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At least 415 records · Page 23

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DOE OSTI2021

Sustainable Lactic Acid Production from Lignocellulosic Biomass

Lignocellulosic biomass is a promising feedstock for sustainable biofuels and bioproducts. Among emerging bioproducts, lactic acid has attracted significant interest because of its growing application in many industries (e.g., packaging, medical, and pharmaceutical). In this study, BioSTEAM—an open-source platform—was leveraged for the design, simulation, and evaluation (via techno-economic analysis, TEA, and life cycle assessment, LCA) of lignocellulosic lactic acid biorefineries. With a minimum product selling price (MPSP) between 1.38 and 1.91 kg –1 (5th–95th percentiles, baseline at 1.57 kg –1 ), the biorefinery was capable of producing market-competitive lactic acid (market price between 1.7 and 2.1 kg –1 ), and its performance could be further enhanced (e.g., MPSP down to 1.09 kg –1 , global warming potential of 2.79 kg CO 2 -eq·kg –1 , and fossil energy consumption of 31.7 MJ·kg –1 ) with advancements in key technological parameters (fermentation yield and separation process conversions) and optimization in process operation. Sensitivity analyses focused on the fermentation unit (across titer, yield, and productivity; neutral vs low-pH fermentation) and feedstock characteristics (carbohydrate content and price) were also included to quantify their impact on the sustainability of the biorefinery. Overall, this research highlights the ability of agile TEA/LCA to screen promising biorefinery designs, prioritize research needs, and establish a road map for the continued development of bioproducts and biofuels.

09 BIOMASS FUELS↗

DOE OSTI2020

The SrrAB two-component system regulates Staphylococcus aureus pathogenicity through redox sensitive cysteines

Staphylococcus aureus infections can lead to diseases that range from localized skin abscess to life-threatening toxic shock syndrome. The SrrAB two-component system (TCS) is a global regulator of S. aureus virulence and critical for survival under environmental conditions such as hypoxic, oxidative, and nitrosative stress found at sites of infection. Despite the critical role of SrrAB in S. aureus pathogenicity, the mechanism by which the SrrAB TCS senses and responds to these environmental signals remains unknown. Bioinformatics analysis showed that the SrrB histidine kinase contains several domains, including an extracellular Cache domain and a cytoplasmic HAMP-PAS-DHp-CA region. In this work, we show that the PAS domain regulates both kinase and phosphatase enzyme activity of SrrB and present the structure of the DHp-CA catalytic core. Importantly, this structure shows a unique intramolecular cysteine disulfide bond in the ATP-binding domain that significantly affects autophosphorylation kinetics. In vitro data show that the redox state of the disulfide bond affects S. aureus biofilm formation and toxic shock syndrome toxin-1 production. Moreover, with the use of the rabbit infective endocarditis model, we demonstrate that the disulfide bond is a critical regulatory element of SrrB function during S. aureus infection. Our data support a model whereby the disulfide bond and PAS domain of SrrB sense and respond to the cellular redox environment to regulate S. aureus survival and pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Improving E3SM Land Model Photosynthesis Parameterization via Satellite SIF, Machine Learning, and Surrogate Modeling

The parameterization of key photosynthesis parameters is one of the key uncertain sources in modeling ecosystem gross primary productivity (GPP). Solar-induced chlorophyll fluorescence (SIF) offers a good proxy for GPP since it marks the actual process of photosynthesis; while machine learning (ML) provides a robust approach to model the GPP-SIF relationship. Here, we trained the boosted regressing tree (BRT) and the Random Forest ML models with Greenhouse Gases Observing Satellite SIF data and in situ GPP observations from 49 eddy covariance towers. These trained ML GPP-SIF models were fed into the Energy Exascale Earth System Model (E3SM) Land Model (ELM) to generate ELM-simulated global SIF estimates, which were then benchmarked against satellite SIF observations with a surrogate modeling approach. Our results indicated good modeling performance of the ML-based GPP-SIF relationship. The ELM model when fed with the ML GPP-SIF models also can well predict the spatial-temporal variations in SIF. We also found high model accuracy for the surrogate modeling. Model parameter sensitivity analysis suggested that the fraction of leaf nitrogen in RuBisCO (flnr) is the most sensitive parameter to the SIF; other sensitive parameters include the Ball-Berry stomatal conductance slope (mbbopt) and the vcmax entropy (vcmaxse). The posterior uncertainty in simulated GPP was greatly reduced after benchmarking, and the model produced improved spatial patterns of mean GPP relative to FLUXCOM GPP. Our integrated approach provides a new avenue for improving land models and using remote-sensing SIF, which can be further improved in the future with more ground- and satellite-based observations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Simplified Applied Loads of a Transonic Truss-Braced Wing Derived from Computational Fluid Dynamics

The transonic truss-braced wing (TTBW) concept is under consideration by the NASA Advanced Air Transport Technology (AATT) project due to its potential to reduce fuel consumption of transport aircraft. To properly evaluate the TTBW concept, detailed structural modeling and subsequent test planning is underway, which requires a simplified set of discrete applied loads that simulate the distributed aerodynamic pressures. Given the unique architecture of the TTBW and its intended operation in the transonic regime, computational fluid dynamics (CFD) is the ideal approach to employ to ensure the aerodynamics of this configuration are sufficiently captured. To convert aerodynamic results into input for structural models, application of a data transfer tool, Discrete Data Transfer Between Dissimilar Meshes (DDTBDM), is presented to resolve aerodynamic pressures from CFD into single load vectors at hardpoints along both the wing and the strut. Evaluation of mapping the aerodynamic forces to hardpoints at rib and spar intersections in a structural model is performed, and the results are also compared with a linear static aeroelastic analysis. The structural responses indicate that distributing forces along only the wing and strut forward spars is insufficient for simulating the distributed aerodynamic loads. Adding moments along the forward spars improved the global response of the wing, but the point moments created unrealistic local rotations within the structure. When distributing loads along both the forward and aft spars of the wing and strut, the global response was less sensitive to the inclusion of point moments, which indicated the arrangement of point forces alone was sufficient input for structural design work and testing and provided a more continuous loading profile.

Finite Element↗

NASA NTRSDate not supplied

Simplified Applied Loads of a Transonic Truss-Braced Wing Derived from Computational Fluid Dynamic

Finite Element↗

DOE OSTI2020

Effects of fuel composition and octane sensitivity on polycyclic aromatic hydrocarbon and soot emissions of gasoline–ethanol blend surrogates

The sooting propensity of a fuel is closely coupled with the fuel composition and chemistry. A detailed understanding of their effects is, therefore, needed to develop next-generation fuels which can minimize particulate emissions. With this overarching goal, the present work numerically investigates the effects of fuel composition and octane sensitivity (S) on polycyclic aromatic hydrocarbons (PAH) and soot emissions, for four-component gasoline-ethanol blend surrogates comprising isooctane, n-heptane, toluene, and ethanol. A partially-premixed counterflow flame is chosen as the canonical configuration for this study and simulations are performed using CHEMKIN-Pro-employing a kinetic mechanism developed by Park et al. (2017). In addition, a, detailed soot model based on the sectional method is used to capture the spatial characteristics of soot emissions. The kinetic mechanism and soot model are validated using available experimental data for various targets. A total of 86 TPRF-E mixtures, spanning a wide range of concentration of each component, and a wide range of S are analyzed. The effect of each non-paraffinic fuel component on the resultant PAH and soot emissions is investigated. PAH and soot emissions are found to vary significantly depending upon the blend composition. Additionally, based on the parametric sweeps, a regression analysis is carried out to identify global parameters that govern the formation of PAHs and soot. The analysis shows that both toluene content and S have a prominent effect on the formation of PAHs and soot, with toluene content having a stronger impact. Moreover, larger PAHs have higher dependency on toluene content and S. Furthermore, a detailed analysis is carried out to understand the physical and chemical phenomena associated with the observed trends of PAH and soot emissions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1981

Instability of non-zonal baroclinic flows - Multiple-scale analysis

The linear instability of a non-zonal flow can be reduced to an eigenvalue-eigenfunction problem, governed by a nonseparable partial differential equation (Niehaus, 1980). Approximate solutions, found by the method of multiple scales, are derived here and compared with earlier results found using a spectral method. The amplitude maxima are correctly located. The zonal variations of local wavenumber and of amplitude are qualitatively correct, but not sufficiently extreme. Because the method is oversensitive to local conditions, and less sensitive to global constraints, this comparison provides theoretical limits to the possibility of parameterizing transient eddies in terms of the local time mean state of the atmosphere. The method can be extended easily to flows with more realistic vertical structure.

Niehaus, M. C. W.↗

NASA NTRSDate not supplied

Regional and Model-Specific Response Types in A Global Gridded Crop Model Ensemble

Crop models are often employed to project crop yields under changing conditions such as global warming and associated management change for adaptation. Multi-model ensembles are promoted to enhance the robustness of projections, but questions remain on what causes often large differences between projections of individual models. Global Gridded Crop Models (GGCMs) are especially exposed to this question when applied for assessing climate change impacts, adaptation, environmental impacts of agricultural production, because their results are used in downstream analyses, such as in integrated assessment or economic modeling for projecting future land-use change. Even though global gridded crop models are often based on detailed field-scale models or have implemented similar modeling principles in other ecosystem models, global-scale models are subject to substantial uncertainties from both model structure and parametrization as well as from calibration and input data quality. AgMIP’s Global Gridded Crop Model Intercomparison (GGCMI) has thus set out to intercompare GGCMs in order to evaluate model performance, describe model uncertainties, identify inconsistencies within the ensemble and underlying reasons, and to ultimately improve models and modeling capacities. In phase 2 of the GGCMI activities, 12 modeling groups followed a modeling protocol that asked for up to 1404 31-year global simulations at 0.5 arc-degree spatial resolution to assess models’ sensitivities to changes in carbon dioxide (C; 4 different levels) temperature (T; 7 different offset levels), water supply (W; 9 levels), and nitrogen (N; 3 levels), the so-called CTWN experiment (Franke et al. 2020; http://dx.doi.org/10.5194/gmd-13-2315-2020). We here present analyses of model response types using impact response surfaces along the C, T, W, and N dimensions, respectively and collectively. Doing so, we can understand differences in simulated responses per driver rather than aggregated changes in yields. We find that models’ sensitivities to the individual driver dimensions are substantially different and often more different across models than across regions. A cluster analysis finds regional and model-specific patterns. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response type clusters across models suggests that models need to undergo further scrutiny. We suggest establishing standards in model process evaluation not only against historical dynamics but also against dedicated experiments across the CTWN dimensions.

crop models↗

NASA NTRS2013

Mars-GRAM 2010: Additions and Resulting Improvements

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM has been utilized during previous aerobraking operations in the atmosphere of Mars. Mars-GRAM has also been used in the prediction and validation of Mars Pathfinder hypersonic aerodynamics, the aerothermodynamic and entry dynamics studies for Mars Polar Lander, the landing site selection process for the Mars Science Laboratory (MSL), the Mars Aerocapture System Study (MASS) as well as the Aerocapture Technology Assessment Group (TAG). Most recently, Mars-GRAM 2010 was used to develop the onboard atmospheric density estimator that is part of the Autonomous Aerobraking Development Plan. The most recent release of Mars-GRAM 2010 contains several changes including an update to Fortran 90/95 and the addition of adjustment factors. Following the completion of a comparison analysis between Mars-GRAM, Thermal Emission Spectrometer (TES), as well as Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) aerobraking density data, adjustment factors were added to Mars-GRAM 2010 that alter the input data from National Aeronautics and Space Administration (NASA) Ames Mars General Circulation Model (MGCM) and the University of Michigan Mars Thermospheric General Circulation Model (MTGCM) for the mapping year 0 user-controlled dust case. The addition of adjustment factors resolved the issue of previous versions of Mars-GRAM being less than realistic when used for sensitivity studies for mapping year 0 and large optical depth values, such as tau equal to 3. Mars-GRAM was evaluated at locations and times of TES limb observations and adjustment factors were determined. For altitudes above 80 km and below 135 km, Mars-GRAM (MTGCM) densities were compared to aerobraking densities measured by Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) to determine the adjustment factors. The adjustment factors generated by this process had to satisfy the gas law as well as the hydrostatic relation and are expressed as a function of height (z), Latitude (Lat) and areocentric solar longitude (Ls). The greatest adjustments are made at large optical depths such as tau greater than 1. The addition of the adjustment factors has led to better correspondence to TES Limb data from 0-60 km altitude as well as better agreement with MGS, ODY and MRO data at approximately 90-130 km altitude. Improved Mars-GRAM atmospheric simulations for various locations, times and dust conditions on Mars will be presented at the workshop session. The latest results validating Mars-GRAM 2010 versus Mars Climate Sounder data will also be presented. Mars-GRAM 2010 updates have resulted in improved atmospheric simulations which will be very important when beginning systems design, performance analysis, and operations planning for future aerocapture, aerobraking or landed missions to Mars.

Justh, Hilary L.↗

NASA NTRS1991

Measuring earth orientation with the Global Positioning System

A globally distributed network of high-precision receivers which obtain data from the full Global Positioning System (GPS) configuration of 18 or more satellites may soon become an efficient and economical method for the rapid determination of short-term variations in earth orientation. A covariance analysis has been performed to evaluate the errors associated with GPS monitoring of earth orientation. Earth orientation parameters were modeled either as constants over observing windows of various lengths, or as stochastic process-noise variables. The sensitivity of earth orientation estimates to systematic errors in selected model parameters was also examined. GPS measurements appear to be highly competitive with those from other techniques, and have the potential to generate nearly continuous centimeter-level earth orientation information to aid both spacecraft navigation and the study of high-frequency earth orientation-related processes.

Freedman, Adam P.↗

NASA NTRS1993

Design and analysis of numerical experiments

Methods for the design and analysis of numerical experiments that are especially useful and efficient in multidimensional parameter spaces are presented. The analysis method, which is similar to kriging in the spatial analysis literature, fits a statistical model to the output of the numerical model. The method is applied to a fully nonlinear, global, equivalent-barotropic dynamical model. The statistical model also provides estimates for the uncertainty of predicted numerical model output, which can provide guidance on where in the parameter space to conduct further experiments, if necessary. The method can provide significant improvements in the efficiency with which numerical sensitivity experiments are conducted.

Bowman, Kenneth P.↗

NASA NTRS2018

Examining Dense Data Usage near the Regions with Severe Storms in All-Sky Microwave Radiance Data Assimilation and Impacts on GEOS Hurricane Analyses

Many numerical weather prediction (NWP) centers assimilate radiances affected by clouds and precipitation from microwave sensors, with the expectation that these data can provide critical constraints on meteorological parameters in dynamically sensitive regions to make significant impacts on forecast accuracy for precipitation. The Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center assimilates all-sky microwave radiance data from various microwave sensors such as all-sky GPM Microwave Imager (GMI) radiance in the Goddard Earth Observing System (GEOS) atmospheric data assimilation system (ADAS), which includes the GEOS atmospheric model, the Gridpoint Statistical Interpolation (GSI) atmospheric analysis system, and the Goddard Aerosol Assimilation System (GAAS). So far, most of NWP centers apply same large data thinning distances, that are used in clear-sky radiance data to avoid correlated observation errors, to all-sky microwave radiance data. For example, NASA GMAO is applying 145 km thinning distances for most of satellite radiance data including microwave radiance data in which all-sky approach is implemented. Even with these coarse observation data usage in all-sky assimilation approach, noticeable positive impacts from all-sky microwave data on hurricane track forecasts were identified in GEOS-5 system. The motivation of this study is based on the dynamic thinning distance method developed in our all-sky framework to use of denser data in cloudy and precipitating regions due to relatively small spatial correlations of observation errors. To investigate the benefits of all-sky microwave radiance on hurricane forecasts, several hurricane cases selected between 2016-2017 are examined. The dynamic thinning distance method is utilized in our all-sky approach to understand the sources and mechanisms to explain the benefits of all-sky microwave radiance data from various microwave radiance sensors like Advanced Microwave Sounder Unit (AMSU-A), Microwave Humidity Sounder (MHS), and GMI on GEOS-5 analyses and forecasts of various hurricanes.

Kim, Min-Jeong↗

NASA NTRS2000

Interactive Soil Dust Aerosol Model in the GISS GCM: Sensitivity of the Soil Dust Cycle to Radiative Properties of Soil Dust Aerosols - Part 1

The sensitivity of the soil dust aerosol cycle to the radiative forcing by soil dust aerosols is studied. Four experiments with the NASA/GISS atmospheric general circulation model, which includes a soil dust aerosol model, are compared, all using a prescribed climatological sea surface temperature as lower boundary condition. In one experiment, dust is included as dynamic tracer only (without interacting with radiation), whereas dust interacts with radiation in the other simulations. Although the single scattering albedo of dust particles is prescribed to be globally uniform in the experiments with radiatively active dust, a different single scattering albedo is used in those experiments to estimate whether regional variations in dust optical properties, corresponding to variations in mineralogical composition among different source regions, are important for the soil dust cycle and the climate state. On a global scale, the radiative forcing by dust generally causes a reduction in the atmospheric dust load corresponding to a decreased dust source flux. That is, there is a negative feedback in the climate system due to the radiative effect of dust. The dust source flux and its changes were analyzed in more detail for the main dust source regions. This analysis shows that the reduction varies both with the season and with the single scattering albedo of the dust particles. By examining the correlation with the surface wind, it was found that the dust emission from the Saharan/Sahelian source region and from the Arabian peninsula, along with the sensitivity of the emission to the single scattering albedo of dust particles, are related to large scale circulation patterns, in particular to the trade winds during Northern Hemisphere winter and to the Indian monsoon circulation during summer. In the other regions, such relations to the large scale circulation were not found. There, the dependence of dust deflation to radiative forcing by dust particles is probably dominated by physical processes with short time scales. The experiments show that dust radiative forcing can lead to significant changes both in the soil dust cycle and in the climate state. To estimate dust concentration and radiative forcing by dust more accurately, dust size distributions and dust single scattering albedo in the model should be a function of the source region, because dust concentration and climate response to dust radiative forcing are sensitive to dust radiative parameters.

Perlwitz, Jan↗

NASA NTRS2016

Soil Moisture Active Passive Mission Mass Properties Optimization and Analysis

The Soil Moisture Active Passive (SMAP) mission creates global soil moisture measurements every 2-3 days by spinning a lightweight, ~6 meter diameter deployable mesh reflector. This represents the largest spinning antenna ever to be used on a NASA satellite. The paper discusses the mass properties challenges that were overcome in implementing the mission, including the definition of a combined imbalance term called the Effective Product of Inertia, the selection of an optimum Spun Instrument focal length and edge offset that fostered a reduced mass properties sensitivity, the inclusion of late game Spun Instrument configuration flexibility, the use of balance mass locations that leveraged the large moment arm provided by the reflector, and a subassembly measurement campaign that reduced mass properties uncertainties on testable components.

Hendry, Morgan L., IV↗

DOE OSTI2023

A High-Pressure Shock Tube Study of Hydrogen and Ammonia Addition to Natural Gas for Reduced Carbon Emissions in Power Generation Gas Turbines

Ignition delay times from undiluted mixtures of natural gas (NG)/H2/Air and NG/NH3/Air were measured using a high-pressure shock tube at the University of Central Florida. The combustion temperatures were experimentally tested between 1000-1500 K near a constant pressure of 25 bar. Mixtures were kept undiluted to replicate the same chemistry pathways seen in gas turbine combustion chambers. Recorded combustion pressures exceeded 200 bar due to the large energy release, hence why these were performed at the high-pressure shock tube facility. The data is compared to the predictions of the NUIGMech 1.1 mechanism for chemical kinetic model validation and refinement. An exceptional agreement was shown for stoichiometric conditions in all cases but strayed at lean and rich equivalence ratios, especially in the lower temperature regime of H2 addition and all temperature ranges of the baseline NG mixture. Hydrogen addition also decreased ignition delay times by nearly 90%, while NH3 fuel addition made no noticeable difference in ignition delay time. NG/NH3 exhibited similar chemistry to pure NG under the same conditions, which is shown in a sensitivity analysis, demonstrating hydrogen chemistry to be dominant in NG/H2 mixtures and hydrocarbon chemistry to be dominant in NG/NH3 mixtures. The reaction CH3 + O2 = CH3O + O is identified and suggested as a possible modification target to improve model performance. Increasing the robustness of chemical kinetic models via experimental validation will directly aid in designing next-generation combustion chambers for use in gas turbines, which in turn will greatly lower global emissions and reduce greenhouse effects.

Pierro, Michael↗

NASA NTRS1993

Climate Sensitivity Studies of the Greenland Ice Sheet Using Satellite AVHRR, SMMR, SSM/I and in Situ Data

The feasibility of using satellite data for climate research over the Greenland ice sheet is discussed. In particular, we demonstrate the usefulness of Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) and Global Area Coverage (GAC) data for narrow-band albedo retrieval. Our study supports the use of lower resolution AVHRR (GAC) data for process studies over most of the Greenland ice sheet. Based on LAC data time series analysis, we can resolve relative albedo changes on the order of 2-5%. In addition, we examine Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) passive microwave data for snow typing and other signals of climatological significance. Based on relationships between in situ measurements and horizontally polarized 19 and 37 GHz observations, wet snow regions are identified. The wet snow regions increase in aerial percentage from 9% of the total ice surface in June to a maximum of 26% in August 1990. Furthermore, the relationship between brightness temperatures and accumulation rates in the northeastern part of Greenland is described. We found a consistent increase in accumulation rate for the northeastern part of the ice sheet from 1981 to 1986.

Steffen, K.↗

NASA NTRS1984

A rotor optimization using regression analysis

The design and development of helicopter rotors is subject to the many design variables and their interactions that effect rotor operation. Until recently, selection of rotor design variables to achieve specified rotor operational qualities has been a costly, time consuming, repetitive task. For the past several years, Kaman Aerospace Corporation has successfully applied multiple linear regression analysis, coupled with optimization and sensitivity procedures, in the analytical design of rotor systems. It is concluded that approximating equations can be developed rapidly for a multiplicity of objective and constraint functions and optimizations can be performed in a rapid and cost effective manner; the number and/or range of design variables can be increased by expanding the data base and developing approximating functions to reflect the expanded design space; the order of the approximating equations can be expanded easily to improve correlation between analyzer results and the approximating equations; gradients of the approximating equations can be calculated easily and these gradients are smooth functions reducing the risk of numerical problems in the optimization; the use of approximating functions allows the problem to be started easily and rapidly from various initial designs to enhance the probability of finding a global optimum; and the approximating equations are independent of the analysis or optimization codes used.

Giansante, N.↗

NASA NTRS2020

Evaluation of adjoint-based observation impacts as a function of forecast length using an Observing System Simulation Experiment

Adjoints of numerical weather prediction models may be employed for Forecast Sensitivity to Observation (FSO) in order to monitor the contribution of ingested observation data on short-term forecast skill. However, the calculation of short-term forecast error is difficult due to the lack of a truly independent dataset for verification. In an Observing System Simulation Experiment framework, the Nature Run is able to provide a true and complete verification dataset and allows accurate evaluation of short term forecast errors. In this work, an OSSE developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office is used to explore the impact of observational data on forecasts in the 6 to 48 hour range. An adjoint of the Global Earth Observing System model is employed to compare the observation impacts estimated using both self-analysis verification and the true Nature Run verification. Self-analysis verification is found to inflate the estimated forecast error growth during the early forecast period, resulting in overestimations of observation impacts, particularly in the 6-12 hour forecast range. By 48 hours, the self-analysis verification estimates of forecast error and observation impacts more closely match the true values. The fraction of beneficial observations is also overinflated at short forecast times when self-analysis verification is used. The progression of impacts of an individual observation or data type depends on the character of the growth of the initial condition error that each observation affects.

numerical weather prediction↗