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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 613 records · Page 34

Results of tests using a 0.0125-scale model (70-QT) of the space shuttle vehicle orbiter in the AEDC VKF tunnel B (IA22), volume 2

Tabulated data of an experimental investigation are presented which was conducted in the AEDC/VKF Tunnel B to obtain interaction effects of RCS thruster jet plumes on SSV aerodynamics during staging to simulate RTLS abort. Interaction effects of the orbiter RCS thruster jet plumes on the orbiter and ET aerodynamics were investigated. RCS thruster jet plumes were simulated using both air and a 15 percent argon 85 percent helium gas mixture. The ET angle of attack range was -40 to +25 deg at sideslip angles of 0, 3, and 6 degrees. Orbiter angle of attack was varied from -15 to +10 degrees at sideslip angles of 0 and 3 deg. External tank full scale separation distances simulated were 0 to 1400 in. axially; 0 to 54 in. laterally; and a range of -100 to 1000 in. vertically. Data were also obtained on the ET in the interference-free flow field. Quiescent (no tunnel flow) thruster plume interaction data were obtained on the orbiter and orbiter-ET combination. Tests were conducted at Mach number 6 and a Reynolds number of 0.86 million per foot.

Daileda, J. J.↗

Static jet noise test results of four 0.35 scale-model QCGAT mixer nozzles

As part of the NASA Quiet Clean General Aviation Turbofan (QCGAT) engine mixer-nozzle exhaust system program, static jet exhaust noise was recorded at microphone angles of 45 to 155 deg relative to the nozzle inlet for a conventional profile coaxial nozzle and three 12-lobed coaxial mixer nozzles. Both flows in all four nozzles are internally mixed before being discharged from a single exhaust nozzle. The conventional profile coaxial nozzle jet noise is compared to the current NASA Lewis coaxial jet noise prediction and after applying an adjustment to the predicted levels based on the ratio of the kinetic energy of the primary and secondary flows, the prediction is within a standard deviation of 0.9 dB of the measured data. The mass average (mixed flow) prediction is also compared to the noise data for the three mixer nozzles with a reasonably good fit after applying another kinetic energy ratio adjustment (standard deviation of 0.7 to 1.5 dB with the measured data). The tests included conditions for the full-scale engine at takeoff (T.O.), cutback (86% T.O.) and approach (67% T.O.).

Groesbeck, D. E.↗

Measured Boundary Layer Transition and Rotor Hover Performance at Model Scale

An experiment involving a Mach-scaled, 11:08 f t: diameter rotor was performed in hover during the summer of 2016 at NASA Langley Research Center. The experiment investigated the hover performance as a function of the laminar to turbulent transition state of the boundary layer, including both natural and fixed transition cases. The boundary layer transition locations were measured on both the upper and lower aerodynamic surfaces simultaneously. The measurements were enabled by recent advances in infrared sensor sensitivity and stability. The infrared thermography measurement technique was enhanced by a paintable blade surface heater, as well as a new high-sensitivity long wave infrared camera. The measured transition locations showed extensive amounts, x=c>0:90, of laminar flow on the lower surface at moderate to high thrust (CT=s > 0:068) for the full blade radius. The upper surface showed large amounts, x=c > 0:50, of laminar flow at the blade tip for low thrust (CT=s < 0:045). The objective of this paper is to provide an experimental data set for comparisons to newly developed and implemented rotor boundary layer transition models in CFD and rotor design tools. The data is expected to be used as part of the AIAA Rotorcraft SimulationWorking Group

Overmeyer, Austin D.↗

Computational Approach for Rapidly Predicting Temperature–Dependent Polymer Solubilities Using Molecular–Scale Models

One promising approach to recycle multicomponent plastic waste (e. g., multilayer plastic films) is selective dissolution. Selective dissolution is a solvent-mediated process in which differences in polymer solubility in a carefully chosen solvent system are exploited to recover a target polymer. Here, a computational approach was developed that rapidly predicts temperature-dependent polymer solubilities to guide the design of solvent systems for solvent-mediated polymer recycling. Polymer conformations were obtained from molecular dynamics simulations by modeling the polymer as a short oligomer and then used as input to the conductor-like screening model for real solvents (COSMO-RS) for solubility predictions. Using polyethylene (PE) and ethylene vinyl alcohol (EVOH) as representative polymers, the effect of simulation parameters was systematically studied, and predicted solubilities were found to be in good agreement with experimental measurements. Furthermore, the applicability of the approach was demonstrated by identifying selective solvents for PE and EVOH dissolution from a library of 524 solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic-scale modeling of C/N kinetic stability descriptors for PGM-free electrocatalysts at finite temperatures

The durability of platinum group metal-free (PGM-free) electrocatalysts is a major barrier to their usage in polymer electrolyte fuel cell cathodes. C and N removal from active sites may play an important role in the catalyst’s ability to maintain high activity. While C degradation mechanisms are kinetically controlled, previous studies have focused on thermodynamic descriptors. In this work, we develop a temperature-dependent kinetic descriptor of C and N stability using an electron beam-damage model. Our approach considers the electron beam energy threshold (EBET) describing the knock-on displacement of C and N atoms as a stability descriptor for atomic structures. The stability of different sites is calculated to be different showing this approach can discriminate between similar sites with varied configurations. Additionally, we provide important insight regarding TEM beam damage of proposed active sites. We calculate 60 keV electrons can damage some proposed active site structures even at room temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Local Electronic Structure of Supercritical CO 2 from X-ray Raman Spectroscopy and Atomistic-Scale Modeling

Supercritical CO 2 is encountered in several technical and natural systems related to biology, geophysics, and engineering. While the structure of gaseous CO 2 has been studied extensively, the properties of supercritical CO 2 , particularly close to the critical point, are not well-known. Here, in this work, we combine X-ray Raman spectroscopy, molecular dynamics simulations, and first-principles density functional theory (DFT) calculations to characterize the local electronic structure of supercritical CO 2 at conditions around the critical point. The X-ray Raman oxygen K-edge spectra manifest systematic trends associated with the phase change of CO 2 and the intermolecular distance. Extensive first-principles DFT calculations rationalize these observations on the basis of the 4sσ Rydberg state hybridization. X-ray Raman spectroscopy is found to be a sensitive tool for characterizing electronic properties of CO 2 under challenging experimental conditions and is demonstrated to be a unique probe for studying the electronic structure of supercritical fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-Scale Modeling for Plasma-Enhanced Ammonia Decomposition over Carbides and Nitrides

Ammonia is a carbon-free hydrogen carrier, but its decomposition typically requires high temperatures over costly Ru-based catalysts due to the large barrier for N≡N bond formation. We develop a multiscale framework combining density functional theory, zero-dimensional plasma kinetics, and microkinetic modeling to elucidate how non-thermal plasma (NTP) enables low-temperature NH 3 decomposition over Co-based carbides and nitrides, benchmarked against Ru and Co. Under thermal conditions, all catalysts are limited by N≡N bond formation, with Co 3 C(001) most active owing to its negatively charged surface, strong N* binding, and low activation barriers of N≡N bond formation. Plasma-induced vibrational excitation of NH 3 and its reactive radicals promotes a radical-driven •NH 2 –N* coupling pathway that dominates on Co 3 C(001) and Co 3 N(001), shifting the rate-limiting step to NH 3 (v1) dissociation, increasing turnover frequencies by up to 6 orders of magnitude, and reducing the temperature needed to reach a turnover frequency of 5 s –1 from >680 °C (Ru and Co under thermal condition) to 267 °C (Co 3 C) and 415 °C (Co 3 N). These results identify Co-based carbides and nitrides as promising plasma-active catalysts for energy-efficient hydrogen production from ammonia.

ammonia decomposition↗

Atomic-scale modeling of the dissolution of oxidized platinum nanoparticles in an explicit water environment

Pt nanoparticles (NPs) are currently being investigated for use in fuel cells; however, Pt NP oxidation as a function of size, morphology, and temperature is not well understood or currently quantified. In this study, the stability and dissolution of oxidized platinum NPs is examined via classical molecular dynamics in an explicit water environment. The NPs considered range in size from 1.35 to 2.92 nm in diameter and included five different monolayer (ML) coverages of O*. The simulations were performed at 300, 450, and 600 K with the many-body, reactive third-generation charge-optimized many-body or COMB3 potentials and examine the kinetics of NP dissolution in water. The Pt–O layer, which reduces the kinetic activity for Pt atom dissolution, is projected to make dissolution more favorable for O* MLs smaller than 0.5. The simulations further indicate that the Pt NPs' kinetic rates of dissolution are slowed by an increase in the number of adsorbed species caused by the dissociation of water molecules at the reconstructed facets of the Pt NPs. Furthermore, these findings quantify the effect of oxygen and temperature on the stability and dissolution of oxidized platinum NP in an explicit water environment similar to the conditions in fuel cells and electrocatalysis.

08 HYDROGEN↗

Understanding Carbon Dioxide Transfer in Direct Methanol Fuel Cells Using a Pore-Scale Model

Abstract The gas flow of carbon dioxide from the catalyst layer (CL) through the microporous layer (MPL) and gas diffusion layer (GDL) has great impacts on the water and fuel management in direct methanol fuel cells (DMFCs). This work has developed a liquid–vapor two-phase model considering the counter flow of carbon dioxide gas, methanol, and water liquid solution in porous electrodes of DMFC. The model simulation includes the capillary pressure as well as the pressure drop due to flow resistance through the fuel cell components. The pressure drop of carbon dioxide flow is found to be about two to three orders of magnitude higher than the pressure drop of the liquid flow. The big difference between liquid and gas pressure drops can be explained by two reasons: volume flowrate of gas is three orders of magnitude higher than that of liquid; only a small fraction of pores (<5%) in hydrophilic fuel cell components are available for gas flow. Model results indicate that the gas pressure and the mass transfer resistance of liquid and gas are more sensitive to the pore size distribution than the thickness of porous components. To buildup high gas pressure and high mass transfer resistance of liquid, the MPL and CL should avoid micro-cracks during manufacture. Distributions of pore size and wettability of the GDL and MPL have been designed to reduce the methanol crossover and improve fuel efficiency. The model results provide design guidance to obtain superior DMFC performance using highly concentrated methanol solutions or even pure methanol.

Electrochemistry↗

Sensitivity and Effective Parameterization of a Multi-Scale Model of Proton-Exchange-Membrane Water Electrolysis

The development of proton-exchange-membrane water electrolysis (PEMWE) is crucial to establishing a green-hydrogen infrastructure. Active research in hydrogen technologies is focused on minimizing costs, improving efficiency, and mitigating safety risks. In this study, sensitivity analyses were performed using a physics-based model and used to identify critical parameters capable of reducing overpotentials and safety risks. These parameters include operational (i.e. temperature), structural (i.e. thickness of the components), and material properties (i.e. exchange current density). Simulated results suggest that better engineering of the membrane electrode assemblies (MEA) can offset intrinsic limitations. Membrane thickness and conductivity yielded the largest percent change on performance. Gas crossover was observed to be sensitive to diffusion, solubility, and bubble formation. Current density regimes were identified, where each crossover parameter was most influential. MEA parameterization serves as a framework for theoretical PEMWE optimization simulations and input for design criteria for future research targets.

Dizon, A↗

SNOWMASS2021 (AF7): Sub-scale models and infrastructure for accelerator magnet development

The LHC is undoubtfully the most important instrument the HEP community has on its disposal and is widely considered an amazing technological achievement. At the core of this instrument lay accelerator magnets based on NbTi technology – a technology well developed and widely used in the commercial sector too. Yet, a decade after the accelerator started it still did not reach its design collision energy of 14 TeV and it operated for years well below it. The reason for this is simple – magnet training (even though only a subset of the magnets is mostly affected).

43 PARTICLE ACCELERATORS↗

Physics-Informed Learning for Predictive Multi-Scale Modeling of Water Cycle and Extreme Events

Climate and earth system models have limited skill in predicting water cycle and associated extremes such as intense rain- and wind-producing storms and resulting hazards across all timescales. Water cycle predictions are inherently limited by the predictability of the chaotic system, but large potential for improving predictions remains untapped due to limited use of data-model integration to improve predictive modeling. This white paper proposes a hybrid data-physics paradigm based on physics-informed neural networks (PINNs) to improve the Energy Exascale Earth System Model (E3SM). In particular, we aim to predict and quantify uncertainties of water cycle processes and low probability high impact events.

54 ENVIRONMENTAL SCIENCES↗