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At least 1,729 records · Page 96

An infrared radiation routine for use in numerical atmospheric models

Previous methods for calculating radiative fluxes due to water vapor and CO2 absorption bands are extended to take into consideration the entire water vapor and CO2 bands, including e-type absorption in the window region and the overlapping of different absorptions. Cooling rate profiles in the water vapor bands for a tropical atmosphere were computed by a detailed line-by-line method and by a far-wing approximation method, and the error of both methods is less than 0.2 C/day. Cooling rate profiles in the 15 micron band including overlapping of CO2 absorption with water vapor were calculated by a method in which flux transmittance is computed by means of a linear expansion and the multiplication rule, and maximum errors of 0.3 C/day were found in comparison with the exact line-by-line method.

Chow, M.-D.↗

Feedback control laws for highly maneuverable aircraft

During the first half of the year, the investigators concentrated their efforts on completing the design of control laws for the longitudinal axis of the HARV. During the second half of the year they concentrated on the synthesis of control laws for the lateral-directional axes. The longitudinal control law design efforts can be briefly summarized as follows. Longitudinal control laws were developed for the HARV using mu synthesis design techniques coupled with dynamic inversion. An inner loop dynamic inversion controller was used to simplify the system dynamics by eliminating the aerodynamic nonlinearities and inertial cross coupling. Models of the errors resulting from uncertainties in the principal longitudinal aerodynamic terms were developed and included in the model of the HARV with the inner loop dynamic inversion controller. This resulted in an inner loop transfer function model which was an integrator with the modeling errors characterized as uncertainties in gain and phase. Outer loop controllers were then designed using mu synthesis to provide robustness to these modeling errors and give desired response to pilot inputs. Both pitch rate and angle of attack command following systems were designed. The following tasks have been accomplished for the lateral-directional controllers: inner and outer loop dynamic inversion controllers have been designed; an error model based on a linearized perturbation model of the inner loop system was derived; controllers for the inner loop system have been designed, using classical techniques, that control roll rate and Dutch roll response; the inner loop dynamic inversion and classical controllers have been implemented on the six degree of freedom simulation; and lateral-directional control allocation scheme has been developed based on minimizing required control effort.

Garrard, William L.↗

Methods to Improve the Maintenance of the Earth Catalog of Satellites During Severe Solar Storms

The objective of this thesis is to investigate methods to improve the ability to maintain the inventory of orbital elements of Earth satellites during periods of atmospheric disturbance brought on by severe solar activity. Existing techniques do not account for such atmospheric dynamics, resulting in tracking errors of several seconds in predicted crossing time. Two techniques are examined to reduce of these tracking errors. First, density predicted from various atmospheric models is fit to the orbital decay rate for a number of satellites. An orbital decay model is then developed that could be used to reduce tracking errors by accounting for atmospheric changes. The second approach utilizes a Kalman filter to estimate the orbital decay rate of a satellite after every observation. The new information is used to predict the next observation. Results from the first approach demonstrated the feasibility of building an orbital decay model based on predicted atmospheric density. Correlation of atmospheric density to orbital decay was as high as 0.88. However, it is clear that contemporary: atmospheric models need further improvement in modeling density perturbations polar region brought on by solar activity. The second approach resulted in a dramatic reduction in tracking errors for certain satellites during severe solar Storms. For example, in the limited cases studied, the reduction in tracking errors ranged from 79 to 25 percent.

Wilkin, Paul G.↗

Effects of Correlated and Uncorrelated Gamma Rays on Neutron Multiplicity Counting

Neutron multiplicity counting relies on time correlation between neutron events to assay the fissile mass, (α,n) to spontaneous fission neutron ratio, and neutron self-multiplication of samples. Gamma-ray sensitive neutron multiplicity counters may misidentify gamma rays as neutrons and therefore miscalculate sample characteristics. Time correlated and uncorrelated gamma-ray-like signals were added into gamma-ray free neutron multiplicity counter data to examine the effects of gamma ray signals being misidentified as neutron signals on assaying sample characteristics. Multiplicity counter measurements with and without gamma-ray-like signals were compared to determine the assay error associated with gamma-ray-like signals at various gamma-ray and neutron rates. Correlated and uncorrelated gamma-ray signals each produced consistent but different measurement errors. Correlated gamma-ray signals most strongly led to fissile mass overestimates, whereas uncorrelated gamma-ray signals most strongly lead to (α,n) neutron overestimates. Gamma-ray sensitive neutron multiplicity counters may be able to account for the effects of gamma-rays on measurements to mitigate measurement uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

SU-E-J-235: Varian Portal Dosimetry Accuracy at Detecting Simulated Delivery Errors

Purpose: To use receiver operating characteristic (ROC) analysis to quantify the Varian Portal Dosimetry (VPD) application's ability to detect delivery errors in IMRT fields. Methods: EPID and VPD were calibrated/commissioned using vendor-recommended procedures. Five clinical plans comprising 56 modulated fields were analyzed using VPD. Treatment sites were: pelvis, prostate, brain, orbit, and base of tongue. Delivery was on a Varian Trilogy linear accelerator at 6MV using a Millenium120 multi-leaf collimator. Image pairs (VPD-predicted and measured) were exported in dicom format. Each detection test imported an image pair into Matlab, optionally inserted a simulated error (rectangular region with intensity raised or lowered) into the measured image, performed 3%/3mm gamma analysis, and saved the gamma distribution. For a given error, 56 negative tests (without error) were performed, one per 56 image pairs. Also, 560 positive tests (with error) with randomly selected image pairs and randomly selected in-field error location. Images were classified as errored (or error-free) if percent pixels with γ<κ was < (or ≥) τ. (Conventionally, κ=1 and τ=90%.) A ROC curve was generated from the 616 tests by varying τ. For a range of κ and τ, true/false positive/negative rates were calculated. This procedure was repeated for inserted errors of different sizes. VPD was considered to reliably detect an error if images were correctly classified as errored or error-free at least 95% of the time, for some κ+τ combination. Results: 20mm{sup 2} errors with intensity altered by ≥20% could be reliably detected, as could 10mm{sup 2} errors with intensity was altered by ≥50%. Errors with smaller size or intensity change could not be reliably detected. Conclusion: Varian Portal Dosimetry using 3%/3mm gamma analysis is capable of reliably detecting only those fluence errors that exceed the stated sizes. Images containing smaller errors can pass mathematical analysis, though may be detected by visual inspection. This work was not funded by Varian Oncology Systems. Some authors have other work partly funded by Varian Oncology Systems.

60 APPLIED LIFE SCIENCES↗

Electron-nitrogen molecular collisions in high-temperature nonequilibrium air

Ab initio calculation of vibrational excitation and deexcitation cross sections of N2 by low energy resonant electron impact have been carried out. The calculation includes initial target state in v = 0-12 and final target state in v = 0-17. The calculated cross sections are found to agree with available experimental data to within reported experimental error. Effect of target rotation has been investigated. Comparison of vibrational excitation cross sections at J = 0, 50, and 150 shows that the major effect of target rotation is to lower the resonance energy. Vibrational excitation and deexcitation rate coefficients are tabulated for electron temperatures of 1100-55,000 K. The present tabulation supercedes an earlier compilation by the Naval Research Laboratory that was derived from experimental data with a factor-of-two error. The tabulated rate coefficients are suited for flowfield modeling of aeroassisted orbital transfer vehicles.

Huo, W. M.↗

Performance of Goddard Earth Observing System GCM Column Radiation Models under Heterogeneous Cloud Conditions

We test the performance of the shortwave (SW) and longwave (LW) Column Radiation Models (CORAMs) of Chou and collaborators with heterogeneous cloud fields from a global single-day dataset produced by NCAR's Community Atmospheric Model with a 2-D CRM installed in each gridbox. The original SW version of the CORAM performs quite well compared to reference Independent Column Approximation (ICA) calculations for boundary fluxes, largely due to the success of a combined overlap and cloud scaling parameterization scheme. The absolute magnitude of errors relative to ICA are even smaller for the LW CORAM which applies similar overlap. The vertical distribution of heating and cooling within the atmosphere is also simulated quite well with daily-averaged zonal errors always below 0.3 K/d for SW heating rates and 0.6 K/d for LW cooling rates. The SW CORAM's performance improves by introducing a scheme that accounts for cloud inhomogeneity. These results suggest that previous studies demonstrating the inaccuracy of plane-parallel models may have unfairly focused on worst scenario cases, and that current radiative transfer algorithms of General Circulation Models (GCMs) may be more capable than previously thought in estimating realistic spatial and temporal averages of radiative fluxes, as long as they are provided with correct mean cloud profiles. However, even if the errors of the particular CORAMs are small, they seem to be systematic, and the impact of the biases can be fully assessed only with GCM climate simulations.

Oreopoulos, L.↗

Heat conduction errors and time lag in cryogenic thermometer installations

Installation practices are recommended that will increase rate of heat exchange between the thermometric sensing element and the cryogenic fluid, in addition to bringing about a reduction in the rate of undesired heat transfer to higher temperature objects. Formulas and numerical data are given that help to estimate the magnitude of heat conduction errors and of time lag in response.

Warshawsky, I.↗

Recovered supernova Ia rate from simulated LSST images

Aims.TheVera C. RubinObservatory’s Legacy Survey of Space and Time (LSST) will revolutionize time-domain astronomy by detecting millions of different transients. In particular, it is expected to increase the number of known type Ia supernovae (SN Ia) by a factor of 100 compared to existing samples up to redshift ∼1.2. Such a high number of events will dramatically reduce statistical uncertainties in the analysis of the properties and rates of these objects. However, the impact of all other sources of uncertainty on the measurement of the SN Ia rate must still be evaluated. The comprehension and reduction of such uncertainties will be fundamental both for cosmology and stellar evolution studies, as measuring the SN Ia rate can put constraints on the evolutionary scenarios of different SN Ia progenitors. Methods.We used simulated data from the Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) and LSST Data Preview 0 to measure the SN Ia rate on a 15 deg 2 region of the “wide-fast-deep” area. We selected a sample of SN candidates detected in difference images, associated them to the host galaxy with a specially developed algorithm, and retrieved their photometric redshifts. We then tested different light-curve classification methods, with and without redshift priors (albeit ignoring contamination from other transients, as DC2 contains only SN Ia). We discuss how the distribution in redshift measured for the SN candidates changes according to the selected host galaxy and redshift estimate. Results.We measured the SN Ia rate, analyzing the impact of uncertainties due to photometric redshift, host-galaxy association and classification on the distribution in redshift of the starting sample. We find that we are missing 17% of the SN Ia, on average, with respect to the simulated sample. As 10% of the mismatch is due to the uncertainty on the photometric redshift alone (which also affects classification when used as a prior), we conclude that this parameter is the major source of uncertainty. We discuss possible reduction of the errors in the measurement of the SN Ia rate, including synergies with other surveys, which may help us to use the rate to discriminate different progenitor models.

Astronomy & Astrophysics↗

Assessing Mountains as Natural Reservoirs With a Multimetric Framework

Anthropogenic climate change will continue to diminish the unique role that mountains perform as natural reservoirs and alter long‐held assumptions of water management. Climate models are important tools to help constrain uncertainty and understand processes that shape this decline. To ensure that climate model estimates provide stakeholder relevant information, the formulation of multimetric model evaluation frameworks informed by stakeholder interactions are critical. In this study, we present one such multimetric framework to evaluate snowpack data sets in the California Sierra Nevada: the snow water equivalent (SWE) triangle. SWE triangle metrics help to describe snowpack characteristics associated with total water volume buildup, peak water availability, and the rate of water release. This approach highlights compensating errors that would not be reflected in conventional large‐scale spatiotemporal analysis. To test our multimetric evaluation framework, we evaluate several publicly available snow products including the Sierra Nevada Snow Reanalysis, Livneh (L15), and the North American Land Data Assimilation System version 2 data sets. We then evaluate regional climate model skill within the North American Coordinated Regional Climate Downscaling Experiment. All data sets analyzed show variation across the various SWE triangle metrics, even within observationally constrained snow products. This spread was especially shown in spring season melt rates. Melt rate biases were prevalent throughout most regional climate model simulations, regardless of snow accumulation dynamics, and will need to be addressed to improve their utility for water stakeholders.

54 ENVIRONMENTAL SCIENCES↗

Error analysis for relay type satellite-aided search and rescue systems

An analysis was made of the errors in the determination of the position of an emergency transmitter in a satellite aided search and rescue system. The satellite was assumed to be at a height of 820 km in a near circular near polar orbit. Short data spans of four minutes or less were used. The error sources considered were measurement noise, transmitter frequency drift, ionospheric effects and error in the assumed height of the transmitter. The errors were calculated for several different transmitter positions, data rates and data spans. The only transmitter frequency used was 406 MHz, but the results can be scaled to different frequencies. In a typical case, in which four Doppler measurements were taken over a span of two minutes, the position error was about 1.2 km.

Marini, J. W.↗

Dendritic solidification. I - Analysis of current theories and models. II - A model for dendritic growth under an imposed thermal gradient

A critical review of the present dendritic growth theories and models is presented. Mathematically rigorous solutions to dendritic growth are found to rely on an ad hoc assumption that dendrites grow at the maximum possible growth rate. This hypothesis is found to be in error and is replaced by stability criteria which consider the conditions under which a dendrite tip advances in a stable fashion in a liquid. The important elements of a satisfactory model for dendritic solidification are summarized and a theoretically consistent model for dendritic growth under an imposed thermal gradient is proposed and described. The model is based on the modification of an analysis due to Burden and Hunt (1974) and predicts correctly in all respects, the transition from a dendritic to a planar interface at both very low and very large growth rates.

Laxmanan, V.↗

Bias-Correcting Carbon Fluxes Derived From Land-Surface Satellite Data for Retrospective and Near Real-Time Assimilation Systems

The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide(CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital in-put datasets, e.g., inventories, in situ measurements, and re-processed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth’s surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases inCO2which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal fore-casts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA’s Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

CO2↗

An a priori evaluation of a principal component and artificial neural network based combustion model in diesel engine conditions

A principal component analysis (PCA) and artificial neural network (ANN) based chemistry tabulation approach is presented. ANNs are used to map the thermochemical state onto a low-dimensional manifold consisting of five control variables that have been identified using PCA. Three canonical configurations are considered to train the PCA-ANN model: a series of homogeneous reactors, a nonpremixed flamelet, and a two-dimensional lifted flame. The performance of the model in predicting the thermochemical manifold of a spatially-developing turbulent jet flame in diesel engine thermochemical conditions is a priori evaluated using direct numerical simulation (DNS) data. The PCA-ANN approach is compared with a conventional tabulation approach (tabulation using ad hoc defined control variables and linear interpolation). The PCA-ANN model provides higher accuracy and requires several orders of magnitude less memory. Here, these observations indicate that the PCA-ANN model is superior for chemistry tabulation, especially for modelling complex chemistries that present multiple combustion modes as observed in diesel combustion. The performance of the PCA-ANN model is then compared to the optimal estimator, i.e. the conditional mean from the DNS. The results indicate that the PCA-ANN model gives high prediction accuracy, comparable to the optimal estimator, especially for major species and the thermophysical properties. Higher errors are observed for the minor species and reaction rate predictions when compared to the optimal estimator. It is shown that the prediction of minor species and reaction rates can be improved by using training data that exhibits a variation of parameters as observed in the turbulent flame. The output of the ANN is analysed to assess mass conservation. It is observed that the ANN incurs a mean absolute error of 0.05% in mass conservation. Furthermore, it is demonstrated that this error can be reduced by modifying the cost function of the ANN to penalise for deviation from mass conservation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of ionospheric refraction error corrections for GRARR systems

A determination is presented of the ionospheric refraction correction requirements for the Goddard range and range rate (GRARR) S-band, modified S-band, very high frequency (VHF), and modified VHF systems. The relation ships within these four systems are analyzed to show that the refraction corrections are the same for all four systems and to clarify the group and phase nature of these corrections. The analysis is simplified by recognizing that the range rate is equivalent to a carrier phase range change measurement. The equation for the range errors are given.

Mallinckrodt, A. J.↗

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗

SU-F-T-275: A Correlation Study On 3D Fluence-Based QA and 2D Dose Measurement-Based QA

Purpose: The aim of this paper was to demonstrate the feasibility and creditability of computing and verifying 3D fluencies to assure IMRT and VMAT treatment deliveries, by correlating the passing rates of the 3D fluence-based QA (P(ά)) to the passing rates of 2D dose measurementbased QA (P(Dm)). Methods: 3D volumetric primary fluencies are calculated by forward-projecting the beam apertures and modulated by beam MU values at all gantry angles. We first introduce simulated machine parameter errors (MU, MLC positions, jaw, gantry and collimator) to the plan. Using passing rates of voxel intensity differences (P(Ir)) and 3D gamma analysis (P(γ)), calculated 3D fluencies, calculated 3D delivered dose, and measured 2D planar dose in phantom from the original plan are then compared with those from corresponding plans with errors, respectively. The correlations of these three groups of resultant passing rates, i.e. 3D fluence-based QA (P(ά,Ir) and P(ά,γ)), calculated 3D dose (P(Dc,Ir) and P(Dc,γ)), and 2D dose measurement-based QA (P(Dm,Ir) and P(Dm,γ)), will be investigated. Results: 20 treatment plans with 5 different types of errors were tested. Spearman’s correlations were found between P(ά,Ir) and P(Dc,Ir), and also between P(ά,γ) and P(Dc,γ), with averaged p-value 0.037, 0.065, and averaged correlation coefficient ρ-value 0.942, 0.871 respectively. Using Matrixx QA for IMRT plans, Spearman’s correlations were also obtained between P(ά,Ir) and P(Dm,Ir) and also between P(ά,γ) and P(Dm,γ), with p-value being 0.048, 0.071 and ρ-value being 0.897, 0.779 respectively. Conclusion: The demonstrated correlations improve the creditability of using 3D fluence-based QA for assuring treatment deliveries for IMRT/VMAT plans. Together with advantages of high detection sensitivity and better visualization of machine parameter errors, this study further demonstrates the accuracy and feasibility of 3D fluence based-QA in pre-treatment QA and daily QA. Research reported in this study is supported by the Agency for Healthcare Research and Quality (AHRQ) under award 1R01HS0222888. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗

The limitations of wind measurement accuracy for balloon systems

The error in horizontal wind field measurements as computed from the trajectory of balloons with linear and quadratic rise rates (as functions of altitude) has been derived. Balloon trajectories through light, moderate, and severe wind fields have been considered. Figures are presented which show the wind error vs altitude for various rise rates in each wind field, assuming linear smoothing of the trajectory data. The rise rate profile of the Jimsphere is analyzed as a special case. The results and figures presented are useful in determining the ultimate capability of rising balloon systems in general and for the Jimsphere system in particular for measuring wind from the surface to 18 km. Using the figures presented, it is possible to estimate the wind accuracy that can be achieved by any type of rising balloon by knowing only its rise rate behavior vs altitude. In addition, the results can be used in balloon design to determine what rise rate function is needed to achieve specified wind accuracies. A table is presented which shows the balloon radius for smooth and roughened spheres needed to achieve 2 to 20 m/sec rise rates at 10 and 14 km altitudes.

Luers, J. K.↗