscore the importance of correctly capturing the effects of turbulence for high fidelity predictions.

multiphase flow↗
DOE OSTI2023

Microbial growth under drought is confined to distinct taxa and modified by potential future climate conditions

Climate change increases the frequency and intensity of drought events, affecting soil functions including carbon sequestration and nutrient cycling, which are driven by growing microorganisms. Yet we know little about microbial responses to drought due to methodological limitations. Here, we estimate microbial growth rates in montane grassland soils exposed to ambient conditions, drought, and potential future climate conditions (i.e., soils exposed to 6 years of elevated temperatures and elevated CO 2 levels). For this purpose, we combined 18 O-water vapor equilibration with quantitative stable isotope probing (termed ‘vapor-qSIP’) to measure taxon-specific microbial growth in dry soils. In our experiments, drought caused >90% of bacterial and archaeal taxa to stop dividing and reduced the growth rates of persisting ones. Under drought, growing taxa accounted for only 4% of the total community as compared to 35% in the controls. Drought-tolerant communities were dominated by specialized members of the Actinobacteriota, particularly the genus Streptomyces. Six years of pre-exposure to future climate conditions (3 °C warming and + 300 ppm atmospheric CO 2 ) alleviated drought effects on microbial growth, through more drought-tolerant taxa across major phyla, accounting for 9% of the total community. Our results provide insights into the response of active microbes to drought today and in a future climate, and highlight the importance of studying drought in combination with future climate conditions to capture interactive effects and improve predictions of future soil-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Geometry-Driven Longitudal Topic Model

A simple and scalable framework for longitudinal analysis of Twitter data is developed that combines latent topic models with computational geometric methods. Dimensionality reduction tools from computational geometry are applied to learn the intrinsic manifold on which the latent, temporal topics reside. Then shortest path distances on the manifold are used to link together these topics. The proposed framework permits visualization of the low-dimensional embedding which provides clear interpretation of the complex, high-dimensional trajectories that may exist among latent topics. Practical application of the proposed framework is demonstrated through its ability to capture and effectively visualize natural progression of latent COVID-19 related topics learned from Twitter data. Interpretability of the trajectories is achieved by comparing to real-world events. In addition, the framework permits study of spatial variation in Twitter behavior for learned topics. The analysis demonstrates that the proposed framework is able to capture granular-level impact of COVID-19 on public discussions. We end by arguing that Twitter data, when analyzed within the proposed framework, can serve as a valuable supplementary data stream for COVID-related studies.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Liquefied Bleed for Stability and Efficiency of High Speed Inlets

A mission analysis code was developed to perform a trade study on the effectiveness of liquefying bleed for the inlet of the first stage of a TSTO vehicle. By liquefying bleed, the vehicle weight (TOGW) could be reduced by 7 to 23%. Numerous simplifying assumptions were made and lessons were learned. Increased accuracy in future analyses can be achieved by: Including a higher fidelity model to capture the effect of rescaling (variable vehicle TOGW). Refining specific thrust and impulse models ( T m a and Isp) to preserve fuel-to-air ratio. Implementing LH2 for T m a and Isp. Correlating baseline design to other mission analyses and correcting vehicle design elements. Implementing angle-of-attack effects on inlet characteristics. Refining aerodynamic performance (to improve L/D ratio at higher Mach numbers). Examining the benefit with partial cooling or densification of the bleed air stream. Incorporating higher fidelity weight estimates for the liquefied bleed system (heat exchange and liquid storage versus bleed duct weights) could be added when more fully developed. Adding trim drag or 6-degree-of-freedom trajectory analysis for higher fidelity. Investigating vehicle optimization for each of the bleed configurations.

Saunders, J. David↗
DOE OSTI2022

Stochastic Modeling in a Multimaterial Continuum Mixture Shock Physics Code

Stochastic modelling approaches are presented to capture random effects at multiple time and length scales. Random processes that occur at the microscale produce nondeterministic effects at the macroscale. Here we present three stochastic modeling approaches that describe random processes at microscopic length scales and map these processes to the macroscopic length scale. The first stochastic modeling approach is based upon a particle based numerical technique to solve a Stochastic Differential Equation (SDE) using an arbitrary diffusion process to capture random processes at the microstructural level. The second approach prescribes a Probability Density Function (PDF) for the drift and diffusion of the random variable derived using the forward and backward Kolmogorov equations. This method requires mean and drift evolution PDF transport equations. The third approach is the coupling of multiple random variables which are dependent on each other. The relationship of the PDFs and a coupling function, known as a copula, produces a Joint Probability Density Function (JPDF). These stochastic modeling approaches are implemented into a Multiple Component (MC) shock physics computational code and used to model statistical fracture and reactive flow applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Effect of chemical disorder on the electronic stopping of solid solution alloys

The electronic stopping power of nickel-based equiatomic solid solutions alloys NiCr, NiFe and NiCo for protons and alpha projectiles is investigated in detail using real-time time-dependent density functional theory over a wide range of velocities. Recently developed numerical electronic structure methods are used to probe fundamental aspects of electron-ion coupling non-perturbatively and in a fully atomistic context, capturing the effect of the atomic scale disorder. The effects of particular electronic band structures and density of states reflect in the low velocity limit behavior. We compare our results for the alloys with those of a pure nickel target to understand how alloying affects the electronic stopping. We discover that NiCo and NiFe have similar stopping behavior as Ni while NiCr has an asymptotic stopping power that is more than a factor of two larger than its counterparts for velocities below 0.1 a.u.. Overall, we show that the low-velocity limit of electronic stopping power can be manipulated by controlling the broadening of the d-band through the chemical disorder. In this regime, the Bragg’s additive rule for the stopping of composite materials also fails for NiCr.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Code Benchmark of the HTTF Pressurized Conduction Cooldown Test Using SAM

The High Temperature Test Facility (HTTF) at Oregon State University is an integral system test facility to simulate postulated reactor transients of prismatic high-temperature gas-cooled reactors(HTGRs). A series of test campaigns was launched, providing abundant test data that could be used to benchmark reactor system analysis codes like the System Analysis Module (SAM). In this study, a SAM model of the facility is developed based on the two-dimensional (2D) ring model approach. All components including the ceramic matrix, graphite heaters, helium coolant channels, core barrel, upcomer, pressure vessel, and reactor cavity cooling system are modeled as concentric cylindrical rings. The model is used to simulate one of the benchmark problems-Pressurized Conduction Cooldown (PCC)-within the scope of the Organisation for Economic Co-operation and Development Nuclear Energy Agency International HTTF Benchmark. The simulations consist of two parts. In the first part, operating and boundary conditions as well as thermophysical properties of materials are specified for the benchmark problem. In this work, results from the first part will be used in code-to-code comparison. In the second part, the SAM model is used to simulate Test PG-27, which is the first PCC test carried out in the HTTF, with only two of the ten heater banks activated. The results in the second part are used for code-to-data comparison. Because the helium coolant flow rate is not measured in this facility, it is estimated using the input power and inlet/outlet coolant temperatures. Additionally, radial heat flow in the ceramic blocks is complicated by hundreds of cylindrical coolant channels and heater rods embedded in them. As such, it is necessary to deduce an effective thermal conductivity for the ceramic to analyze the core thermal behavior. SAM predictions of the helium coolant and ceramic temperatures are compared with test data measured in three equivalent sectors. Overall, the SAM results agree reasonably well with test data within the variation of data among the three sectors, which demonstrates SAM's capability in capturing transient effects in HTGR using the simplified 2D ring model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2016

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

Soil Moisture Active Passive↗
DOE OSTI2025

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗
DOE OSTI2024

An experimentally validated electro-thermal EV battery pack model incorporating cycle-life aging and cell-to-cell variations

Lithium-ion batteries are used in a wide variety of applications. To meet the power and energy demands of these applications battery packs are composed of hundreds to thousands of cells. The electrical and thermal interactions between cells introduce additional complexity in the pack dynamics. To capture these effects, a battery pack model composed of 192 cells based on a first-generation (2012) Nissan Leaf battery pack is developed in MATLAB/Simulink/Simscape. Here, with this model, we simulate the electrical dynamics (using a first-order equivalent-circuit model), the thermal dynamics (using a first-order lumped-parameter thermal model), and the aging dynamics (using a semi-empirical severity factor-based model) of every cell in the pack and we also create a pack thermal model that explicitly captures the heat exchange between the modules, and the cells contained within, during operation. The models are calibrated and validated, both at the cell and pack level, with experimental data. Two different case studies of this pack model are investigated. In the first case study, an initial, normally-distributed, cell-to-cell capacity variation is introduced and its effect on the pack voltage and module temperatures is studied. In the second case study, we deliberately insert cells with lower than nominal capacity into the pack and we investigate how this type of initial cell-to-cell capacity variation affects the pack’s ability to deliver energy over time. Finally, we also study how parallel-connected cells can reduce the effects of cell-to-cell variations at the expense of increased aging of the pack overall.

25 ENERGY STORAGE↗
NASA NTRS1992

Coupled radiation effects in thermochemical nonequilibrium shock-capturing flowfield calculations

Lunar and Mars return conditions are examined using the LAURA flowfield code and the LORAN radiation code to assess the effect of radiative coupling on axisymmetric thermochemical nonequilibrium flows. Coupling of the two codes is achieved iteratively. Special treatment required to couple radiation in a shock-capturing method is discussed. Results indicate that while coupling effects are generally the same as occur in equilibrium flows, under certain conditions radiation can modify the chemical kinetics of a nonequilibrium flow and thus alter relaxation processes. Coupling effects are found to be small for all cases considered, except for a five meter diameter aerobrake returning from Mars at 13.6 km/sec.

Hartung, Lin C.↗
DOE OSTI2022

Mitigating the Impacts of Uncertain Geomagnetic Disturbances on Electric Grids: A Distributionally Robust Optimization Approach

Severe geomagnetic disturbances (GMDs) increase the magnitude of the electric field on the Earth’s surface (E-field) and drive geomagnetically-induced currents (GICs) along the transmission lines in electric grids. These additional currents can pose severe risks, such as current distortions, transformer saturation and increased reactive power losses, each of which can lead to system unreliability. Today several mitigation actions (e.g., changing grid topology) exist that can reduce the harmful GIC effects on the grids. Making such decisions can be challenging, however, because the magnitude and direction of the E-field are uncertain and non-stationary. In this paper, we model uncertain E-fields using the distributionally robust optimization (DRO) approach that determines optimal transmission grid operations such that the worst-case expectation of the system cost is minimized. We also capture the effect of GICs on the nonlinear AC power flow equations. For solution approaches, we develop an accelerated column-and-constraint generation (CCG) algorithm by exploiting a special structure of the support set of uncertain parameters representing the E-field. Extensive numerical experiments based on “epri-21” and “uiuc-150” systems, designed for GMD studies, demonstrate (i) the computational performance of the accelerated CCG algorithm, (ii) the superior performance of distributionally robust grid operations that satisfy nonlinear, nonconvex AC power flow equations and GIC constraints, in comparison with standard stochastic programming-based methods during the out-of-sample testing.

42 ENGINEERING↗
DOE OSTI2024

Dynamic density functional theory of polymers with salt in electric fields

Here we present a dynamic density functional theory for modeling the effects of applied electric fields on the local structure of polymers with added salt (polymer electrolytes). Time-dependent equations for the local electrostatic potential and volume fractions of polymer, cation, and anion of added salt are developed using the principles of linear irreversible thermodynamics. For such a development, a field theoretic description of the free energy of polymer melts doped with salts is used, which captures the effects of local variations in the dielectric function. Connections of the dynamic density functional theory with experiments are established by relating the three phenomenological Onsager’s transport coefficients of the theory to the mutual diffusion of electrolyte, ionic conductivity, and transference number of one of the ions. The theory is connected with a statistical mechanical model developed by Bearman and Kirkwood [J. Chem. Phys. 28, 136 (1958)] after relating the three transport coefficients to friction coefficients. The steady-state limit of the dynamic density functional theory is used to understand the effects of dielectric inhomogeneity on the phase separation in polymer electrolytes. The theory developed here provides not only a way to connect with experiments but also to develop multi-scale models for studying connections between local structure and ion transport in polymer electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

The behavior of a liquid drop levitated and drastically flattened by an intense sound field

The deformation and break-up are studied of a liquid drop in levitation through the radiation pressure. Using high-speed photography ripples are observed on the central membrane of the drop, atomization of the membrane by emission of satellite drops from its unstable ripples, and shattering of the drop after upward buckling like an umbrella, or after horizontal expansion like a sheet. These effects are captured on video. The ripples are theorized to be capillary waves generated by the Faraday instability excited by the sound vibration. Atomization occurs whenever the membrane becomes so thin that the vibration is sufficiently intense. The vibration leads to a destabilizing Bernoulli correction in the static pressure. Buckling occurs when an existent equilibrium is unstable to a radial (i.e., tangential) motion of the membrane because of the Bernoulli effect. Besides, the radiation stress at the rim of the drop is a suction stress which can make equilibrium impossible, leading to the horizontal expansion and the subsequent break-up.

Lee, C. P.↗