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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 NTRS2020

El Niño Related Tropical Land Surface Water and Energy Response in MERRA-2

Though El Niño events each have distinct evolutionary character they typically provide systematic large scale forcing for warming and increased drought frequency across the tropical continents. We assess this response in the MERRA-2 reanalysis and in a ten-member model AMIP ensemble. The lagged response (3-4 months) of mean tropical land temperature to El Niño warming in the Pacific Ocean is well represented. MERRA-2 reproduces the patterns of precipitation in the tropical regions, while the AMIP ensemble reproduces some regional responses better than others. Model skill is dependent on event forcing strength and temporal proximity to the peak of the sea surface warming. A composite approach centered on maximum Niño3.4 SSTs and lag relationships to energy fluxes and transports is used to identify mechanisms supporting tropical land warming. The composite necessarily moderates weather scale variability of the individual events, while retaining the systematic features across all events. We find that that reduced continental upward motions lead to reduced cloudiness and more shortwave radiation at the surface, as well as reduced precipitation. The increased shortwave heating at the land surface, along with reduced soil moisture leads to warmer surface temperature, more sensible heating and warming of the lower troposphere. While the composite provides a broad picture of the mechanisms governing the hydrologic response to El Niño forcing, the regional and temporal response in any given event can be quite variable. The 2015-16 El Niño, one of the strongest events, demonstrates some of the forced response noted in the composite, but with shifts in the evolution that depart from the composite, demonstrating the limitations of the composite and individuality of El Niño.

Michael G Bosilovich↗
NASA NTRS2019

A Model Study of the Relative Influences of Scavenging and Circulation on 230Th and 231Pa in the Western North Atlantic

The oceanic cycles of thorium-230 and protactinium-231 are affected by a number of processes, such as removal by adsorption to settling particles and transport by ocean currents. Measurements obtained as part of GEOTRACES and earlier programs have shown that, in the North Atlantic, the activities of dissolved 230Th (230Thd) and 231Pa (231Pad) at abyssal depths are lower near the western margin than in the basin interior. At least two factors could explain the lower 230Thd and 231Pad near the margin: (i) intensified scavenging in benthic nepheloid layers (BNLs) extending a thousand meters or more above the seafloor; and (ii) ventilation by relatively 230Thd- and 231Pad-poor waters emanating from the Deep Western Boundary Current (DWBC).Here a regional ocean circulation model with ?eddy-permitting' resolution (1/4) that incorporates 230Th and 231Pa is used in an effort to reproduce the observed distributions of 230Th and 231Pa in the western North Atlantic. In this model, 230Th and 231Pa removal from solution is governed by a prescribed distribution of particulate matter that is derived from a recent synthesis of nephelometer and transmissometer data. The model simulates a meandering Gulf Stream and a DWBC along the continental slope and rise, although noticeable differences with physical observations also exist. A model solution is found that explains most of the variance of 230Thd measurements (85%) and 231Pad measurements (81%) from (pre-)GEOTRACES cruises. On the other hand, measurements of particulate 230Th (230Thp) and 231Pa (231Pap) are more difficult to reproduce, with the same solution accounting for only 49% (11%) of the 230Thp (231Pap) variance. Sensitivity experiments suggest that the low 230Thd and 231Pad activities observed near the western margin are due to enhanced removal rates of both nuclides in BNLs rather than to deep water ventilation from the western boundary. The radionuclide activities present in the DWBC at its inflow location are also found to strongly influence the basin-scale distributions of 230Th and 231Pa. Overall, our study points to BNLs as important sites of 230Th and 231Pa scavenging in the ocean and illustrates the difficulty to explain simultaneously radionuclide measurements in dissolved and particulate forms in the studied area.

Lerner, Paul↗
NASA NTRS2020

Improving Quantitative Laboratory Analysis of Phycobiliproteins to Provide High Quality Validation Data for Ocean Color Remote Sensing Algorithm

Identification and characterization of phytoplankton communities and their physiology is a primary aim of NASA's PACE satellite mission. The concentration and composition of phytoplankton pigments modulate the spectral distribution of light emanating from the ocean, which is measured by ocean color satellites, and thus provide critical information on phytoplankton community composition and physiological parameters. One diagnostic class of pigments not routinely well-characterized is the phycobiliproteins (PBPs), and NASA has a requirement to collect and distribute high quality in situ data in support of data product validation activities for ocean color missions. Phycobiliproteins are light-harvesting proteins that are the predominant photosynthetic pigments in some classes of phytoplankton including cyanobacteria, such as Synechococcus, Trichodesmium, and Microcystis. With the advance of hyperspectral ocean color sensors such as on PACE (expected to launch in late 2022), it is essential that we implement routine analysis of PBPs that satisfies several considerations: reproducible, high extraction efficiency for a variety of environments, and Suitable for large scale analysis. Published techniques for PBP analysis vary in recommendations for: collection, extraction, disruption mode, and analysis; evidence suggests the variation in results may depend at least in part on the species and even strain(s) of interest. Experiments that tested variations in these parameters have drawn very different conclusions regarding extraction efficiency and reproducibility. Cyanobacteria are more difficult to extract than other PBP-containing algae such as cryptophytes, but can be important primary producers. We used a cryptophyte (Rhodomonas salina) and cyanobacterium (Synechococcus sp.) to compare extraction efficiencies of water samples concentrated via centrifugation to filtered samples using two different extraction buffers (phosphate and asolectin-CHAPS). Samples were analyzed on a fluorometer configured for PC and PE detection. The results have important implications for collection and storage of samples for routine analysis; some previous studies (although not all) have suggested that filtered samples have a much lower extraction efficiency than whole water samples.

Kenemer, Christopher↗
NASA NTRSDate not supplied

A Framework for Evaluating Climate Model Performance Metrics

The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is often used to add value to model projections: consensus projections have been shown to consistently outperform individual models. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, certain models reproduce climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables?e.g., outgoing longwave radiation and surface temperature. Metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument and surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing weighted and unweighted model ensembles. For example, one tested metric weights the ensemble by how well models reproduce the time-series probability distribution of the cloud forcing component of reflected shortwave radiation. The weighted ensemble for this metric indicates lower simulated precipitation (up to .7 mm/day) in tropical regions than the unweighted ensemble: since CMIP5 models have been shown to overproduce precipitation, this result could indicate that the metric is effective in identifying models which simulate more realistic precipitation. Ultimately, the goal of the framework is to identify performance metrics for advising better methods for ensemble averaging models and create better climate predictions.

Noel C Baker↗
NASA NTRS2018

Isochronal Age-mass Discrepancy of Young Stars: SCExAO/CHARIS Integral Field Spectroscopy of the HIP 79124 Triple System

We present SCExAO/CHARIS 1.1-2.4 μm integral field direct spectroscopy of the young HIP 79124 triple system. HIP 79124 is a member of the Scorpius-Centaurus association, consisting of an A0V primary with two low-mass companions at a projected separation of < 1″. Thanks to the high quality wavefront corrections provided by SCExAO, both companions are decisively detected without the employment of any PSF-subtraction algorithm to eliminate quasi-static noise. The spectrum of the outer C object is very well matched by Upper Scorpius M4 ± 0.5 standard spectra, with a T(eff) = 2945 ± 100 K and a mass of ∼350 M(Jup). HIP 79124 B is detected at a separation of only 180 mas in a highly-correlated noise regime, and it falls in the spectral range M6 ± 0.5 with T(eff) = 2840 ± 190 K and ∼100 M(Jup). Previous studies of stellar populations in Sco-Cen have highlighted a discrepancy in isochronal ages between the lower-mass and higher-mass populations. This could be explained either by an age spread in the region, or by conventional isochronal models failing to reproduce the evolution of low-mass stars. The HIP 79124 system should be coeval, and therefore it provides an ideal laboratory to test these scenarios. We place the three components in a color-magnitude diagram and find that the models predict a younger age for the two low-mass companions (∼3 Myr) than for the primary star (∼6 Myr). These results imply that the omission of magnetic effects in conventional isochronal models inhibit them from reproducing early low-mass stellar evolution, which is further supported by the fact that new models that include such effects provide more consistent ages in the HIP 79124 system.

Ruben Asensio-Torres↗
NASA NTRSDate not supplied

Causes of Model Biases in Simulating Inorganic Aerosol Composition During KORUS-AQ and Implications for the Estimate of Transboundary Pollution

East Asia is a region of increasing economic growth which has led to severe PM2.5 pollution in urban areas. The joint NASA-NIER Korea-United States Air Quality (KORUS-AQ) field campaign in May-June 2016 provided an extensive dataset of ground, airborne, and remote sensing observations to test model simulations of PM2.5 pollution transport and potential control measures. During KORUS-AQ, a period of haze was observed in which PM2.5 rapidly increased to the highest levels observed during the campaign. This increase is associated with increasing inorganic aerosol. While a portion of this increase is due to long-range transport, there is observational evidence that aerosol formation from local precursors was also enhanced. This suggests that domestic policy measures could have a greater than expected influence on controlling PM2.5. However, models have difficulty reproducing PM2.5 levels, particularly the composition of secondary inorganic aerosol. Models generally underestimate sulfate and overestimate nitrate and fail to represent the peak levels of PM2.5 during haze events. These biases have been chiefly attributed to errors in chemical mechanisms and model meteorology, not issues with underlying emissions inventories. Here, we use observations from KORUS-AQ interpreted by the GEOS-Chem chemical transport model to improve the model’s ability to reproduce secondary inorganic aerosol concentrations during the campaign and explore mechanisms to improve model biases during the haze event. We assess the fraction of inorganic aerosol from the improved model simulation that results from transboundary transport during KORUS-AQ and test the model sensitivity to potential emission reduction measures that could improve air quality in Seoul during different meteorological periods including haze episodes.

Katie Travis↗
NASA NTRS2020

Sub-Mesoscales at Ocean Fronts: Dissipation of Eddy Kinetic Energy

D’Asaro et al. measured the dissipation of eddy kinetic energy at the Kuroshio ocean front, found it to be 1-2 orders of magnitude larger than the value predicted by the law of the wall and suggested that the enhancement is due to sub-mesoscales, SM. To assess their suggestion, we employ two SM models. In the first model the buoyancy flux is based on baroclinic instabilities only and there is no momentum flux (Reynolds stresses). The model is unable to reproduce the Kuroshio data. The second model includes baroclinic instabilities, wind stress and Reynolds stresses. It reproduces the data satisfactorily. The analytic formula for the dissipation that we present can be used in OGCMs to parameterize dissipation at ocean fronts other than Kuroshio, e.g., Gulf Stream and ACC, an extension that could improve the predictions of climate studies.

sub-mesoscale models↗
NASA NTRS2020

Bias in CMIP6 Models as Compared to Observed Regional Dimming and Brightening

Anthropogenic aerosol emissions have increased considerably over the last century, but climate effects and quantification of the emissions are highly uncertain as one goes back in time. This uncertainty is partly due to a lack of observations in the pre-satellite era, making the observations we do have before 1990 additionally valuable. Aerosols suspended in the atmosphere scatter and absorb incoming solar radiation and thereby alter the Earth's surface energy balance. Previous studies show that Earth system models (ESMs) do not adequately represent surface energy fluxes over the historical era. We investigated global and regional aerosol effects over the time period 1961–2014 by looking at surface downwelling shortwave radiation (SDSR). We used observations from ground stations as well as multiple experiments from eight ESMs participating in the Coupled Model Intercomparison Project Version 6 (CMIP6). Our results show that this subset of models reproduces the observed transient SDSR well in Europe but poorly in China. We suggest that this may be attributed to missing emissions of sulfur dioxide in China, sulfur dioxide being a precursor to sulfate, which is a highly reflective aerosol and responsible for more reflective clouds. The emissions of sulfur dioxide used in the models do not show a temporal pattern that could explain observed SDSR evolution over China. The results from various aerosol emission perturbation experiments from DAMIP, RFMIP and AerChemMIP show that only simulations containing anthropogenic aerosol emissions show dimming, even if the dimming is underestimated. Simulated clear-sky and all-sky SDSR do not differ greatly, suggesting that cloud cover changes are not a dominant cause of the biased SDSR evolution in the simulations. Therefore we suggest that the discrepancy between modeled and observed SDSR evolution is partly caused by erroneous aerosol and aerosol precursor emission inventories. This is an important finding as it may help interpret whether ESMs reproduce the historical climate evolution for the right or wrong reason.

surface downwelling shortwave radiation (SDSR)↗
NASA NTRS2020

Structure and Parameter Uncertainty in Centennial Projections of Forest Community Structure and Carbon Cycling

Secondary forest regrowth shapes community succession and biogeochemistry for decades, including in the Upper Great Lakes region. Vegetation models encapsulate our understanding of forest function, and whether models can reproduce multi‐decadal succession patterns is an indication of our ability to predict forest responses to future change. We test the ability of a vegetation model to simulate C cycling and community composition during 100 years of forest regrowth following stand‐replacing disturbance, asking (a) Which processes and parameters are most important to accurately model Upper Midwest forest succession? (b) What is the relative importance of model structure versus parameter values to these predictions? We ran ensembles of the Ecosystem Demography model v2.2 with different representations of processes important to competition for light. We compared the magnitude of structural and parameter uncertainty and assessed which sub‐model–parameter combinations best reproduced observed C fluxes and community composition. On average, our simulations underestimated observed net primary productivity (NPP) and leaf area index (LAI) after 100 years and predicted complete dominance by a single plant functional type (PFT). Out of 4,000 simulations, only nine fell within the observed range of both NPP and LAI, but these predicted unrealistically complete dominance by either early hardwood or pine PFTs. A different set of seven simulations were ecologically plausible but under‐predicted observed NPP and LAI. Parameter uncertainty was large; NPP and LAI ranged from ~0% to >200% of their mean value, and any PFT could become dominant. The two parameters that contributed most to uncertainty in predicted NPP were plant–soil water conductance and growth respiration, both unobservable empirical coefficients. We conclude that (a) parameter uncertainty is more important than structural uncertainty, at least for ED‐2.2 in Upper Midwest forests and (b) simulating both productivity and plant community composition accurately without physically unrealistic parameters remains challenging for demographic vegetation models.

canopy radiative transfer↗
NASA NTRS2021

Bias-Correcting Carbon Fluxes Derived From Land-Surface Satellite Data for Retrospective and Near Real-Time Assimilation Systems

The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide(CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital in-put datasets, e.g., inventories, in situ measurements, and re-processed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth’s surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases inCO2which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal fore-casts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA’s Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

CO2↗
NASA NTRS2021

Performance of JAXA’s SGLI standard ocean color products for oceanic to coastal waters: chlorophyll a concentration and light absorption coefficients of colored dissolved organic matter

We present the performance of JAXA’s SGLI standard algorithms for estimating chlorophyll a (chl a) concentration and the light absorption coefcients of colored dissolved organic matter (CDOM) using recently compiled high-quality data obtained from oceanic to coastal waters. Prior to the evaluation of the algorithms, we frst compare two forward models (Gordon et al. in J Geophys Res 93(D9):10909-10924, 1988: G88 and Park and Ruddick in Appl Opt 44(7):1236–1249, 2005: PR05) using a wide range of inherent optical properties (IOPs) to (1) examine if the water refectance is appropriately reproduced and (2) correct measured refectance in terms of its bidirectionality. Based on a good reproducibility of water refectance using the PR05, the optimized IOPs are further used for explaining errors in estimates of chl a concentration and CDOM absorption when using the SGLI, the GSM (Maritorena et al. in Appl Opt 41:2705–2714, 2002), and the QAA (Lee et al. in Appl Opt 41:5755, 2002) inversion algorithms. Results show that the mean error for estimating chl a concentration using the SGLI algorithm is 110% for our dataset. Although this error is lower than that of the GSM and the QAA algorithms, a signifcant underestimate at chl a higher than 2.0 mg m−3 is observed, which is further shown by independent match-up analyses. Another SGLI CDOM product includes the mean error of 50% and shows deviation at high CDOM range (>1.0 per m). A similar trend is observed for the GSM but not for the QAA when a global relationship of CDOM to colored detrital matter is applied. The sources of errors are discussed for potentially improving the retrievals

Second-generation GLobal Imager (SGLI)↗
NASA NTRSDate not supplied

Modeling the Crystallization of Martian Igneous Compositions

The martian crust is dominated by basalts and ultramafic rocks [1]. Understanding the crystallization sequence of martian igneous rocks is critical for constraining the petrologic and geochemical evolution of the crust and mantle. Experimental studies have investigated the parental liquid compositions and crystallization behavior using martian meteorite compositions [2-7], as well as compositions measured by rovers on the martian surface [8,9]. While experiments deliver crucial results, they are often limited by time and resources. Therefore, modeling approaches are an ideal tool to complement experimental results. The application of the MELTS software package [10, 11], to calculate the crystallization of martian compositions, reproduces important compositional details of magma crystallization but significant uncertainties regarding the pressure of the olivine-pyroxene multiple saturation point have been reported [12], and in the temperatures of initial crystallization [12, 13]. Recently, a new melting model, MAGMARS, has been shown to reproduce martian primary melts more accurately [14]. Here, we constrain the applicability of Gibbs free energy minimization software Perple_X [15] for martian compositions by comparing our modeled results to experimentally derived crystallization paths for two martian compositions.

J Semprich↗
NASA NTRS2022

Advances and Challenges in Observations and Modeling of the Global-Sun Dynamics and Dynamo

Computational heliophysics has shed light on the fundamental physical processes inside the Sun, such as the differential rotation, meridional circulation, and dynamo-generation of magnetic fields. However, despite the substantial advances, the current results of 3D MHD simulations are still far from reproducing helioseismic inferences and surface observations. The reason is the multi-scale nature of the solar dynamics, covering a vast range of scales, which can-not be solved with the current computational resources. In such a situation, significant progress has been achieved by the mean-field approach, based on the separation of small-scale turbulence and large-scale dynamics. The mean-field simulations can reproduce solar observations, qualitatively and quantitatively, and uncover new phenomena. However, they do not reveal the complex physics of large-scale convection, solar magnetic cycles, and the magnetic self-organization that causes sunspots and solar eruptions. Thus, developing a synergy of these approaches seems to be a necessary but very challenging task.

SMD↗
NASA NTRS2022

The Simulation and Subseasonal Forecasting of Hydrological Variables: Insights from a Simple Water Balance Model

Past work has shown that a land surface model’s (LSM’s) implicit (not explicitly coded) relationships between soil moisture and both evapotranspiration (ET) and runoff largely determine the LSM’s hydrological behavior. Here we estimate the relationships that appear to be operating in the real world and compare them to those of the LSM component of a state-of-the-art Earth system model (ESM). The two sets of relationships are determined by calibrating them within a simple water balance model (WBM): once using stream gauge observations from small, unregulated rivers over the eastern half of the U.S., and once using the runoffs generated by the LSM as part of a state-of-the-art atmospheric reanalysis. Hydrological simulations and subseasonal hydrological forecasts performed with the two calibrated versions of the WBM provide two key results. First, the version calibrated to the LSM-generated runoffs does successfully reproduce, to first order, the hydrological behavior of the full LSM within its ESM environment. Second, of the two WBM versions, the one calibrated to the observations reproduces more accurately a broad collection of fully independent streamflow observations as well as a similarly broad collection of in-situ soil moisture measurements. Taken together, the two results suggest that the observations-calibrated ET and runoff efficiency functions do successfully represent, at least to some degree, soil moisture controls over hydrological variability in Nature and can serve as potentially useful targets for further LSM development.

Water Balance Model↗
NASA NTRS2022

A Framework for Deep Learning Emulation of Numerical Models With a Case Study in Satellite Remote Sensing

Numerical models based on physics represent the state of the art in Earth system modeling and comprise our best tools for generating insights and predictions. Despite rapid growth in computational power, the perceived need for higher model resolutions overwhelms the latest generation computers, reducing the ability of modelers to generate simulations for understanding parameter sensitivities and characterizing variability and uncertainty. Thus, surrogate models are often developed to capture the essential attributes of the full-blown numerical models. Recent successes of machine learning methods, especially deep learning (DL), across many disciplines offer the possibility that complex nonlinear connectionist representations may be able to capture the underlying complex structures and nonlinear processes in Earth systems. A difficult test for DL-based emulation, which refers to function approximation of numerical models, is to understand whether they can be comparable to traditional forms of surrogate models in terms of computational efficiency while simultaneously reproducing model results in a credible manner. A DL emulation that passes this test may be expected to perform even better than simple models with respect to capturing complex processes and spatiotemporal dependencies. Here, we examine, with a case study in satellite-based remote sensing, the hypothesis that DL approaches can credibly represent the simulations from a surrogate model with comparable computational efficiency. Our results are encouraging in that the DL emulation reproduces the results with acceptable accuracy and often even faster performance. We discuss the broader implications of our results in light of the pace of improvements in high-performance implementations of DL and the growing desire for higher resolution simulations in the Earth sciences.

Bayesian Deep Learning↗
NASA NTRSDate not supplied

Developing a Vision for Maturing the Heliophysics Infrastructure towards Open Science: The DIARieS Analysis Ecosystem

In the dawn of open science and the upcoming requirements, we speak about the existing state of Heliophysics infrastructure and detail the evolution required to address capability or interconnection shortcomings. Such a daunting barrier calls for an analysis ecosystem with multi-faceted capability. We propose such an ecosystem, called DIARieS, to be built upon five conceptual pillars: Discovery, Implementation, Analysis, Reproducibility, and Sharing of results. The combination of these concepts in a single platform will enable users to more intuitively combine recent advances in technology to create ‘DIARieS’ of their workflows, which can be easily made open to others in the community. The DIARieS ecosystem will also increase our efficiency by streamlining our various workflow processes, including automatic incorporation of the impending requirements of open science. The various components of the ecosystem will simplify software installation and data implementation, including automatically generated citation lists based on the components included. Automatic containerization and version control of the ecosystem will make the custom workflows easily reproducible. Employing widget technology will ease the difficulty of producing publication and commercial quality visualizations and applying common analyses techniques. Incorporating multiple technologies will streamline the various sharing methods common in our work environments today. Overall, the totality of capabilities to be offered by this analysis ecosystem will drastically simplify the application of open science principles to our work in addition to improving our efficiency and ease of collaboration. This talk summarizes a vision of the proposed ecosystem, which is described in more detail in Ringuette et al. (2022: https://doi.org/10.1016/j.asr.2022.05.012).

infrastructure↗
NASA NTRSDate not supplied

High Speed Data Investigation of an LOX/LNG Combustor Assisted by Non-linear Acoustic Simulations

During testing of a regenerative cooled liquid oxygen/liquid natural gas combustor large amplitude combustion instabilities were observed in half of the series conducted. These instabilities produced an unsteady pressure Root Mean Square (RMS) value greater than the chamber steady state pressure. Quick look investigations of the test data presented some standard indications of non-linear tangential instability such as a non-sinusoidal time series, and larger peaks than trough. Also observed in the data quick look were some atypical findings including a first harmonic amplitude larger than the fundamental, and numerous side bands on the fundamental and subsequent harmonics. A simplified model of the combustor was created using a commercially available finite element software. The first tangential acoustic mode was then simulated using a non-linear wave equation in conjunction with a time explicit discontinuous Gelarkin flow solver. Numerous simulations were evaluated providing valuable insight and reproducing the atypical findings in the data. Side bands were created through non-linear signal modulation like an AM radio. This happens due to the non-linear steepening and relaxing that occurs in large amplitude oscillations. The simulation was also able to reproduce a signal with a first harmonic amplitude larger than the fundamental. Investigating the pressure signal at multiple locations across the chamber head end revealed radial dependent frequency content. A literature review of the topic revealed corroboration of these effect in idealized geometries.

Combustion Stability↗
NASA NTRSDate not supplied

Hybrid-Electric Aero-Propulsion Controls Laboratory: Overview and Capability

A hardware-in-the-loop (HIL) laboratory is developed to investigate control technologies for electrified aircraft propulsion (EAP). The laboratory emulates a propulsion system by reproducing the mechanical shaft interface to the electrical power system in hardware. The experimental electric power system includes supercapacitor energy storage and a dynamically variable electrical load. A novel method of scaling power and inertia is provided in software to accurately reproduce the transient, off-design turbomachinery performance dynamics without including actual turbomachinery. An overview of how the HIL system can accommodate a broad range of EAP architectures, including power extraction and insertion, with capability for transient energy management is described. The real-time system operates in the 100kW power class and is instrumented to emulate turbomachinery – power system interactions. The platform is an agile, flexible laboratory for low-cost, risk-reduction development and testing of propulsion control, operability, and energy management technologies.

Controls↗