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At least 91 records · Page 5

Wake-Resolving Acoustic Tomography: Advances through Numerical Covariance Methods

Acoustic tomography offers path-integrated measurements of atmospheric velocity and temperature fluctuations with high spatial resolution. Classical implementations of time-dependent stochastic inversion rely on homogeneous, isotropic covariance models that are poorly suited to the anisotropic structure of wind turbine wakes. By directly estimating heterogeneous covariances from large-eddy simulations (LESs) into the time-dependent stochastic inversion operator, we relax implicit assumptions in the analytical models used historically. Retrievals using these LES-informed models improve agreement with true fields in variance, turbulent kinetic energy, and spectral content compared to analytical and precursor-based covariance models. The results indicate that LES-informed covariance models can enhance the accuracy of acoustic tomography retrievals in complex, anisotropic flows such as wind turbine wakes in some cases and highlight instances where analytical models still offer competitive performance, despite their simplifying assumptions.

17 WIND ENERGY↗

Evaluation of an Airborne Spacing Concept to Support Continuous Descent Arrival Operations

This paper describes a human-in-the-loop experiment of an airborne spacing concept designed to support Continuous Descent Arrival (CDA) operations. The use of CDAs with traditional air traffic control (ATC) techniques may actually reduce an airport's arrival throughput since ATC must provide more airspace around aircraft on CDAs due to the variances in the aircraft trajectories. The intent of airborne self-spacing, where ATC delegates the speed control to the aircraft, is to maintain or even enhance an airport s landing rate during CDA operations by precisely achieving the desired time interval between aircraft at the runway threshold. This paper describes the operational concept along with the supporting airborne spacing tool and the results of a piloted evaluation of this concept, with the focus of the evaluation on pilot acceptability of the concept during off-nominal events. The results of this evaluation show a pilot acceptance of this airborne spacing concept with little negative performance impact over conventional CDAs.

Murdoch, Jennifer L.↗

Long-range Doppler lidar measurements of wind turbine wakes and their interaction with turbulent atmospheric boundary-layer flow at Perdigao 2017

As part of the Perdigão 2017 campaign, vertical RHI (range-height indicator) scans with long-range pulsed Doppler wind lidars were performed aligned with the main wind direction and a wind turbine (WT) located on a mountain ridge. The measurements are used to not only retrieve flow velocities, but also their variance and - by using the turbulent broadening of the Doppler spectrum - also turbulent kinetic energy (TKE) dissipation rate. The study shows that turbulence in the WT wake is dependent on the turbulence of the inflow, but also on atmospheric stability. In stable atmospheric conditions, wakes could be analyzed up to five rotor diameters downstream (D) and showed the maximum turbulence in the wake at 2-3 D, whereas in unstable conditions, the maximum was found at 2 D and the wake could not be detected further than 3 D. A clear dependency of wake turbulence enhancement on inflow turbulence intensity is found, which levels out to no further enhancement at turbulence intensities of 30%.

17 WIND ENERGY↗

Development and Deployment of NASA's Budget Execution Dashboard

This paper discusses the successful implementation of a highly visible company-wide management system and its potential to change managerial and accounting policies, processes and practices in support of organizational goals. Applying the conceptual framework of innovation in organizations, this paper describes the development and deployment process of the NASA Budget Execution Dashboard and the first two fiscal years of its use. It discusses the positive organizational changes triggered by the dashboard, like higher visibility of financial goals and variances between plans and actuals, increased involvement of all management levels in tracking and correcting of plan deviations, establishing comparable data standards across a strongly diversified organization, and enhanced communication between line organizations (NASA Centers) and product organizations (Mission Directorates). The paper also discusses the critical success factors experienced in this project: Strong leadership and division of management roles, rapid and responsive technology development, and frequent communication among stakeholders.

Putz, Peter↗

Experimental Impacts into Chondritic Targets: Disruption of an L6 Chondrite by Multiple Impacts - Part 1

A fragment of an L6 chondrite (ALH 85017,13) with an initial mass (M(sub 0)) of 464.1 g was the target in a series of experimental impacts in which the largest remaining fragment (M(sub R)) after each shot was impacted by a 3.18-mm ceramic sphere at a nominal speed of 2 km/s. This continued until the mass of the largest remaining piece was less than half the mass of the target presented to that shot (M(sub S)). Two chunks of Bushveldt gabbro with similar initial masses were also impacted under the same conditions until M(sub R) was less than half M(sub 0). The two gabbro targets required a total of 1.51x10(exp 7) and 1.75x10(exp 7) erg/g to attain 0.27 and 0.33 M(sub R)/M(sub 0), respectively; the chondrite, however, was considerably tougher, reaching 0.40 and 0.21 M(sub R)/M(sub 0) only after receiving 2.37x10(exp 7) and 3.10x10(exp 7) erg g-1, respectively. The combined ejecta and spallation products from the gabbro impacts were coarser than those from the chondrite and in sufficient quantities that the new surface areas exceeded those from the meteorite until the fifth shot in the chondrite series, which was the number of impacts required to disrupt each gabbro target (i.e., MR/M0 = 0.5). Unlike the behavior shown in previous regolith-evolution series, neither gabbro target produced an enhancement in the size fraction reflecting the mean size of the crystals composing the rock (about 3 mm), an effect possibly related to the width of the shock pulse. The original chondrite was so fine-grained and fractured, and the variance in its grain-size distribution so large, that effects related to grain-size were relegated to the <63- m fraction. Impacts into ALH 85017 produced abundant, fine-grained debris, but otherwise the slopes of its size distributions were comparable to those from other experiments involving natural and fabricated terrestrial targets. The characteristic slopes of the chondrite's size distributions, however, were notably more constant over the entire nine-impact series than those from any of the terrestrial targets, a testament to the control over comminution apparently exerted by pre-existing fractures and other, microscopic damage in the meteorite. The enhancement in the finer fraction of debris from ALH 85017 indicates that ordinary chondrites in solar orbit would be very efficient contributors to the cosmic-dust complex. At the same time, the greater resistance to disruption displayed by ordinary chondrites relative to that exhibited by igneous rocks indicates that a selection effect could be operative between the annealed, ordinary-chondritic breccias and relatively weaker, differentiated meteorites. Preferential survival from their time in the regoliths of their parent bodies through their transit to Earth and passage through the atmosphere suggests that meteorite collections could be biased in favor of the ordinary chondrites.

Cintala, Mark J.↗

Implications of stop-and-go traffic on training learning-based car-following control

Learning-based car-following control (LCC) of connected and autonomous vehicles (CAVs) is gaining significant attention with the advancement of computing power and data accessibility. While the flexibility and large model capacity of model-free architecture enable LCC to potentially outperform the model-based car-following (CF) model in improving traffic efficiency and mitigating congestion, the generalizability of LCC for traffic conditions different from the training environment/dataset is not well-understood. Herein, this study seeks to explore the impact of stop-and-go traffic in the training dataset on the generalizability of LCC. It uses the characteristics of lead vehicle trajectories to describe stop-and-go traffic, and links the theory of identifiability (i.e., obtaining a unique parameter estimation result using sensor measurements) to the generalizability of behavior cloning (BC) and policy-based deep reinforcement learning (DRL). Correspondingly, the study shows theoretically that: (i) stop-and-go traffic can enable the property of identifiability and enhance the control performance of BC-based LCC in different traffic conditions; (ii) stop-and-go traffic is not necessary for DRL-based LCC to generalize to different traffic conditions; (iii) DRL-based LCC trained with only constant-speed lead vehicle trajectories (not sufficient to ensure identifiability) can be generalized to different traffic conditions; and (iv) stop-and-go traffic increases variance in the training dataset, which improves the convergence of parameter estimation while negatively impacting the convergence of DRL to the optimal control policy. Numerical experiments validate the above findings, illustrating that BC-based LCC entails comprehensive training datasets for generalizing to different traffic conditions, while DRL-based LCC can achieve generalization with simple free-flow traffic training environments. This further suggests DRL as a more promising and cost-effective LCC approach to reduce operational costs, mitigate traffic congestion, and enhance safety and mobility, which can accelerate the deployment and acceptance of CAVs.

33 ADVANCED PROPULSION SYSTEMS↗

Supporting automation in spacecraft activity planning with simulation and visualization

Automation is gaining momentum in spacecraft operations, however, at a much slower pace than comparable application domains. The reasons behind slow adoption is (1) the need for high reliability and (2) the limited interaction between human operators and the automated systems. For automated systems to be adopted and trusted by humans, humans need to gain intuition about the decision making process of the automated system and trust in its execution [1]. In this paper, we present how simulation and visualization can enhance adoption of an automated on-board activity scheduling system, specifically in the context of Mars2020 rover mission[2]. The visualization aims to communicate to the users degree of variance and uncertainty in possible schedule execution. Our preliminary validation results suggest that the proposed visualization increases operators’ confidence in—and likelihood of adopting—the automated scheduling system.

Chien, Steve↗

Plasma electron observations in the wake of Venus

Two plasma regimes were observed in the Venus wake, one characterized by negative-going anisotropies accompanied by high bulk speeds and low magnetic variance, and the other characterized by positive-going anisotropies accompanied by low bulk speeds and high magnetic variance. The two modes alternate in time in a stochastic bimodal fashion as interplanetary magnetic field discontinuities propagate past Venus and switch on the positive anisotropies. The positive mode probably represents enhanced planetary ion pickup which results in instabilities, the damping of which energizes the electrons in the distant wake.

Yeates, C. M.↗

Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

Abstract Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR− and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.

59 BASIC BIOLOGICAL SCIENCES↗

Seasonal-to-Interannual Variability in Antarctic Sea-Ice Dynamics, and Its Impact on Surface Fluxes and Water Mass Production

Strong seasonal and interannual signals in Antarctic bottom-water outflow remain unexplained yet are highly correlated with anomalies in net sea-ice growth in coastal polynyas. The mechanisms responsible for driving salination and replenishment and rejuvenation of the dense shelf "source" waters likely also generate pulses of bottom water outflow. The objective of this research is to investigate time-scales of variability in the dynamics of sea-ice in the Southern Ocean in order to determine the primary sites for production of dense shelf waters. We are using a merged satellite/buoy sea-ice motion data set for the period 1978-present day to compute the dynamics of opening and closing of coastal polynyas over the continental shelf. The Ocean Circulation and Climate Advanced Model (OCCAM) ocean general circulation model with coupled sea-ice dynamics is presently forced using National Center for Environmental Prediction (NCEP) data to simulate fluxes and the salination impact of the ocean shelf regions. This work is relevant in the context of measuring the influence of polar sea-ice dynamics upon polar ocean characteristics, and thereby upon global thermohaline ocean circulation. Interannual variability in simulated net freezing rate in the Southern Weddell Sea is shown for the period 1986-1993. There is a pronounced maximum of ice production in 1988 and minimum in 1991 in response to anomalies in equatorward meridional wind velocity. This follows a similar approximate 8-year interannual cycle in Sea Surface Temperature (SST) and satellite-derived ice-edge anomalies reported elsewhere as the "Antarctic Circumpolar Wave." The amplitude of interannual fluctuations in annual net ice production are about 40% of the mean value, implying significant interannual variance in brine rejection and upper ocean heat loss. Southward anomalies in wind stress induce negative anomalies in open water production, which are observed in passive microwave satellite images. Thus, cycles of enhanced poleward wind stress reduce ice growth by compacting the ice along the coastline and closing open water in leads and polynyas. Model simulations confirm that years of low ice production, such as 1991, coincide with years of lower than normal bottom water outflow. Future plans include the assimilation of satellite ice concentrations and ice drift dynamics to more accurately constrain boundary conditions in the model.

Drinkwater, Mark R.↗

Causes of Long-Term Drought in the United States Great Plains

The United States Great Plains (USGP) experienced a number of multi-year droughts during the last century, most notably the droughts of the 1930s and 1950s. This study examines the causes of such droughts using ensembles of long term (1930-1999) simulations carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTs). The results show that the model produces long-term (multi-year) variations in the USGP precipitation that are similar to those observed. A correlative analysis suggests that the ensemble mean low frequency (time scales longer than about 6 years) rainfall variations in the USGP are linked to a pan-Pacific pattern of SST variability that is the leading empirical orthogonal function (EOF) in the low frequency SST data. The link between the SST and the Great Plains precipitation is confirmed in idealized AGCM simulations, in which the model is forced by the 2 polarities of the pan-Pacific SST pattern. The idealized simulations further show that it is primarily the tropical part of the SST anomalies that influence the USGP. As such, the USGP tend to have above normal precipitation when the tropical Pacific SSTs are above normal, while there is a tendency for drought when the tropical SSTs are cold. The upper tropospheric response to the pan-Pacific SST EOF shows a global-scale pattern with a strong wave response in the Pacific and a substantial zonally-symmetric component in which USGP pluvial (drought) conditions are associated with reduced (enhanced) heights throughout the extra-tropics. The potential predictability of rainfall in the USGP associated with SSTs is rather modest, with on average about 1/3 of the total low frequency rainfall variance forced by SST anomalies. Further idealized experiments with climatological SST, suggest that the remaining low frequency variance in the USGP precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a six-fold increase in the variance in annual USGP precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce year-to-year memory in the hydrological cycle that is consistent with a red noise process, in which the low frequencies in the deep soil are the result of integrating a net forcing (precipitation-evaporation-runoff) that is white noise on interannual time scales. As such, the role of low frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.

Schubert, Siegfried D.↗

Weak-form latent space dynamics identification

Recent work in data-driven modeling has demonstrated that a weak formulation of model equations enhances the noise robustness of a wide range of computational methods. In this paper, we demonstrate the power of the weak form to enhance the LaSDI (Latent Space Dynamics Identification) algorithm, a recently developed data-driven reduced order modeling technique. We introduce a weak form-based version WLaSDI (Weak-form Latent Space Dynamics Identification). WLaSDI first compresses data, then projects onto the test functions and learns the local latent space models. Notably, WLaSDI demonstrates significantly enhanced robustness to noise. With WLaSDI, the local latent space is obtained using weak-form equation learning techniques. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form guarantees a robust and precise latent space recovery, hence allowing for a fast, robust, and accurate simulation. We demonstrate the efficacy of WLaSDI vs. LaSDI on several common benchmark examples including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in the case of 1D inviscid Burgers' simulations with the addition of up to 100% Gaussian white noise, the relative error remains consistently below 6% for WLaSDI, while it can exceed 10,000% for LaSDI. Similarly, for radial advection simulations, the relative errors stay below 15% for WLaSDI, in stark contrast to the potential errors of up to 10,000% with LaSDI. Moreover, speedups of several orders of magnitude can be obtained with WLaSDI. For example applying WLaSDI to 1D Burgers' yields a 140X speedup compared to the corresponding full order model.

97 MATHEMATICS AND COMPUTING↗

Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction

We introduce a novel neural network, SkyReconNet, which combines the expanded receptive fields of dilated convolutional layers along with standard convolutions, to capture both the global and local features for reconstructing the missing information in an image. We implement our network to inpaint the masked regions in a full-sky cosmic microwave background (CMB) map. Inpainting CMB maps is a particularly formidable challenge when dealing with extensive and irregular masks, such as galactic masks which can obscure substantial fractions of the sky. The hybrid design of SkyReconNet leverages the strengths of standard and dilated convolutions to accurately predict CMB fluctuations in the masked regions by effectively utilizing the information from surrounding unmasked areas. During training, the network optimizes its weights by minimizing a composite loss function that combines the structural similarity index measure (SSIM) and mean squared error (MSE). SSIM preserves the essential structural features of the CMB, ensuring an accurate and coherent reconstruction of the missing CMB fluctuations, while MSE minimizes the pixelwise deviations, thus enhancing the overall accuracy of the predictions. The predicted CMB maps and their corresponding angular power spectra align closely with the targets, achieving the performance limited only by the fundamental uncertainty of cosmic variance. The network’s generic architecture enables application to other physics-based challenges involving data with missing or defective pixels, systematic artifacts, etc. In conclusion, our results demonstrate its effectiveness in addressing the challenges posed by large irregular masks, offering a significant inpainting tool not only for CMB analyses but also for image-based experiments across disciplines where such data imperfections are prevalent.

Cosmic microwave background↗

Tracking the GLOMR satellite

The task of day-to-day low orbiting satellite tracking utilizing the NAVSPASUR orbital elements is discussed and methods for improving pass time predictions are presented. Estimates are needed for preprogramming of satellite-initiated communications scheduling which requires an accuracy of approximately 30 seconds. This can be achieved by removing the variance associated with the NAVSPASUR D sub 2 (decay) term. Finally, the shock evidenced in GLOMR's orbit on February 7, 1986 is documented and attributed to a severe solar storm with immediately enhanced drag. GLOMR's life expectancy in orbit is now estimated to have dropped approximately 17% by the end of orbit in early February, 1987.

Reiss, Keith W.↗

High-Temperature 2D Optical Relaxation Visualizes Enhanced Oxygen Exchange Kinetics at Metal-Mixed Conducting Oxide Interfaces

Solid-state heterointerfaces are of interest for emergent local behavior that is distinct from either bulk parent compound. One technologically relevant example is the case of mixed ionic/electronic conductor (MIEC)–metal interfaces, which play an important role in electrochemistry. Metal–MIEC composite electrodes can demonstrate improved catalytic activity vs single-phase MIECs, improving fuel cell efficiency. Similarly, MIEC surface reaction kinetics are often evaluated using techniques that place metal current collectors in contact with the surface under evaluation, potentially altering the response vs the native surface. Here, techniques enabling direct and local in situ observation of the behavior at and around such heterointerfaces are needed. Here, we develop a spatially resolved optical transmission relaxation (2D-OTR) method providing continuous evaluation of local, high-temperature, controlled atmosphere defect kinetics across a ~1 cm2 sample area simultaneously in a contact-free manner. We apply it to observe the spatial variance of oxygen incorporation and evolution rates at ~525–620 °C, in response to step changes in oxygen partial pressure, on MIEC SrTi 0.65 Fe 0.35 O 3–x films as a function of distance from porous Pt and Au layers. Using this model geometry, we find significant enhancements in kinetics adjacent to the metals that decay over a few millimeter distance. To extract kinetic parameters, we fit the short-term optical data (initial portion of relaxations) with an exponential decay function appropriate for surface-exchange-limited kinetics, yielding apparent surface exchange coefficients (k chem ) with spatial resolution, decreasing with distance from the metal. To understand the kinetic processes governing the complete (long-term) optical relaxations, we performed COMSOL simulations, which demonstrated that a combination of laterally varying k chem and in-plane diffusion controls the observed kinetics over the full time range. Further support for spatially varying kchem comes from demonstrations of changing surface and bulk chemistry vs distance from the metal–MIEC interface, by X-ray photoelectron and optical absorption spectroscopies, respectively. Although microporous Pt and Au are not excellent electrodes in isolation, both metals exert a synergistic effect on the oxygen surface exchange rate in the presence of the mixed conducting film.

36 MATERIALS SCIENCE↗

Temporal covariance structure of multi-spectral phenotypes and their predictive ability for end-of-season traits in maize

Vegetation indices (VIs) derived from multi-spectral imaging (MSI) platforms can be used to study properties of crop canopy, providing non-destructive phenotypes that could be used to better understand growth curves throughout the growing season. To investigate the amount of variation present in several VIs and their relationship with important end-of-season traits, genetic and residual (co)variances for VIs, grain yield and moisture were estimated using data collected from maize hybrid trials. The VIs considered were Normalized Difference Vegetation Index (NDVI), Green NDVI, Red Edge NDVI, Soil-Adjusted Vegetation Index, Enhanced Vegetation Index and simple Ratio of Near Infrared to Red (Red) reflectance. Genetic correlations of VIs with grain yield and moisture were used to fit multi-trait models for prediction of end-of-season traits and evaluated using within site/year cross-validation. To explore alternatives to fitting multiple phenotypes from MSI, random regression models with linear splines were fit using data collected in 2016 and 2017. Heritability estimates ranging from (0.10 to 0.82) were observed, indicating that there exists considerable amount of genetic variation in these VIs. Furthermore, strong genetic and residual correlations of the VIs, NDVI and NDRE, with grain yield and moisture were found. Considerable increases in prediction accuracy were observed from the multi-trait model when using NDVI and NDRE as a secondary trait. Finally, random regression with a linear spline function shows potential to be used as an alternative to mixed models to fit VIs from multiple time points.

59 BASIC BIOLOGICAL SCIENCES↗

Inferring Plant Acclimation and Improving Model Generalizability With Differentiable Physics‐Informed Machine Learning of Photosynthesis

Net photosynthesis (A N ) is a key component of the global carbon cycle influencing climate feedback over decadal scales. Although plant acclimation to environmental changes can modify A N , traditional vegetation models in Earth system models (ESMs) often rely on plant functional type (PFT)-specific parameterizations or simplified acclimation assumptions limiting generalizability across time, space, and PFTs. In this study, we developed a differentiable photosynthesis model to learn the environmental dependencies of V c,max25 (maximum carboxylation rate at 25°C, representing photosynthetic capacity), as this genre of hybrid physics-informed machine learning can seamlessly train neural networks and process-based equations together. Compared to PFT-specific parameterization of V c,max25 , learning the environment dependencies of key photosynthetic parameters improved model spatiotemporal generalizability. Applying environmental acclimation to V c,max25 led to substantial variations in global mean A N indicating the need to address acclimation in ESMs. The model effectively captured multivariate observations (V c,max25 , A N , and stomatal conductance (g s )) simultaneously with multivariate constraints, improving generalization across space and PFTs. It also learned sensible acclimation relationships of V c,max25 to different environmental conditions. The model explained more than 54%, 57%, and 62% of the variance of A N , g s , and V c,max25 , respectively, presenting a first global-scale spatial test benchmark of A N and g s . These results highlight the potential for differentiable modeling to enhance process-based modules in ESMs and effectively leverage information from large, multivariate data sets.

54 ENVIRONMENTAL SCIENCES↗

Potential capabilities of Reynolds stress turbulence model in the COMMIX-RSM code

A Reynolds stress turbulence model has been implemented in the COMMIX code, together with transport equations describing turbulent heat fluxes, variance of temperature fluctuations, and dissipation of turbulence kinetic energy. The model has been verified partially by simulating homogeneous turbulent shear flow, and stable and unstable stratified shear flows with strong buoyancy-suppressing or enhancing turbulence. This article outlines the model, explains the verifications performed thus far, and discusses potential applications of the COMMIX-RSM code in several domains, including, but not limited to, analysis of thermal striping in engineering systems, simulation of turbulence in combustors, and predictions of bubbly and particulate flows.

Chang, F. C.↗