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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 OSTI2021

SISGR: Chemomechanics of Far-From-Equilibrium Interfaces (COFFEI)

Portable, reliable, and deployable devices for energy storage and conversion require fundamental changes in design of solid-state composites comprising ceramics and metals. These materials comprise the electrodes and electrolytes of next-generation solid-oxide fuel cells and all solid-state batteries, forming solid-state functional composites. The advent of solid-state batteries – which replace liquid electrolytes with solid electrolytes capable of lithium ion transport for reliable energy storage in portable batteries – and the increased demand space for all solid-state fuel cells capable of oxygen reduction at intermediate temperatures remain important challenges for improved material stability and decreased system cost. However, little is understood about three fundamental facets of materials that enable such solid-state energy applications. First, how do such materials deform, fracture, or delaminate under operando conditions? Second, how does such mechanical deformation limit or facilitate electronic and ionic transport within and across such material interfaces? Third, how we can predictably design interface-rich composites to engineer both structural and electrochemical stability? This COFFEI Group comprised expertise from Materials Science & Engineering and Nuclear Science & Engineering to integrate unique in situ experiments, simulations, and fabricated interfaces that address these fundamental questions in solid-state interfaces of nanoscale composites that will guide solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric materials that enable such applications. In particular, we built on COFFEI’s understanding of chemomechanical coupling among defect concentrations, ionic transport, electron transport, and stored elastic energy that is particularly acute in the far-from-equilibrium conditions typical of energy device applications. By tailoring our focus to solid-state interfaces, we addressed these important issues by (a) developing and applying advanced in situ and ex situ characterization tools to characterize model materials and interfaces synthesized with molecular-level control, under both laboratory-controlled and extreme environments representative of energy device operation; and (b) employing computational modeling and simulation frameworks to predict transport mechanisms, reactivity and stability of these model materials and interfaces under significant chemical strains typical of energy device operation. Recent progress provided insights to additional materials systems and electrochemomechanical fatigue and fracture that were not fully envisioned when the program was initiated. Specifically, in the final three years of COFFEI we pursued two integrated thrusts, with complementary focus. Thrust I focused on failure-resistant electrochemomechanical composites, while Thrust II focused on strain-modulated conductivity and reactivity across interfaces. In contrast to our initial COFFEI focus, these thrusts concentrated wholly on solid-state material interfacial interactions and included greater integration of multiscale visualization including in situ electron microscopy of strained structures/interactions and mesoscale simulations. Successful development of functionally superior and long-lived battery and fuel cell systems and stress adaptable oxides requires a deeper, fundamental understanding of the coupling among the historically important subfields of solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric metal oxide electrodes. In this program, the understanding and the application of chemomechanical coupling of defect concentrations, ionic transport, electro-catalytic activity and stored elastic energy, particularly acute in the far-from-equilibrium conditions typical of energy device applications, are being refined and implications for device operation clarified, including for miniaturized solid-state batteries and fuel cells.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Thermal History and Mantle Dynamics of Venus

One objective of this research proposal is to develop a 3-D thermal history model for Venus. The basis of our study is a finite-element computer model to simulate thermal convection of fluids with highly temperature- and pressure-dependent viscosities in a three-dimensional spherical shell. A three-dimensional model for thermal history studies is necessary for the following reasons. To study planetary thermal evolution, one needs to consider global heat budgets of a planet throughout its evolution history. Hence, three-dimensional models are necessary. This is in contrasts to studies of some local phenomena or local structures where models of lower dimensions may be sufficient. There are different approaches to treat three-dimensional thermal convection problems. Each approach has its own advantages and disadvantages. Therefore, the choice of the various approaches is subjective and dependent on the problem addressed. In our case, we are interested in the effects of viscosities that are highly temperature dependent and that their magnitudes within the computing domain can vary over many orders of magnitude. In order to resolve the rapid change of viscosities, small grid spacings are often necessary. To optimize the amount of computing, variable grids become desirable. Thus, the finite-element numerical approach is chosen for its ability to place grid elements of different sizes over the complete computational domain. For this research proposal, we did not start from scratch and develop the finite element codes from the beginning. Instead, we adopted a finite-element model developed by Baumgardner, a collaborator of this research proposal, for three-dimensional thermal convection with constant viscosity. Over the duration supported by this research proposal, a significant amount of advancements have been accomplished.

Hsui, Albert T.↗
NASA NTRS2011

Origins of Protein Functions in Cells

In modern organisms proteins perform a majority of cellular functions, such as chemical catalysis, energy transduction and transport of material across cell walls. Although great strides have been made towards understanding protein evolution, a meaningful extrapolation from contemporary proteins to their earliest ancestors is virtually impossible. In an alternative approach, the origin of water-soluble proteins was probed through the synthesis and in vitro evolution of very large libraries of random amino acid sequences. In combination with computer modeling and simulations, these experiments allow us to address a number of fundamental questions about the origins of proteins. Can functionality emerge from random sequences of proteins? How did the initial repertoire of functional proteins diversify to facilitate new functions? Did this diversification proceed primarily through drawing novel functionalities from random sequences or through evolution of already existing proto-enzymes? Did protein evolution start from a pool of proteins defined by a frozen accident and other collections of proteins could start a different evolutionary pathway? Although we do not have definitive answers to these questions yet, important clues have been uncovered. In one example (Keefe and Szostak, 2001), novel ATP binding proteins were identified that appear to be unrelated in both sequence and structure to any known ATP binding proteins. One of these proteins was subsequently redesigned computationally to bind GTP through introducing several mutations that introduce targeted structural changes to the protein, improve its binding to guanine and prevent water from accessing the active center. This study facilitates further investigations of individual evolutionary steps that lead to a change of function in primordial proteins. In a second study (Seelig and Szostak, 2007), novel enzymes were generated that can join two pieces of RNA in a reaction for which no natural enzymes are known. Recently it was found that, as in the previous case, the proteins have a structure unknown among modern enzymes. In this case, in vitro evolution started from a small, non-enzymatic protein. A similar selection process initiated from a library of random polypeptides is in progress. These results not only allow for estimating the occurrence of function in random protein assemblies but also provide evidence for the possibility of alternative protein worlds. Extant proteins might simply represent a frozen accident in the world of possible proteins. Alternative collections of proteins, even with similar functions, could originate alternative evolutionary paths.

Seelig, Burchard↗
DOE OSTI2021

Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection

A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed differential equation model. These results illustrate how realistic, spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

The Virtual Test Bed Project

This is a report of my activities as a NASA Fellow during the summer of 2003 at the NASA Kennedy Space Center (KSC). The core of these activities is the assigned project: the Virtual Test Bed (VTB) from the Spaceport Engineering and Technology Directorate. The VTB Project has its foundations in the NASA Ames Research Center (ARC) Intelligent Launch & Range Operations program (ILRO). The objective of the VTB project is to develop a unique collaborative computing environment where simulation models can be hosted and integrated in a seamless fashion. This collaborative computing environment will have as emphasis operational models. This report will focus on the decisions about the different simulation modeling environments considered, simulation platform development, technology and operational models assessment, and computing infrastructure implementation.

Rabelo, Luis↗
NASA NTRS2011

More-Accurate Model of Flows in Rocket Injectors

An improved computational model for simulating flows in liquid-propellant injectors in rocket engines has been developed. Models like this one are needed for predicting fluxes of heat in, and performances of, the engines. An important part of predicting performance is predicting fluctuations of temperature, fluctuations of concentrations of chemical species, and effects of turbulence on diffusion of heat and chemical species. Customarily, diffusion effects are represented by parameters known in the art as the Prandtl and Schmidt numbers. Prior formulations include ad hoc assumptions of constant values of these parameters, but these assumptions and, hence, the formulations, are inaccurate for complex flows. In the improved model, these parameters are neither constant nor specified in advance: instead, they are variables obtained as part of the solution. Consequently, this model represents the effects of turbulence on diffusion of heat and chemical species more accurately than prior formulations do, and may enable more-accurate prediction of mixing and flows of heat in rocket-engine combustion chambers. The model has been implemented within CRUNCH CFD, a proprietary computational fluid dynamics (CFD) computer program, and has been tested within that program. The model could also be implemented within other CFD programs.

Hosangadi, Ashvin↗
NASA NTRS2001

Assessment of the time constant of relaxation: insights from simulations and hemodynamic measurements

The objective of this study was to use high-fidelity animal data and numerical simulations to gain more insight into the reliability of the estimated relaxation constant derived from left ventricular pressure decays, assuming a monoexponential model with either a fixed zero or free moving pressure asymptote. Comparison of the experimental data with the results of the simulations demonstrated a trade off between the fixed zero and the free moving asymptote approach. The latter method more closely fits the pressure curves and has the advantage of producing an extra coefficient with potential diagnostic information. On the other hand, this method suffers from larger standard errors on the estimated coefficients. The method with fixed zero asymptote produces values of the time constant of isovolumetric relaxation (tau) within a narrow confidence interval. However, if the pressure curve is actually decaying to a nonzero pressure asymptote, this method results in an inferior fit of the pressure curve and a biased estimation of tau.

NASA Discipline Cardiopulmonary↗
NASA NTRS1996

A dynamical model for reflex activated head movements in the horizontal plane

We present a controls systems model of horizontal-plane head movements during perturbations of the trunk, which for the first time interfaces a model of the human head with neural feedback controllers representing the vestibulocollic (VCR) and the cervicocollic (CCR) reflexes. This model is homeomorphic such that model structure and parameters are drawn directly from anthropomorphic, biomechanical and physiological studies. Using control theory we analyzed the system model in the time and frequency domains, simulating neck movement responses to input perturbations of the trunk. Without reflex control, the head and neck system produced a second-order underdamped response with a 5.2 dB resonant peak at 2.1 Hz. Adding the CCR component to the system dampened the response by approximately 7%. Adding the VCR component dampened head oscillations by 75%. The VCR also improved low-frequency compensation by increasing the gain and phase lag, creating a phase minimum at 0.1 Hz and a phase peak at 1.1 Hz. Combining all three components (mechanics, VCR and CCR) linearly in the head and neck system reduced the amplitude of the resonant peak to 1.1 dB and increased the resonant frequency to 2.9 Hz. The closed loop results closely fit human data, and explain quantitatively the characteristic phase peak often observed.

NASA Discipline Neuroscience↗
DOE OSTI2022

Platinum nanoparticle compression: Combining in situ TEM and atomistic modeling

The mechanical behavior of nanoparticles governs their performance and stability in many applications. However, the small sizes of technologically relevant nanoparticles, with diameters in the range of 10 nm or less, significantly complicate experimental examination. These small nanoparticles are difficult to manipulate onto commercial test platforms and deform at loads that are below the typical noise floor of the testing instruments. Here, we synthesized small platinum nanoparticles directly onto a mechanical tester and used a modified nanomanipulator to enhance load resolution to the nanonewton scale. We demonstrated the in situ compression of an 11.5-nm platinum nanoparticle with simultaneous high-resolution measurements of load and particle morphology. Molecular dynamics simulations were performed on similarly sized particles to achieve complementary measurements of load and morphology, along with atomic resolution of dislocations. The experimental and simulation results revealed comparable values for the critical resolved shear stress for failure, 1.28 and 1.15 GPa, respectively. Altogether, this investigation demonstrated the promise of, and some initial results from, the combination of atomistic simulations and in situ experiments with an unprecedented combination of high spatial resolution and high load resolution to understand the behavior of metal nanoparticles under compression.

42 ENGINEERING↗
DOE OSTI2022

Sensitivity Analysis of an Electrospray Dehumidification System

Electrically enhanced condensation achieved by an electrospray system can enhance dehumidification in HVAC applications if successfully scaled up. The first step towards scale-up is identifying critical design and operating parameters that significantly impact dehumidification for the electrospray system. Sensitivity analysis is one approach for identifying critical parameters. This paper presents a methodology that can efficiently perform quantitative sensitivity analysis on a computationally expensive high fidelity simulation model, which is a computational fluid dynamics (CFD) model of the electrospray system. The methodology employs surrogate modeling and Sobol sensitivity analysis. We estimate the main and total effect Sobol sensitivity indices of four operating parameters of the electrospray system. The results reveal that the most important parameter is the size of the sprayed droplets, followed by the volumetric flow rate of the bulk air and injected water in the system. The water injection velocity of the spray was found to have little to no impact on dehumidification.

Young, David↗
DOE OSTI2020

A generalized approximate control variate framework for multifidelity uncertainty quantification

We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A linked-scale coupled model of mass erosion and redistribution in plasma-exposed micro-foam surfaces

Surface evolution due to exposure to harsh environments is of importance in many scientific and technological applications. In plasma-exposed materials, the surface receives charged particles from the plasma, leading to a series of processes that drive the system far from equilibrium and may lead to the severe deterioration of the surface properties. Although surface morphological changes are driven by atomic collisions taking place over picoseconds and nanometers, these processes result in mass loss and redistribution of matter over much larger length and time scales. This necessitates a multi-scale approach capable of capturing the range of processes linking primary atomic collision events with engineering-level surface geometry changes. In this paper, we develop a computational model to simulate the morphological evolution and effective erosion rate of micro-architected tungsten foams during low-energy plasma ion bombardment. Furthermore, the model acts on several length scales, with the energy and angular dependence of the sputtering yield of flat tungsten surfaces determined using the SRIM code based on the binary collision approximation. This information is introduced into a low-fluence, short-term Monte Carlo raytracing model, and further into a high-fluence, long-term particle transport model. In the latter, material particles representing billions of atoms are described in a digitized 3-D representation of the foam structure from X-ray tomography data, and are sputtered off and redeposited using the atomistic information. We show that the redeposition of sputtered atoms leads to partial self-healing in the bottom layers with a sharp reduction in the sputtering coefficient of low density foams, roughly 25% of the solid W value. This is in qualitative agreement with recent experiments on low porosity W structures. At high fluence, the foam structure degrades considerably as there are fewer ligaments available to recapture sputtered atoms and, consequently, the sputtering rate increases again.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Two-layer cathode architecture for high-energy density and high-power density solid state batteries

Solid state batteries with high-energy density and high-power density require the development of thick and energy dense cathodes. Structured cathode electrodes with a double-layer configuration were enabled using a freeze tape casting technique. A bottom dense layer was utilized to enhance the energy density whereas a top porous layer with vertically aligned walls was utilized to enhance the power density. The porous structure of the power layer was achieved by ice templating this layer on top of the densified energy layer of the cathode. This configuration was found to better utilize the active material of the cathodes and was optimized using numerical simulation and computer modeling. Cells with Li metal anode and LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) at approximately 5 and 20 mg/cm 2 were cycled at 70 °C at different C-rates. Poly(ethylene oxide) (PEO) with lithium bis-trifluoromethanesulfonimide (LiTFSI) was used for the catholyte and the solid-state electrolyte. The structured cathodes exhibited more than double capacity values as well as better Coulombic efficiency compared to non-structured (single-layer) thick cathodes. In conclusion, synchrotron X-ray tomography and scanning electron microscopy were used to characterize the microstructure of the cathodes.

25 ENERGY STORAGE↗
DOE OSTI2025

Temperature sensitivity of the equilibrium neutronics and accident analysis of the HTR-10

Pebble-Bed High-Temperature Gas-cooled Reactors (PB-HTGR) are moderated by the graphite in the fuel pebbles and the graphite reflector surrounding the pebble-bed. Because graphite is by far the most abundant material in PB-HTGRs and the primary moderator, accurate modeling of the graphite material, including density, impurities, and temperatures, is crucial for accurate computational modeling and simulation of these reactors. While main characteristics of the graphite components are often known, the local temperature is less well known and often averaged over all components. Here, this work studies the impact of considering accurate temperature profiles in the graphite material on the generation of a small PB-HTGR model at the state of equilibrium operation and on short-term accident progression. The fuel compositions for the PB-HTGR were determined using a jump-in equilibrium modeling method, the Axial Radial Zone Equilibrium Modeling (AR-ZEM) method. In contrast to previous work, the AR-ZEM method was used considering thermal-hydraulic feedback from the MELCOR code to determine temperatures of the fuel pebbles and the surrounding graphite reflector. The consideration of an axial and radial temperature profile in the core and reflector, as opposed to uniform material temperatures, had an impact of almost 1,300 pcm on the equilibrium core eigenvalue and caused significant differences in the discharged plutonium fuel inventory with up to 4.9% and 11.0% for Pu-239 and Pu-242, respectively. To assess the impact on short-term accident progression, two Anticipated Transient Without SCRAM (ATWS) events, a Pressurized Loss of Forced Coolant (PLOFC) and a Control Rod Withdrawal (CRW) with loss of flow, were simulated with MELCOR. The use of temperature profiles in the equilibrium core models did not reveal a significant impact on the temperature, power, or reactivity responses during the transients. In conclusion, a need for consideration of accurate temperature profiles, in particular for the graphite reflector, was found for the generation of equilibrium PB-HTGRs core models using jump-in methods, but detailed temperature profiles may not be necessary when performing conservative transient analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Modeling High Current Pulsed Discharge in AA Battery Cathodes: The Effect of Localized Charging during Rest

During high current operation, substantial heterogeneity develops within battery cathodes, particularly when their thickness is large. Heterogeneity relaxation during subsequent rest is important for understanding battery performance under pulsed conditions. Localized charge balancing phenomena within batteries at zero net current are not well understood and merit investigation. In this work, the heterogeneity within cathodes of commercial alkaline Zn–MnO 2 batteries is measured during discharge and monitored during rest using energy dispersive X-ray diffraction (EDXRD). Significant gradients in protonation form during discharge and partially relax under rest. It is demonstrated that the proton gradient relaxation is through local redox activity at zero net current, where local (de)protonation works to redistribute charge across the cathode thickness. To support this redox-based relaxation, a fundamental kinetic study on prismatic MnO 2 cathodes is conducted to determine an appropriate model to describe both discharge and charge kinetics of MnO 2 . These kinetics are incorporated into a computational model to simulate the proton gradient formation and partial relaxation under identical discharge conditions as the operando EDXRD experiments. Model and experimental data are found to be in excellent agreement, correctly predicting localized charge balancing at rest.

Batteries↗
DOE OSTI2021

Contribution of the Two Types of Ekman Pumping Induced Eddy Heat Flux to the Total Vertical Eddy Heat Flux

Based on eddy-rich (0.1° horizontal resolution for ocean) Community Earth System Model simulations, we compute the Ekman pumping induced vertical eddy heat flux using two formulations: the classical and the Stern-Ekman pumping. The two mechanisms yield similar patterns in the eddy-induced vertical heat flux, showing strong upward heat flux in ocean frontal regions such as the western boundary current regions. Using the Gulf Stream Extension region as an example, we estimate (1) the Stern-Ekman pumping induced eddy heat flux is 23% and 12% of the total vertical eddy heat flux at 50 m depth during summer and winter, respectively; (2) the classical Ekman pumping accounts for 82% and 88% of the Stern-Ekman pumping induced eddy heat flux at 50 m during summer and winter, respectively. The second finding indicates eddy current feedback on wind stress is the primary cause for the upward eddy heat flux generated by Ekman pumping.

58 GEOSCIENCES↗
DOE OSTI2026

Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions

High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.

Prantikos, Konstantinos [Argonne National Laborato↗