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At least 109 records · Page 6

Identification of nonlinear structural elements by force-state mapping

A major contributor to the passive damping and potentially nonlinear behavior of large space structures is the behavior of the joints. Proposed is an experimental technique called 'force-state mapping' that will allow ground testing of these key structural elements. The technique includes the use of very accurate instrumentation to measure the force transmission properties of a structural element as a function of its mechanical state. When these data are presented in the form of a force-state map, the nonlinearities exhibit distinctively recognizable patterns. This presentation of the data allows the extraction of the describing parameters of the linear and nonlinear behavior and the energy dissipation characteristics of the joint. A series of tests were carried out on an idealized laboratory test article to demonstrate the technique. Strong structural nonlinearities, including a cubic hardening spring, friction, and impact phenomena, were introduced and measured. Parameters identified by the force-state mapping technique are compared with those made by traditional techniques and the errors involved in the measurement are estimated.

Crawley, E. F.↗

Latent Heating Structures Derived from TRMM

Rainfall is the fundamental variable within the Earth's hydrological cycle because it is both the main forcing term leading to variations in continental and oceanic surface water budgets. The vertical distribution of latent heat release, which is accompanied with rain, modulates large-scale meridional and zonal circulations within the tropics as well as modifying the energetic efficiency of mid-latitude weather systems. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water.This paper focuses on the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission 0. The TRMM observatory, whose development was a joint US-Japan space endeavor, was launched in November 1997. TRMM measurements provide an accurate account of rainfall over the global tropics, information which can be .used to estimate the four-dimensional structure of latent heating across the entire tropical and sub-tropical regions. Various algorithm methodologies for estimating latent heating based on rain rate measurements from TRMM observations are described. The strengths and weaknesses of these algorithms, as well as the latent heating products generated by these algorithms, are also discussed along with validation analyses of the products. The investigation paper provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, and concludes with remarks designed to stimulate further research on latent heating retrieval

Tao, W.-K.↗

TPSAS-NF1676L-34796-DND

The recently completed 2015-2017 EVS-2 mission NAAMES (The North Atlantic Aerosols and Marine Ecosystems Study) provides a unique set of airborne remote sensing and ship-based in situ measurements in a remote and under-sampled region of the Earth?s ocean. The NASA SABOR (Ship-Aircraft Bio-Optical Research) campaign was conducted during the summer of 2014, also in the Atlantic Ocean, out of the Chesapeake Bay and in the eastern coastal region of the United States. For both campaigns, the NASA GISS Research Scanning Polarimeter, a multi-angle, multi-spectral polarimeter measured the upwelling polarized radiances from aircraft. And for both campaigns, ship-based in situ measurements of the ocean were collected jointly with the aircraft measurements. We present results from the new RSP-MAPP (1) that is based on optimal estimation and that can retrieve simultaneous aerosol microphysical properties (including effective radius, single-scattering albedo, and real refractive index) and ocean color products using accurate radiative transfer, Mie calculations, and the DP (Detritus Plankton) series of accurate, numerically efficient ocean bio-optical models. The RSP-MAPP algorithm was applied to data collected during SABOR and NAAMES to retrieve aerosol microphysics and ocean products for all Aerosols-Above-Ocean (AAO) scenes. The RSP-MAPP products are compared against i) collocated aerosol extinction and backscatter profiles collected by the NASA LaRC airborne High Spectral Resolution Lidar (HSRL-1), including lidar depth profiles of the ocean diffuse attenuation coefficient and the hemispherical backscatter coefficient, and ii) collocated ship-based in situ measurements of the ocean.

Snorre Stamnes↗

Improved Pyrotechnic Shock Scaling Method Based on Shock Response Spectrum and Statistical Energy Analysis

It has been more than forty years since the pyrotechnic shock scaling method was introduced. The scaling method estimates the attenuation of the Shock Response Spectrum (SRS) based on the distance from the source, structural configurations, types of structural joints and interfaces, and intervening structure [1]. The method has been successfully used in the spacecraft community countless times and still is frequently used to develop pyrotechnic shock requirements at various levels of assembly of a spacecraft. However, since the method was derived empirically from a limited set of shock test data [2], the aerospace community has been looking for an alternative approach. In this paper, a computational scaling method based on Statistical Energy Analysis (SEA) is re-visited. SEA is traditionally used as a method for investigating the diffusion of acoustic and vibratory energies of a system at steady-state [3]. Previously, an approach using the SRS as an acceleration constraint condition to the SEA model was introduced to estimate the attenuation from a shock source [4,5]. In the current investigation, additional examples are provided to further validate the approach. In addition, responses in the time domain are produced by the Local Modal Phase Reconstruction (LMPR) approach which was recently introduced to the community [6].

Fernandez, Juan P.↗

LACIE (Large Area Crop Inventory Experiment) Programme

Large Area Crop Inventory Experiment was a three year experiment conducted jointly by the United States Department of Agriculture, NASA, and NOAA (National Oceanic and Atmospheric Administration) to determine if global wheat production can be forecast from LANDSAT data to within 90% of actual yield for each observed 9 years out of 10. Data for the third crop year (1976-1977) was compiled. The proportional area of cultivated land devoted to wheat was estimated based on a statistical sampling of LANDSAT data. Yield is presently estimated by NOAA using regression models developed from historical weather and yield information. Results are discussed.

Whitman, R. I.↗

An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height, and ECMWF surface wind velocity during 1993

The following monthly mean global distributions for 1993 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (U.S.) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) satellite; 10-m height wind speed and direction estimated from the Active Microwave Instrument (AMI) on the European Space Agency (ESA) European Remote Sensing (ERS-1) satellite; sea surface height estimated from the joint U.S.-France Topography Experiment (TOPEX)/POSEIDON spacecraft; and 10-m height wind speed and direction produced by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of annual mean, monthly mean, and sampling distributions are displayed.

Halpern, D.↗

Generalized Cycle Benchmarking Algorithm for Characterizing Midcircuit Measurements

Midcircuit measurements (MCMs) are crucial ingredients in the development of fault-tolerant quantum computation. While there have been rapid experimental progresses in realizing MCMs, a systematic method for characterizing noisy MCMs is still under exploration. In this work, we develop a cycle benchmarking (CB)-type algorithm to characterize noisy MCMs. The key idea is to use a joint Fourier transform on the classical and quantum registers and then estimate parameters in the Fourier space, analogous to Pauli fidelities used in CB-type algorithms for characterizing the Pauli-noise channel of Clifford gates. Furthermore, we develop a theory of the noise learnability of MCMs, which determines what information can be learned about the noise model (in the presence of state preparation and terminating measurement noise) and what cannot, which shows that all learnable information can be learned using our algorithm. As an application, we show how to use the learned information to test the independence between measurement noise and state-preparation noise in an MCM. Finally, we conduct numerical simulations to illustrate the practical applicability of the algorithm. Similar to other CB-type algorithms, we expect the algorithm to provide a useful toolkit that is of experimental interest. Published by the American Physical Society 2025

Zhang, Zhihan (ORCID:0009000862907691)↗

gdess: A framework for evaluating simulated atmospheric CO 2 in Earth System Models

Atmospheric carbon dioxide (CO 2 ) plays a key role in the global carbon cycle and global warming. Climate-carbon feedbacks are often studied and estimated using Earth System Models (ESMs), which couple together multiple model components—including the atmosphere, ocean, terrestrial biosphere, and cryosphere—to jointly simulate mass and energy exchanges within and between these components. Despite tremendous advances, model intercomparisons and benchmarking are aspects of ESMs that warrant further improvement (Fer et al., 2021; Smith et al., 2014). Such benchmarking is critical because comparing the value of state variables in these simulations against observed values provides evidence for appropriately refining model components; moreover, researchers can learn much about Earth system dynamics in the process (Randall et al., 2019). We introduce `gdess` (a.k.a., Greenhouse gas Diagnostics for Earth System Simulations), which parses observational datasets and ESM simulation output, combines them to be in a consistent structure, computes statistical metrics, and generates diagnostic visualizations. In its current incarnation, `gdess` facilitates evaluating a model's ability to reproduce observed temporal and spatial variations of atmospheric CO 2 . The diagnostics implemented modularly in `gdess` support more rapid assessment and improvement of model-simulated global CO 2 sources and sinks associated with land and ocean ecosystem processes. We intend for this set of automated diagnostics to form an extensible, open source framework for future comparisons of simulated and observed concentrations of various greenhouse gases across Earth system models.

97 MATHEMATICS AND COMPUTING↗

Automatic Calibration and Health Monitoring of Infrastructure Sensors

Smart transportation infrastructure relies on networks of heterogeneous sensors - cameras, radars, and lidars - continuously monitoring traffic conditions. However, executing the initial spatial calibration of multiple sensors and the subsequent health monitoring presents significant operational challenges. Environmental factors, mechanical vibrations, and gradual drift cause spatial misalignment, degrading fusion performance and tracking accuracy. Traditional calibration approaches require manual intervention with specialized targets or survey equipment, resulting in service interruptions and high maintenance costs. This work presents an automated framework for initial calibration and continuous health monitoring without human intervention or service disruption. Our approach addresses two critical problems: (1) detecting when sensors become miscalibrated during operation, and (2) automatically re-establishing spatial alignment using only operational traffic data. The health monitoring component analyzes measurement innovations - differences between sensor observations and predicted object states - to detect systematic biases indicative of calibration drift. By computing bias magnitude, directional consistency, and rejection rates, the system identifies miscalibrations as small as 0.5 meters. Unlike traditional methods requiring known calibration targets, our diagnostic operates continuously on live traffic observations, enabling early detection before fusion quality degrades. The automatic recalibration algorithm leverages overlapping sensor fields-of-view and temporal correlation of vehicle observations. Using graph-based optimization, the system automatically discovers which sensor pairs observe common regions, estimates pairwise spatial transformations using RANSAC-based robust estimation, and jointly optimizes all sensor poses through bundle adjustment. The framework handles practical deployment challenges, including different sensor sampling rates (1-10 Hz), varying installation positions, unknown orientations, and limited overlap regions (>10%). When approximate sensor positions are available from installation surveys (+/-1m accuracy), the algorithm additionally estimates sensor orientations, refining both position and rotation to sub-meter and sub-degree accuracy. We validate the framework on multi-hour traffic datasets from six heterogeneous sensors with sampling rates ranging from 1 Hz to 10 Hz. Results demonstrate successful calibration even with sparse overlap (<20%) and automatic detection of miscalibrations exceeding 0.8 meters. This work enables a "deploy-and-forget" sensor infrastructure that maintains calibration autonomously, reducing maintenance costs while improving tracking accuracy. The techniques generalize beyond transportation to any multi-sensor monitoring application requiring robust spatial alignment, including smart cities, industrial monitoring, and surveillance systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of a Metocean Reference Site near the Massachusetts and Rhode Island Wind Energy Areas

This project developed the first long-term U.S.-based offshore MetOcean Reference Site (MORS-1) by capitalizing on a unique combination of one of the few existing publicly available offshore wind energy metocean observational campaigns in the United States and the only existing research-grade offshore fixed tower. Data collected at MORS-1 has facilitated improved wind resource assessments, improved short-term power production estimates, and reduced costs for sensor validation and calibration efforts, which translate into reduced overall wind energy project risk and cost for developers. Now operational, MORS-1 serves the needs of both industry and researchers using a nonprofit, joint industry-academic partnership model. Led by the Woods Hole Oceanographic Institution, the MORS-1 development effort focused on creating both a recognized organizational structure that will ensure support of the MORS-1 by the wider wind energy industry and research community, and a highly validated data collection and sensor validation facility that will serve as the premier location for cost- and uncertainty-reducing resource characterization and research efforts.

17 WIND ENERGY↗

Estimating CO 2 fluxes through integrating spatial and temporal input layers via deep learning algorithms

Background Accurate estimation of net ecosystem exchange of CO 2 fluxes (Fc) is essential for understanding carbon cycle processes and assessing ecosystem carbon budgets. However, conventional modeling approaches often emphasize temporal dynamics while overlooking the pronounced spatial heterogeneity within the footprint of eddy covariance (EC) towers, potentially limiting predictive accuracy and interpretability of Fc estimates. To address this challenge, we developed a spatiotemporal model that integrates high-resolution footprint-weighted spatial information with sequential environmental drivers. Results The integrated model combines a deeper graph convolutional network to characterize fine-scale spatial variability within EC footprints and a gated recurrent unit network to capture temporal dependencies in biophysical conditions. Using multi-year flux tower observations, remote sensing vegetation indices and footprint modeling, we evaluate the proposed method across three land cover types. This spatiotemporal model consistently outperforms temporal-only and spatial-only baselines, achieving the highest overall accuracy (R 2 = 0.9569) and the lowest RMSE (1.8128 μmol m −2 s −1 ) and MAE (1.1939 μmol m −2 s −1 ). Performance gains are particularly evident in ecosystems with strong vegetation heterogeneity, where spatial structure substantially modulates Fc variability. Conclusions This study demonstrates the importance of joint modeling spatial heterogeneity and temporal dynamics for improving Fc estimation and provides a robust method for advancing footprint-based Fc estimates across diverse ecosystems, supporting refined assessments of terrestrial carbon fluxes, and enhancing scientific foundations for carbon studies.

CO2 flux estimate↗

The Compilation and Validation of the Spectroscopic Redshift Catalogs for the DESI-COSMOS and DESI-XMM-LSS Fields

Over several dedicated programs that include targets beyond the main cosmological samples, the Dark Energy Spectroscopic Instrument collected spectra for 304,970 unique objects in two fields centered on the COSMOS and XMM-LSS fields. In this work, we develop spectroscopic redshift robustness criteria for those spectra, validate these criteria using visual inspection, and provide two custom value-added catalogs with our redshift characterizations. With these criteria, we reliably classify 212,935 galaxies below z < 1.6, 9713 quasars, and 35,222 stars. The resulting catalogs achieve a redshift purity exceeding 99.4% across all galaxy samples. As a critical element in characterizing the selection function, we provide the description of 70 different algorithms that were used to select these targets from imaging data. To facilitate joint imaging/spectroscopic analyses, we provide row-matched photometry from the Dark Energy Camera, Hyper-Suprime Cam, and public COSMOS2020 photometric catalogs. Finally, we demonstrate example applications of these large catalogs to photometric redshift estimation, cluster finding, and completeness studies.

Ratajczak, J. [Univ. of Utah, Salt Lake City, UT (↗

DAO's Finite-volume/Physical-space Data Assimilation System: Stratospheric Applications

In this talk we describe the next-generation data assimilation system being developed at NASA's Data Assimilation Office (DAO), with emphasis on the applications to stratospheric forecasts and stratospheric constituent transport. This data assimilation system includes the General Circulation Model jointly developed by the DAO and the Climate and Global Dynamics Division (CGDD) at NCAR. This model is based on the finite-volume dynamical core) developed at DAO with physical parameterizations from the NCAR Climate Community Model. The Physical-space Statistical Analysis System (PSAS) is used to combine a first guess from the NASA-NCAR GCM with observational data to provide an updated estimate of the state of the atmosphere. Case studies for the (northern) Winter of 2000 will be discussed.

daSilva, Arlindo↗

GRAIL Refinements to Lunar Seismic Structure

The present ]day internal structure of the Moon provides insight not only into its own formation and evolution, but also that of all rocky planetary bodies. The most direct way to probe a planet fs interior structure is through seismology. As part of the Apollo lunar missions, four seismometers were deployed on the nearside surface of the Moon between the years 1969 and 1972. These instruments operated continuously until 1977, forming the only substantial extraterrestrial seismic data set in existence. These data have been used to constrain various aspects of the seismic velocity and density structure of the Moon. Typical 1-D models recognize a 30-60 km thick crust overlying a nearly constant ]velocity mantle, and extend to a depth of approximately 1000 km, below which the lack of penetrating moonquake ray ]paths precludes the seismic determination of deeper structure. Previously, the lack of observed moonquakes from the far side of the Moon has been used to infer the presence of a highly attenuating (possibly molten) core. Indirect geophysical measurements such as moment of inertia, magnetic induction, lunar laser ranging, and elemental abundances of mare basalts also place varying constraints on core size and state. In combination with seismic studies, these indirect measurements have been used to arrive at a commonly accepted model of the Moon's deepest interior that includes a solid inner and fluid outer core, overlain by a partial melt boundary layer. We recently applied modern array seismology techniques to the Apollo data and revealed detailed core structure, including the first direct confirmation of the presence of a solid inner core. Our study focused on the identification of core ]reflected phases in deep moonquake seismograms. The resulting model of the Moon fs innermost structure was found to be consistent with the commonly accepted model. However, the modeled layer radii may vary by tens of kilometers, as is expected when accounting for uncertainties such as moonquake location, timing errors, and potential seismic heterogeneities. In addition, the modeled velocities may vary with a 1-to-1 trade ]off with the modeled reflector depth. The GRAIL (Gravity Recovery and Interior Laboratory) mission, launched in Sept. 2011, placed two nearly identical spacecraft in lunar orbit. The two satellites make extremely high-resolution measurements of the lunar gravity field, which can be used to constrain the interior structure of the Moon using a "crust to core" approach. GRAIL fs constraints on crustal thickness, mantle structure, core radius and stratification, and core state (solid vs. molten) will complement seismic investigations in several ways. Here we present a progress report on our efforts to advance our knowledge of the Moon fs internal structure using joint gravity and seismic analyses. We will focus on methodology, including 1) refinements to the seismic core constraint accomplished through array processing of Apollo seismic data, made by applying a set of travel time corrections based on GRAIL structure estimates local to each Apollo seismic station; 2) modeling deep lunar structure through synthetic seismograms, to test whether the seismic core model can reproduce the core reflections observed in the Apollo seismograms; and 3) a joint seismic and gravity inversion in which we attempt to fit a family of seismic structure models with the gravity constraints from GRAIL, resulting in maps of seismic velocities and densities that vary from a nominal model both laterally and with depth.

Weber, Renee↗

Status of the Spacelab Program

Based on current estimates of Space Shuttle traffic in the 1980's about one third of the flights will utilize Spacelab, a system which will greatly increase the Shuttle's capability for conducting science, applications and technology missions lasting seven to thirty days. Spacelab is the largest international cooperative space program involving the United States to date with nine European countries working through their space agency, ESRO, to design and develop the system to joint U.S./European requirements. Europe will provide all necessary development funding. The U.S. will operate Spacelab and will procure additional Spacelabs as required.

Lohman, R. L.↗

CFD flowfield simulation of Delta Launch Vehicles in a power-on configuration

This paper summarizes recent work at McDonnell Douglas Aerospace (MDA) to develop and validate computational fluid dynamic (CFD) simulations of under expanded rocket plume external flowfields for multibody expendable launch vehicles (ELVs). Multi engine reacting gas flowfield predictions of ELV base pressures are needed to define vehicle base drag and base heating rates for sizing external nozzle and base region insulation thicknesses. Previous ELV design programs used expensive multibody power-on wind tunnel tests that employed chamber/nozzle injected high pressure cold or hot-air. Base heating and pressure measurements were belatedly made during the first flights of past ELV's to correct estimates from semi-empirical engineering models or scale model tests. Presently, CFD methods for use in ELV design are being jointly developed at the Space Transportation Division (MDA-STD) and New Aircraft Missiles Division (MDA-NAMD). An explicit three dimensional, zonal, finite-volume, full Navier-Stokes (FNS) solver with finite rate hydrocarbon/air and aluminum combustion kinetics was developed to accurately compute ELV power-on flowfields. Mississippi State University's GENIE++ general purpose interactive grid generation code was chosen to create zonal, finite volume viscous grids. Axisymmetric, time dependent, turbulent CFD simulations of a Delta DSV-2A vehicle with a MB-3 liquid main engine burning RJ-1/LOX were first completed. Hydrocarbon chemical kinetics and a k-epsilon turbulence model were employed and predictions were validated with flight measurements of base pressure and temperature. Zonal internal/external grids were created for a Delta DSV-2C vehicle with a MB-3 and three Castor-1 solid motors burning and a Delta-2 with an RS-27 main engine (LOX/RP-1) and 9 GEM's attached/6 burning. Cold air, time dependent FNS calculations were performed for DSV-2C during 1992. Single phase simulations that employ finite rate hydrocarbon and aluminum (solid fuel) combustion chemistry are currently in progress. Reliable and efficient Eulerian algorithms are needed to model two phase (solid-gas) momentum and energy transfer mechanisms for solid motor fuel combustion products.

Pavish, D. L.↗

Data-Driven Closures and Assimilation for Stiff Multiscale Random Dynamics

Here, we introduce a data-driven and physics-informed framework for propagating uncertainty in stiff, multiscale random ordinary differential equations (RODEs) driven by correlated (colored) noise. Unlike systems subjected to Gaussian white noise, a deterministic equation for the joint probability density function (PDF) of RODE state variables does not exist in closed form. Moreover, such an equation would require as many phase-space variables as there are states in the RODE system. To alleviate this curse of dimensionality, we instead derive exact, albeit unclosed, reduced-order PDF (RoPDF) equations for low-dimensional observables/quantities of interest. The unclosed terms take the form of state-dependent conditional expectations, which are directly estimated from data at sparse observation times. However, for systems exhibiting stiff, multiscale dynamics, data sparsity introduces regression discrepancies that compound during RoPDF evolution. This is overcome by introducing a kinetic-like defect term to the RoPDF equation, which is learned by assimilating in sparse, low-fidelity RoPDF estimates. Two assimilation methods are considered, namely nudging and deep neural networks, which are successfully tested against Monte Carlo simulations.

97 MATHEMATICS AND COMPUTING↗

A Study to Estimate the Effectiveness of Visual Testing Training for Aviation Maintenance Management

The Air Commerce Act of 1926 set the beginning for standards in aviation maintenance. Even after deregulation in the late l970s, maintenance standards and requirements still have not changed far from their initial criteria. After a potential candidate completes Federal Aviation Administration training prerequisites, they may test for their Airframe and Powerplant (A&P) certificate. Performing maintenance in the aviation industry for a minimum of three years, the technician may then test for their Inspection Authorization (IA). After receiving their Airframe and Powerplant certificate, a technician is said to have a license to perform. At no time within the three years to eligibility for Inspection Authorization are they required to attend higher-level inspection training. What a technician learns in the aviation maintenance industry is handed down from a seasoned technician to the new hire or is developed from lessons learned on the job. Only in Europe has the Joint Aviation Authorities (JAA) required higher-level training for their aviation maintenance technicians in order to control maintenance related accidents (Lu, 2005). Throughout the 1990s both the General Accounting Office (GAO) and the National Transportation Safety Board (NTSB) made public that the FAA is historically understaffed (GAO, 1996). In a safety recommendation the NTSB stated "The Safety Board continues to lack confidence in the FAA's commitment to provide effective quality assurance and safety oversight of the ATC system (NTSB, 1990)." The Federal Aviation Administration (FAA) has been known to be proactive in creating safer skies. With such reports you would suspect the FAA to also be proactive in developing more stringent inspection training for aviation maintenance technicians. The purpose of this study is to estimate the effectiveness of higher-level inspection training, such as Visual Testing (VT) for aviation maintenance technicians, to improve the safety of aircraft and to make recommendations to management with regard to the value of such training.

Law, Lewis Lyle↗