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At least 1,513 records · Page 84

Active Aeroelastic Wing Aerodynamic Model Development and Validation for a Modified F/A-18A Airplane

A new aerodynamic model has been developed and validated for a modified F/A-18A airplane used for the Active Aeroelastic Wing (AAW) research program. The goal of the program was to demonstrate the advantages of using the inherent flexibility of an aircraft to enhance its performance. The research airplane was an F/A-18A with wings modified to reduce stiffness and a new control system to increase control authority. There have been two flight phases. Data gathered from the first flight phase were used to create the new aerodynamic model. A maximum-likelihood output-error parameter estimation technique was used to obtain stability and control derivatives. The derivatives were incorporated into the National Aeronautics and Space Administration F-18 simulation, validated, and used to develop new AAW control laws. The second phase of flights was used to evaluate the handling qualities of the AAW airplane and the control law design process, and to further test the accuracy of the new model. The flight test envelope covered Mach numbers between 0.85 and 1.30 and dynamic pressures from 600 to 1250 pound-force per square foot. The results presented in this report demonstrate that a thorough parameter identification analysis can be used to improve upon models that were developed using other means. This report describes the parameter estimation technique used, details the validation techniques, discusses differences between previously existing F/A-18 models, and presents results from the second phase of research flights.

Cumming, Stephen B.↗

Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new-generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach.While the new algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarsemodes,while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single-scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10-30% in the refractive index, and 10-40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part study.

aerosol retrieval algorithm↗

Extensive analysis of reconstruction algorithms for DESI 2024 baryon acoustic oscillations

Reconstruction of the baryon acoustic oscillation (BAO) signal has been a standard procedure in BAO analyses over the past decade and has helped to improve the BAO parameter precision by a factor of ∼2 on average. The Dark Energy Spectroscopic Instrument (DESI) BAO analysis for the first year (DR1) data uses the “standard” reconstruction framework, in which the displacement field is estimated from the observed density field by solving the linearized continuity equation in redshift space, and galaxy and random positions are shifted in order to partially remove non-linearities. There are several approaches to solving for the displacement field in real survey data, including the multigrid (MG), iterative Fast Fourier Transform (iFFT), and iterative Fast Fourier Transform particle (iFFTP) algorithms. In this work, we analyze these algorithms and compare them with various metrics including two-point statistics and the displacement itself using realistic DESI mocks. We focus on three representative DESI samples, the emission line galaxies (ELG), quasars (QSO), and the bright galaxy sample (BGS), which cover the extreme redshifts and number densities, and potential wide-angle effects. We conclude that the MG and iFFT algorithms agree within 0.4% in post-reconstruction power spectrum on BAO scales with the RecSym convention, which does not remove large-scale redshift space distortions (RSDs), in all three tracers. The RecSym convention appears to be less sensitive to displacement errors than the RecIso convention, which attempts to remove large-scale RSDs. However, iFFTP deviates from the first two; thus, we recommend against using iFFTP without further development. In addition, we provide the optimal settings for reconstruction for five years of DESI observation. The analyses presented in this work pave the way for DESI DR1 analysis as well as future BAO analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

Mathematical analysis study for radar data processing and enchancement. Part 2: Modeling of propagation path errors

A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altitude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This report is in two parts. This is part 2, a discussion of the modeling of propagation path errors.

James, R.↗

Troughs on Martian Ice Sheets: Analysis of Their Closure and Mass Balance

At the Copenhagen workshop on Martian polar processes, Ralf Greve commented that the flow regime surrounding scarps and troughs of the Martian polar ice sheets cannot be modeled using traditional "plan view" ice-sheet models. Such models are inadequate because they typically use reduced equations that embody certain simplifications applicable only to terrestrial ice sheets where the upper ice sheet surface is smooth. In response to this suggestion, we have constructed a 2-dimensional, time dependent "side view" (two spatial dimensions: one horizontal, one vertical) model of scarp closure that is designed to overcome the difficulties described by Greve. The purpose of the model is to evaluate the scales of stress variation and styles of flow closure so as to estimate errors that may be encountered by "plan view" models. We show that there may be avenues whereby the complications associated with scarp closure can be overcome in "plan view" models through appropriate parameterizations of 3-dimensional effects. Following this, we apply the flow model to simulate the evolution of a typical scarp on the North Polar Cap of Mars. Our simulations investigate: (a) the role of "radiation trapping" (see our companion abstract) in creating and maintaining "spiral-like" scarps on the ice sheet, (b) the consequences of different flowlaws and ice compositions on scarp evolution and, in particular, scarp age, and (c) the role of dust and debris in scarp evolution.

Fountain, A.↗

Instrumentation and Performance Analysis Plans for the HIFiRE Flight 2 Experiment

Supersonic combustion performance of a bi-component gaseous hydrocarbon fuel mixture is one of the primary aspects under investigation in the HIFiRE Flight 2 experiment. In-flight instrumentation and post-test analyses will be two key elements used to determine the combustion performance. Pre-flight computational fluid dynamics (CFD) analyses provide valuable information that can be used to optimize the placement of a constrained set of wall pressure instrumentation in the experiment. The simulations also allow pre-flight assessments of performance sensitivities leading to estimates of overall uncertainty in the determination of combustion efficiency. Based on the pre-flight CFD results, 128 wall pressure sensors have been located throughout the isolator/combustor flowpath to minimize the error in determining the wall pressure force at Mach 8 flight conditions. Also, sensitivity analyses show that mass capture and combustor exit stream thrust are the two primary contributors to uncertainty in combustion efficiency.

Gruber, Mark↗

An Online Joint Optimization–Estimation Architecture for Distribution Networks

Here in this article, we propose an optimal joint optimization-estimation architecture for distribution networks, which jointly solves the optimal power flow (OPF) problem and static state estimation (SE) problem through an online gradient-based feedback algorithm. The main objective is to enable a fast and timely interaction between the OPF decisions and state estimators with limited sensor measurements. First, convergence and optimality of the proposed algorithm are analytically established. Then, the proposed gradient-based algorithm is modified by introducing statistical information of the inherent estimation and linearization errors for an improved and robust performance of the online OPF decisions. Overall, the proposed method eliminates the traditional separation of operation and monitoring, where optimization and estimation usually operate at distinct layers and different time scales. Hence, it enables a computationally affordable, efficient, and robust online operational framework for distribution networks under time-varying settings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Three dimensional cluster analysis for atom probe tomography using Ripley’s K-function and machine learning

The size and structure of spatial molecular and atomic clustering can significantly impact material properties and is therefore important to accurately quantify. Ripley’s K-function (K(r)), a measure of spatial correlation, can be used to perform such quantification when the material system of interest can be represented as a marked point pattern. This work demonstrates how machine learning models based on K (r)-derived metrics can accurately estimate cluster size and intra-cluster density in simulated three dimensional (3D) point patterns containing spherical clusters of varying size; over 90% of model estimates for cluster size and intra-cluster density fall within 11% and 18% error of the true values, respectively. These K (r)-based size and density estimates are then applied to an experimental APT reconstruction to characterize MgZn clusters in a 7000 series aluminum alloy. Here we find that the estimates are more accurate, consistent, and robust to user interaction than estimates from the popular maximum separation algorithm. Using K (r) and machine learning to measure clustering is an accurate and repeatable way to quantify this important material attribute.

36 MATERIALS SCIENCE↗

Consistent lensing and clustering in a low- S 8 Universe with BOSS, DES Year 3, HSC Year 1, and KiDS-1000

ABSTRACT We evaluate the consistency between lensing and clustering based on measurements from Baryon Oscillation Spectroscopic Survey combined with galaxy–galaxy lensing from Dark Energy Survey (DES) Year 3, Hyper Suprime-Cam Subaru Strategic Program (HSC) Year 1, and Kilo-Degree Survey (KiDS)-1000. We find good agreement between these lensing data sets. We model the observations using the Dark Emulator and fit the data at two fixed cosmologies: Planck (S8 = 0.83), and a Lensing cosmology (S8 = 0.76). For a joint analysis limited to large scales, we find that both cosmologies provide an acceptable fit to the data. Full utilization of the higher signal-to-noise small-scale measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic inconsistency parameter for each redshift bin, A, that decouples the lensing and clustering. With a wide range of scales, we find different results for the consistency between the two cosmologies. Limiting the analysis to the bins for which the impact of the lens sample selection is expected to be minimal, for the Lensing cosmology, the measurements are consistent with A = 1; A = 0.91 ± 0.04 (A = 0.97 ± 0.06) using DES+KiDS (HSC). For the Planck case, we find a discrepancy: A = 0.79 ± 0.03 (A = 0.84 ± 0.05) using DES+KiDS (HSC). We demonstrate that a kinematic Sunyaev–Zeldovich-based estimate for baryonic effects alleviates some of the discrepancy in the Planck cosmology. This analysis demonstrates the statistical power of small-scale measurements; however, caution is still warranted given modelling uncertainties and foreground sample selection effects.

79 ASTRONOMY AND ASTROPHYSICS↗

An Overview of Wind Energy Production Prediction Bias, Losses, and Uncertainties

The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the industry is recording near-zero average energy prediction bias. Herein, we present an overview of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including the improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight the opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty, and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary on how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the manuscript.

literature review↗

Measurement uncertainty and feasibility study of a flush airdata system for a hypersonic flight experiment

Presented is a feasibility and error analysis for a hypersonic flush airdata system on a hypersonic flight experiment (HYFLITE). HYFLITE heating loads make intrusive airdata measurement impractical. Although this analysis is specifically for the HYFLITE vehicle and trajectory, the problems analyzed are generally applicable to hypersonic vehicles. A layout of the flush-port matrix is shown. Surface pressures are related airdata parameters using a simple aerodynamic model. The model is linearized using small perturbations and inverted using nonlinear least-squares. Effects of various error sources on the overall uncertainty are evaluated using an error simulation. Error sources modeled include boundarylayer/viscous interactions, pneumatic lag, thermal transpiration in the sensor pressure tubing, misalignment in the matrix layout, thermal warping of the vehicle nose, sampling resolution, and transducer error. Using simulated pressure data for input to the estimation algorithm, effects caused by various error sources are analyzed by comparing estimator outputs with the original trajectory. To obtain ensemble averages the simulation is run repeatedly and output statistics are compiled. Output errors resulting from the various error sources are presented as a function of Mach number. Final uncertainties with all modeled error sources included are presented as a function of Mach number.

Whitmore, Stephen A.↗

The alpha Centauri Line of Sight: D/H Ratio, Physical Properties of Local Interstellar Gas, and Measurement of Heated Hydrogen (The 'Hydrogen Wall') Near the Heliopause

We analyze high-resolution spectra of the nearby (1.34 pc) stars alpha Cen A (G2 V) and alpha Cen B (K1 V), which were obtained with the Goddard High Resolution Spectrograph on the Hubble Space Telescope. The observations consist of echelle spectra of the Mg II 2800 A and Fe II 2599 A resonance lines and the Lyman-alpha lines of hydrogen and deuterium. The interstellar gas has a velocity (v = - 18.0 +/- 0.2 km/s) consistent with the local flow vector proposed for this line of sight by Lailement & Berlin (1992). The temperature and nonthermal velocity inferred from the Fe II, Mg II, and D I line profiles are T = 5400 +/- 500 K and xi = 1.20 +/- 0.25 km/s, respectively. However, single-component fits to the H I Lyman-alpha lines yield a Doppler parameter (b(sub HI) = 11.80 km/s) that implies a significantly warmer temperature of 8350 K, and the velocity of the H I absorption (v = - 15.8 +/- 0.2 km/s) is redshifted by about 2.2 km/s with respect to the Fe II, Mg II, and D I lines. The one-component model of the interstellar gas suggests natural logarithm N base HI = 18.03 +/- 0.01 and D/H = (5.7 +/- 0.2) x 10(exp -6) . These parameters lead to a good fit to the observed spectra, but this model does not explain the higher temperature and redshift of H I relative to the other interstellar lines. The most sensible way to resolve the discrepancy between H(I) and the other lines is to add a second absorption component to the H(I) lines. This second component is hotter (T approx. equals 30,000 K), is redshifted relative to the primary component by 2-4 km/s, and has a column density too low to be detected in the Fe(II), Mg(II), and D(I) lines. We propose that the gas responsible for this component is located near the heliopause, consisting of the heated H I gas from the interstellar medium that is compressed by the solar wind. This so-called 'hydrogen wall' is predicted by recent multifluid gasdynamical models of the interstellar gas and solar wind interaction. Our data provide the first measurements of the temperature and column density of H(I) in the hydrogen wall. After considering the effects that a corresponding hydrogen wall around alpha Cen would have on our analysis, our best estimates for the parameters of the solar hydrogen wall are natural log N(sup (2))(H(I)) = 14.74 +/- 0.24, b(sup (2))(H(I)) = 21.9 +/- 1.7 km/s (corresponding to T = 29,000 +/- 5000 K), and v(sup (2))(H(I)) greater than -16km/s. Unfortunately, the existence of this heated H(I) reduces our ability to compute the H(I) column density of the interstellar medium accurately because, with slight alterations to our assumed stellar Lyman-alpha profiles, we discovered that acceptable two-component fits also exist with natural log N(H(I))approx. 17.6. We, therefore, quote large error bars for the H I column density along the alpha Cen line of sight, natural log N(H(I)) = 17.80 +/- 0.30. For this range in N(H(I)), n(H(I)) = 0.15 /cu.cm (+/- a factor of 2) and D/H = (0.5-1.9) x 10(exp -5). This is the first direct measurement of the H(I) density in a local cloud and allows us to predict the distance from the Sun to the edge of the local cloud along various lines of sight. This range in D/H is consistent with the value D/H = 1.6 x 10(exp -5) previously derived for the Capella and Procyon lines of sight. We cannot tell whether D/H ratio varies or is constant in the local interstellar medium, but we do find that the D(I)/Mg(II) ratio for the alpha Cen line of sight is about 4 times smaller than for the Capella and Procyon lines of sight. Therefore, either D/H or the Mg depletion varies significantly over distance scales of only a few parsecs.

Linsky, Jeffrey L.↗

Consistency of Post-Newtonian Waveforms with Numerical Relativity

General relativity predicts the gravitational radiation signatures of mergers of compact binaries,such as coalescing binary black hole systems. Derivations of waveform predictions for such systems are required for optimal scientific analysis of observational gravitational wave data, and have so far been achieved primarily with the aid of the post-Newtonian (PN) approximation. The quaIity of this treatment is unclear, however, for the important late inspiral portion. We derive late-inspiral wave forms via a complementary approach, direct numerical simulation of Einstein's equations, which has recently matured sufficiently for such applications. We compare waveform phasing from simulations covering the last approximately 14 cycles of gravitational radiation from an equal-mass binary system of nonspinning black holes with corresponding 3PN and 3.5PN waveforms. We find phasing agreement consistent with internal error estimates based in either approach, at the level of one radian over approximately 10 cycles. The result suggests that PN waveforms for this system are effective roughly until the system reaches its last stable orbit just prior to the final merger.

Baker, John G.↗

Consistency of Post-Newtonian Waveforms with Numerical Relativity

General relativity predicts the gravitational radiation signatures of mergers of compact binaries, such as coalescing binary black hole systems. Derivations of waveform predictions for such systems are required for optimal scientific analysis of observational gravitational wave data, and have so far been achieved primarily with the aid of the post-Newtonian (PN) approximation. The quality of this treatment is unclear, however, for the important late inspiral portion. We derive late-inspiral waveforms via a complementary approach, direct numerical simulation of Einstein's equations, which has recently matured sufficiently for such applications. We compare waveform phasing from simulations covering the last approximately 14 cycles of gravitational radiation from an equal-mass binary system of nonspinning black holes with the corresponding 3PN and 3.5PN orbital phasing. We find agreement consistent with internal error estimates based on either approach at the level of one radian over approximately 10 cycles. The result suggests that PN waveforms for this system are effective roughly until the system reaches its last stable orbit just prior to the final merger/

Baker, John G.↗

Attribution of Flux Partitioning Variations Between Land Surface Models over the Continental U.S.

Accurate quantification of the terrestrial evapotranspiration (ET) components of plant transpiration (T), soil evaporation (E) and evaporation of the intercepted water (I) is necessary for improving our understanding of the links between the carbon and water cycles. Recent studies have noted that, among the modeled estimates, large disagreements exist in the relative contributions of T, E and I to the total ET. As these models are often used in data assimilation environments for incorporating and extending ET relevant remote sensing measurements, understanding the sources of inter-model differences in ET components is also necessary for improving the utilization of such remote sensing measurements. This study quantifies the contributions of two key factors explaining inter-model disagreements to the uncertainty in total ET: (1) contribution of the local partitioning and (2) regional distribution of ET. The analysis is conducted by using outputs from a suite of land surface models in the North American Land Data Assimilation System (NLDAS) configuration. For most of these models, transpiration is the dominant component of the ET partition. The results indicate that the uncertainty in local partitioning dominates the inter-model spread in modeled soil evaporation E. The inter-model differences in T are dominated by the uncertainty in the distribution of ET over the Eastern U.S. and the local partitioning uncertainty in the Western U.S. The results also indicate that uncertainty in the T estimates is the primary driver of total ET errors. Over the majority of the U.S., the contribution of the two factors of uncertainty to the overall uncertainty is non-trivial.

uncertainty↗

Attribution of Flux Partitioning Variations Between Land Surface Models Over the Continental U.S.

Accurate quantification of the terrestrial evapotranspiration (ET) components of plant transpiration (T), soil evaporation (E) and evaporation of the intercepted water (I) is necessary for improving our understanding of the links between the carbon and water cycles. Recent studies have noted that, among the modeled estimates, large disagreements exist in the relative contributions of T, E and I to the total ET. As these models are often used in data assimilation environments for incorporating and extending ET relevant remote sensing measurements, understanding the sources of inter-model differences in ET components is also necessary for improving the utilization of such remote sensing measurements. This study quantifies the contributions of two key factors explaining inter-model disagreements to the uncertainty in total ET: (1) contribution of the local partitioning and (2) regional distribution of ET. The analysis is conducted by using outputs from a suite of land surface models in the North American Land Data Assimilation System (NLDAS) configuration. For most of these models, transpiration is the dominant component of the ET partition. The results indicate that the uncertainty in local partitioning dominates the inter-model spread in modeled soil evaporation E. The inter-model differences in T are dominated by the uncertainty in the distribution of ET over the Eastern U.S. and the local partitioning uncertainty in the Western U.S. The results also indicate that uncertainty in the T estimates is the primary driver of total ET errors. Over the majority of the U.S., the contribution of the two factors of uncertainty to the overall uncertainty is non-trivial.

evapotranspiration partitioning; transpiration; so↗

Estimating Controller Intervention Probabilities for Optimized Profile Descent Arrivals

Simulations of arrival traffic at Dallas/Fort-Worth and Denver airports were conducted to evaluate incorporating scheduling and separation constraints into advisories that define continuous descent approaches. The goal was to reduce the number of controller interventions required to ensure flights maintain minimum separation distances of 5 nmi horizontally and 1000 ft vertically. It was shown that simply incorporating arrival meter fix crossing-time constraints into the advisory generation could eliminate over half of the all predicted separation violations and more than 80% of the predicted violations between two arrival flights. Predicted separation violations between arrivals and non-arrivals were 32% of all predicted separation violations at Denver and 41% at Dallas/Fort-Worth. A probabilistic analysis of meter fix crossing-time errors is included which shows that some controller interventions will still be required even when the predicted crossing-times of the advisories are set to add a 1 or 2 nmi buffer above the minimum in-trail separation of 5 nmi. The 2 nmi buffer was shown to increase average flight delays by up to 30 sec when compared to the 1 nmi buffer, but it only resulted in a maximum decrease in average arrival throughput of one flight per hour.

continous descent arrivals↗

GRAVSAT error analysis by means of global spectral analyses of the marine geoid from SEASAT altimeter data

The geographical variability of short wavelength geoid power spectra (geoid roughness), was mapped for the world's oceans between latitudes 72 deg N and 72 deg S. A spectral analysis of SEASAT altimeter data, reduced to sea surface heights, was performed at 2 minute intervals for 15 consecutive days of the 3-day repeat orbit. The geoid roughness represented by these spectra for wavelengths shorter than about 220 km is separated from the total sea height variance and is displayed in the form of a global contour map. The global average geoid roughness is 32 cm RMS, varying from a high in excess of 2 m RMS near deep ocean trenches to a low of 2 cm RMS in the southeast Pacific near the East Pacific Rise. This average value agrees well with previous estimates based on gravimetry and GEOS-3 altimetry. In general, the smoothest areas in the marine geoid overlie relatively young seafloor adjacent mid-ocean spreading centers, where even short-wavelength topographic variations tend to be isostatically compensated.

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