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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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NASA NTRSDate not supplied

Use of an Internal Mercury-Argon Lamp for the Calibration of Raman Frequency in Large Raman Images of Astromaterials

Raman imaging is an emerging tool for the analysis of meteorites, as it is capable of describing the mineralogy and organics within a petrographic context. Adequately examining the heterogeneous composition of a meteorite often requires the collection of large Raman images with long collection times on the time-scale of days. However, the frequency calibration of the Raman instrument/spectrometer drifts on long timescales resulting in low frequency precision for the Raman spectra comprising a large Raman image. Here we utilize a Hg-Ar calibration lamp integrated into our Raman microscope to calibrate the Raman spectra within a Raman image. We characterize this method of calibration in detail.

Ryan S. Jakubek↗
NASA NTRS2018

Architecture for Space-Based Exoplanet Spectroscopy in Mid-Infrared

Characterizing exoearths at wavelength about 10 micron offers many benefits over visible coronagraphy. Apart from providing direct access to a number of significant bio-signatures, direct-imaging in the mid-infrared can provides 1000 times or more relaxation to contrast requirements while greatly shortening the time-scales over which the system must be stable. This in-turn enables tremendous relief to optical manufacturing, control and stability tolerances bringing them inline with current technology state of the art. In this paper, we explore a reference design that co-optimizes a large segmented linearized aperture telescope with one-dimensional phase-induced aperture apodization providing high-contrast imaging for spectroscopic analysis. By rotating about a parent star, the chemical signatures of its planets are characterized while affording additional means for background suppression.

Vasisht, Gautam↗
NASA NTRS2021

Conditions in the WR 140 Wind-collision Region Revealed by the 1.083-um He I Line Profile

We present spectroscopy of the P Cygni profile of the 1.083-μm He i line in the WC7 + O5 colliding-wind binary (CWB) WR140 (HD 193793), observed in 2008, before its periastron passage in 2009, and in 2016–17, spanning the subsequent periastron passage. Both absorption and emission components showed strong variations. The variation of the absorption component as the O5 star was occulted by the wind-collision region (WCR) sets a tight constraint on its geometry. While the sightline to the O5 star traversed the WCR, the strength and breadth of the absorption component varied significantly on time-scales of days. An emission sub-peak was observed on all our profiles. The variation of its radial velocity with orbital phase was shown to be consistent with formation in the WCR as it swung round the stars in their orbit. Modelling the profile gave a measure of the extent of the sub-peak forming region. In the phase range 0.93–0.99, the flux in the sub-peak increased steadily, approximately inversely proportionally to the stellar separation, indicating that the shocked gas in the WCR where the line was formed was adiabatic. After periastron, the sub-peak flux was anomalously strong and varied rapidly, suggesting formation in clumps down-stream in the WCR. For most of the time, its flux exceeded the 2–10-keV X-ray emission, showing it to be a significant coolant of the shocked wind.

Peredur M Williams↗
NASA NTRS2020

PPDIST, global 0.1° daily and 3-hourly precipitation probability distribution climatologies for 1979–2018

We introduce the Precipitation Probability DISTribution (PPDIST) dataset, a collection of global high-resolution (0.1°) observation-based climatologies (1979–2018) of the occurrence and peak intensity of precipitation (P) at daily and 3-hourly time-scales. The climatologies were produced using neural networks trained with daily P observations from 93,138 gauges and hourly P observations (resampled to 3-hourly) from 11,881 gauges worldwide. Mean validation coefficient of determination (R^(2)) values ranged from 0.76 to 0.80 for the daily P occurrence indices, and from 0.44 to 0.84 for the daily peak P intensity indices. The neural networks performed significantly better than current state-of-the-art reanalysis (ERA5) and satellite (IMERG) products for all P indices. Using a 0.1 mm 3 per h threshold, P was estimated to occur 12.2%, 7.4%, and 14.3% of the time, on average, over the global, land, and ocean domains, respectively. The highest P intensities were found over parts of Central America, India, and Southeast Asia, along the western equatorial coast of Africa, and in the intertropical convergence zone.

Hylke E. Beck↗
NASA NTRSDate not supplied

A Gaussian Process Enhancement to Linear Parameter Varying Models

Simulation and analysis for modern engineering systems now routinely requires the merging of multiple disciplines, physical-domains, time-scales, and data sets — all at ever increasing levels. These capabilities are especially needed in the domain of Advanced Air Mobility, where rapidly emerging vehicle designs are significantly more complex, while having to be both cost-effective and safe. To meet these engineering challenges, machine learning methods are an attractive option for merging models and data across multiple areas while providing uncertainty quantification and maintaining computational efficiency. This paper examines the use of Gaussian process machine learning to generalize and enhance the commonly used class of quasi-Linear Parameter Varying models for fast full-envelope simulation while also supporting control system design and analysis with model uncertainty. Gaussian process machine learning is selected because it: can fuse multiple data sets, enables an easy trade-off between data fitting and smoothing, provides model uncertainty quantification, scales well with increasing complexity, and does not generally require starting from a large training data set. To demonstrate the benefits of the approach, a robust stability analysis with Gaussian process uncertainty is shown for a NASA reference design of an electric quad-rotor air-taxi concept vehicle with motor parameter uncertainty.

Gaussian Process↗
NASA NTRS2021

An Investigation on Seasonal and Diurnal Cycles of TOA Shortwave Radiations from DSCOVR/EPIC, CERES, MERRA-2, and ERA5

Reflected shortwave (SW) solar radiations at the top of atmosphere from Clouds and the Earth’s Radiant Energy System (CERES), Modern Era-Retrospective analysis for Research and Applications version 2 (MERRA-2), and ECMWF Reanalysis 5th Generation (ERA5) are examined to better under-stand their differences in spatial and temporal variations (seasonal and diurnal cycle time-scale) with respect to the observations from the Earth Polychromatic Imaging Camera (EPIC) on Deep Space Climate Observatory (DSCOVR) satellite. Comparisons between two reanalyses (MERRA-2 and ERA5) and EPIC reveal that MERRA-2 has a generally larger deviation from EPIC than ERA5, in terms of the SW radiance and diurnal variability in all seasons, which can be attributed to larger cloud biases in MERRA-2. MERRA-2 produces more ice/liquid water content than ERA5 over the tropical warm pool, leading to positive SW biases in cloud and radiance, while both reanalyses underestimate the observed SW radiance from EPIC in the stratus-topped region off the western coast of US/Mexico in the boreal summer. Himalaya/Tibet region in the boreal spring/summer and the midlatitude Southern Hemisphere in the boreal winter are the regions where MERRA-2 and ERA5 deviate largely from EPIC but their deviations have the opposite sign. Vertical structures of cloud ice/liquid water content explain reasonably well these contrasting differences between the two reanalyses. As two independent observa-ions, CERES and EPIC agree well with each other in terms of the SW radiance maps, showing 2-3% mean absolute errors over the tropical-midlatitudes. The CERES-EPIC consistency further confirms that the reanalyses still have challenges in representing the SW flux and its global distribution. In the CERES-EPIC observation differences, CERES slightly overestimates the diurnal cycle (as a function of local solar time) of the observed EPIC irradiance in the morning and underestimates in the after-noon, while the opposite is the case in the reanalyses.

Reflected shortwave radiance↗
NASA NTRS2021

Conditions in the WR 140 Wind-Collision Region Revealed by the 1.083-mu m Hei Line Profile

We present spectroscopy of the P Cygni profile of the 1.083-μm He I line in the WC7+O5 colliding-wind binary (CWB) WR 140 (HD 193793), observed in 2008, before its periastron passage in 2009, and in 2016–2017, spanning the subsequent periastron passage. Both absorption and emission components showed strong variations. The variation of the absorption component as the O5 star was occulted by the wind-collision region (WCR) sets a tight constraint on its geometry. While the sightline to the O5 star traversed the WCR, the strength and breadth of the absorption component varied significantly on time-scales of days. An emission subpeak was observed on all our profiles. The variation of its radial velocity with orbital phase was shown to be consistent with formation in the WCR as it swung round the stars in their orbit. Modelling the profile gives a measure of the extent of the subpeak-forming region. In the phase range 0.93–0.99, the flux in the subpeak increased steadily, approximately inversely proportionally to the stellar separation, indicating that the shocked gas in the WCR where the line was formed was adiabatic. After periastron, the subpeak flux was anomalously strong and varied rapidly, suggesting formation in clumps downstream in the WCR. For most of the time, its flux exceeded the 2–10-keV X-ray emission, showing it to be a significant coolant of the shocked wind.

Peredur M Williams↗
NASA NTRS2020

Streaming Instability with Multiple Dust Species – I. Favourable Conditions for the Linear Growth

A recent study suggests that the streaming instability, one of the leading mechanisms for driving the formation of planetesimals, may not be as efficient as previously thought. Under some disc conditions, the growth time-scale of the instability can be longer than the disc lifetime when multiple dust species are considered. To further explore this finding, we use both linear analysis and direct numerical simulations with gas fluid and dust particles tomutually validate and study the unstablemodes of the instability in more detail.We extend the previously studied parameter space by one order of magnitude in both the range of the dust-size distribution [Ts, min, Ts, max] and the total solid-to-gas mass ratio ε and introduce a third dimension with the slope q of the size distribution. We find that the fast-growth regime and the slow-growth regime are distinctly separated in the ε–Ts, max space, while this boundary is not appreciably sensitive to q or Ts, min.With a wide range of dust sizes present in the disc (e.g. Ts, min  10−3), the growth rate in the slow-growth regime decreases as more dust species are considered.With a narrow range of dust sizes (e.g. Ts, max/Ts, min = 5), on the other hand, the growth rate in most of the ε–Ts, max space is converged with increasing dust species, but the fast and the slow growth regimes remain clearly separated. Moreover, it is not necessary that the largest dust species dominate the growth of the unstable modes, and the smaller dust species can affect the growth rate in a complicated way. In any case, we find that the fast-growth regime is bounded by ε  1 or Ts, max  1, which may represent the favourable conditions for planetesimal formation.

Zhaohuan Zhu↗
NASA NTRS2022

Statistical Properties of the Population of the Galactic Center Filaments II: The Spacing between Filaments

We carry out a population study of magnetized radio filaments in the Galactic centre using MeerKAT data by focusing on the spacing between the filaments that are grouped. The morphology of a sample of 43 groupings containing 174 magnetized radio filaments are presented. Many grouped filaments show harp-like, fragmented cometary tail-like, or loop-like structures in contrast to many straight filaments running mainly perpendicular to the Galactic plane. There are many striking examples of a single filament splitting into two prongs at a junction, suggestive of a flow of plasma along the filaments. Spatial variations in spectral index, brightness, bending, and sharpening along the filaments indicate that they are evolving on a 105−6-yr time-scale. The mean spacings between parallel filaments in a given grouping peaks at ∼16 arcsec. We argue by modeling that the filaments in a grouping all lie on the same plane and that the groupings are isotropically oriented in 3D space. One candidate for the origin of filamentation is interaction with an obstacle, which could be a compact radio source, before a filament splits and bends into multiple filaments. In this picture, the obstacle or sets the length scale of the separation between the filaments. Another possibility is synchrotron cooling instability occurring in cometary tails formed as a result of the interaction of cosmic ray driven Galactic centre outflow with obstacles such as stellar winds. In this picture, the mean spacing and the mean width of the filaments are expected to be a fraction of a parsec, consistent with observed spacing.

plasmas↗
NASA NTRSDate not supplied

Coupled Material Response Simulations of Dragonfly Capsule and DrEAM Reconstruction

Icarus is a three-dimensional, unstructured, finite-volume material response solver developed at NASA Ames Research Center and has been recently used to analyze the material response of the Dragonfly capsule for a variety of problems. Since the Dragonfly capsule will be instrumented in a similar manner to the Mars 2020 and MSL capsules, it is important to assess how our current simulation tools can aid in understanding Dragonfly Entry Aerosciences Measurements (DrEAM). In this presentation, the Ares multi-physics tool that couples Icarus to the flow and radiation physics of the aerothermal environment will be used to better understand how modeling sensitivities might affect environment reconstructions and our understanding of measured data. Ares couples Icarus to the US3D flow solver and NERO, a reduced-order, finite-volume radiation transport solver and uses a customized time-scale management to enable coupled simulations for a large portion of the Dragonfly trajectory. As a result of the coupling, a more accurate and consistent assessment of modelling sensitivities to aerothermal reconstruction can be assessed. For example, the radiometer is sensitive to the quantity of CN in the flow, which is a byproduct of the free-stream methane but also the pyrolysis gas products injected into the boundary layer due to ablation of the heatshield. Ares will be used to conduct a simulation of the full Dragonfly capsule for 50 seconds of the trajectory. The different aerothermal and material response models will be discussed and the key results will be presented in terms of the simulated thermocouple and radiometer measurements on the backshell.

Ablation↗
NASA NTRSDate not supplied

Developments to the Ares Multi-Physics Framework

Increasingly challenging problems in Entry, Descent, and Landing (EDL) have motivated the development of a computational framework that encompasses the advances in high-fidelity modeling and a robust foundation for TPS design in a single software package. This is the objective of the Ares multi-physics solver which, to date, couples the US3D flow solver with Icarus (material response) and Nero (radiation), through detailed time-scale management, while also incorporating the physics of fluid-solid boundaries such as gas-surface interaction chemistry and shape change. Ares, which is currently in the development stage, is being assessed against a variety of EDL relevant problems such as arc-jet tests of varying geometries and materials (Figs. 1 and 2), the earth entry of MSR-EES and the Titan entry of Dragonfly. This presentation will focus on the findings to-date regarding development of the technology as well as its standing with respect to available experimental data and/or reference solutions.

CFD↗
NASA NTRSDate not supplied

Turbulence Modeling near Gas-Liquid Interfaces for Cryogenic Fluid Management

In cryogenic fluid management (CFM), gas-liquid interface turbulence transport (ITT) heavily influences crucial design parameters of spaceflight missions. ITT and phase change processes require length-scales and time-scales that are around 4-8 orders of magnitude smaller than the scales of CFM operations in spaceflights. A sharp interface method based parsimonious yet elegant turbulence modeling approach was developed from experimental observations and high-fidelity numerical studies. The technique was validated using flight-scale CFM tests.

cryogenic fluid management↗
NASA NTRSDate not supplied

Time-History Statistics of Soot Formation in A Model Gas Turbine Combustor

Soot formation is a complex dynamic and intermittent process determined by properties of the fuel, combustor design, and combustor operation. Although the major steps in soot formation (i.e., formation of precursors, inception, growth and evolution) are similar for a variety of carbonaceous fuels, applications, and operating conditions, it remains unclear when the temporal transition between these steps occurs. An engineering prediction tool coupled with computational fluid physics (CFD), therefore needs to accurately model all these complex steps. To develop such a model, we propose the time-history concept for understanding the time dependency of soot formation as a function of local properties (i.e., temperature, velocity, local fuel air ratio, etc.). We continue our previous work with modeling the DLR aero-combustor [1] with our updated in-house CFD code, Open National Combustion Code (OpenNCC), that now includes a Multiple Time-Scale Flamelet Progress Variable approach and a the semi-empirical two-equation soot model. We injected massless tracer particles upstream of the injector region of the combustor to collect time-history statistics of the solution variables. The correlations between the collected statistics with respect to the experimental soot volume fraction data showed that time-history effect of certain flow variables, including turbulent kinetic energy (TKE), and multiple species is indeed important for soot formation. We then conducted a time-history based correlation analysis to determine the key species and the concentration ranges critical for soot formation (C6H5-based nucleation, acetylene-based surface growth, and oxidation with OH and O2). Based on the time-history correlation coefficient (THCC) analysis, we propose possible modifications to improve the current two-equation model.

LES↗
DOE OSTI2022

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗
DOE OSTI2023

High Power Targetry R&D and support for future generation accelerator

A high-power target system is a key beam element to complete future High Energy Physics (HEP) experiments. The target endures high power pulsed beam, leading to high cycle thermal stresses/pressures and thermal shocks. The increased beam power will also create significant challenges such as corrosion and radiation damage that can cause harmful effects on the material and degrade their mechanical and thermal properties during irradiation. This can eventually lead to the failure of the material and drastically reduce the lifetime of targets and beam intercepting devices. Designing a reliable target is already a challenge for MW class facilities today and has led several major accelerator facilities to operate at lower power due to target concerns. With present plans to increase beam power for next generation accelerator facilities in the next decade and the multi-year time-scale to acquire the knowledge on material behavior under such extreme environment, timely R&D of robust high-power targets is critical to fully secure the physics benefits of ambitious accelerator power upgrades. The next generation of high-power targets for future accelerators will use more complex geometries, novel materials, and new concepts allowing better high heat flux cooling methods. Advanced numerical simulations need to be developed to satisfy the physical design requirements of reliable beam-intercepting devices. In parallel, radiation hardened beam instrumentation irradiation methods for high-power targets must be further developed. Additional irradiation facilities are needed since only a few facilities worldwide offer beams for target testing, and the beam provided may not be appropriate for the specific facility or project. Thus, a comprehensive research and development program must be implemented to address the challenges that multi-MW targets face.

Pellemoine, F.↗
DOE OSTI2023

Simulating Catalysis with Realistic Pellet Geometries Using Mesoflow: A Case Study of Catalytic Propane Dehydrogenation

We present a case study of catalytic propane dehydrogenation with our open-source multiphysics solver, Mesoflow. The solver was developed to simulate reactive flow coupled to heterogeneous catalytic reactions and deactivation in the context of complex, mesoscale geometry. The method leverages cartesian block-structured adaptive mesh refinement to capture realistic catalyst microstructural features acquired directly from X-ray computed tomography data. A kinetic model for propane dehydrogenation and catalyst deactivation was developed based on temporal analysis of products (TAP) reactor experiments. The TAP reactor experiments allow for precise characterization of intrinsic kinetic reaction steps which are implemented into Mesoflow simulations to model the spatial and temporal evolution of reactants, products, and catalyst active sites. The short-term and long-term deactivation behavior is studied by using XCT data collected from fresh and aged catalyst pellets, which exhibit different microstructural features. This study employs time-splitting algorithms to connect disparate reaction and flow timescales, enabling the simulations to achieve realistic deactivation timescales on the order of minutes while the flow time-scales for small particles (100 microns) are several milliseconds. We also introduce a flexible automated python script that writes the necessary files to construct a Mesoflow simulation from user-created chemical mechanisms. We will also introduce a few new features that are added to Mesoflow such as higher order schemes, implicit chemistry integrators and the ability to run on AMD and NVIDIA graphics-processing-units.

AMReX↗
DOE OSTI2023

Self-tuning wave energy converter (WEC) controller for changing sea states

Systems and methods for a WEC controller that uses a self-tuning proportional-integral control law prescribing motor torques to maximize electrical power generation and automatically tune the controller to maximize power absorption. In an embodiment, the controller may be part of any resonant WEC system. The control law relies upon an identified model of device intrinsic impedance to generate a frequency-domain estimate of the wave-induced excitation force and measurements of device velocities. The control law was tested in irregular sea-states that evolved over hours (a rapid, but realistic time-scale) and that changed instantly (an unrealistic scenario to evaluate controller response).

Bacelli, Giorgio↗
DOE OSTI2023

Latent Neural ODE for Integrating Multi-Timescale Measurements in Smart Distribution Grids

Under a smart grid paradigm, there has been an increase in sensor installations to enhance situational awareness. The measurements from these sensors can be leveraged for real-time monitoring, control, and protection. However, these measurements are typically irregularly sampled. These measure-ments may also be intermittent due to communication bandwidth limitations. To tackle this problem, this paper proposes a novel latent neural ordinary differential equations (LODE) approach to aggregate the unevenly sampled multivariate time-series measurements. The proposed approach is flexible in performing both imputations and predictions while being computationally efficient. Simulation results on IEEE 37 bus test systems illustrate the efficiency of the proposed approach.

multi time-scale measurements↗