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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
NASA NTRS1990

Heterogeneous reactions on nitric acid trihydrate

The first direct measurements are reported of the reaction probabilities at stratospheric temperatures for two important heterogeneous reactions on nitric acid trihydrate (NAT), the compound which makes up the predominant, type I form of polar stratospheric cloud (PSC). Sticking coefficients and solubilities of HCl and NAT, which are important in modeling physicochemical processes in the stratosphere, are also reported. The results show that the conversion of the chlorine reservoir species in the stratosphere to photochemically active forms can occur within a few days of the first appearance of type I PSCs during the polar winter.

Moore, S. B.↗
DOE OSTI2023

Electrochemical Performance of Mixed Redox-Active Organic Molecules in Redox Flow Batteries

Designing electrolytes based on mixture of different organic redox active molecules brings the opportunity of enhancing the volumetric energy density of flow batteries and removes the requirement of high solubility for individual organic species in the mixture. Here, in the present work, we conduct computational and experimental analysis to investigate the electrochemical performance of mixed redox-active organic molecules. A zero-dimensional transient model is employed to investigate the changes in the half-cell potential and the concentrations and partial currents of individual redox reactions in a mixture of organic molecules over time. The model demonstrates the effects of individual properties of species such as kinetic rate constants, mass transfer coefficients, concentration ratios and standard redox potentials and reports the effect of energy-losing homogenous chemical redox reaction on the voltage efficiency and concentration ratios of the mixed species. Pairs of anthraquinone negolyte species were selected for an experimental case study. A mixture of 2,6-N-TSAQ and 2,6-DHAQ showed 40% increase in the volumetric energy density compared to the performance of 2,6-DHAQ alone. Based on the results of the experimental and computational analysis, we propose guidelines for the design of suitable mixed redox-active organic species.

25 ENERGY STORAGE↗
DOE OSTI2023

The kinetics of the PuO 2 to Pu 2 O 3 conversion

Here in an oxidizing environment, the oxide formed on plutonium (Pu) metal is composed of a plutonium dioxide (PuO 2 ) top layer and a thin cubic plutonium sesquioxide (Pu 2 O 3 ) middle layer. In a reducing environment, the PuO 2 layer auto-reduces to cubic Pu 2 O 3 . The speed and extent of this conversion depend on the combination of temperature and time. While PuO 2 provides a strong diffusion barrier against unwanted Pu corrosion by gaseous species (like hydrogen), Pu 2 O 3 does not, since its crystal structure has chains of oxygen vacancies. The kinetics of the PuO 2 reduction are, therefore, of fundamental interest and enable researchers to better protect Pu from corrosion. In this report, the oxygen-diffusion-limited kinetics of the dioxide to sesquioxide conversion were obtained by dynamically heating a PuO 2 -covered Pu sample from 294 to 418 K in a high-vacuum vessel equipped with an in situ spectroscopic ellipsometer. The physical/chemical constraints in the conversion process were combined with the ellipsometry method of multi-sample analysis to track the percentage of PuO 2 and to compute the extent of Pu 2 O 3 formation. The resulting diffusion coefficients were compared against and then combined with complementary literature data to produce a comprehensive set of kinetic parameters for reliably modeling oxide conversion over a larger temperature range than spanned by prior studies. The extracted thermal activation energy barrier (43.7 kJ/mol) and pre-exponential factor (5.0 × 10 -10 cm 2 /s) for the oxygen-diffusion-limited process can be used to accurately model the PuO 2 to Pu 2 O 3 transformation in vacuum and/or inert gas applications.

36 MATERIALS SCIENCE↗
NASA NTRS2015

A Metric to Quantify Shared Visual Attention in Two-Person Teams

Introduction: Critical tasks in high-risk environments are often performed by teams, the members of which must work together efficiently. In some situations, the team members may have to work together to solve a particular problem, while in others it may be better for them to divide the work into separate tasks that can be completed in parallel. We hypothesize that these two team strategies can be differentiated on the basis of shared visual attention, measured by gaze tracking. 2) Methods: Gaze recordings were obtained for two-person flight crews flying a high-fidelity simulator (Gontar, Hoermann, 2014). Gaze was categorized with respect to 12 areas of interest (AOIs). We used these data to construct time series of 12 dimensional vectors, with each vector component representing one of the AOIs. At each time step, each vector component was set to 0, except for the one corresponding to the currently fixated AOI, which was set to 1. This time series could then be averaged in time, with the averaging window time (t) as a variable parameter. For example, when we average with a t of one minute, each vector component represents the proportion of time that the corresponding AOI was fixated within the corresponding one minute interval. We then computed the Pearson product-moment correlation coefficient between the gaze proportion vectors for each of the two crew members, at each point in time, resulting in a signal representing the time-varying correlation between gaze behaviors. We determined criteria for concluding correlated gaze behavior using two methods: first, a permutation test was applied to the subjects' data. When one crew member's gaze proportion vector is correlated with a random time sample from the other crewmember's data, a distribution of correlation values is obtained that differs markedly from the distribution obtained from temporally aligned samples. In addition to validating that the gaze tracker was functioning reasonably well, this also allows us to compute probabilities of coordinated behavior for each value of the correlation. As an alternative, we also tabulated distributions of correlation coefficients for synthetic data sets, in which the behavior was modeled as a first-order Markov process, and compared correlation distributions for identical processes with those for disparate processes, allowing us to choose criteria and estimate error rates. 3) Discussion: Our method of gaze correlation is able to measure shared visual attention, and can distinguish between activities involving different instruments. We plan to analyze whether pilots strategies of sharing visual attention can predict performance. Possible measurements of performance include expert ratings from instructors, fuel consumption, total task time, and failure rate. While developed for two-person crews, our approach can be applied to larger groups, using intra-class correlation coefficients instead of the Pearson product-moment correlation.

Gontar, Patrick↗
DOE OSTI2020

Quantitative Analysis of the Effects of Natural and Human Factors on a Hydrological System in Zhangweinan Canal Basin

Drought is a water deficit state caused by large-scale climate change that cannot be avoided by a water resource management system. Water scarcity refers to the unsustainable utilization of water resources over a long time, which is the result of water management policies. However, water deficits caused by drought and water scarcity often occur simultaneously and are indistinguishable. This study proposes a model-based simulation framework that can quantitatively distinguish natural factors (drought) from human factors (water scarcity) in a hydrological system. The simulation was applied to the Zhangweinan Canal Basin, based on the runoff sequences from 1950 to 2004. The results show that the runoff curve number, soil depth, soil available water, soil evaporation compensation coefficient, base runoff α coefficient and the maximum canopy interception have the highest sensitivity to runoff, and that the calibrated and validated SWAT model can effectively simulate the runoff process in the Zhangweinan Canal Basin and similar areas. Abrupt changes in human activities in 1975 and water scarcity led to the disappearance of the summer peak runoff period in both wet and dry years. Human factors are the main reason for the change in the hydrological system in the study area; the runoff loss caused by human factors is four times that caused by natural factors according to the proposed variable threshold. This study proposes a model-based simulation framework that can help water resource managers to distinguish the effects of drought and water scarcity in water-stressed areas and adjust management accordingly.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Preliminary analysis of ERS-1 SAR for forest ecosystem studies

An image obtained by the C-band VV-polarized ERS-1 SAR is examined with respect to potential land applications. A scene obtained near noon on August 15, 1991, along the U.S.-Canadian border near Sault Ste. Marie is calibrated relative to an array of trihedral corner reflectors and active radar calibrators distributed across the swath. Extensive contemporaneous ground observations of forest stands are used to predict the radar backscattering coefficient sigma at the time of the SAR overpass using a first-order vector radiative transfer model. These predictions generally agree with the calibrated ERS-1 data to within 1 dB. It is demonstrated that the dynamic range of sigma is sufficient to perform limited discrimination of various forest and grassland communities even for a single-date observation. Furthermore, retrieval of near-surface soil moisture is feasible for grass-covered soils when plant biomass is less than 1 tonne/ha.

Dobson, M. G.↗
NASA NTRS2008

How Deep and Hot was Earth's Magma Ocean? Combined Experimental Datasets for the Metal-silicate Partitioning of 11 Siderophile Elements - Ni, Co, Mo, W, P, Mn, V, Cr, Ga, Cu and Pd

Since approximately 1990 high pressure and temperature (PT) experiments on metal-silicate systems have showed that partition coefficients (D) for siderophile (iron-loving) elements are much different than those measured at low PT conditions. The high PT data have been used to argue for a magma ocean during growth of the early Earth. Initial conclusions were based on experiments and calculations for a small number of elements such as Ni and Co. However, for many elements only a limited number of experimental data were available then, and they only hinted at values of metal-silicate D's at high PT conditions. In the ensuing decades there have been hundreds of new experiments carried out and published on a wide range of siderophile elements. At the same time several different models have been advanced to explain the siderophile elements in the earth's mantle: a) intermediate depth magma ocean; 25-30 GPa, b) deep magma ocean; up to 50 GPa, and c) early reduced and later oxidized magma ocean. Some studies have drawn conclusions based on a small subset of siderophile elements, or a set of elements that provides little leverage on the big picture (like slightly siderophile elements), and no single study has attempted to quantitatively explain more than 5 elements at a time. The purpose of this abstract is to update the predictive expressions outlined by Righter et al. (1997) with new experimental data from the last decade, test the predictive ability of these expressions against independent datasets (there are more data now to do this properly), and to apply the resulting expressions to the siderophile element patterns in Earth's upper mantle. The predictive expressions have the form: lnD = alnfO2 + b/T + cP/T + d(1Xs) + e(1Xc) + SigmafiXi + g These expressions are guided by the thermodynamics of simple metal-oxide equilibria that control each element, include terms that mimic the activity coefficients of each element in the metal and silicate, and quantify the effect of variable oxygen fugacity. Preliminary results confirm that D(Ni) and D(Co) converge at pressures near 25-30 GPa and approximately 2200 K, and show that D(Pd) and D(Cu) become too low at the PT conditions of the deepest models. Furthermore, models which force fit V and Cr mantle concentrations by metal-silicate equilibrium overlook the fact that at early Earth mantle fO2, these elements will be more compatible in Mg-perovskite and (Fe,Mg)O than in metal. Thus an intermediate depth magma ocean, at 25-30 GPa, 2200 K, and at IW-2, can explain more mantle siderophile element concentrations than other models.

Righter, Kevin↗
DOE OSTI2021

Application of Machine Learning Techniques to an Agent-Based Model of Pantoea

Agent-based modeling (ABM) is a powerful simulation technique which describes a complex dynamic system based on its interacting constituent entities. While the flexibility of ABM enables broad application, the complexity of real-world models demands intensive computing resources and computational time; however, a metamodel may be constructed to gain insight at less computational expense. Here, we developed a model in NetLogo to describe the growth of a microbial population consisting of Pantoea . We applied 13 parameters that defined the model and actively changed seven of the parameters to modulate the evolution of the population curve in response to these changes. We efficiently performed more than 3,000 simulations using a Python wrapper, NL4Py . Upon evaluation of the correlation between the active parameters and outputs by random forest regression, we found that the parameters which define the depth of medium and glucose concentration affect the population curves significantly. Subsequently, we constructed a metamodel, a dense neural network, to predict the simulation outputs from the active parameters and found that it achieves high prediction accuracy, reaching an R 2 coefficient of determination value up to 0.92. Our approach of using a combination of ABM with random forest regression and neural network reduces the number of required ABM simulations. The simplified and refined metamodels may provide insights into the complex dynamic system before their transition to more sophisticated models that run on high-performance computing systems. The ultimate goal is to build a bridge between simulation and experiment, allowing model validation by comparing the simulated data to experimental data in microbiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Insights into the soft brittle-to-ductile transition from discrete dislocation dynamics

The Brittle-to-ductile transition (BDT) in body centered cubic metals exhibits a soft transition wherein the fracture toughness gradually rises to before the onset of ductility. The resultant brittle-to-ductile transition temperature can be described with an Arrhenius relationship whose activation energy is related to plasticity in the material. To provide further insight into the nature of the BDTT, in this work we utilized a discrete dislo- cation dynamics model with a crack to simulate the BDT and how it depends on the thermally activated nature of plasticity. The interrelationship between the BDT activation energy and the dislocation mobility parameters were determined via the calculation of first order sensitivity coefficients. This analysis allows us to demonstrate that the activation energy for the BDT is directly related to the activation energy for plasticity through an effective stress that defines this relationship. This effective stress physically is the average stress on the dislocations that move out of the crack. Lastly, we are able to show that this effective stress is dictated by the low temperature fracture toughness or cleave energy of the material and the source position, the latter of which can be affected by processing. Collectively, these results provide new insight into what controls the thermal activation of the BDT and what are the important parameters to control it.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A mixture parameterized biologically based dosimetry model to predict body burdens of polycyclic aromatic hydrocarbons in developmental zebrafish toxicity assays

Polycyclic aromatic hydrocarbons (PAHs) are a group of environmental toxicants found ubiquitously as complex mixtures in human-impacted environments. Developmental zebrafish exposures have been used widely to study PAH toxicity, but most studies report nominal exposure concentrations. Nominal exposure concentrations can be unreliable dose metrics due to differences in toxicant bioavailability resulting from disparate exposure methodologies and chemical properties. Toxicokinetic modeling can predict toxicant tissue doses to facilitate comparison between exposures of different chemicals, methodologies, and biological models. We parameterize a biologically based dosimetry model for developmental zebrafish toxicity assays for 9 PAHs. The model was optimized with measurements from media, tissue, and plastic plate walls throughout a static developmental exposure to a mixture of 10 PAHs of high abundance within the Portland Harbor Superfund Site. Plate binding, volatilization, zebrafish permeability, and tissue—media partitioning coefficients vary widely between PAHs. Model predictions accounted for 83% and 54% of 48 hpf body burdens within a factor of 2 resulting from exposures to mixtures and individual PAHs, respectively. Accounting for solubility significantly improves model performance. Competition for active sites in metabolizing enzymes may change biotransformation kinetics between individual PAH and mixture exposures. Area under the curve estimations of concentrations in zebrafish resulted in altered hazard rankings from nominal exposure concentrations. Future work will be oriented to generalizing the model to other PAHs. This PAH dosimetry model improves the interpretability of developmental zebrafish toxicity assays by providing time-resolved body burdens from nominal exposure concentrations.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS2013

Sweeping Jet Actuators - A New Design Tool for High Lift Generation

Active Flow Control (AFC) experiments performed at the Caltech Lucas Wind Tunnel on a generic airplane vertical tail model proved the effectiveness of sweeping jets in improving the control authority of a rudder. The results indicated that a momentum coefficient (C(sub u)) of approximately 2% increased the side force in excess of 50% at the maximum conventional rudder deflection angle in the absence of yaw. However, sparsely distributed actuators providing a collective C(sub u) approx. = 0.1% were able to increase the side force in excess of 20%. This result is achieved by reducing the spanwise flow along the swept back rudder and its success is attributed to the large sweep back angle of the vertical tail. This current effort was sponsored by the NASA Environmentally Responsible Aviation (ERA) project.

Graff, Emilio↗
DOE OSTI2024

Comment on “Thermodynamic Models for the (HClO 4 + NaClO 4 ){aq} and (HBr + NaBr){aq} Systems at 298.15 K and 0.1 MPa” Authored by Oakes, C. S., Ward, A. L., Chugunov, N. Journal of Chemical & Engineering Data , 68 , 2554–2562

Oakes et al. (2023) published a review article in this journal. In that paper, Oakes et al. (2023) developed thermodynamic models to describe electrolyte solutions for HClO 4 –NaClO 4 –H 2 O and HBr–NaBr–H 2 O systems, based on literature data. In their paper, previously published work from researchers in the field was criticized; some of it is ours. Here, in this brief Comment, we first comment on their models, and then we briefly provide a technical response to that criticism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Theoretical Model for Computing Freezing Point Depression of Lithium-Ion Battery Electrolytes

Reliable prediction of freezing point depression in liquid electrolytes will accelerate the development of improved Li-ion batteries which can operate in low temperature environments. In this work we establish a computational methodology to calculate activity coefficients and liquidus lines for battery-relevant liquid electrolytes. Electronic structure methods are used in conjuction with classical molecular dynamics simulations and theoretical expressions for Born solvation energy, ion-atmosphere effects from Debye-Hückel theory and solvent entropic effects. The framework uses no a priori knowledge beyond neat solvent properties and the concentration of salt. LiPF 6 in propylene carbonate (PC), LiPF 6 in dimethyl carbonate (DMC) and LiClO 4 in DMC are investigated up to 1 molal with accuracy better than 3 °C when compared to experimental freezing point measurements. Finally, we find that the difference in freezing point depression between the propylene carbonate-based electrolyte and the dimethyl carbonate electrolytes originates from the difference in the solvent dielectric constant.

25 ENERGY STORAGE↗
DOE OSTI2021

Biomass pyrolysis devolatilization kinetics of herbaceous and woody feedstocks

Devolatilization kinetics were determined using a modified micropyrolyzer reactor for several biomass feedstocks: switchgrass, corn stover, red oak, and pine. Here, the micropyrolyzer was directly coupled to a flame ionization detector (FID) to track the release of volatiles from the biomass. Time series data from these experiments was analyzed to determine apparent devolatilization rates. Care was taken to assure the experiments were isothermal and kinetically limited calculating a Biot number less than 0.1 and pyrolysis numbers greater than 10, which simplifies the derivation of devolatilization rates. A single, first order reaction was able to model devolatilization rates at temperatures up to 500 °C. No correlation was found between the inorganic content of the biomass and its rate of devolatilization. Apparent activation energies were in the range of 54.9–88.4 kJ mol –1 . The rate coefficient at 500 °C was calculated as 1.90–5.14 s –1 for the four feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs): An Efficient Physics-Informed Neural Networks Framework for Interface Problems

Here, we present an efficient physics-informed neural networks (PINNs) framework, termed Adaptive Interface-PINNs (AdaI-PINNs), to improve the modeling of interface problems with discontinuous coefficients and/or interfacial jumps. This framework is an enhanced version of its predecessor, Interface PINNs or I-PINNs (Sarma et al.; https://doi.org/10.1016/j.cma.2024.117135), which involves domain decomposition and assignment of different predefined activation functions to the neural networks in each subdomain across a sharp interface, while keeping all other parameters of the neural networks identical. In AdaI-PINNs, the activation functions vary solely in their slopes, which are trained along with the other parameters of the neural networks. This makes the AdaI-PINNs framework fully automated without requiring preset activation functions. Comparative studies on one-dimensional, two-dimensional, and three-dimensional benchmark elliptic interface problems reveal that AdaI-PINNs outperform I-PINNs, reducing computational costs by 2-6 times while producing similar or better accuracy.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1979

A method for obtaining practical flutter-suppression control laws using results of optimal control theory

The results of optimal control theory are used to synthesize a feedback filter. The feedback filter is used to force the output of the filtered frequency response to match that of a desired optimal frequency response over a finite frequency range. This matching is accomplished by employing a nonlinear programing algorithm to search for the coefficients of the feedback filter that minimize the error between the optimal frequency response and the filtered frequency response. The method is applied to the synthesis of an active flutter-suppression control law for an aeroelastic wind-tunnel model. It is shown that the resulting control law suppresses flutter over a wide range of subsonic Mach numbers. This is a promising method for synthesizing practical control laws using the results of optimal control theory.

Newson, J. R.↗
NASA NTRS1982

The Seasat altimeter data and its accuracy assessment

A description is given of the Seasat satellite radar altimeter, which was designed to measure (1) the altitude of the satellite above the ocean surface, (2) surface wave height, and (3) the ocean-surface backscatter coefficient from which wind speed may be inferred. The atmospheric and geophysical effects influencing radar altimeter measurement accuracies and the attendant correction models adopted for the altimeter geophysical data record are summarized, along with Seasat Altimeter/Precision Orbit Determination Experiment Team activities directed towards the validation and improvement of these models and investigations assessing the accuracy of both the altimeter measurements and the computed satellite altitude ephemeris.

Tapley, B. D.↗
NASA NTRS1992

Self-diffusion of magnesium in spinel and in equilibrium melts - Constraints on flash heating of silicates

An isotopic tracer is used to measure Mg self-diffusion in spinel and coexisting melt at bulk chemical equilibrium. The diffusion coefficients were calculated from the measured isotope profiles using a model that includes the complementary diffusion of Mg-24, Mg-25, and Mg-26 in both phases with the constraint that the Mg content of each phase is constant. The activation energy and preexponential factor for Mg self-diffusion in spinel are, respectively, 384 +/- 7 kJ and 74.6 +/- 1.1 sq cm/s. These data indicate Mg diffusion in spinel is much slower than previous estimates. The activation energy for Mg self-diffusion in coexisting melt is 343 +/- 25 kJ and the preexponential factor is 7791.9 +/- 1.3 sq cm/s. These results are used to evaluate cooling rates of plagioclase-olivine inclusions (POIs) in the Allende meteorite. Given a maximum melting temperature for POIs of about 1500 C, these results show that a 1-micron radius spinel would equilibrate isotopically with a melt within about 60 min.

Sheng, Y. J.↗