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At least 757 records · Page 42

Numerical study of the effects of icing on viscous flow over wings

The progress made during the period 1 Jan. - 30 Jun. 1993 on the numerical study of the effects of icing on viscous flow over wings is summarized. The tasks performed were development of 3-D boundary layer methods for accurate estimates of the velocity field and surface heat transfer rates in the vicinity of the leading edge ice shape; studies of the effects of icing on 3-D highlift system performance; and continued improvement and validation of the 3-D Navier-Stokes solver. Results are discussed.

Sankar, L. N.↗

Mapping Environmental Contaminants at Ray Mine, AZ

Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) data was collected over Ray Mine as part of a demonstration project for the Environmental Protection Agency (EPA) through the Advanced Measurement Initiative (AMI). The overall goal of AMI is to accelerate adoption and application of advanced measurement technologies for cost effective environmental monitoring. The site was selected to demonstrate the benefit to EPA in using advanced remote sensing technologies for the detection of environmental contaminants due to the mineral extraction industry. The role of the Jet Propulsion Laboratory in this pilot study is to provide data as well as performing calibration, data analysis, and validation of the AVIRIS results. EPA is also interested in developing protocols that use commercial software to perform such work on other high priority EPA sites. Reflectance retrieval was performed using outputs generated by the MODTRAN radiative transfer model and field spectra collected for the purpose of calibration. We are presenting advanced applications of the ENVI software package using n-Dimensional Partial Unmixing to identify image-derived endmembers that best match target materials reference spectra from multiple spectral libraries. Upon identification of the image endmembers the Mixture Tuned Match Filter algorithm was applied to map the endmembers within each scene. Using this technique it was possible to map four different mineral classes that are associated with mine generated acid waste.

McCubbin, Ian↗

Characterization of Unsteady Flow Structures Near Leading-Edge Slat: PIV Measurements - Part 1

A comprehensive computational and experimental study has been performed at the NASA Langley Research Center as part of the Quiet Aircraft Technology (QAT) Program to investigate the unsteady flow near a leading-edge slat of a two-dimensional, high-lift system. This paper focuses on the experimental effort conducted in the NASA Langley Basic Aerodynamics Research Tunnel (BART) where Particle Image Velocimetry (PIV) data was acquired in the slat cove and at the slat trailing edge of a three-element, high-lift model at 4, 6, and 8 degrees angle of attack and a freestream Mach Number of 0.17. Instantaneous velocities obtained from PIV images are used to obtain mean and fluctuating components of velocity and vorticity. The data show the recirculation in the cove, reattachment of the shear layer on the slat lower surface, and discrete vortical structures within the shear layer emanating from the slat cusp and slat trailing edge. Detailed measurements are used to examine the shear layer formation at the slat cusp, vortex shedding at the slat trailing edge, and convection of vortical structures through the slat gap. Selected results are discussed and compared with unsteady, Reynolds-Averaged Navier-Stokes (URANS) computations for the same configuration in a companion paper by Khorrami, Choudhari, and Jenkins (2004). The experimental dataset provides essential flow-field information for the validation of near-field inputs to noise prediction tools.

Jenkins, Luther N.↗

HIWRAP Radar Development for High-Altitude Operation on the NASA Global Hawk and ER-2

The NASA High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) is a solid-state transmitter-based, dual-frequency (Ka- and Ku-band), dual-beam (30 degree and 40 degree incidence angle), conical scan Doppler radar system, designed for operation on the NASA high-altitude (20 km) aircrafts, such as the Global Hawk Unmanned Aerial System (UAS). Supported by the NASA Instrument Incubator Program (IIP), HIWRAP was developed to provide high spatial and temporal resolution 3D wind and reflectivity data for the research of tropical cyclone and severe storms. With the simultaneous measurements at both Ku- and Ka-band two different incidence angles, HIWRAP is capable of imaging Doppler winds and volume backscattering from clouds and precipitation associated with tropical storms. In addition, HIWRAP is able to obtain ocean surface backscatter measurements for surface wind retrieval using an approach similar to QuikScat. There are three key technology advances for HIWRAP. Firstly, a compact dual-frequency, dual-beam conical scan antenna system was designed to fit the tight size and weight constraints of the aircraft platform. Secondly, The use of solid state transmitters along with a novel transmit waveform and pulse compression scheme has resulted in a system with improved performance to size, weight, and power ratios compared to typical tube based Doppler radars currently in use for clouds and precipitation measurements. Tube based radars require high voltage power supply and pressurization of the transmitter and radar front end that complicates system design and implementation. Solid state technology also significantly improves system reliability. Finally, HIWRAP technology advances also include the development of a high-speed digital receiver and processor to handle the complex receiving pulse sequences and high data rates resulting from multi receiver channels and conical scanning. This paper describes HIWRAP technology development for dual-frequency operation at high-altitudes using low peak power transmitters and pulse compression. The hardware will be described along with the methods and concepts for the system design. Finally, we will present recent preliminary results from flights on the NASA Global Hawk in support of the NASA Genesis and Rapid Intensification Processes (GRIP) field campaign, and on the NASA ER-2 as fixed nadir pointing mode for the NASA Global Precipitation Measurement (GPM) ground validation (GV) mission - Midlatitude Continental Convective Cloud Experiment (MC3E)

Li, Lihua↗

PICSAR-QED: a Monte Carlo module to simulate strong-field quantum electrodynamics in particle-in-cell codes for exascale architectures

Abstract Physical scenarios where the electromagnetic fields are so strong that quantum electrodynamics (QED) plays a substantial role are one of the frontiers of contemporary plasma physics research. Investigating those scenarios requires state-of-the-art particle-in-cell (PIC) codes able to run on top high-performance computing (HPC) machines and, at the same time, able to simulate strong-field QED processes. This work presents the PICSAR-QED library, an open-source, portable implementation of a Monte Carlo module designed to provide modern PIC codes with the capability to simulate such processes, and optimized for HPC. Detailed tests and benchmarks are carried out to validate the physical models in PICSAR-QED, to study how numerical parameters affect such models, and to demonstrate its capability to run on different architectures (CPUs and GPUs). Its integration with WarpX, a state-of-the-art PIC code designed to deliver scalable performance on upcoming exascale supercomputers, is also discussed and validated against results from the existing literature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ANOPP validation study: Lockheed L-1011

The aircraft noise prediction program (ANOPP) was used to predict the far-field noise characteristics of an L-1011 aircraft equipped with RB.211-524B engines. Actual flight noise was compared with noise predicted for the same operating and weather conditions. Correlation of predicted and measured results was very good in the aft quadrant of radiated noise. Predicted noise levels were significantly different from measured values in the forward quadrant because fan noise was predicted high. Since the major noise sources were fan and core, corrections are supplied to adjust ANOPP fan and core noise components so that the total predicted noise matches the measured L-1011 noise levels.

Godby, L.↗

Quantum Langevin theory for two coupled phase-conjugated electromagnetic waves

We provide a general macroscopic phenomenological formula of quantum Langevin equations for two coupled phase-conjugated electromagnetic fields with linear loss (gain) and complex nonlinear coupling coefficient. The macroscopic phenomenological formula is obtained from the coupling matrix to preserve the field commutation relations and correlations, which does not require knowing the microscopic details of light-matter interaction and internal atomic structures. To validate this phenomenological formula, we take spontaneous four-wave mixing in a double-Λ four-level atomic system as an example to numerically confirm that our macroscopic phenomenological result is consistent with that obtained from the microscopic Heisenberg-Langevin theory. We find that a complex-valued nonlinear coupling coefficient can lead to noises even without linear gain or loss. Lastly, we apply the quantum Langevin equations to study the effects of linear gain and loss, complex phase mismatching, as well as complex nonlinear coupling coefficient in entangled photon pair (biphoton) generation, particularly to their temporal quantum correlations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Deriving effective electrode–ion interactions from free-energy profiles at electrochemical interfaces

Understanding ion adsorption at electrified metal–electrolyte interfaces is essential for accurate modeling of electrochemical systems. Here, in this study, we systematically investigate the free energy profiles of Na + , Cl − , and F − ions at the Au(111)–water interface using enhanced sampling molecular dynamics with both classical force fields and machine-learned interatomic potentials (MLIPs). Our classical metadynamics results reveal a strong dependence of predicted ion adsorption on the Lennard-Jones parameters, highlighting that—without due care—standard mixing rules can lead to qualitatively incorrect descriptions of ion–metal interactions. We present a systematic methodology for tuning the cross term LJ parameters to control adsorption energetics in agreement with more accurate models. As a surrogate for an ab initio model, we employed the recently released Universal Models for Atoms MLIP, which validates classical trends and displays strong specific adsorption for chloride, weak adsorption for fluoride, and no specific adsorption for sodium, in agreement with experimental and theoretical expectations. By integrating molecular-level adsorption free energies into continuum models of the electric double layer, we show that specific ion adsorption substantially alters the interfacial ion population, the potential of zero charge, and the differential capacitance of the system. Our results underscore the critical importance of force field parameterization and advanced interatomic potentials for the predictive modeling of ion-specific effects at electrified interfaces and provide a robust framework for bridging molecular simulations and continuum electrochemical models.

Roncoroni, Fabrice [Lawrence Berkeley National Lab↗

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Analytic expressions for spacecraft attitude and rate estimation performance of an attitude estimation filter in terms of sensor specifications are useful tools for spacecraft design. Farrenkopf (1978) famously found analytic expressions for steady-state pre-update and post-update attitude and gyro bias estimate error variances for an attitude estimation filter for a single-axis spacecraft with a Rate Output Gyro (ROG). Markley and Reynolds (2000) extended the analysis for a Rate-Integrating Gyro (RIG) with angle white noise. These expressions allow for the rapid evaluation of system performance during preliminary mission design phases. One contribution of this paper is the analytic calculation of the steady-state pre-update and post-update angular rate estimate uncertainty for both the ROG and RIG cases. The primary contribution of this paper is the extension of the results for both the ROG and the RIG cases to the situation of an attitude sensor outage. This situation arises frequently in practice; for example when a star sensor’s field of view is occluded, when a star sensor’s readings are unreliable during a thruster burn that vibrates the spacecraft, or during star sensor outages due to radiation upsets. Analytic expressions for the attitude estimate uncertainty, gyro bias estimate uncertainty, and angular rate estimate uncertainty are given in terms of the attitude sensor outage interval, the star tracker measurement noise, and gyro noise parameters. Validity of the analytic results is demonstrated via Monte Carlo simulation.

Galante, Joseph M.↗

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Analytic expressions for spacecraft attitude and rate estimation performance of an attitude estimation filter in terms of sensor specifications are useful tools for spacecraft design. Farrenkopf (1978) famously found analytic expressions for steady-state pre-update and post-update attitude and gyro bias estimate error variances for an attitude estimation filter for a single-axis spacecraft with a Rate Output Gyro (ROG). Markley and Reynolds (2000) extended the analysis for a Rate-Integrating Gyro (RIG) with angle white noise. These expressions allow for the rapid evaluation of system performance during preliminary mission design phases. One contribution of this paper is the analytic calculation of the steady-state pre-update and post-update angular rate estimate uncertainty for both the ROG and RIG cases. The primary contribution of this paper is the extension of the results for both the ROG and the RIG cases to the situation of an attitude sensor outage. This situation arises frequently in practice; for example when a star sensor’s field of view is occluded, when a star sensor’s readings are unreliable during a thruster burn that vibrates the spacecraft, or during star sensor outages due to radiation upsets. Analytic expressions for the attitude estimate uncertainty, gyro bias estimate uncertainty, and angular rate estimate uncertainty are given in terms of the attitude sensor outage interval, the star tracker measurement noise, and gyro noise parameters. Validity of the analytic results is demonstrated via Monte Carlo simulation.

Galante, Joseph M.↗

Large Eddy Simulations of Turbulent and Buoyant Flows in Urban and Complex Terrain Areas Using the Aeolus Model

Fast and accurate predictions of the flow and transport of materials in urban and complex terrain areas are challenging because of the heterogeneity of buildings and land features of different shapes and sizes connected by canyons and channels, which results in complex patterns of turbulence that can enhance material concentrations in certain regions. To address this challenge, we have developed an efficient three-dimensional computational fluid dynamics (CFD) code called Aeolus that is based on first principles for predicting transport and dispersion of materials in complex terrain and urban areas. The model can be run in a very efficient Reynolds average Navier–Stokes (RANS) mode or a detailed large eddy simulation (LES) mode. The RANS version of Aeolus was previously validated against field data for tracer gas and radiological dispersal releases. As a part of this work, we have validated the Aeolus model in LES mode against two different sets of data: (1) turbulence quantities measured in complex terrain at Askervein Hill; and (2) wind and tracer data from the Joint Urban 2003 field campaign for urban topography. As a third set-up, we have applied Aeolus to simulate cloud rise dynamics for buoyant plumes from high-temperature explosions. For all three cases, Aeolus LES predictions compare well to observations and other models. These results indicate that Aeolus LES can be used to accurately simulate turbulent flow and transport for a wide range of applications and scales.

42 ENGINEERING↗

Thermal WIMPs and the scale of new physics: global fits of Dirac dark matter effective field theories

We assess the status of a wide class of WIMP dark matter (DM) models in light of the latest experimental results using the global fitting framework GAMBIT. We perform a global analysis of effective field theory (EFT) operators describing the interactions between a gauge-singlet Dirac fermion and the Standard Model quarks, the gluons and the photon. In this bottom-up approach, we simultaneously vary the coefficients of 14 such operators up to dimension 7, along with the DM mass, the scale of new physics and several nuisance parameters. Our likelihood functions include the latest data from Planck, direct and indirect detection experiments, and the LHC. For DM masses below 100 GeV, we find that it is impossible to satisfy all constraints simultaneously while maintaining EFT validity at LHC energies. For new physics scales around 1 TeV, our results are influenced by several small excesses in the LHC data and depend on the prescription that we adopt to ensure EFT validity. Furthermore, we find large regions of viable parameter space where the EFT is valid and the relic density can be reproduced, implying that WIMPs can still account for the DM of the universe while being consistent with the latest data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Mineralized Remains of Morphotypes of Filamentous Cyanobacteria in Carbonaceous Meteorites

The quest for conclusive evidence of microfossils in meteorites has been elusive. One difficulty arises from the fact than many abiotic or inorganic microstructures, mineral grains, and coating artifacts can mimic the smaller representatives of the microbial world that possess very simple morphologies (unicellular cocci or bacilli). However, there exist a wide variety of large, filamentous trichomic prokaryotic microorganisms (cyanobacteria and sulfur bacteria) with sufficiently well known and complex morphologies that they can be recognized and are known to be of unquestionable biogenic origin. The taphonomic modes of fossilization and their of their life habits and processes frequently result in distinctive chemical biosignatures associated with carbonization, silicification, calcification, phosphatization and metal-binding properties of their cell-walls, trichomes, sheaths and extracellular polymeric substances (EPS). Strong differences of mineral concentrations in closely associated and visibly differentiated cellular microstructures provide strong evidence of biogenicity. This evidence is further enhanced by the detection of recognizable and distinct microstructures (e.g., uniseriate or multiseriate filaments, trichomes, sheaths, cells of proper sizes and size distributions) and growth characteristics (e.g., basal or apical cells, true or false branching of trichomes, tapered or uniform filaments, robust or thin sheaths) and reproductive and nitrogen fixation habits (e.g., baeocytes, hormogonia, akinetes and heterocysts), Microfossils of cyanobacteria and cyanobacterial mats and stromatolites have been recognized a described from many of the most ancient rocks on Earth. The crucial problem lies in developing valid protocols and methodologies for establishing that the putative microfossils are truly indigenous and not merely recent microbial contaminants. During the past several years, we have conducted Field Emission Scanning Electron Microscopy (FESEM) investigations of freshly fractured interior surfaces of carbonaceous meteorites, terrestrial rocks, and recent microbial extremophiles and filamentous cyanobacteria. These studies have resulted in the detection in a several carbonaceous meteorites of the mineralized remains of a wide variety of complex filamentous trichomic microorganisms. These embedded forms are consistent in size and microstructure with well-preserved morphotypes of mat- forming filamentous trichomic cyanobacteria and the degraded remains of microfibrils of cyanobacterial sheaths. We present the results of comparative imaging studies and EDAX elemental analyses of recent cyanobacteria (e.g. Calothrix, Oscillatoria, and Lyngbya) that are similar in size, morphology and microstructure to morphotypes found embedded in meteorites. EDAX elemental studies reveal that forms found in carbonaceous meteorites often have highly carbonized sheaths in close association with permineralized filaments, trichomes and microbial cells. Ratios of critical bioelements (C:O, C:N, C:P, and C:S) reveal dramatic differences between microfossils in Earth rocks and meteorites and in filaments, trichomes, hormogonia, and cells of recent cyanobacteria.

Hoover, Richard B.↗

Validating the Use of Gaussian Process Regression for Adaptive Mapping of Residual Stress Fields

Probing the stress state using a high density of measurement points is time intensive and presents a limitation for what is experimentally feasible. Alternatively, individual strain fields used for determining stresses can be reconstructed from a subset of points using a Gaussian process regression (GPR). Results presented in this paper evidence that determining stresses from reconstructed strain fields is a viable approach for reducing the number of measurements needed to fully sample a component’s stress state. The approach was demonstrated by reconstructing the stress fields in wire-arc additively manufactured walls fabricated using either a mild steel or low-temperature transition feedstock. Effects of errors in individual GP reconstructed strain maps and how these errors propagate to the final stress maps were assessed. Implications of the initial sampling approach and how localized strains affect convergence are explored to give guidance on how best to implement a dynamic sampling experiment.

36 MATERIALS SCIENCE↗

Strong IMF By-Related Plasma Convection in the Ionosphere and Cusp Field-Aligned Currents Under Northward IMF Conditions

We present in this paper an investigation of IMF-By related plasma convection and cusp field-aligned currents using FAST data and AMIE model during a prolonged interval with large positive IMF By and northward Bz conditions (By/Bz much greater than 1). Using the FAST single trajectory observations to validate the global convection patterns at key times and key locations, we have demonstrated that the AMIE procedure provides a reasonably good description of plasma circulations in the ionosphere during this interval. Our results show that the plasma convection in the ionosphere is consistent with the anti-parallel merging model. When the IMF has a strongly positive By component under northward conditions, we find that the global plasma convection forms two cells oriented nearly along the Sun-earth line in the ionosphere. In the northern hemisphere, the dayside cell has clockwise convection mainly circulating within the polar cap on open field lines. A second cell with counterclockwise convection is located in the nightside circulating across the polar cap boundary, The observed two-cell convection pattern appears to be driven by the reconnection along the anti-parallel merging lines poleward of the cusp extending toward the dusk side when IMF By/Bz much greater than 1. The magnetic tension force on the newly reconnected field lines drives the plasma to move from dusk to dawn in the polar cusp region near the polar cap boundary. The field-aligned currents in the cusp region flow downward into the ionosphere. The return field-aligned currents extend into the polar cap in the center of the dayside convection cell. The field-aligned currents are closed through the Peterson currents in the ionosphere, which flow poleward from the polar cap boundary along the electric field direction.

Le, G.↗

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗

Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning

Cover cropping between cash crop growing seasons is a multifunctional conservation practice. Timely and accurate monitoring of cover crop traits, notably aboveground biomass and nutrient content, is beneficial to agricultural stakeholders to improve management and understand outcomes. Currently, there is a scarcity of spatially and temporally resolved information for assessing cover crop growth. Remote sensing has a high potential to fill this need, but conventional empirical regression operated with coarse-resolution multispectral data has large uncertainties. Therefore, this study utilized airborne hyperspectral imaging techniques and developed new process-guided machine learning approaches (PGML) for cover crop monitoring. Specifically, we deployed an airborne hyperspectral system covering visible to shortwave-infrared wavelengths (400–2400 nm) to acquire high spatial (0.5 m) and spectral (3–5 nm) resolution reflectance over 23 cover crop fields across Central Illinois in March and April of 2021. Airborne hyperspectral surface reflectance with high spectral and spatial resolution can be well matched with field data to quantify cover crop traits. Furthermore, the PGML models were pre-trained by synthetic data from soil-vegetation radiative transfer modeling (one million records), and then fine-tuned with field data of cover crop biomass and nutrient content. Results show that airborne hyperspectral data with PGML can achieve high accuracy to predict cover crop aboveground biomass (R 2 = 0.72, relative RMSE = 15.16%) and nitrogen content (R 2 = 0.69, relative RMSE = 16.59%) through leave-one-field-out cross-validation. Unlike the pure data-driven approach (e.g., partial least-squares regression), PGML incorporated radiative transfer knowledge and obtained higher predictive performance with fewer field data. Meanwhile, with field data for model fine-tuning, PGML predicted biomass more accurately than the inversion of radiative transfer models. Here we also found that the red edge has a high contribution in quantifying aboveground biomass and nitrogen content, followed by green and shortwave spectra. This study demonstrated the first attempt of utilizing hyperspectral remote sensing to accurately quantify cover crop traits. We highlight the strength of PGML in exploiting sensing data to quantify ecosystem variables to advance agroecosystem monitoring for sustainable agricultural management.

60 APPLIED LIFE SCIENCES↗

Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks

Tomographic background oriented Schlieren (Tomo-BOS) imaging measures density or temperature fields in three dimensions using multiple camera BOS projections, and is particularly useful for instantaneous flow visualizations of complex fluid dynamics problems. We propose a new method based on physics-informed neural networks (PINNs) to infer the full continuous three-dimensional (3-D) velocity and pressure fields from snapshots of 3-D temperature fields obtained by Tomo-BOS imaging. The PINNs seamlessly integrate the underlying physics of the observed fluid flow and the visualization data, hence enabling the inference of latent quantities using limited experimental data. In this hidden fluid mechanics paradigm, we train the neural network by minimizing a loss function composed of a data mismatch term and residual terms associated with the coupled Navier–Stokes and heat transfer equations. We first quantify the accuracy of the proposed method based on a two-dimensional synthetic data set for buoyancy-driven flow, and subsequently apply it to the Tomo-BOS data set, where we are able to infer the instantaneous velocity and pressure fields of the flow over an espresso cup based only on the temperature field provided by the Tomo-BOS imaging. Moreover, we conduct an independent PIV experiment to validate the PINN inference for the unsteady velocity field at a centre plane. To explain the observed flow physics, we also perform systematic PINN simulations at different Reynolds and Richardson numbers and quantify the variations in velocity and pressure fields. Furthermore, the results in this paper indicate that the proposed deep learning technique can become a promising direction in experimental fluid mechanics.

97 MATHEMATICS AND COMPUTING↗