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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rigorous computation of short-range order unifies its controversial effects in complex concentrated alloys

Direct experimental observations of chemical short-range order (SRO) in complex concentrated alloys (CCAs) have triggered high interest. However, the reported effects of SRO on yield stresses are controversial, and their atomic-scale mechanisms are elusive, which limits our ability to utilize SRO in alloy design. Here we tackle this challenge using an advanced computational approach that rigorously takes into account the critical lattice distortion in CCAs and further verify our theoretical predictions with experiments. We show that the CoCrNi model alloy has a narrow temperature window around 670 °C for SRO formation. This explains why the mechanical effect of SRO is observed in some experiments but not in others. Here, we propose an effective alloy-doping method to control SRO and reveal atomic-bonding types that dominate SRO formation for different alloys. The strategies and insights generally apply to a broad spectrum of alloys, laying the foundation for designing advanced alloys by manipulating their SRO.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Magnetic field evolution in white dwarfs: The hall effect and complexity of the field

We calculate the evolution of the magnetic fields in white dwarfs, taking into account the Hall effect. Because this effect depends nonlinearly upon the magnetic field strength B, the time dependences of the various multipole field components are coupled. The evolution of the field is thus significantly more complicated than has been indicated by previous investigations. Our calculations employ recent white dwarf evolutionary sequences computed for stars with masses 0.4, 0.6, 0.8, and 1.0 solar mass. We show that in the presence of a strong (up to approximately 10(exp 9) G) internal toroidal magnetic field; the evolution of even the lowest order poloidal modes can be substantially changed by the Hall effect. As an example, we compute the evolution of an initially weak quadrupole component, which we take arbitrarily to be approximately 0.1%-1% of the strength of a dominant dipole field. We find that coupling provided by the Hall effect can produce growth of the ratio of the quadrupole to the dipole component of the surface value of the magnetic field strength by more than a factor of 10 over the 10(exp 9) to 10(exp 10) year cooling lifetime of the white dwarf. Some consequences of these results for the process of magnetic-field evolution in white dwarfs are briefly discussed.

Muslimov, A. G.↗
NASA NTRS2000

Potential Applications of Satellite Based Low Frequency Microwave Measurements of Snow and Ice

In this presentation we will examine some potential applications of low frequency microwave radar and radiometer data to remote sensing of snow and ice conditions over land. We focus on the following low frequency bands; L-band (1.28 GHz), S-band (2.69 GHz), and C-band (5.0 GHz). To predict the effect of snow cover on microwave emission, we need to characterize the dielectric properties of the snow in terms of important physical parameters such as snow density, temperature, and wetness. For the case of dry snow, we use an empirical mixing formula which gives the effective complex permittivity of snow as a function of density, temperature, and frequency. For wet snow, we use another mixing formula which gives the effective complex permittivity as a function of snow wetness. With dry snow, the loss at low microwave frequencies is very small so the corresponding penetration depths are very large (eg., 100 m). Clearly seasonal snow covers are far too thin to have a direct scattering or emission effect on these low frequency bands. There are, however, indirect effects introduced because of altered reflection at the snow/soil boundary, and an extra reflecting interface at the snow/air boundary. For C-band, layers of snow with different densities can have an impact if the number of layers grows sufficiently large. (eg., many meters of snow pack with cm-scale density layering.) Wet snow poses a more difficult problem. Liquid water is much more effective than ice at scattering and absorbing L-band radiation, so even a small amount of wetness will greatly reduce penetration. For example, with a snow wetness of 1 percent (volume fraction), and a density of 300 kg/cu. m, the penetration depths for L-band, S-band, and C-band are about 1.6 m, 0.3 m, and 0.15 m respectively. Very wet snow has more than 10 percent liquid water, and the corresponding L-band penetration is less than 0.2 m. Because the penetration distance is a strong function of frequency, it may be possible to identify a particular class of snow where the wetness is a few percent, and the depth is around one meter by looking at the frequency gradient.

West, Richard D.↗
DOE OSTI2025

Supercritical water desalination and oxidation (SCWDO): Effectiveness on complex solutions, technoeconomic, and CO 2 impact for produced water treatment

The modern energy-economy is increasingly causing the production of highly saline brines, including from produced water. Supercritical water desalination can concentrate and extract minerals from these brines, but the effects of mixed salt interactions, organic degradation with additives, and the technology's economics are not well understood at supercritical condition. The present study evaluated and experimentally studied an integrated supercritical water desalination and oxidation (SCWDO) process for treating real-produced water samples from oil/natural gas field. The complex interactions between the various anions and cations in produced water were extensively evaluated. Most of the divalent and trivalent ions were extracted below 250 °C while the majority of the monovalent salt were removed between 380 to 410 °C. The treated real produced water was of drinking water quality, with <500 mg/l of total dissolved solid (TDS) and with 100% organics removal. Furthermore, the heat liberated during the organic oxidation could be utilized internally and for electricity generation for enhanced the energy efficiency and lower cost of produced water treatment. With system optimization, the proposed SCWDO process can essentially be made a net zero energy process. A novel process flow diagram for the commercial scale self-powered hybrid SCWDO technology was proposed as a cost-effective produced water treatment to mitigate the environmental crises. Techno-economic analysis showed that produced water treatment cost with SCWDO can be reduced to 2–3 $/m 3 and can be up to 60 % cheaper to traditional deep well reinjection. Additionally, the proposed SCWDO process could achieve net negative CO 2 emission.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Metabolic complexity drives divergence in microbial communities

Microbial communities are shaped by environmental metabolites, but the principles that govern whether different communities will converge or diverge in any given condition remain unknown, posing fundamental questions about the feasibility of microbiome engineering. Here, in this work, we studied the longitudinal assembly dynamics of a set of natural microbial communities grown in laboratory conditions of increasing metabolic complexity. We found that different microbial communities tend to become similar to each other when grown in metabolically simple conditions, but they diverge in composition as the metabolic complexity of the environment increases, a phenomenon we refer to as the divergence-complexity effect. A comparative analysis of these communities revealed that this divergence is driven by community diversity and by the assortment of specialist taxa capable of degrading complex metabolites. An ecological model of community dynamics indicates that the hierarchical structure of metabolism itself, where complex molecules are enzymatically degraded into progressively simpler ones that then participate in cross-feeding between community members, is necessary and sufficient to recapitulate our experimental observations. In addition to helping understand the role of the environment in community assembly, the divergence-complexity effect can provide insight into which environments support multiple community states, enabling the search for desired ecosystem functions towards microbiome engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Systemic effects of rising atmospheric vapor pressure deficit on plant physiology and productivity

Abstract Earth is currently undergoing a global increase in atmospheric vapor pressure deficit (VPD), a trend which is expected to continue as climate warms. This phenomenon has been associated with productivity decreases in ecosystems and yield penalties in crops, with these losses attributed to photosynthetic limitations arising from decreased stomatal conductance. Such VPD increases, however, have occurred over decades, which raises the possibility that stomatal acclimation to VPD plays an important role in determining plant productivity under high VPD. Furthermore, evidence points to more far‐ranging and complex effects of elevated VPD on plant physiology, extending to the anatomical, biochemical, and developmental levels, which could vary substantially across species. Because these complex effects are typically not considered in modeling frameworks, we conducted a quantitative literature review documenting temperature‐independent VPD effects on 112 species and 59 traits and physiological variables, in order to develop an integrated and mechanistic physiological framework. We found that VPD increase reduced yield and primary productivity, an effect that was partially mediated by stomatal acclimation, and also linked with changes in leaf anatomy, nutrient, and hormonal status. The productivity decrease was also associated with negative effects on reproductive development, and changes in architecture and growth rates that could decrease the evaporative surface or minimize embolism risk. Cross‐species quantitative relationships were found between levels of VPD increase and trait responses, and we found differences across plant groups, indicating that future VPD impacts will depend on community assembly and crop functional diversity. Our analysis confirms predictions arising from the hydraulic corollary to Darcy's law, outlines a systemic physiological framework of plant responses to rising VPD, and provides recommendations for future research to better understand and mitigate VPD‐mediated climate change effects on ecosystems and agro‐systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using machine-learning to understand complex microstructural effects on the mechanical behavior of Ti-6Al-4V alloys

Structural materials properties are highly dependent on their microstructure. Their microstructure is in turn affected by multiple fabrication and thermo-mechanical treatment parameters, all of which conform a highly-dimensional parametric space with often hidden correlations that are difficult to extract by experimentation alone. This is particularly true for alloys of the dual-phase Ti-6Al-4V family, with their greatly complex and rich microstructures, which combine several intrinsic length scales associated with multiple grain and subgrain structures, grains with different crystal lattices (α and β phases), and complex chemistry. In this paper we use a comprehensive set of machine learning techniques to develop predictive tools relating the yield strength and hardening rate of these alloys to a set of input parameters covering extensive ranges. The data generator is a finite-element crystal plasticity model for polycrystal deformation that takes into account slip anisotropy and employs standard dislocation evolution models for the α and β phases of Ti-based alloys. Our dataset includes over two thousand independent simulations and is used to train the machine learning models, which are then used to establish correlations between microstructural parameters and the alloys’ mechanical response. Our results point to the most influential parameters affecting yield strength and hardening rate, information that can then be used to guide experimental synthesis and characterization efforts to save time and resources.

36 MATERIALS SCIENCE↗
NASA NTRS1996

The effects of complex chemistry on triple flames

The structure, ignition, and stabilization mechanisms for a methanol (CH3OH)-air triple flame are studied using Direct Numerical Simulations (DNS). The methanol (CH3OH)-air triple flame is found to burn with an asymmetric shape due to the different chemical and transport processes characterizing the mixture. The excess fuel, methanol (CH3OH), on the rich premixed flame branch is replaced by more stable fuels CO and H2, which burn at the diffusion flame. On the lean premixed flame side, a higher concentration of O2 leaks through to the diffusion flame. The general structure of the triple point features the contribution of both differential diffusion of radicals and heat. A mixture fraction-temperature phase plane description of the triple flame structure is proposed to highlight some interesting features in partially premixed combustion. The effects of differential diffusion at the triple point add to the contribution of hydrodynamic effects in the stabilization of the triple flame. Differential diffusion effects are measured using two methods: a direct computation using diffusion velocities and an indirect computation based on the difference between the normalized mixture fractions of C and H. The mixture fraction approach does not clearly identify the effects of differential diffusion, in particular at the curved triple point, because of ambiguities in the contribution of carbon and hydrogen atoms' carrying species.

Echekki, T.↗
DOE OSTI2021

Optimal renormalization of multiscale systems

While model order reduction is a promising approach in dealing with multi-scale time-dependent systems that are too large or too expensive to simulate for long times, the resulting reduced order models can suffer from instabilities. We have recently developed a time-dependent renormalization approach to stabilize such reduced models. In the current work, we extend this framework by introducing a parameter that controls the time-decay of the memory of such models and optimally selecting this parameter based on limited fully resolved simulations. First, we demonstrate our framework on the inviscid Burgers equation whose solution develops a finite-time singularity. Our renormalized reduced order models are stable and accurate for long times while using for their calibration only data from a full order simulation before the occurrence of the singularity. Furthermore, we apply this framework to the 3D Euler equations of incompressible fluid flow, where the problem of finite-time singularity formation is still open and where brute force simulation is only feasible for short times. Our approach allows us to obtain for the first time a perturbatively renormalizable model which is stable for long times and includes all the complex effects present in the 3D Euler dynamics. We find that, in each application, the renormalization coefficients display algebraic decay with increasing resolution, and that the parameter which controls the time-decay of the memory is problem-dependent.

Price, Jacob↗
DOE OSTI2021

Ab initio metadynamics calculations reveal complex interfacial effects in acetic acid deprotonation dynamics

Acid-base reactions play a central role in solution chemistry, with carboxylic acids being particularly important in atmospheric chemical processes. In this work, we harness metadynamics calculations with Born-Oppenheimer molecular dynamics (BOMD) simulations to understand deprotonation dynamics of acetic acid (CH 3 COOH) in both bulk and air-water interfacial environments. Collective variables are carefully chosen in our well-tempered metadynamics simulations to capture the deprotonation process in various aqueous configurations. Herein, our findings show that the free energy barrier for deprotonation of acetic acid at the air-water interface is lower than in the bulk, in accordance with the available experimental data. Furthermore, our well-tempered metadynamics calculations suggest that the variations in free energy are primarily due to intricate solvation shell effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Informed total-error-minimizing priors: Interpretable cosmological parameter constraints despite complex nuisance effects

While Bayesian inference techniques are standard in cosmological analyses, it is common to interpret resulting parameter constraints with a frequentist intuition. This intuition can fail, for example, when marginalizing high-dimensional parameter spaces onto subsets of parameters, because of what has come to be known as projection effects or prior volume effects. We present the method of informed total-error-minimizing (ITEM) priors to address this problem. An ITEM prior is a prior distribution on a set of nuisance parameters, such as those describing astrophysical or calibration systematics, intended to enforce the validity of a frequentist interpretation of the posterior constraints derived for a set of target parameters (e.g., cosmological parameters). Our method works as follows. For a set of plausible nuisance realizations, we generate target parameter posteriors using several different candidate priors for the nuisance parameters. We reject candidate priors that do not accomplish the minimum requirements of bias (of point estimates) and coverage (of confidence regions among a set of noisy realizations of the data) for the target parameters on one or more of the plausible nuisance realizations. Of the priors that survive this cut, we select the ITEM prior as the one that minimizes the total error of the marginalized posteriors of the target parameters. As a proof of concept, we applied our method to the density split statistics measured in Dark Energy Survey Year 1 data. We demonstrate that the ITEM priors substantially reduce prior volume effects that otherwise arise and that they allow for sharpened yet robust constraints on the parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Biological insights from multi-omics analysis strategies: Complex pleotropic effects associated with autophagy

Research strategies that combine molecular data from multiple levels of genome expression (i.e., multi-omics data), often referred to as a systems biology strategy, has been advocated as a route to discovering gene functions. In this study we conducted an evaluation of this strategy by combining lipidomics, metabolite mass-spectral imaging and transcriptomics data from leaves and roots in response to mutations in two AuTophaGy-related ( ATG ) genes of Arabidopsis . Autophagy is an essential cellular process that degrades and recycles macromolecules and organelles, and this process is blocked in the atg7 and atg9 mutants that were the focus of this study. Specifically, we quantified abundances of ~100 lipids and imaged the cellular locations of ~15 lipid molecular species and the relative abundance of ~26,000 transcripts from leaf and root tissues of WT, atg7 and atg9 mutant plants, grown either in normal (nitrogen-replete) and autophagy-inducing conditions (nitrogen-deficient). The multi-omics data enabled detailed molecular depiction of the effect of each mutation, and a comprehensive physiological model to explain the consequence of these genetic and environmental changes in autophagy is greatly facilitated by the a priori knowledge of the exact biochemical function of the ATG7 and ATG9 proteins.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1995

Modeling complex chemical effects in turbulent nonpremixed combustion

Virtually all of the energy derived from the consumption of combustibles occurs in systems which utilize turbulent fluid motion. Since combustion is largely related to the mixing of fluids and mixing processes are orders of magnitude more rapid when enhanced by turbulent motion, efficiency criteria dictate that chemically powered devices necessarily involve fluid turbulence. Where combustion occurs concurrently with mixing at an interface between two reactive fluid bodies, this mode of combustion is called nonpremixed combustion. This is distinct from premixed combustion where flame-fronts propagate into a homogeneous mixture of reactants. These two modes are limiting cases in the range of temporal lag between mixing of reactants and the onset of reaction. Nonpremixed combustion occurs where this lag tends to zero, while premixed combustion occurs where this lag tends to infinity. Many combustion processes are hybrids of these two extremes with finite non-zero lag times. Turbulent nonpremixed combustion is important from a practical standpoint because it occurs in gas fired boilers, furnaces, waste incinerators, diesel engines, gas turbine combustors, and afterburners etc. To a large extent, past development of these practical systems involved an empirical methodology. Presently, efficiency standards and emission regulations are being further tightened (Correa 1993), and empiricism has had to give way to more fundamental research in order to understand and effectively model practical combustion processes (Pope 1991). A key element in effective modeling of turbulent combustion is making use of a sufficiently detailed chemical kinetic mechanism. The prediction of pollutant emission such as oxides of nitrogen (NO(x)) and sulphur (SO(x)) unburned hydrocarbons, and particulates demands the use of detailed chemical mechanisms. It is essential that practical models for turbulent nonpremixed combustion are capable of handling large numbers of 'stiff' chemical species equations.

Smith, Nigel S. A.↗
NASA NTRS1986

Computation of turbulent rotating channel flow with an algebraic Reynolds stress model

An Algebraic Reynolds Stress Model has been implemented to modify the Kolmogorov-Prandtl eddy viscosity relation to produce an anisotropic turbulence model. The eddy viscosity relation becomes a function of the local turbulent production to dissipation ratio and local turbulence/rotation parameters. The model is used to predict fully-developed rotating channel flow over a diverse range of rotation numbers. In addition, predictions are obtained for a developing channel flow with high rotation. The predictions are compared with the experimental data available. Good predictions are achieved for mean velocity and wall shear stress over most of the rotation speeds tested. There is some prediction breakdown at high rotation (rotation number greater than .10) where the effects of the rotation on turbulence become quite complex. At high rotation and low Reynolds number, the laminarization on the trailing side represents a complex effect of rotation which is difficult to predict with the described models.

Warfield, M. J.↗