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At least 343 records · Page 19

Geoscience Laser Ranging System - Estimated accuracy of geodetic parameters and their dependence on system characteristics

Covariance analysis of the performance of the Geoscience Laser Ranging System (GLRS) indicates that three-dimensional relative positions can be recovered to an accuracy of several millimeters over spatial scales from a few kilometers to several hundred kilometers and over temporal scales as short as several days. The key factors influencing the accuracy are range noise, number of targets and their locations, system pointing capability, dwell time on the targets, orbital geometry, and gravity field uncertainties. Based on the present trade-off studies, GLRS is designed to provide range measurements with 10 mm or better accuracy, fire at a rate of 40 pulses-per-second, point over a cone extending to 50 deg from nadir, and operate with a dwell time on individual targets of 2 s or less. Given a strain rate of 10 to the -14th/s, estimated GLRS accuracy parameters suggest that the deformation can be detected in less than a month if it extends over 100 km and in less than 6 months if it extends over 10 km.

Cohen, Steven C.↗

ADS-B Mixed sUAS and NAS System Capacity Analysis and DAA Performance

Automatic Dependent Surveillance-Broadcast (ADS-B) technology was introduced more than twenty years ago to improve surveillance within the US National Airspace Space (NAS) as well as in many other countries. Via the NextGen initiative, implementation of ADS-B technology across the US is planned in stages between 2012 and 2025. ADS-B's automatic one second epoch packet transmission exploits on-board GPS-derived navigational information to provide position information, as well as other information including vehicle identification, ground speed, vertical rate and track angle. The purpose of this technology is to improve surveillance data accuracy and provide access to better situational awareness to enable operational benefits such as shorter routes, reduced flight time and fuel burn, and reduced traffic delays, and to allow air traffic controllers to manage aircraft with greater safety margins. Other than the limited amount of information bits per packet that can be sent, ADS-B's other hard-limit limitation is capacity. Small unmanned aircraft systems (sUAS) can utilize limited ADS-B transmission power, in general, thus allowing this technology to be considered for use within a combined NAS and sUAS environment, but the potential number and density of sUAS predicted for future deployment calls into question the ability of ADS-B systems to meet the resulting capacity requirement. Hence, studies to understand potential limitations of ADS-B to fulfill capacity requirements in various sUAS scenarios are of great interest. In this paper we, validate/improve on, previous work performed by the MITRE Corporation concerning sUAS power and capacity in a sUAS and General Aviation (GA) mixed environment. In addition, we implement its inherent media access control layer capacity limitations which was not shown in the MITRE paper. Finally, a simple detect and avoid (DAA) algorithm is implemented to display that ADS-B technology is a viable technology for a mixed NAS/sUAS environment even in proposed larger mixed density environments.

Matheou, Konstantin J.↗

ADS-B Mixed sUAS and NAS System Capacity Analysis and DAA Performance

Automatic Dependent Surveillance-Broadcast (ADS-B) technology was introduced more than twenty years ago to improve surveillance within the US National Airspace Space (NAS) as well as in many other countries. Via the NextGen initiative, implementation of ADS-B technology across the US is planned in stages between 2012 and 2025. ADS-B's automatic one second epoch packet transmission exploits on-board GPS-derived navigational information to provide position information, as well as other information including vehicle identification, ground speed, vertical rate and track angle. The purpose of this technology is to improve surveillance data accuracy and provide access to better situational awareness to enable operational benefits such as shorter routes, reduced flight time and fuel burn, and reduced traffic delays, and to allow air traffic controllers to manage aircraft with greater safety margins. Other than the limited amount of information bits per packet that can be sent, ADS-B's other hard-limit limitation is capacity. Small unmanned aircraft systems (sUAS) can utilize limited ADS-B transmission power, in general, thus allowing this technology to be considered for use within a combined NAS and sUAS environment, but the potential number and density of sUAS predicted for future deployment calls into question the ability of ADS-B systems to meet the resulting capacity requirement. Hence, studies to understand potential limitations of ADS-B to fulfill capacity requirements in various sUAS scenarios are of great interest. In this paper we, validate/improve on, previous work performed by the MITRE Corporation concerning sUAS power and capacity in a sUAS and General Aviation (GA) mixed environment. In addition, we implement its inherent media access control layer capacity limitations which was not shown in the MITRE paper. Finally, a simple detect and avoid (DAA) algorithm is implemented to display that ADS-B technology is a viable technology for a mixed NAS/sUAS environment even in proposed larger mixed density environments.

Matheou, Konstantin↗

The Ionized Gas and Nuclear Environment in NGC 3783: Variability and Modeling of the 900 ks CHANDRA Spectrum - IV

We present a detailed analysis of the 900 ks spectrum of NGC3783 obtained by Chandra in 2000-2001 (Kaspi et al. 2002). We split the data in various ways to look for time dependent and luminosity dependent spectral variations. This analysis, the measured equivalent widths of a large number of X-ray lines, and our photoionization calculations, lead us to the following conclusions: 1) NGC 3783 fluctuated in luminosity, by a factor N 1.5, during individual 170 ks observations. The fluctuations were not associated with significant spectral variations. 2) On a longer time scale, of 20-120 days, we discovered two very different spectral shapes that are noted the high state and the low state spectra. The observed changes between the two can be described as the appearance and disappearance of a soft continuum component. The spectral variations are not related, in a simple way, to the brightening or the fading of the short wavelength continuum, as observed in other objects. NGC3783 seems to be the first AGN to show this unusual behavior. 3) The appearance of the soft continuum component is consistent with beeing the only spectral variation and there is no need to invoke changes in the absorber s opacity. In particular, all absorption lines with reliable measurements show the same equivalent width, within the observational uncertainties, during high and low states. 4) Photoionization model calculations show that a combination of three ionization components, each split into two kinematic components, explain very well the intensity of almost all absorption lines and the bound-free absorption. The components span a large range of ionization and a total column of about 3 x 10(exp 22) per square centimeter Moreover, all components are thermally stable and are situated on the vertical branch of the stability curve.. This means that they are in pressure equilibrium and perhaps occupy the same volume of space. This is the first detection of such a multi-component equilibrium gas in AGN. 5) The only real discrepancy between the model and the observations is the wavelength of the iron M-shell UTA feature. This is most likely due to an underestimation of the dielectronic recombination O VI and discuss its possible origin. 6) The lower limit on the distance of the absorbing gas in NGC3783 is between 0.2 and 3.2 pc, depending of the specific ionization component. The constant pressure assumption imposes an upper limit of about 25 pc on the distance of the least ionized gas from the central sourec.

Netzer, Hagai↗

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

Babcock, Chad↗

Importance of Trade Dependencies for Agricultural Inputs: A Case Study of Finland

Approximately 80% of the world's population lives in countries that are dependent on food imports to sustain an adequate food supply. Besides these food imports, further dependencies also arise due to the requirements for agricultural inputs, including energy, fertilisers, feed and agricultural machinery. While the trade of agricultural inputs is relatively well represented in economic analysis, the quantification is often in terms of monetary values, and thus the assessments of the actual input quantities are very limited. In this paper, we develop a framework for analysis of the traded input quantities at the country-level and demonstrate its utility through an in-depth analysis of Finland's dependency on agricultural inputs. Further, we assess the importance of these inputs for domestic food production from a resilience perspective. We find that Finland, a country with relatively high food self-sufficiency but also a great dependency on imported agricultural inputs, experienced an increase in its dependency over the period 1996-2016. In case of trading partners, the story is more mixed: while trading partners for soybeans increased, those decreased in case of electricity while no significant change was observed in other commodities. In Finland, the rapeseed dependency on imports (ratio of net imports and consumption) grew from around 0% to almost 50% between the years 1987-2013. Changes for electricity remained substantially smaller, with dependency only slightly growing during the study period. Crude oil and soybean supplies are totally dependent on imports as neither is produced in Finland. Interestingly, the highest dependencies for agricultural inputs were on different countries than that for foodstuff imports. Thus, when identifying and assessing approaches to increase resilience to trade-related shocks, it is essential to understand both foodstuff and agricultural input dependencies within the global food system.

trade dependencies↗

The BioMole Facility: Advancement of In Situ Microbiome Analysis for the International Space Station

Characterization of the International Space Station (ISS) microbiome has been enabled by sample return and Earth-based analysis. As human exploration pushes beyond low-Earth orbit, microbial-related crew health, planetary protection, and space research requires in situ capabilities. Steps toward reducing Earth-dependence for complex sample analysis began in 2016 with the amplification of DNA within the miniPCR thermal cycler and DNA sequencing with the MinION sequencer onboard the ISS; for both, samples were prepared on Earth. In 2017, these platforms synergistically enabled the in-situ identification of unknown bacteria collected and cultured from ISS surfaces, thereby shifting the paradigm that microbial cultures had to be returned to Earth. The following year, a culture-independent, swab-to-sequencer method further advanced spaceflight microbiology, demonstrating that culturing could be excluded and provided enhanced insight into the bacterial profile of ISS surfaces. Based on the success of these payloads in confirming the ability to meet crew health identification requirements and the benefits accompanying a culture-independent method, the BioMole Facility was established by the medical operations Crew Health Care Systems team. BioMole is the set of hardware, consumables, and procedures required to support sample preparation and nanopore sequencing onboard the ISS. BioMole goals include expanding sample sources, comparing data to previous methods, demonstrating onboard data analytics, and validating new hardware. To date, comparative surface analysis, molecular- and culture-based, has been completed. Additionally, the demonstration of a sample-to-answer process was achieved when BioMole data was processed onboard using the IBM Open Data and AI Edge software platform installed on the ISS-residing Spaceborne Computer-2. The taxonomic profiles generated from the edge analysis were as expected and paralleled that of the downlinked processed data. Future BioMole efforts involve microbial profiling of the ISS water system, ISS validation of the MinION Mk1C, and an expansion to a research facility available to investigators.

Sarah L. Castro-Wallace↗

Bayes Analysis and Reliability Implications of Stress-Rupture Testing a Kevlar/Epoxy COPV Using Temperature and Pressure Acceleration

Composite Overwrapped Pressure Vessels (COPVs) that have survived a long service time under pressure generally must be recertified before service is extended. Flight certification is dependent on the reliability analysis to quantify the risk of stress rupture failure in existing flight vessels. Full certification of this reliability model would require a statistically significant number of lifetime tests to be performed and is impractical given the cost and limited flight hardware for certification testing purposes. One approach to confirm the reliability model is to perform a stress rupture test on a flight COPV. Currently, testing of such a Kevlar49 (Dupont)/epoxy COPV is nearing completion. The present paper focuses on a Bayesian statistical approach to analyze the possible failure time results of this test and to assess the implications in choosing between possible model parameter values that in the past have had significant uncertainty. The key uncertain parameters in this case are the actual fiber stress ratio at operating pressure, and the Weibull shape parameter for lifetime; the former has been uncertain due to ambiguities in interpreting the original and a duplicate burst test. The latter has been uncertain due to major differences between COPVs in the database and the actual COPVs in service. Any information obtained that clarifies and eliminates uncertainty in these parameters will have a major effect on the predicted reliability of the service COPVs going forward. The key result is that the longer the vessel survives, the more likely the more optimistic stress ratio model is correct. At the time of writing, the resulting effect on predicted future reliability is dramatic, increasing it by about one "nine," that is, reducing the predicted probability of failure by an order of magnitude. However, testing one vessel does not change the uncertainty on the Weibull shape parameter for lifetime since testing several vessels would be necessary.

Phoenix, S. Leigh↗

Sporadic E Morphology from GPS-CHAMP Radio Occultation

The scintillations of phase and amplitude in terms of signal-to-noise ratio (SNR) of the GPS radio occultation signal are caused by thin ionization layers. These thin irregular electron density layers in the E region ionosphere are often called sporadic E (Es). For a monthly retrieval of Es morphology we use the variances of the phase and SNR fluctuations of worldwide ~6000 GPS/CHAMP occultations in the E region. The Es climatology is studied globally with the SNR and phase variances in terms of monthly zonal means, seasonal maps, and diurnal and long-term variations. The zonal mean variances reveal strong, extended Es activities at summertime midlatitudes but weak, confined activities in wintertime high latitudes, peaking at ~105 km. Global maps at 105-km altitude show clear dependence of Es activities on the geomagnetic dip angle, where the summertime midlatitude Es occurs mostly at dip angles of 30 deg. - 60 deg. and the wintertime high-latitude enhancement occurs mostly at dip angles greater than 80 deg. The midlatitude Es variances exhibit a strong semidiurnal variation with peak hours near 0800 1000 and 2000 local solar time, respectively. The peak hours are delayed slightly with decreasing height, suggesting influences from the semidiurnal tide. To provide more insights on the observed SNR and phase variances, we model radio wave propagation for the CHAMP observing geometry under several perturbed cases in the E region ionosphere. The model simulations indicate that the SNR variance has the maximum response to Es perturbations at vertical wavelengths of 1.2 km, whereas the phase response maximizes at ~2 km (for the 1-s variance analysis). The characteristic scale depends little on the truncation time used in the SNR variance analysis, but it increases with the truncation time for the phase variances. Initial studies show that reasonable global Es morphology can be produced on a monthly and seasonal basis with the CHAMP one-antenna occultations. Better results from other existing and upcoming GPS occultation missions are anticipated in future studies, and they will significantly improve our understanding of this important phenomenon.

signal to noise ration (SNR)↗

Quantitative approaches for multiscale structural analysis with atomic resolution electron microscopy

Atomic-resolution imaging with scanning transmission electron microscopy is a powerful tool for characterizing the nanoscale structure of materials, in particular features such as defects, local strains, and symmetry-breaking distortions. In addition to advanced instrumentation, the effectiveness of the technique depends on computational image analysis to extract meaningful features from complex datasets recorded in experiments, which can be complicated by the presence of noise and artifacts, small or overlapping features, and the need to scale analysis over large representative areas. Here, we present image analysis approaches which synergize real and reciprocal space information to efficiently and reliably obtain meaningful structural information with picometer scale precision across hundreds of nanometers of material from atomic-resolution electron microscope images. Damping superstructure peaks in reciprocal space allows symmetry-breaking structural distortions to be disentangled from other sources of inhomogeneity and measured with high precision. Real-space fitting of the wavelike signals resulting from Fourier filtering enables absolute quantification of lattice parameter variations and strain, as well as the uncertainty associated with these measurements. Implementations of these algorithms are made available as an open source python package.

36 MATERIALS SCIENCE↗

Regression Model Optimization for the Analysis of Experimental Data

A candidate math model search algorithm was developed at Ames Research Center that determines a recommended math model for the multivariate regression analysis of experimental data. The search algorithm is applicable to classical regression analysis problems as well as wind tunnel strain gage balance calibration analysis applications. The algorithm compares the predictive capability of different regression models using the standard deviation of the PRESS residuals of the responses as a search metric. This search metric is minimized during the search. Singular value decomposition is used during the search to reject math models that lead to a singular solution of the regression analysis problem. Two threshold dependent constraints are also applied. The first constraint rejects math models with insignificant terms. The second constraint rejects math models with near-linear dependencies between terms. The math term hierarchy rule may also be applied as an optional constraint during or after the candidate math model search. The final term selection of the recommended math model depends on the regressor and response values of the data set, the user s function class combination choice, the user s constraint selections, and the result of the search metric minimization. A frequently used regression analysis example from the literature is used to illustrate the application of the search algorithm to experimental data.

Ulbrich, N.↗

Linearized unsteady jet analysis

The introduction of a time dependency into a jet flow to change the rate at which it mixes with a coflowing stream or ambient condition is investigated. The advantages and disadvantages of the unsteady flow are discussed in terms of steady state mass and momentum transfer. A linear system which is not limited by frequency constraints and evolves through a simplification of the equations of motion is presented for the analysis of the unsteady flow field generated by the time dependent jet.

Viets, H.↗

Fiducial-cosmology-dependent systematics for the DESI 2024 full-shape analysis

We assess the impact of the fiducial cosmology choice on cosmological inference from full-shape (FS) fits of the galaxy power spectrum in the DESI 2024 Data Release 1 (DR1). Using a suite of AbacusSummit DR1 mock catalogues based on the Planck 2018 best-fit cosmology, we quantify potential systematic shifts introduced by analysing the data under five secondary cosmologies — featuring variations in matter density, thawing dark energy, higher effective number of neutrino species, reduced clustering amplitude, and the DESI DR1 BAO best-fit w 0 w a CDM cosmology — relative to DESI's baseline Planck 2018 cosmology. We investigate two complementary FS analysis approaches: full-modelling (FM) and ShapeFit (SF), each with distinct sensitivities to the assumed fiducial model. Across all tracers, we find for FM that systematic shifts induced by fiducial cosmology mismatches remain well below the DESI DR1 statistical uncertainties, with maximum deviations of 0.22σ DR1 in ΛCDM scenarios and 0.12σ DR1+SN when including SN Ia mock data in extended w 0 w a CDM fits. For SF, the shifts in the compressed parameters remain below 0.45σ DR1 for all tracers and cosmologies.

dark energy experiments↗

Competition between roughness and strength for scale-dependent surfaces

Rocks famously have scale-dependent strength, yet the actual dependence is notoriously hard to measure or incorporate into any theoretical framework. Natural rough surfaces present an opportunity to solve the problem. Surfaces sliding in shear evolve as protrusions collide. These asperities can deform or break, thus creating a new surface shape. In particular, natural surfaces have roughness at all scales as well as scale-dependent strength. Based on a scaling analysis, we have previously suggested that the scale-dependent aspect ratio of steady-state surfaces should be proportional to the scale-dependent shear strain at yield. If true, scale-dependent strength could easily be inferred from natural surfaces. Thus, moving beyond the scaling argument to a rigorous treatment of scale-dependent strength for multiscale rough surfaces in shear is important. However, analytic frameworks for analyzing multiscale problems are challenging, as conventional continuum mechanics typically involves a single value for a material property across scales. Here, in this work, we build on the formalism of Persson (2001) that presents a method to compute contact area for rough surfaces with a prescribed topographic spectrum using a stochastic differential equation. The Persson formalism allows for plastic yield under normal loading of otherwise elastic materials and leaves open the possibility of scale-dependent yield stress. In this study, we pursue this route to develop a theory and numerical results for the yielding of a rough, elastoplastic surface with scale-dependent yield stress. Here, we examine surfaces for which the power spectrum of the topography 𝐶 and yield stress 𝑌 follow power laws as a function of scale 𝜆, such that 𝐶∼𝜆 −𝑚 and 𝑌∼𝜆 −𝑛 , respectively. In this formal treatment of the problem, we focus on surfaces in contact and the resulting yield and do not impose shear. Numerical solutions show that the deviation from the elastic scaling solution is bounded as expected by the prior 1D heuristic scaling argument that anticipates the Hurst exponent as 1−𝑛. We also show that the plasticity is expected to erode the contacts if 𝑚 is lower than 𝑛−3, which corresponds to a Hurst exponent lower than 1−𝑛/2. This result is rigorously sound for 2D, i.e., realistic surfaces, and quantitatively different than the prior scaling argument. The theory now permits a correspondingly quantitative approach to interpreting natural surfaces.

elasticity↗

Adjoint-Based Methodology for Time-Dependent Optimization

This paper presents a discrete adjoint method for a broad class of time-dependent optimization problems. The time-dependent adjoint equations are derived in terms of the discrete residual of an arbitrary finite volume scheme which approximates unsteady conservation law equations. Although only the 2-D unsteady Euler equations are considered in the present analysis, this time-dependent adjoint method is applicable to the 3-D unsteady Reynolds-averaged Navier-Stokes equations with minor modifications. The discrete adjoint operators involving the derivatives of the discrete residual and the cost functional with respect to the flow variables are computed using a complex-variable approach, which provides discrete consistency and drastically reduces the implementation and debugging cycle. The implementation of the time-dependent adjoint method is validated by comparing the sensitivity derivative with that obtained by forward mode differentiation. Our numerical results show that O(10) optimization iterations of the steepest descent method are needed to reduce the objective functional by 3-6 orders of magnitude for test problems considered.

Yamaleev, N. K.↗

Analysis of Terminal Deletions using a Generalized Time-Dependent Model of Radiation-Induced Formation of Chromosomal Aberrations

We have developed a model that can simulate different types of radiation induced chromosomal aberrations (CA's) and can provide predictions on the frequency and size of chromosomes with terminal deletions. Chromosomes with terminal deletions lack telomeres and this can elicit sister chromatid unions and the prolonged breakage/fusion/bridge (B/F/B) cycles that have been observed in mammalian tumors. The loss of a single telomere has been shown to cause extensive genomic instability through the B/F/B cycle process. Our model uses a stochastic process of DNA broken end joining, in which a realistic spectrum of CA's is created from improperly joined DNA free ends formed by DNA double strand breaks (DSBs). The distribution of the DNA free ends is given by a mechanistic model that takes into account the chromatin structure and track structure for high-LET radiation. The model allows for DSB clustering from high-LET radiation and simulates the formation of CA's in stages that correspond to the actual time after radiation exposure. The time scale for CA formation is derived from experimental data on DSB repair kinetics. At any given time a nucleus may have intact chromosomes, CA's, and/or unrepaired fragments, some of which are defined as terminal deletions, if they are capped by one telomere. The model produces a spectrum of terminal deletions with their corresponding probabilities and size distributions for different heavy ions exposures for the first division after exposure. This data provides valuable information because there is limited experimental data available in the literature on the on the actual size of terminal deletions. We compare our model output to the available experimental data and make a reasonable extrapolation on the number of chromosomes lacking telomeres in human lymphocytes exposed to heavy ions. This model generates data which may lead to predictions on the rate of genomic instability in cells after exposure to high charge and energy nuclei affecting astronauts during space missions.

Ponomarev, Artem L.↗

Boundary flexibility method of component mode synthesis using static Ritz vectors

A method of dynamic substructuring is presented which provides for the incorporation of a set of static Ritz vectors, referred to as boundary flexibility vectors, as a replacement and/or supplement to conventional eigenvectors in component mode synthesis. The suggested boundary flexibility Ritz vectors are generated by an extension of Wilson's load-dependent Ritz vector algorithm for transient dynamic analysis. The extended algorithm is not load-dependent, is applicable to both fixed-and free-interface components, and results in a general component mode synthesis model appropriate for any type of dynamic analysis.

Abdallah, A. A.↗

An Efficient Reachability Analysis Algorithm

A document discusses a new algorithm for generating higher-order dependencies for diagnostic and sensor placement analysis when a system is described with a causal modeling framework. This innovation will be used in diagnostic and sensor optimization and analysis tools. Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in-situ platforms. This algorithm will serve as a power tool for technologies that satisfy a key requirement of autonomous spacecraft, including science instruments and in-situ missions.

Vatan, Farrokh↗