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At least 217 records · Page 12

Simulation of Turbine Tone Noise Generation Using a Turbomachinery Aerodynamics Solver

As turbofan engine bypass ratios continue to increase, the contribution of the turbine to the engine noise signature is receiving more attention. Understanding the relative importance of the various turbine noise generation mechanisms and the characteristics of the turbine acoustic transmission loss are essential ingredients in developing robust reduced-order models for predicting the turbine noise signature. A computationally based investigation has been undertaken to help guide the development of a turbine noise prediction capability that does not rely on empiricism. As proof-of-concept for this approach, two highly detailed numerical simulations of the unsteady flow field inside the first stage of a modern high-pressure turbine were carried out. The simulations were computed using TURBO, which is an unsteady Reynolds-Averaged Navier-Stokes code capable of multi-stage simulations. Spectral and modal analysis of the unsteady pressure data from the numerical simulation of the turbine stage show a circumferential modal distribution that is consistent with the Tyler-Sofrin rule. Within the high-pressure turbine, the interaction of velocity, pressure and temperature fluctuations with the downstream blade rows are all possible tone noise source mechanisms. We have taken the initial step in determining the source strength hierarchy by artificially reducing the level of temperature fluctuations in the turbine flowfield. This was accomplished by changing the vane cooling flow temperature in order to mitigate the vane thermal wake in the second of the two simulations. The results indicated that, despite a dramatic change in the vane cooling flow, the computed modal levels changed very little indicating that the contribution of temperature fluctuations to the overall pressure field is rather small compared with the viscous and potential field interaction mechanisms.

VanZante, Dale↗

Biomass Burning Emissions from Fire Remote Sensing

Knowledge of the emission source strengths of different (particulate and gaseous) atmospheric constituents is one of the principal ingredients upon which the modeling and forecasting of their distribution and impacts depend. Biomass burning emissions are complex and difficult to quantify. However, satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP), which has a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. In this presentation, we will show how the satellite measurement of FRP is facilitating the quantitative characterization of biomass burning and smoke emission rates, and the implications of this unique capability for improving our understanding of smoke impacts on air quality, weather, and climate. We will also discuss some of the challenges and uncertainties associated with satellite measurement of FRP and how they are being addressed.

Ichoku, Charles↗

Detailed Evaluation of MODIS Fire Radiative Power Measurements

Satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the MODIS sensors aboard the polar orbiting Terra and Aqua satellites, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary satellite. During the last few years, FRP has been gaining recognition as an important parameter for facilitating the development of various scientific studies relating to the quantitative characterization of biomass burning and their emissions. Therefore, we are conducting a detailed analysis of the FRP products from MODIS to characterize the uncertainties associated with them, such as those due to the MODIS bow-tie effects and other factors, in order to establish their error budget for use in scientific research and applications. In this presentation, we will show preliminary results of the MODIS FRP data analysis, including comparisons with airborne measurements.

Ichoku, Charles↗

Quantitative Evaluation of MODIS Fire Radiative Power Measurement for Global Smoke Emissions Assessment

Satellite remote sensing is providing us tremendous opportunities to measure the fire radiative energy (FRE) release rate or power (FRP) from open biomass burning, which affects many vegetated regions of the world on a seasonal basis. Knowledge of the biomass burning characteristics and emission source strengths of different (particulate and gaseous) smoke constituents is one of the principal ingredients upon which the assessment, modeling, and forecasting of their distribution and impacts depend. This knowledge can be gained through accurate measurement of FRP, which has been shown to have a direct relationship with the rates of biomass consumption and emissions of major smoke constituents. Over the last decade or so, FRP has been routinely measured from space by both the MODIS sensors aboard the polar orbiting Terra and Aqua satellites, and the SEVIRI sensor aboard the Meteosat Second Generation (MSG) geostationary satellite. During the last few years, FRP has steadily gained increasing recognition as an important parameter for facilitating the development of various scientific studies and applications relating to the quantitative characterization of biomass burning and their emissions. To establish the scientific integrity of the FRP as a stable quantity that can be measured consistently across a variety of sensors and platforms, with the potential of being utilized to develop a unified long-term climate data record of fire activity and impacts, it needs to be thoroughly evaluated, calibrated, and validated. Therefore, we are conducting a detailed analysis of the FRP products from MODIS to evaluate the uncertainties associated with them, such as those due to the effects of satellite variable observation geometry and other factors, in order to establish their error budget for use in diverse scientific research and applications. In this presentation, we will show recent results of the MODIS FRP uncertainty analysis and error mitigation solutions, and demonstrate their implications for biomass burning emissions assessment.

Ichoku, Charles↗

Informing Aerosol Transport Models With Satellite Multi-Angle Aerosol Measurements

As the aerosol products from the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) mature, we are placing greater focus on ways of using the aerosol amount and type data products, and aerosol plume heights, to constrain aerosol transport models. We have demonstrated the ability to map aerosol air-mass-types regionally, and have identified product upgrades required to apply them globally, including the need for a quality flag indicating the aerosol type information content, that varies depending upon retrieval conditions. We have shown that MISR aerosol type can distinguish smoke from dust, volcanic ash from sulfate and water particles, and can identify qualitative differences in mixtures of smoke, dust, and pollution aerosol components in urban settings. We demonstrated the use of stereo imaging to map smoke, dust, and volcanic effluent plume injection height, and the combination of MISR and MODIS aerosol optical depth maps to constrain wildfire smoke source strength. This talk will briefly highlight where we stand on these application, with emphasis on the steps we are taking toward applying the capabilities toward constraining aerosol transport models, planet-wide.

Limbacher, J.↗

The Importance of Earth as a Meteor Detector

In order to understand the complex meteoroid environment that threatens spacecraft in near Earth space, ground based observational techniques provide us with an effective option for evaluating the important parameters of flux, speed, mass, density and directionality. While no observational method (in ]situ or ground based detectors) provides bias free measurements of direct quantities, there are several benefits to using the Earth as a detector for calibrating meteoroid models that extend to the inner Solar System and beyond Earth fs orbit. The Earth constantly interacts with meteoritic particles from comets and asteroids as they evolve from their parent objects through dynamical processes. Modeling these dynamical processes with a physics ]based approach can help reveal the causes of observational features but developing those models involves constraining sequences of poorly defined parameters. These parameters must be tuned to a particular detector that offers direct or indirect measurements of mass, density, flux and speed - the quantities used in evaluating penetration risk. The following topics will be discussed: a) Consistency between ground based and in.situ measurements of flux in Earth orbit. b) Consistency between radar and electro.optical speed determinations and agreement of these with dynamical studies. c) The fact that there are six sporadic sources which cannot be determined by integrated line of sight emissivity: Observations using IRAS or COBE cannot give you all important directionality needed for risk evaluations. d) The large collecting area of the Earth s atmosphere compared to in.situ detectors gives better number statistics in the threat regime. The NASA Meteoroid Environment Office utilizes ground based radar and electro.optical measurements to calibrate the Meteoroid Engineering Model (MEM). As MEM is an engineering design model our main emphasis is on threat size particle, speed, flux and directionality. However, MEM has acknowledged limitations particularly with regard to source strength as a function of mass and work is proceeding with improved distributions that will rectify many of these shortcomings.

Koehler, Heather↗

Photosynthesis-dependent Isoprene Emission from Leaf to Planet in a Global Carbon-chemistry-climate Model

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the FarquharBallBerry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50 of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 6496) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr1 that increases by 30 in the artificial absence of plant water stress and by 55 for potential natural vegetation.

photosynthesis↗

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Dahl, Milo D.↗

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

A code for predicting supersonic jet broadband shock-associated noise was assessed us- ing a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify de ciencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the mea- sured data, a sensitivity analysis of the model parameters with emphasis on the de nition of the convection velocity parameter, and a least-squares t of the predicted to the mea- sured shock-associated noise component spectra, resulted in a new de nition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Dahl, Milo D.↗

High Ice Water Content at Low Radar Reflectivity near Deep Convection: Part II. Evaluation of Microphysical Pathways in Updraft Parcel Simulations

The aeronautics industry has established that a threat to aircraft is posed by atmospheric conditions of substantial ice water content (IWC) where equivalent radar reflectivity (Ze) does not exceed 20-30 dBZ and supercooled water is not present; these conditions are encountered almost exclusively in the vicinity of deep convection. Part 1 (Fridlind et al., 2015) of this two-part study presents in situ measurements of such conditions sampled by Airbus in three tropical regions, commonly near 11 km and -43 C, and concludes that the measured ice particle size distributions are broadly consistent with past literature with profiling radar measurements of Z(sub e) and mean Doppler velocity obtained within monsoonal deep convection in one of the regions sampled. In all three regions, the Airbus measurements generally indicate variable IWC that often exceeds 2 gm (exp -3) with relatively uniform mass median area-equivalent diameter (MMD(sub eq) of 200-300 micrometers. Here we use a parcel model with size-resolved microphysics to investigate microphysical pathways that could lead to such conditions. Our simulations indicate that homogeneous freezing of water drops produces a much smaller ice MMD(sub eq) than observed, and occurs only in the absence of hydrometeor gravitational collection for the conditions considered. Development of a mass mode of ice aloft that overlaps with the measurements requires a substantial source of small ice particles at temperatures of about -10 C or warmer, which subsequently grow from water vapor. One conceivable source in our simulation framework is Hallett-Mossop ice production; another is abundant concentrations of heterogeneous ice freezing nuclei acting together with copious shattering of water drops upon freezing. Regardless of the production mechanism, the dominant mass modal diameter of vapor-grown ice is reduced as the ice-multiplication source strength increases and as competition for water vapor increases. Both mass and modal diameter are reduced by entrainment and by increasing aerosol concentrations. Weaker updrafts lead to greater mass and larger modal diameters of vapor-grown ice, the opposite of expectations regarding lofting of larger ice particles in stronger updrafts. While stronger updrafts do loft more dense ice particles produced primarily by raindrop freezing, we find that weaker updrafts allow the warm rain process to reduce competition for diffusional growth of the less dense ice expected to persist in convective outflow.

Reflectivity↗

On Predicting Transient Pressure in Vacuum Systems Featuring Getter Materials

Getter materials have been used to reduce pressure or partial pressures in a variety of vacuum applications ranging from vacuum tubes to space flight science instruments. Testing of getter materials has tended to emphasize the capacity of candidate materials to collect specific gas species in sufficient quantities to size them in these applications. When determining a getter material’s capacity, it is typically subjected to enough excess target gas to ensure it sorbs as quickly as possible. However, when both the gas source strength and the getter’s sorption rate exhibit transient decay behavior, such data is not sufficient to predict the targeted species’ partial pressure within a vacuum system as a function of time.

M. S. Woronowicz↗

On Predicting Transient Pressure in Vacuum Systems Featuring Getter Materials

Getter materials have been used to reduce pressure or partial pressures in a variety of vacuum applications ranging from vacuum tubes to space flight science instruments. Testing of getter materials has tended to emphasize the capacity of candidate materials to collect specific gas species in sufficient quantities to size them in these applications. When determining a getter material’s capacity, it is typically subjected to enough excess target gas to ensure it sorbs as quickly as possible. However, when both the gas source strength and the getter’s sorption rate exhibit transient decay behavior, such data is not sufficient to predict the targeted species’ partial pressure within a vacuum system as a function of time.

M. S. Woronowicz↗

On Predicting Transient Pressure in Vacuum Systems Featuring Getter Materials

Getter materials have been used to reduce pressure or partial pressures in a variety of vacuum applications ranging from vacuum tubes to space flight science instruments. Testing of getter materials has tended to emphasize the capacity of candidate materials to collect specific gas species in sufficient quantities to size them in these applications. When determining a getter material’s capacity, it is typically subjected to enough excess target gas to ensure it sorbs as quickly as possible. However, when both the gas source strength and the getter’s sorption rate exhibit transient decay behavior, such data is not sufficient to predict the targeted species’ partial pressure within a vacuum system as a function of time.

Michael Woronowicz↗

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collected under structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore, their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distance to the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensemble of trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fitting observed in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inverse physical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of the source strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations of underlying regression methods.

Rao, Nageswara↗

Sound transmission in ducts containing nearly choked flows

The nonlinear theory previously developed by the authors (1977, 1978) is used to obtain numerical results for sound transmission through a nearly choked throat in a variable-area duct. Parametric studies are performed for different source locations, strengths and frequencies. It is shown that the nonlinear interactions in the throat region generate superharmonics of the fundamental (source) frequency throughout the duct. The amplitudes of these superharmonics increase as the source parameters (frequency and strength) are increased toward values leading to acoustic shocks. For a downstream source, superharmonics carry about 20% of the total acoustic power as shocking conditions are approached. For the source strength levels and frequencies considered, streaming effects are negligible.

Callegari, A. J.↗

Modulation of polar auxin transport identifies the molecular determinants of source–sink carbon relationships and sink strength in poplar

Abstract Source-to-sink carbon (C) allocation driven by the sink strength, i.e., the ability of a sink organ to import C, plays a central role in tissue growth and biomass productivity. However, molecular drivers of sink strength have not been thoroughly characterized in trees. Auxin, as a major plant phytohormone, regulates the mobilization of photoassimilates in source tissues and elevates the translocation of carbohydrates toward sink organs, including roots. In this study, we used an ‘auxin-stimulated carbon sink’ approach to understand the molecular processes involved in the long-distance source–sink C allocation in poplar. Poplar cuttings were foliar sprayed with polar auxin transport modulators, including auxin enhancers (AE) (i.e., IBA and IAA) and auxin inhibitor (AI) (i.e., NPA), followed by a comprehensive analysis of leaf, stem and root tissues using biomass evaluation, phenotyping, C isotope labeling, metabolomics and transcriptomics approaches. Auxin modulators altered root dry weight and branching pattern, and AE increased photosynthetically fixed C allocation from leaf to root tissues. The transcriptome analysis identified highly expressed genes in root tissue under AE condition including transcripts encoding polygalacturonase and β-amylase that could increase the sink size and activity. Metabolic analyses showed a shift in overall metabolism including an altered relative abundance levels of galactinol, and an opposite trend in citrate levels in root tissue under AE and AI conditions. In conclusion, we postulate a model suggesting that the source–sink C relationships in poplar could be fueled by mobile sugar alcohols, starch metabolism-derived sugars and TCA-cycle intermediates as key molecular drivers of sink strength.

59 BASIC BIOLOGICAL SCIENCES↗

Contextually aware roadside radiation measurement testbed

Here we demonstrate a contextually aware multimodal roadside radiation measurement detection testbed for traffic monitoring applications in nuclear nonproliferation. Many variables in traffic such as vehicle or cargo size, mass, speed, shape, and distance of closest approach can have significant impacts on the radiation measured from a vehicle-transported radiation source. These factors can lead to uncertainties in the analysis of the radiation source, especially for lower-strength radiation sources of interest. Our testbed, known as the Multimodal Measurement System (MMS) uses non-radiation sensors including magnetometers, geophones, radiofrequency receivers, cameras, and LiDAR to extract contextual information about vehicles passing by the system. These contextual data can then be fused with data from radiation measurements to increase the system’s sensitivity and accuracy in nuclear threat detection applications. This work describes the instrumentation of the MMS and its data acquisition pipeline. Furthermore, we describe the pre-analysis performed on the raw multimodal data streams for data fusion, and the high-level machine learning analyses for detection and characterization. The variety of sensors within the MMS provides a valuable testbed that can be used to identify the combinations of contextual sensors that provide the greatest improvements to radiation source detection and characterization within the restrictions for various proliferation detection applications. The MMS is also modular so that additional combinations of sensors can be explored in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗