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At least 163 records · Page 9

Evaluation of Tablet-Based Methods for Assessment of Contrast Sensitivity

Some astronauts have suffered degradation of vision during long-duration space flight, suffering from a condition that has come to be known as Spaceflight Associated Neuro-ocular Syndrome (SANS). While related morphological changes can be observed with imaging technologies such as optical coherence tomography (OCT), it may be useful to have a rapid method for functional vision assessment. In this paper, we compare three tablet-based methods for rapid assessment of contrast sensitivity. First, a relatively novel method developed expressly for touch screens, in which the subject ”swipes” a frequency/contrast sweep grating to indicate the boundary between visible and invisible patterns; second, a method-of-adjustment task in which the subject adjusts the contrast of a grating patch up and down to bracket the visual threshold; and third, a traditional temporal two-alternative forced choice (2AFC) task, in which the subject is presented with a near-threshold stimulus in one of two intervals, and must report the interval containing the stimulus. The swipe method shows variability comparable to the 2AFC method, and shows good agreement in estimates of the spatial frequency of peak sensitivity. The absolute sensitivity estimated with the swipe method is higher than that of the other methods, perhaps because subjects are biased to trace outside of the visible pattern region, or perhaps due to stimulus differences.

Mulligan, Jeffrey B.

Main bearing response in a waked 15-MW floating wind turbine in below-rated conditions

Increased wind turbine size raises unknowns related to structural flexibility. Moreover, moving to deeper waters, component reliability becomes more critical. This work investigates main bearing response dependence on drivetrain flexibility and wake impingement in a two-turbine wind farm. A 15-MW floating direct-drive turbine is considered. Large eddy simulations (LES) are employed to model neutral, stable and unstable atmospheric conditions at below-rated mean wind speed, while the engineering codes OpenFAST and FAST.Farm simulate turbine and wake behavior. Results indicate significant sensitivities in fatigue estimates to lateral distance between the upstream and downstream turbine. The trends are most substantial in stable conditions, where the waked downwind main bearing sees twice the fatigue damage estimates of the upstream turbine for one position and 50% for another. Main bearing fatigue sensitivity to drivetrain flexibility is minor, while properly including generator rotor inertia loads is important for the axial forces of the locating (axially fixed) bearing, especially in stable conditions.

17 WIND ENERGY

Deep Learning Reconstruction of Daily Soil CO 2 Efflux Reveals Biogeochemical Insights and Reduces Annual Estimate Uncertainty Despite Limited Daily Predictability

Soil CO 2 efflux is commonly measured monthly or seasonally, leaving daily dynamics poorly resolved and contributing to global estimation uncertainty. We trained a single Long Short-Term Memory (LSTM) model to predict daily soil CO 2 efflux across 82 globally distributed sites in COSORE, with 0.2%–46.9% daily data coverage from 2003 to 2020. Despite using far fewer sites than are typically used to train a single deep learning model, with observations biased toward temperate mesic sites, the LSTM model performed well at approximately one-third of sites, reconstructed nearly 2 decades of daily efflux, and outperformed commonly used approaches for estimating daily efflux when applied to the same data set. Performance was weakest at pronounced peaks and troughs and at non-temperate sites with <1.5 years of observations and irregular data patterns. Nevertheless, annual efflux from reconstructed daily data had <40% error even at underperforming sites, substantially improving estimates derived from monthly and seasonal sampling (maximum errors of 95% and 136%, respectively). Temperature sensitivity (Q 10 ) estimated from reconstructed daily predictions closely matched estimates from daily observations, whereas Q 10 values derived from monthly or seasonal observations deviated substantially, suggesting that coarse temporal sampling may contribute to uncertainty in reported Q 10 values. Consistent daily reconstructions further enabled trend analyses for well-performing, predominantly temperate sites and showed increasing soil CO 2 efflux at most sites from 2003 to 2020, with more variable summer trends. Despite limitations, these results demonstrate the potential of LSTM models to reconstruct daily soil CO 2 efflux and reduce estimation uncertainties from sparse observations.

Smykalov, Valerie [Pennsylvania State University,

Gamma-ray burst constraints on the galactic frequency of extra-solar Oort clouds

With the strong CGRO/BATSE evidence that most gamma-ray bursts do not come from galactic neutron stars, models involving the accretion of a comet onto a neutron star (NS) no longer appear to be strong contenders for explaining the majority of bursts. If this is the case, then it is worth asking whether the lack of an observed galactic gamma-ray burst population provides a useful constraint on the number of comets and comet clouds in the galaxy. Owing to the previously unrecognized structural weakness of cometary nuclei, we find the capture cross sections for comet-NS events to be much higher than previously published estimates, with tidal breakup at distances R(sub b) approximately equals to 4 x 10(exp 10) cm from the NS. As a result, impacts of comets onto field NS's penetrating the Oort Clouds of other stars are found to dominate all other galactic NS-comet capture rates by a factor of 100. This in turn predicts that if comet clouds are common, there should be a significant population of repeater sources with (1) a galactic distribution, (2) space-correlated repetition, and (3) a wide range of peak luminosities and luminosity time histories. If all main sequences stars have Oort Clouds like our own, we predict approximately 4000 such repeater sources in the Milky Way at any time, each repeating on timescales of months to years. Based on estimates of the sensitivity of the CGRO/BATSE instrument and assuming isotropic gamma-ray beaming from such events, we estimate that a population of approximately 20-200 of these galactic NS-Oort Cloud gamma-ray repeater sources should be detectable by CGRO. In addition, if giant planet formation is common in the galaxy, we estimate that the accretion of isolated comets injected to the interstellar medium by giant planet formation should produce an additional source of galactic, nonrepeating events. Comparing these estimates to the three to four soft gamma-ray repeater sources detected by BATSE, one is forced to conclude that (1) comet impacts on NS's are inefficient at producing gamma-rays; or (2) the gamma-rays from such events are highly beamed; or (3) the fraction of stars in the galaxy with Oort Cloud like our own is not higher than a few percent.

Shull, J. Michael

Gamma-ray burst constraints on the galactic frequency of extrasolar Oort Clouds

With the strong Compton Gamma-Ray Observatory/Burst and Transient Source Experiment (CGRO/BATSE) evidence that most gamma-ray bursts do not come from galactic neutron stars, models involving the accretion of a comet onto a neutron star (NS) no longer appear to be strong contenders for explaining the majority of bursts. If this is the case, then it is worth asking whether the lack of an observed galactic gamma-ray burst population provides a useful constraint on the number of comets and comet clouds in the galaxy. Owing to the previously unrecognized structural weakness of cometary nuclei, we find the capture cross sections for comet-NS events to be much higher than previously published estimates, with tidal breakup at distances R(sub b) approx. equals 4 x 10(exp 10) cm from the NS. As a result, impacts of comets onto field NSs penetrating the Oort Clouds of other stars are found to dominate all other galactic NS-comet capture rates by a factor of 100. This in turn predicts that if comet clouds are common, there should be a significant population of repeater sources with (1) a galactic distribution, (2) space-correlated repetition, and (3) a wide range of peak luminosities and luminosity time histories. If all main sequence stars have Oort Clouds like our own, we predict approximately 4000 such repeater sources in the Milky Way at any time, each repeating on time scales of months to years. Based on estimates of the sensitivity of the CGRO/BATSE instrument and assuming isotropic gamma-ray beaming from such events, we estimate that a population of approximately 20-200 of these galactic NS-Oort Cloud gamma-ray repeater sources should be detectable by CGRO. In addition, if giant planet formation is common in the galaxy, we estimate that the accretion of isolated comets injected to the interstellar medium by giant planet formation should produce an additional source of galactic, nonrepeating, events. Comparing these estimates to the 3-4 soft gamma-ray repeater sources detected by BATSE, one is forced to conclude that (1) comet impacts on NSs are inefficient at producing gamma rays; or (2) the gamma rays from such events are highly beamed; or (3) the fraction of stars in the galaxy with Oort Clouds like our own is not higher than a few percent.

Shull, J. Michael

Variability in Galactic Cosmic Radiation- Induced DNA Damage Response in Inbred Mice Is Modulated by Genetics

In radiation biology, the ability to predict cancer risk associated with exposure to low doses of high-LET (Linear Energy Transfer) ionizing radiation remains a challenge. Epidemiological methods lack the sensitivity and power to provide detailed risk estimates for cancer and ignore individual sensitivity. We have hypothesized that DNA repair capacity is the primary factor differentiating peoples radiation sensitivity. We previously showed in immortalized human cell lines that characterizing the dose and time dependence of p53-binding protein 1 (53BP1) foci formation in the nucleus following X-rays exposure is sufficient to predict DNA repair response to any other LET in the same cell line. We now tested this hypothesis across a population of mice with different genetic background. Fibroblast cells were extracted and cultivated from 76 individual mice from 15 different strains and exposed to HZE (high (H) atomic number (Z) and energy (E) galactic cosmic ray particles) particles and X-rays. Individual radiation sensitivities were investigated by high throughput measurement of DNA repair kinetics that evaluated 53bp1 foci numbers as a surrogate for DNA double-strand breaks at various times post-irradiation. Instead of just counting foci which can be hard to distinguish for high-LET or high doses, we also took into account the track structure of high-LET particles to compute the remaining number of unrepaired tracks as a function of time post-irradiation. As expected, the percentage of unrepaired track over a 48 hours follow-up period increased with LET. In addition, repair rate was modulated by genetics, with animals from the same strain showing small variance while large rate differences were observed between strains. Radiation strain sensitivity ranking was estimated based on repair rates from exposure to each LET evaluated in this work, and ranking for high-LET correlated better with ranking from high dose of X-ray, not low dose. At the in-vivo level, drops in T-cells and B-cells number measured 24 hours after 0.1 Gy (Gray) X-ray exposure, correlated with slower DNA repair kinetic in fibroblast cells of the same strains of mice. At the genomic level, mouse genome wide association (GWA) analysis identified seven significant genetic loci on chromosomes 2, 3, 7, 10, 11, 13 and 19 with different significance depending on the LET. Interestingly, for the two highest LET, a common locus on Chromosome 10 was identified with high enrichment for DNA repair associated genes.Overall, this work suggests that repair kinetics of primary skin fibroblasts is a good surrogate marker for in-vivo radiation sensitivities in other tissues and that this response is modulated by genetics. Our study also confirms that DNA repair kinetics following high doses of X-ray can be used to predict radiation sensitivity to high-LET.

High-LET Radiation

Probability techniques for reliability analysis of composite materials

Traditional design approaches for composite materials have employed deterministic criteria for failure analysis. New approaches are required to predict the reliability of composite structures since strengths and stresses may be random variables. This report will examine and compare methods used to evaluate the reliability of composite laminae. The two types of methods that will be evaluated are fast probability integration (FPI) methods and Monte Carlo methods. In these methods, reliability is formulated as the probability that an explicit function of random variables is less than a given constant. Using failure criteria developed for composite materials, a function of design variables can be generated which defines a 'failure surface' in probability space. A number of methods are available to evaluate the integration over the probability space bounded by this surface; this integration delivers the required reliability. The methods which will be evaluated are: the first order, second moment FPI methods; second order, second moment FPI methods; the simple Monte Carlo; and an advanced Monte Carlo technique which utilizes importance sampling. The methods are compared for accuracy, efficiency, and for the conservativism of the reliability estimation. The methodology involved in determining the sensitivity of the reliability estimate to the design variables (strength distributions) and importance factors is also presented.

Wetherhold, Robert C.

Efficacy of Climate Forcings in PDRMIP Models

Quantifying the efficacy of different climate forcings is important for understanding the real‐world climate sensitivity. This study presents a systematic multimodel analysis of different climate driver efficacies using simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). Efficacies calculated from instantaneous radiative forcing deviate considerably from unity across forcing agents and models. Effective radiative forcing (ERF) is a better predictor of global mean near‐surface air temperature (GSAT) change. Efficacies are closest to one when ERF is computed using fixed sea surface temperature experiments and adjusted for land surface temperature changes using radiative kernels. Multimodel mean efficacies based on ERF are close to one for global perturbations of methane, sulfate, black carbon, and insolation, but there is notable intermodel spread. We do not find robust evidence that the geographic location of sulfate aerosol affects its efficacy. GSAT is found to respond more slowly to aerosol forcing than CO2 in the early stages of simulations. Despite these differences, we find that there is no evidence for an efficacy effect on historical GSAT trend estimates based on simulations with an impulse response model, nor on the resulting estimates of climate sensitivity derived from the historical period. However, the considerable intermodel spread in the computed efficacies means that we cannot rule out an efficacy‐induced bias of ±0.4 K in equilibrium climate sensitivity to CO2 doubling when estimated using the historical GSAT trend.

T B Richardson

Understanding Differences in Upper Stratospheric Ozone Response to Changes in Chlorine and Temperature as Computed Using CCMVal Models

Projections of future ozone levels are made using models that couple a general circulation model with a representation of atmospheric photochemical processes, allowing interactions among photochemical processes, radiation, and dynamics. Such models are known as chemistry and climate models (CCMs). Although developed from common principles and subject to the same boundary conditions, simulated ozone time series vary for projections of changes in ozone depleting substances (ODSs) and greenhouse gases. In the upper stratosphere photochemical processes control ozone level, and ozone increases as ODSs decrease and temperature decreases due to greenhouse gas increase. Simulations agree broadly but there are quantitative differences in the sensitivity of ozone to chlorine and to temperature. We obtain insight into these differences in sensitivity by examining the relationship between the upper stratosphere annual cycle of ozone and temperature as produced by a suite of models. All simulations conform to expectation in that ozone is less sensitive to temperature when chlorine levels are highest because chlorine catalyzed loss is nearly independent of temperature. Differences in sensitivity are traced to differences in simulated temperature, ozone and reactive nitrogen when chlorine levels are close to background. This work shows that differences in the importance of specific processes underlie differences in simulated sensitivity of ozone to composition change. This suggests a) the multi-model mean is not a best estimate of the sensitivity of upper ozone to changes in ODSs and temperature; b) the spread of values is not an appropriate measure of uncertainty.

Douglass, A. R.

Soil Moisture Buffers the Impact of Precipitation Variability on Ecosystem Productivity

Water availability governs ecosystem productivity, yet estimates of vegetation sensitivity to water can differ greatly depending on whether the sensitivity is examined spatially or temporally. In particular, the spatial sensitivity is often reported to be much stronger than temporal sensitivities, leading to highly uncertain projections of ecosystem responses to future climate change when using space-for-time substitution. The large difference between spatial and temporal sensitivities remains unexplained. Prior research, however, primarily relied on precipitation as the water availability proxy, whereas vegetation responds to soil moisture. Here, we combined satellite estimates of vegetation productivity with soil moisture data across water-limited ecosystems of the continental United States (CONUS) to identify a convergent sensitivity of productivity to water availability. Using precipitation, we show that temporal sensitivity is 66% lower than spatial sensitivity overall. Our analysis identified the cause of the difference to be primarily driven by the seasonal variability of water availability, rooting depth, and soil properties. When using soil moisture instead of precipitation, we observed widespread convergence in the spatial and temporal sensitivities—that is, the two sensitivities became much more similar in magnitude across all water-limited ecosystems within CONUS. These results show that overlooking soil hydrology can inflate perceived discrepancies between spatial and temporal vegetation sensitivities, leading to biased projections of ecosystem dynamics under future hydro-climatic change.

Wang, Huiqi [University of California, Berkeley, C

Southern California Megacity CO2, CH4, and CO Flux Estimates Using Ground- and Space-Based Remote Sensing and a Lagrangian Model

We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the So-CAB to be 104±26 Tg CO2 yr(exp -1) for the study period of July 2013–August 2016. We obtain a slightly higher estimate of 120±30 Tg CO2 yr(exp -1) using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360±90 Gg CH4 y(exp -1)) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342–440 Gg CH4 yr(exp -1)). CO emissions are estimated at 487±122 Gg CO yr(exp -1), much lower than previous top-down estimates (1440 Gg CO yr(exp -1)). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25%, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.

Total Carbon Column Observing Network (TCCON)

Efficient calculation of optimum design sensitivity

Two methods for obtaining the sensitivity of an optimized design to changes in problem parameters are presented. The first-order method uses gradient information to estimate the required sensitivity. The second-order method uses second derivatives of the design objective and constraint functions to provide a quadratic approximation to the new design which results from changing the specified parameter. It is shown that the sensitivity of the optimized design may be discontinuous with respect to the new parameter. This discontinuity is accounted for in the present methods. These methods are compared to a previous approach based on the Kuhn-Tucker necessary conditions for optimality. It is shown that the present methods provide the appropriate sensitivity information in an efficient manner. The methods are demonstrated by a structural synthesis example.

Vanderplaats, G. N.

Sensitivity analysis of the add-on price estimate for the silicon web growth process

The web growth process, a silicon-sheet technology option, developed for the flat plate solar array (FSA) project, was examined. Base case data for the technical and cost parameters for the technical and commercial readiness phase of the FSA project are projected. The process add on price, using the base case data for cost parameters such as equipment, space, direct labor, materials and utilities, and the production parameters such as growth rate and run length, using a computer program developed specifically to do the sensitivity analysis with improved price estimation are analyzed. Silicon price, sheet thickness and cell efficiency are also discussed.

Mokashi, A. R.

Evaluation of bio-optical algorithms to remotely sense marine primary production from space

In situ bio-optical measurements from several oceanographic campaigns were analyzed to derive a direct relationship between water column primary production P (sub t) ocean color as expressed by the ratio of reflectances R (sub 1) at 440 nm and R (sub 3) at 550 nm and photosynthetically available radiation (PAR). The study is restricted to the Morel case I waters for which the following algorithm is proposed: log (P(sub f)) = -4.286 - 1.390 log (R(sub 1)/R(sub3)) + 0.621 log (PAR), with P(sub t) in g C m(exp -2)/d and PAR in J m(exp -2)/d. Using this algorithm the rms accuracy of primary production estimate is 0.17 on a logarithmic scale, i.e., a factor of 1.5. Using spectral reflectance measurements in the entire visible spectral range, the central wavelength, spectral bandwidth, and radiometric noise level requirements are investigated for the channels to be used by an ocean color space mission dedicated to estimating global marine primary production and the associated carbon fluxes. Nearly all the useful information is provided by two channels centered at 440 nm and 550 nm, but the accuracy of primary production estimate appears weakly sensitive to spectral bandwidth, which, consequently, may be enlarged by several tens of nanometers. The sensitivity to radiometric noise, on the contrary, is strong, and a noise equivalent reflectance of 0.005 degraded the accuracy on the primary production estimate by a factor 2 (0.14-0.25 on a logarithmic scale). The results should be applicable to evaluating the primary production of oligotrophic and mesotrophic waters, which constitute most of the open ocean.

Berthelot, Beatrice

Use of robust estimators in parametric classifiers

The parametric approach to density estimation and classifier design is a well studied subject. The parametric approach is desirable because basically it reduces the problem of classifier design to that of estimating a few parameters for each of the pattern classes. The class parameters are usually estimated using maximum-likelihood (ML) estimators. ML estimators are, however, very sensitive to the presence of outliers. Several robust estimators of mean and covariance matrix and their effect on the probability of error in classification are examined. Comments are made about alpha-ranked (alpha-trimmed) estimators.

Safavian, S. Rasoul

Development and Applications of a Stage Stacking Procedure

The preliminary design of multistage axial compressors in gas turbine engines is typically accomplished with mean-line methods. These methods, which rely on empirical correlations, estimate compressor performance well near the design point, but may become less reliable off-design. For land-based applications of gas turbine engines, off-design performance estimates are becoming increasingly important, as turbine plant operators desire peaking or load-following capabilities and hot-day operability. The current work develops a one-dimensional stage stacking procedure, including a newly defined blockage term, which is used to estimate the off-design performance and operability range of a 13-stage axial compressor used in a power generating gas turbine engine. The new blockage term is defined to give mathematical closure on static pressure, and values of blockage are shown to collapse to curves as a function of stage inlet flow coefficient and corrected shaft speed. In addition to these blockage curves, the stage stacking procedure utilizes stage characteristics of ideal work coefficient and adiabatic efficiency. These curves are constructed using flow information extracted from computational fluid dynamics (CFD) simulations of groups of stages within the compressor. Performance estimates resulting from the stage stacking procedure are shown to match the results of CFD simulations of the entire compressor to within 1.6% in overall total pressure ratio and within 0.3 points in overall adiabatic efficiency. Utility of the stage stacking procedure is demonstrated by estimation of the minimum corrected speed which allows stable operation of the compressor. Further utility of the stage stacking procedure is demonstrated with a bleed sensitivity study, which estimates a bleed schedule to expand the compressors operating range.

Kulkarni, Sameer

Making Sense of Palaeoclimate Sensitivity

Many palaeoclimate studies have quantified pre-anthropogenic climate change to calculate climate sensitivity (equilibrium temperature change in response to radiative forcing change), but a lack of consistent methodologies produces a wide range of estimates and hinders comparability of results. Here we present a stricter approach, to improve intercomparison of palaeoclimate sensitivity estimates in a manner compatible with equilibrium projections for future climate change. Over the past 65 million years, this reveals a climate sensitivity (in K W−1 m2) of 0.3-1.9 or 0.6-1.3 at 95% or 68% probability, respectively. The latter implies a warming of 2.2-4.8 K per doubling of atmospheric CO2, which agrees with IPCC estimates.

Rohling, E. J.

Satellite radiation observations and climate theory

The representative applications of satellite observations of the earth radiation budget in climate studies are discussed. Consideration is given to the use of satellite observational data for validating numerical estimates of the sensitivity of longwave radiation, surface temperature, and cloud amount to changes in the radiation budget. Particular emphasis is given to the application of satellite observations to the validation of temperature estimates obtained from the NOAA Seasonal Hemispheric Zonal Average Model (SZHAM).

Ohring, G.