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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Emergence of Lanes and Turbulent-like Motion in Active Spinner Fluid

Assemblies of self-rotating particles are gaining interest as a novel realization of active matter with unique collective behaviors such as edge currents and non-trivial dynamic states. Here, we develop a continuum model for a system of fluid-embedded spinners by coarse-graining the equations of motion of the discrete particles. We apply the model to explore mixtures of clockwise and counterclockwise rotating spinners. We find that the dynamics is sensitive to fluid inertia: in the inertialess system, after transient turbulent-like motion the spinners segregate and form steady traffic lanes. At small but finite Reynolds number instead, the turbulent-like motion persists and the system exhibits a chirality breaking transition leading to a single rotation sense state. Our results shed light on the dynamic behavior of non-equilibrium materials exemplified by active spinners.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Compression behavior of dense H 2 -He mixtures up to 160 GPa

We have studied the compression behavior of H 2 -He mixtures in comparison with pure H 2 and He using powder synchrotron x-ray diffraction and present the pressure-volume (PV) compression data of H 2 -He mixtures to 160 GPa. The results indicate that both H 2 and He in H 2 -He mixtures remain in hcp to the maximum pressure studied, yet develop a substantial level of lattice distortion in the (100) plane, most profound in He-rich solids and below 66 GPa. The measured PV data also indicate softening of He (or H 2 )-rich lattice upon increasing the level of the guest H 2 (or He) concentration. We suggest that the observed softening and lattice distortion are due to a substitutional incorporation of H2 (guest) molecules into the basal plane of hcp-He (host) lattice and, thereby, reflect the miscibility between H 2 and He in H 2 -He mixtures. Interestingly, solid He exhibits a lesser degree of preferred orientation in H2-He mixtures than in pure He, likely due to the presence of solid H 2 disturbing the crystalline ordering of He-rich solids. Finally, the present PV compression data of H 2 -rich and He-rich solids to 160 GPa deviate from those of pure H 2 and pure He above ~70 and 45 GPa respectively, providing new constraints for development of the EOS for H 2 -He mixtures for planetary models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Generalized master equation for particle transport in binary random media with renewal statistics

Particle transport in binary stochastic mixtures is classically modeled assuming Markovian or exponential mixing statistics but in many applications material memory invalidates the Markov assumption. For non-Markovian mixing characterized by alternating renewal processes, a transport-theoretic framework is presented that provides an exact description of transport in nonscattering random binary media with general non-exponential statistics. Our approach is to Markovianize the problem by augmenting the {material type, particle flux} state space with the age or distance from the last interface. A Chapman-Kolmogorov equation is formulated for the joint probability density of the material type, particle flux, and age, and subsequently reduced to a generalized Master equation (GME) in differential form. This constitutes the primary result of this work. A state-updating Monte Carlo algorithm consistent with the GME is developed and benchmarked against analytical solutions for multiple chord-length laws. For purely absorbing renewal statistical media, the GME reproduces analytical benchmarks for the equilibrium age distribution, interior mean/variance of material-conditioned fluxes, and boundary transmittance. Simulations further demonstrate that a Markov (exponential) approximation of non-exponential statistics can introduce large errors in transmittance and interior flux profiles. Lastly, the reintroduction of memory due to scattering is briefly addressed through heuristic considerations.

Fluctuations & noise↗
DOE OSTI2024

PhILMs: Collaboratory on Mathematics and Physics-Informed Learning Machines for Multiscale and Multiphysics Problems

The landscape of computational science and engineering is continually evolving, with the challenge of high-dimensional regression problems standing as a significant hurdle in numerous scientific endeavors. Addressing this challenge, our research, funded by this award, has led to the development of an innovative computational framework known as Probabilistic Partition of Unity Networks (PPOU-Nets). This initiative represents a collaborative effort to harness the potential of mathematics and physics-informed machine learning in tackling multiscale and multiphysics problems prevalent in high-dimensional spaces. Through this work, we have proposed a novel methodology that seamlessly integrates adaptive dimensionality reduction and a mixture of experts model, thereby facilitating a more efficient and accurate approximation of complex functions. This research effort has not only advanced the state of computational science but also opened new avenues for exploration in quantum computing and beyond. This report outlines the motivation, methodology, key findings, and implications of our work, underscoring our contributions to the broader scientific community and the potential pathways for future research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantification of gas concentrations in NO/NO 2 /C 3 H 8 /NH 3 mixtures using machine learning

We employ machine learning to decode the composition of unknown gas mixtures from the output of an array of four electrochemical sensors. The sensors use metal oxide electrodes paired with a ceramic electrolyte, yttria-stabilized zirconia (YSZ), to produce voltage responses to the presence of gases in complex mixtures. The voltages from the sensor array serve as inputs to a machine learning pipeline which first carries out multi-class classification of mixtures into types based on which gases are present at non-zero concentrations, and subsequently predicts gas concentrations given the mixture type. Thus, our model is able to take a single reading from the sensor array in response to gas mixtures involving NO, NO 2 , C 3 H 8 , and NH 3 , and output a highly accurate prediction of which gases are present in the mixture, along with the concentrations of each constituent gas. Of note, our computational framework can be easily expanded to include additional gases and additional mixture types, allowing it to be used in numerous automotive, industrial and environmental monitoring settings.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

An experimental and modeling study on auto-ignition kinetics of ammonia/methanol mixtures at intermediate temperature and high pressure

A rapid compression machine (RCM) has been applied to measure the ignition delay times of NH 3 /CH 3 OH mixtures covering pressures of 20 and 40 bar, equivalence ratios of 0.5, 1.0 and 2.0, and temperatures between 845 and 1100 K. Here the measurements show that the NH 3 /CH 3 OH mixtures become more reactive with increasing methanol addition. Addition of merely 1% (molar basis) of CH 3 OH to NH 3 lowers the ignition temperature around 100 K at 40 bar in comparison to pure NH 3 . The ignition delay is a complex function of fuel mixture and stoichiometry. For the 1% CH 3 OH mixture, the leaner mixtures are more reactive, while the reverse trend is found for mixtures with 5%, 20% and pure CH 3 OH. Analysis of the pressure profiles shows three distinct ignition modes for NH 3/ CH 3 OH mixtures, facilitated by the pre-ignition heat release from NH 3 consumption. A detailed mechanism for ignition of NH 3 /CH 3 OH fuel blends has been developed, capable of reproducing the ignition behavior of mixtures with reasonable accuracy. A subset for amine / methanol interactions was established, with rate constants for the key reaction between NH 2 and CH 3 OH calculated from ab initio theory. A sensitivity analysis indicates that the critical reactions during the auto-ignition process vary with the CH 3 OH mole fraction in the fuel. The ammonia chemistry, namely NH 2 + NO, NH2 + NO 2 and NH 2 + HO 2 , is dominant for the mixture with 1% CH 3 OH, while the reactions related to CH 3 OH and H 2 O 2 are more important for the 20% CH 3 OH mixture. The interaction between ammonia and methanol shows a more prominent effect on auto-ignition for mixtures with 5% CH 3 OH in fuel as compared to those with 1% and 20% CH 3 OH. According to the modeling results, methanol addition is found to enrich the O/H radical pool, consuming ammonia and promoting auto-ignition through different reaction pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unsupervised physics-informed disentanglement of multimodal data

Here, we introduce physics-informed multimodal autoencoders (PIMA) - a variational inference framework for discovering shared information in multimodal datasets. Individual modalities are embedded into a shared latent space and fused through a product-of-experts formulation, enabling a Gaussian mixture prior to identify shared features. Sampling from clusters allows cross-modal generative modeling, with a mixture-of-experts decoder that imposes inductive biases from prior scientific knowledge and thereby imparts structured disentanglement of the latent space. This approach enables cross-modal inference and the discovery of features in high-dimensional heterogeneous datasets. Consequently, this approach provides a means to discover fingerprints in multimodal scientific datasets and to avoid traditional bottlenecks related to high-fidelity measurement and characterization of scientific datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Potential Benefits of Handling Mixture Statistics via a Bi-Gaussian EnKF: Tests With All-Sky Satellite Infrared Radiances

The meteorological characteristics of cloudy atmospheric columns can be very different from their clear counterparts. Thus, when a forecast ensemble is uncertain about the presence/absence of clouds at a specific atmospheric column (i.e., some members are clear while others are cloudy), that column's ensemble statistics will contain a mixture of clear and cloudy statistics. Such mixtures are inconsistent with the ensemble data assimilation algorithms currently used in numerical weather prediction. Hence, ensemble data assimilation algorithms that can handle such mixtures can potentially outperform currently used algorithms. In this study, we demonstrate the potential benefits of addressing such mixtures through a bi-Gaussian extension of the ensemble Kalman filter (BGEnKF). The BGEnKF is compared against the commonly used ensemble Kalman filter (EnKF) using perfect model observing system simulated experiments (OSSEs) with a realistic weather model (the Weather Research and Forecast model). Synthetic all-sky infrared radiance observations are assimilated in this study. In these OSSEs, the BGEnKF outperforms the EnKF in terms of the horizontal wind components, temperature, specific humidity, and simulated upper tropospheric water vapor channel infrared brightness temperatures. This study is one of the first to demonstrate the potential of a Gaussian mixture model EnKF with a realistic weather model. Our results thus motivate future research toward improving numerical Earth system predictions though explicitly handling mixture statistics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Insight into premixed diethoxymethane flames: Laminar burning velocities, temperatures, and emissions behaviour

Diethoxymethane ((CH 3 CH 2 O) 2 CH 2 , DEM) is a promising carbon-neutral fuel. DEM is a diether or acetal with a molecular structure similar to oxymethylene ethers (CH 3 O–(CH 2 O)n–CH 3 , OME n ). Thus, DEM can be expected to have a similar combustion behavior to OMEs, reducing harmful emissions such as NO x and particulate matter (PM) in internal combustion engines. From both experimental and kinetic modeling, fundamental studies on DEM are scarce in the literature. More studies are required to gain a detailed insight into the oxidation kinetics of DEM. Laminar burning velocity (LBV) is a critical property that allows a detailed assessment of the potential application of DEM in combustion devices. Unfortunately, the literature on the LBV of DEM is limited. Therefore, in this study we have investigated the LBV of DEM using two reactors for the first time, namely a heat flux burner and a combustion chamber. The experimental data is reported for equivalence ratio between 0.7 and 1.7, initial temperatures of 368–423 K, and initial pressure of 1–5 bar. In addition, we developed a detailed kinetic model extending our recent work of Shrestha et al. (Combust. Flame. 246 (2022) 112,426) to characterize the combustion behavior of DEM utilizing the new experimental data from this work and the literature data. Our model performs remarkably well in capturing the newly measured LBV experimental data over various experimental conditions. We found that DEM and dimethoxy methane (DMM) have similar values of LBVs (within ±1.5 cm/s) for a given condition, which indicates that intermediate chemistry governs the flame chemistry. Despite DEM being a larger molecule that is expected to have slightly lower LBVs than DMM, its effect on the measured values of LBVs is negligible. Finally, we experimentally measured NO x formation in DEM flame for the first time. The stochiometric flame has the highest NO x formation. The proposed model predicted the equivalence ratio dependence of NO x nicely. However, it overestimates the NO x formation for stoichiometric DEM/air mixtures by ~30 %. The model suggests that the thermal NO formation route is favored at lean and stochiometric conditions. In contrast, the prompt NO formation route is enhanced for rich mixtures.

10 SYNTHETIC FUELS↗
DOE OSTI2024

Modeling Europium (II/III) ion solvation in the LiCl-KCl eutectic mixture with polarizable force fields

Here, the solvation processes of Europium (II/III) ions within the molten salt eutectic mixture, 3LiCl-2KCl, are investigated over temperatures ranging from 673 K to 1173 K. New polarizable ion force fields are proposed to model Europium ions in a molten salt eutectic mixture with a goal of accurately capturing the underlying physics in the solutions. In contrast to rigid-ion models, the polarizable Drude model with an adjusted WBK (Wang-Buckingham) force field significantly improves predictions for diffusion coefficients, the average diffusion activation energy, and changes in excess ion chemical potential and partial molar entropy, producing good agreement with experimental measurements.

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

The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior

Lipid membranes are central to cellular life. Complementing experiments, computational modeling has been essential in unraveling complex lipid-biomolecule interactions, crucial in both academia and industry. The Martini model, a coarse-grained force field for efficient molecular dynamics simulations, is widely used to study membrane phenomena but has faced limitations, particularly in capturing realistic lipid phase behavior. Here, we present refined Martini 3 lipid models with a mapping scheme that distinguishes lipid tails that differ by just two carbon atoms, enhancing the structural resolution and thermodynamic accuracy of model membrane systems including ternary mixtures. The expanded Martini lipid library includes thousands of models, enabling simulations of complex and biologically relevant systems. These advancements establish Martini as a robust platform for lipid-based simulations across diverse fields.

Lipids↗
DOE OSTI2022

Load‐Balancing Intense Physics Calculations to Embed Regionalized High‐Resolution Cloud Resolving Models in the E3SM and CESM Climate Models

Abstract We design a new strategy to load‐balance high‐intensity sub‐grid atmospheric physics calculations restricted to a small fraction of a global climate simulation's domain. We show why the current parallel load balancing infrastructure of Community Earth System Model (CESM) and Energy Exascale Earth Model (E3SM) cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud‐resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high‐resolution (MMF‐HR; sub‐km horizontal grid spacing) relative to standard low‐resolution (MMF‐LR) cloud superparameterization elsewhere. To enable MMF runs with Multi‐Domain cloud resolving models (CRMs), our load balancing theory predicts the most efficient computational scale as a function of the high‐intensity work's relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high‐intensity (and rate‐limiting) high‐resolution (HR) grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/low‐resolution CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real‐geography settings. As intended, within the high (low) resolution area, our Multi‐Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF‐LR and MMF‐HR. We suggest this approach can open up a range of creative multi‐resolution climate experiments without requiring unduly large allocations of computational resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of Variable Gas Mixtures on Bubble Size Distribution and Mass Transfer in Gas Fermentation Reactors

Gas fermentation has emerged as a promising new technology for the generation of fuels and chemicals from mixtures of greenhouse and energy rich gas streams (CO2/CH4/H2/CO) via microbial bioreaction. Example pathways include biomethanation (CO2/H2 to CH4), biogas upgrading, CO fermentation and wet-waste conversion. Effective Gas-liquid mass-transfer is an important physical phenomenon that determines the design and scale-up of these systems. There is currently a knowledge-gap regarding bubble-size distributions when using a mixture of gases with vastly different properties, which can have a significant impact on overall mass-transfer. For example, hydrogen bubbles are more buoyant compared to other relatively heavier gases (CO2/CH4/CO), resulting in a large distribution of residence times and bubble sizes. This work therefore develops a deeper understanding of bubble dynamics and interphase mass transfer in such heterogenous gas mixtures through well-resolved computational models. We use a detailed multiphase computational-fluid-dynamics (CFD) model to study the impact of gas-mixtures on overall mass-transfer in bubble column and air-lift reactors. The CFD tool previously developed by the authors (1) for simulating aerobic fermentation reactors at scale is used in this study. The Reynolds-averaged mass, momentum, energy, and species transport equations are solved for interpenetrating gas and liquid phase in this model. We use a population balance-based bubble-size-distribution model that is validated against small-scale experiments in our solver. Results pertaining to multiple simulations of gas-fermentation reactors are presented where gas mixtures with varying compositions of CO2/CH4/CO/H2 are imposed at the sparger boundaries. The spatio-temporal variations in bubble-size distribution and mass transfer coefficient is analyzed for varying superficial velocities and gas-compositions for varying sizes of bubble-column and airlift reactors.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Model development for flash boiling spray and validations with isooctane, hexane, ethanol and their binary mixtures

The objective of this study is to develop a comprehensive model for spray atomization under the consideration of flash boiling, which includes nucleation, bubble growth, and droplet breakup. Although flash boiling has been previously studied, there is still no well-established analytical and numerical model of their mechanisms, or general guidelines on the implementation of this atomization strategy. In this study, detailed formulations are elaborated for the unified spray atomization model under both non-flash and flash boiling conditions. Next, the model was implemented into CFD software and 3-D simulations were performed for model validations. Two fuel blends are tested: ethanol-isooctane blends and hexane-isooctane blends. Simulation results were compared with the experimental measurements conducted using two methodologies, DBI (Diffuse Backlight Imaging) system for spray images captured by a high-speed camera, and a PDA (Phase Doppler Anemometry) system for droplet size measurement during the spray injection process. It was found that the current flash boiling model can accurately capture the spray characteristics under different environment conditions, such as the spray plume interactions and liquid penetration. The averaged Sauter mean diameter (SMD) calculations match the measurement sufficiently well. The spray structures for both single- and multi-component fuels during the injection process are well represented by current model.

42 ENGINEERING↗
DOE OSTI2025

Development of a two-zone zero-dimensional mixing model for actively fueled prechamber engines

In this numerical work, a zero-dimensional, two-zone mixing model was developed and validated to capture the mixture preparation process of an actively fueled prechamber engine. The model was developed for ethanol-gasoline fuel blends but is applicable to various fuels of interest relevant to prechamber applications. The model was exercised to demonstrate the effects of boundary conditions, fuel composition, and residual content on the mixture stoichiometry predictions. The 0D model showed reasonable agreement in prechamber equivalence ratio predictions with higher fidelity computational fluid dynamics modeling, but the accuracy of model was constrained to the governing assumptions of the injection process. The modeling assumptions surrounding the non-dimensional injection of mass into the prechamber were scrutinized to identify key areas of model improvement. The results indicate heat transfer effects play a crucial role in the evaporation of the fuel within the confined auxiliary chamber, especially when considering fuels with high latent heat of vaporization. Additionally, the presence of fuel films that collect on the prechamber surfaces complicated the modeled evaporative cooling loses as the modeling suggests the films evaporate primarily by means of conduction from the boundary. Furthermore, the developed model serves as a simplified framework to generate calibration maps of prechamber fueling or run real time as an open loop control strategy such that desired prechamber mixture proportions are effectively targeted.

Zero-dimensional↗
DOE OSTI2021

Standoff Detection of Oil and Powder Mixtures at 12 Meters Using a Tunable Quantum Cascade Laser-Based System with a Close Focus Telescope and Uncooled Infrared Detector

We have designed and demonstrated a quantum cascade laser (QCL) based standoff system that utilizes an uncooled mercury cadmium telluride (MCT) detector with lock-in signal processing for chemical identification at a distance of 12.5 meters in indoor ambient light conditions. In the system, a tunable quad-QCL operating (1 MHz) in quasi-continuous wave mode between 8.45 and 10.03 μm (~1182 to 1000 cm –1 ) serves as the active mid-infrared source for remotely interrogating mineral, powder, and thin film oil samples including powder mixtures (6, 12.5, 25, and 50%) of crystalline quartz (SiO 2 ) in KBr. Light as reflected from a given sample is collected using a 10-inch (25.4 cm) Dall Kirkham telescope and coupled with ZnSe optics to an uncooled MCT detector. Furthermore, the mixture dependence of the highly transparent KBr and strongly absorbing quartz was found to fit a modified version of the Schatz reflectance model for compacted powder mixtures. All reflectance spectra reported are relative to an Au-coated diffuse reflector. A NIST traceable polystyrene standard reflector was also used to determine the QCL wavelength tuning range and calibration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗