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At least 1,279 records · Page 71

Spectral radiance errors in remote sensing ground studies due to nearby objects

Attention is given to the error that can occur in all radiometric measurements owing to the presence of nearby objects. When a researcher positions himself on the side of a target point opposite the sun, his body gives rise to two erroneous effects. First, it blocks a portion of the incoming diffuse sky radiance to the target point, and second, it reflects incoming diffuse and direct solar irradiance and ground exitance onto the target point. It is noted that the same phenomenon occurs for any nearby object, whether it be a field truck, a building structure, or a row of trees. This error deriving from nearby objects is often not recognized by researchers or is considered insignificant with no knowledge of its magnitude. The approach taken here is to mathematically model the radiant transfers that take place between the global irradiance, panel, or scene and the object and to report the magnitude of this error for various solar zenith angles, wavelengths, size and distances of objects (steradian blockage), and spectral reflectances of the scene and object. The scene, object, and panel are assumed to be Lambertian, and the object is always located on the side of the target point opposite the sun.

Kimes, D. S.↗

Ensemble Simulations of the 2012 July 12 Coronal Mass Ejection with the Constant-turn Flux Rope Model

Flux-rope-based magnetohydrodynamic modeling of coronal mass ejections (CMEs) is a promising tool for prediction of the CME arrival time and magnetic field at Earth. In this work, we introduce a constant-turn flux rope model and use it to simulate the 2012 July 12 16:48 CME in the inner heliosphere. We constrain the initial parameters of this CME using the graduated cylindrical shell (GCS) model and the reconnected flux in posteruption arcades. We correctly reproduce all the magnetic field components of the CME at Earth, with an arrival time error of approximately 1 hr. We further estimate the average subjective uncertainties in the GCS fittings by comparing the GCS parameters of 56 CMEs reported in multiple studies and catalogs. We determined that the GCS estimates of the CME latitude, longitude, tilt, and speed have average uncertainties of 5°.74, 11°.23, 24°.71, and 11.4%, respectively. Using these, we have created 77 ensemble members for the 2012 July 12 CME. We found that 55% of our ensemble members correctly reproduce the sign of the magnetic field components at Earth. We also determined that the uncertainties in GCS fitting can widen the CME arrival time prediction window to about 12 hr for the 2012 July 12 CME. On investigating the forecast accuracy introduced by the uncertainties in individual GCS parameters, we conclude that the half-angle and aspect ratio have little impact on the predicted magnetic field of the 2012 July 12 CME, whereas the uncertainties in longitude and tilt can introduce relatively large spread in the magnetic field predicted at Earth.

Talwinder Singh↗

Gravity field determination for Mars Observer

Mars Observer will be the first near circular, low altitude and short-periodic orbiter of Mars. From previous Mars orbiters, such as Mariner 9 and Vikings 1 and 2, a large gravitational oblateness and in general a gravity field ten times stronger than the earth's field have been determined. Because of these, the gravity field will dominate the evolution of the spacecraft's orbital motion and is the principal error source for reconstructing the spacecraft's motion. Thus a gravity calibration (GC) period has been established prior to the mapping phase in order to refine the gravitational field model. This paper describes the plan being made by Navigation to implement the GC strategy. By analyzing simulated Doppler data acquired during the seven day GC period, we give (1) the expected improvement in the gravity field model and (2) the resulting improvement in reconstructed spacecraft orbital motion. In addition, we have developed a strategy for converging the GC gravity model.

Esposito, Pasquale B.↗

Pressure Measurements Using an Airborne Differential Absorption Lidar: Analysis of the Systematic Error Sources - Part 1

Remote airborne measurements of the vertical and horizontal structure of the atmospheric pressure field in the lower troposphere are made with an oxygen differential absorption lidar (DIAL). A detailed analysis of this measurement technique is provided which includes corrections for imprecise knowledge of the detector background level, the oxygen absorption fine parameters, and variations in the laser output energy. In addition, we analyze other possible sources of systematic errors including spectral effects related to aerosol and molecular scattering interference by rotational Raman scattering and interference by isotopic oxygen fines.

Flamant, Cyrille N.↗

The pointing errors of geosynchronous satellites

A study of the correlation between cloud motion and wind field was initiated. Cloud heights and displacements were being obtained from a ceilometer and movie pictures, while winds were measured from pilot balloon observations on a near-simultaneous basis. Cloud motion vectors were obtained from time-lapse cloud pictures, using the WINDCO program, for 27, 28 July, 1969, in the Atlantic. The relationship between observed features of cloud clusters and the ambient wind field derived from cloud trajectories on a wide range of space and time scales is discussed.

Sikdar, D. N.↗

Data clustering for the high-resolution alignment of microstructure and strain fields

The emergence of small-scale deformation mapping by a combination of scanning electron microscopy and digital image correlation (SEM-DIC) has enabled full-field investigations into the complex roles of microstructure on microscale deformation mechanisms. However, these investigations are hindered by errors in alignment between the microstructure data, generally acquired by electron backscatter diffraction (EBSD), and the microscale strain data obtained by SEM-DIC. Distortions, stitching artifacts, and spatial resolution differences between microstructure and strain fields can lead to misalignments on the order of μms. This alignment uncertainty introduces error into microstructure-strain localization analyses and precludes the examination of deformation mechanisms near grain boundaries. To improve alignment between EBSD-obtained grain boundaries and SEM-DIC strain data, an approach was created wherein a mantle was first established around the EBSD-acquired grain boundaries. Strain data was then clustered within this mantle using a k-means algorithm to identify grain boundary strain localization, and these boundary points were fit to obtain a continuous curve for each individual boundary. Clustered point outliers, such as those due to grain boundary-local dislocation slip, were statistically identified by using an absolute error threshold and removed from the grain boundary fit. The ending identification of grain boundaries in the microscale strain data is significantly improved from EBSD-identified boundaries.

36 MATERIALS SCIENCE↗

Exploring the Early Lightning Notification of an Electric Field Mill at the Savannah River Site

At the Savannah River Site (SRS), employees receive automated broadcast notification about lightning only after three strikes have already occurred near the site boundary. To increase employee safety, it is preferential to give employees lead time before lightning strikes occur. We compared measurements from an on-site electric field mill to lightning detection data from the National Lightning Detection Network and the Geostationary Lightning Mapper. Using a difference threshold, we determined that the electric field mill provided a lead time greater than 6 minutes for 95% of lightning events from 2009-2020, with an average lead time of 56 minutes. Detection of events were limited to a 7-mile radius around the field mill. We also identified that the field mill threshold generated many false detections not clearly identified. False detections and detections from only precipitation can be reduced by using a second threshold without creating too many missed detections (Type II errors). The two thresholds used together provide the best information about rapidly changing electric fields and aid in advanced detection necessary to improve the lightning warning system used at SRS.

42 ENGINEERING↗

Analysis of Integrated Vapor Transport Biases

Abstract High-fidelity analyses and forecasts of integrated vapor transport (VT) are central to the study of Earth’s hydrological cycle as well as high-impact phenomena such as monsoons and atmospheric rivers. The impact of the in-line analysis correction-based additive inflation (ACAI) on IVT biases and forecast errors is examined within the Navy Earth System Prediction Capability (Navy ESPC) global coupled system. The ACAI technique uses atmospheric analysis corrections from the data assimilation system to approximate model bias and as a representation of stochastic model error to simultaneously reduce systematic and random errors and improve ensemble performance. ACAI reduces the global average magnitude of the 7- and 14-day IVT bias by 16%–17% during Northern Hemisphere summer, reaching 70% reductions in some tropical regions. The global average IVT bias reduction is similar to the bias reduction for low-level wind speed bias and considerably smaller than the bias reduction in total precipitable water. The localized regions where ACAI increases IVT bias occur where the control IVT biases change sign and structure with increasing forecast lead time, such as the South Asian monsoon region. Substituting analyzed wind or moisture fields for the forecast fields when calculating the forecast IVT confirms that, on average, wind errors dominate the IVT error calculation in the tropics, although wind and moisture error contributions are comparable in the extratropics. The existence of regions where using either analyzed winds or analyzed moisture increases IVT bias or mean absolute error reveals areas with compensating errors.

Reynolds, Carolyn A.↗

Evaluation of an active magnetic resonance tracking system for interstitial brachytherapy

Purpose: In gynecologic cancers, magnetic resonance (MR) imaging is the modality of choice for visualizing tumors and their surroundings because of superior soft-tissue contrast. Real-time MR guidance of catheter placement in interstitial brachytherapy facilitates target coverage, and would be further improved by providing intraprocedural estimates of dosimetric coverage. A major obstacle to intraprocedural dosimetry is the time needed for catheter trajectory reconstruction. Herein the authors evaluate an active MR tracking (MRTR) system which provides rapid catheter tip localization and trajectory reconstruction. The authors assess the reliability and spatial accuracy of the MRTR system in comparison to standard catheter digitization using magnetic resonance imaging (MRI) and CT. Methods: The MRTR system includes a stylet with microcoils mounted on its shaft, which can be inserted into brachytherapy catheters and tracked by a dedicated MRTR sequence. Catheter tip localization errors of the MRTR system and their dependence on catheter locations and orientation inside the MR scanner were quantified with a water phantom. The distances between the tracked tip positions of the MRTR stylet and the predefined ground-truth tip positions were calculated for measurements performed at seven locations and with nine orientations. To evaluate catheter trajectory reconstruction, fifteen brachytherapy catheters were placed into a gel phantom with an embedded catheter fixation framework, with parallel or crossed paths. The MRTR stylet was then inserted sequentially into each catheter. During the removal of the MRTR stylet from within each catheter, a MRTR measurement was performed at 40 Hz to acquire the instantaneous stylet tip position, resulting in a series of three-dimensional (3D) positions along the catheter’s trajectory. A 3D polynomial curve was fit to the tracked positions for each catheter, and equally spaced dwell points were then generated along the curve. High-resolution 3D MRI of the phantom was performed followed by catheter digitization based on the catheter’s imaging artifacts. The catheter trajectory error was characterized in terms of the mean distance between corresponding dwell points in MRTR-generated catheter trajectory and MRI-based catheter digitization. The MRTR-based catheter trajectory reconstruction process was also performed on three gynecologic cancer patients, and then compared with catheter digitization based on MRI and CT. Results: The catheter tip localization error increased as the MRTR stylet moved further off-center and as the stylet’s orientation deviated from the main magnetic field direction. Fifteen catheters’ trajectories were reconstructed by MRTR. Compared with MRI-based digitization, the mean 3D error of MRTR-generated trajectories was 1.5 ± 0.5 mm with an in-plane error of 0.7 ± 0.2 mm and a tip error of 1.7 ± 0.5 mm. MRTR resolved ambiguity in catheter assignment due to crossed catheter paths, which is a common problem in image-based catheter digitization. In the patient studies, the MRTR-generated catheter trajectory was consistent with digitization based on both MRI and CT. Conclusions: The MRTR system provides accurate catheter tip localization and trajectory reconstruction in the MR environment. Relative to the image-based methods, it improves the speed, safety, and reliability of the catheter trajectory reconstruction in interstitial brachytherapy. MRTR may enable in-procedural dosimetric evaluation of implant target coverage.

60 APPLIED LIFE SCIENCES↗

Prediction of Alpha-Particle-Immune Gate-All-Around Field-Effect Transistors (GAA-FET) Based SRAM Design

Alpha particles are known to be a major source of particles creating soft errors in semiconductor devices, such as content flipping in Static Random-Access Memory (SRAM). Recent advancements in transistor nodes have led to the introduction of Gate-All-Around Field Effect Transistors (GAA-FETs), which have better gate control, thus better electrostatics. Moreover, the introduction of bottom dielectric isolation (BDI) eliminates substrate leakage and thus is expected to enhance its radiation hardness. It is thus important to explore if one can design an SRAM that is completely radiation-hard to alpha particles. In this paper, using 3D Technology Computer-Aided-Design (TCAD) simulations, we show that it is possible to design an SRAM using GAA-FET technology so that it is immune to single alpha particle radiation error. In other words, with the design, there will be no single-event upset (SEU) due to alpha particles. We first use ab initio calculations in PHITS to show that there is a maximum linear energy transfer (LET), LET max , for the alpha particle in Si and Si x Ge 1-x . Based on that, by de signing a sub-7nm GAA-FET-based SRAM with BDI, we show that the SRAM does not flip even if the particle strike is in the worst-case scenario for LET > LET max .

42 ENGINEERING↗

Evaluation of COTS Rad Detection Apps

Mobile applications are currently under distribution to smart phones utilizing the built-in charge coupled-device (CCD) camera as a radiation detector. The CCD detector has a very low but measurable gamma interaction cross section so the mechanism is feasible, especially for higher dose rate environments. Given that in a large release of radioactive material these ‘crowd sourced’ measurements will be put forth for consideration, a testing and evaluation of the accuracy and uncertainty of the Apps is a critical endeavor. Not only is the accuracy of the reported measurement of concern to the immediate user’s safety, a quantitative uncertainty is required for a government response such as the Federal Radiological Monitoring and Assessment Center (FRMAC) to accept the values for consideration in the determination of regions exceeding protective action guidelines. Already, prompted by the Fukushima nuclear material releases, several repositories of this crowd-sourced data have been created (http://japan.failedrobot.com, http://www.stubbytour.com/nuc/index_en.asp, and http://www.rdtn.org) although the question remains as to the reliability of measurements incorporated into these repositories. In cases of conflict between the real-time published crowd-sourced data and governmental protective actions prepared literature should be on-hand documenting why the difference, if any, exists. Four applications for iOS devices were obtained along with hardware to benchmark their performance. Gamma/X-Ray Detector by Stephan Hotto, Geiger Camera by Senscare, and RadioactivityCounter App by Hotray LTD are all the applications available for distribution within the US that utilize the CCD camera sensor for detection of radiation levels. The CellRad app under development by Idaho National Laboratory for the Android platform was evaluated. In addition, iRad Geiger with the associated hardware accessory was also benchmarked. Radiation fields were generated in a Cs-137 JL Shepherd Model 89 shielded calibration range. The accuracy of the exposure rate within the box calibrator is +/- 5% of the system settings and NIST traceable. This is the same calibration unit utilized for calibration of US DOE exposure rate meters. Measurements were performed from 0.2 to 40,000 mR/hr. Included in the following sections are discussions on each of the evaluated applications and their performance in reporting radiation field measurements. Unfortunately the applications do not provide a readily identifiable quality of the measurement in order to produce error bars or even out of range conditions. In general all the CCD based applications had issues detecting consistent measurements in radiation fields less than 5 mR/hr. This is most likely attributable to the electronic noise level on the CCD’s becoming comparable to the signal level due to the ionizing radiation photons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An efficient and numerically stable procedure for generating sextic force fields in normal mode coordinates

In this paper, we outline a general, scalable, and black-box approach for calculating high-order strongly coupled force fields in rectilinear normal mode coordinates, based upon constructing low order expansions in curvilinear coordinates with naturally limited mode-mode coupling, and then transforming between coordinate sets analytically. The optimal balance between accuracy and efficiency is achieved by transforming from 3 mode representation quartic force fields in curvilinear normal mode coordinates to 4 mode representation sextic force fields in rectilinear normal modes. Using this reduced mode-representation strategy introduces an error of only 1 cm{sup −1} in fundamental frequencies, on average, across a sizable test set of molecules. We demonstrate that if it is feasible to generate an initial semi-quartic force field in curvilinear normal mode coordinates from ab initio data, then the subsequent coordinate transformation procedure will be relatively fast with modest memory demands. This procedure facilitates solving the nuclear vibrational problem, as all required integrals can be evaluated analytically. Our coordinate transformation code is implemented within the extensible PyPES library program package, at http://sourceforge.net/projects/pypes-lib-ext/.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Results of the Magnetometer Navigation (MAGNAV)lnflight Experiment

The Magnetometer Navigation (MAGNAV) algorithm is currently running as a flight experiment as part of the Wide Field Infrared Explorer (WIRE) Post-Science Engineering Testbed. Initialization of MAGNAV occurred on September 4, 2003. MAGNAV is designed to autonomously estimate the spacecraft orbit, attitude, and rate using magnetometer and sun sensor data. Since the Earth's magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computed magnetic field and measured magnetic field components, as measured by the magnetometer throughout the entire spacecraft orbit, are a function of the spacecraft trajectory and attitude errors. Therefore, these errors are used to estimate both trajectory and attitude. In addition, the time rate of change of the magnetic field vector is used to estimate the spacecraft rotation rate. The estimation of the attitude and trajectory is augmented with the rate estimation into an Extended Kalman filter blended with a pseudo-linear Kalman filter. Sun sensor data is also used to improve the accuracy and observability of the attitude and rate estimates. This test serves to validate MAGNAV as a single low cost navigation system which utilizes reliable, flight qualified sensors. MAGNAV is intended as a backup algorithm, an initialization algorithm, or possibly a prime navigation algorithm for a mission with coarse requirements. Results from the first six months of operation are presented.

Thienel, Julie K.↗

Theoretical investigation of resonant frequencies of unstrapped magnetron with arbitrary side resonators

In this paper, a sector steps approximation method is proposed to investigate the resonant frequencies of magnetrons with arbitrary side resonators. The arbitrary side resonator is substituted with a series of sector steps, in which the spatial harmonics of electromagnetic field are also considered. By using the method of admittance matching between adjacent steps, as well as field continuity conditions between side resonators and interaction regions, the dispersion equation of magnetron with arbitrary side resonators is derived. Resonant frequencies of magnetrons with five common kinds of side resonators are calculated with sector steps approximation method and computer simulation softwares, in which the results have a good agreement. The relative error is less than 2%, which verifies the validity of sector steps approximation method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A High-Resolution Merged Wind Dataset for DYNAMO: Progress and Future Plans

In order to support research on optimal data assimilation methods for the Cyclone Global Navigation Satellite System (CYGNSS), launching in 2016, work has been ongoing to produce a high‐resolution merged wind dataset for the Dynamics of the Madden Julian Oscillation (DYNAMO) field campaign, which took place during late 2011/early 2012. The winds are produced by assimilating DYNAMO observations into the Weather Research and Forecasting (WRF) three‐dimensional variational (3DVAR) system. Data sources from the DYNAMO campaign include the upper‐air sounding network, radial velocities from the radar network, vector winds from the Advanced Scatterometer (ASCAT) and Oceansat‐2 Scatterometer (OSCAT) satellite instruments, the NOAA High Resolution Doppler Lidar (HRDL), and several others. In order the prep them for 3DVAR, significant additional quality control work is being done for the currently available TOGA and SMART‐R radar datasets, including automatically dealiasing radial velocities and correcting for intermittent TOGA antenna azimuth angle errors. The assimilated winds are being made available as model output fields from WRF on two separate grids with different horizontal resolutions ‐ a 3‐km grid focusing on the main DYNAMO quadrilateral (i.e., Gan Island, the R/V Revelle, the R/V Mirai, and Diego Garcia), and a 1‐km grid focusing on the Revelle. The wind dataset is focused on three separate approximately 2‐week periods during the Madden Julian Oscillation (MJO) onsets that occurred in October, November, and December 2011. Work is ongoing to convert the 10‐m surface winds from these model fields to simulated CYGNSS observations using the CYGNSS End‐To‐End Simulator (E2ES), and these simulated satellite observations are being compared to radar observations of DYNAMO precipitation systems to document the anticipated ability of CYGNSS to provide information on the relationships between surface winds and oceanic precipitation at the mesoscale level. This research will improve our understanding of the future utility of CYGNSS for documenting key MJO processes.

Lang, Timothy J.↗

Early season prediction of within-field crop yield variability by assimilating CubeSat data into a crop model

Accurate early season predictions of crop yield at the within-field scale can be used to address a range of crop production, management, and precision agricultural challenges. While the remote sensing of within-field insights has been a research goal for many years, it is only recently that observations with the required spatio-temporal resolutions, together with efficient assimilation methods to integrate these into modeling frameworks, have become available to advance yield prediction efforts. Here we explore a yield prediction approach that combines daily high-resolution CubeSat imagery with the APSIM crop model. The approach employs APSIM to train a linear regression that relates simulated yield to simulated leaf area index (LAI). That relationship is then used to identify the optimal regression date at which the LAI provides the best prediction of yield: in this case, approximately 14 weeks prior to harvest. Instead of applying the regression on satellite imagery that is coincident, or closest to, the regression date, our method implements a particle filter that integrates CubeSat-based LAI into APSIM to provide end-of-season high-resolution (3 m) yield maps weeks before the optimal regression date. The approach is demonstrated on a rainfed maize field located in Nebraska, USA, where suitable collections of both imagery and in-situ data were available for assessment. The procedure does not require in-field data to calibrate the regression model, with results showing that even with a single assimilation step, it is possible to provide yield estimates with good accuracy up to 21 days before the optimal regression date. Yield spatial variability was reproduced reasonably well, with a strong correlation to independently collected measurements (R 2 = 0.73 and rRMSE = 12%). When the field averaged yield was compared, our approach reduced yield prediction error from 1 Mg/ha (control case based on a calibrated APSIM model), to 0.5 Mg/ha (using satellite imagery alone), and then to 0.2 Mg/ha (results with assimilation up to three weeks prior to the optimal regression date). Such a capacity to provide spatially explicit yield predictions early in the season has considerable potential to enhance digital agricultural goals and improve end-of-season yield predictions.

54 ENVIRONMENTAL SCIENCES↗

Residential mobility and childhood leukemia

Highlights: • Children who moved were older, had younger mothers, and lower SES. • Non-movers showed stronger associations with EMF exposures and childhood leukemia. • Adjustment for variables predicting mobility, save dwelling, did not alter results. • Mobility does not appear to explain observed links between EMF and leukemia. Studies of environmental exposures and childhood leukemia studies do not usually account for residential mobility. Yet, in addition to being a potential risk factor, mobility can induce selection bias, confounding, or measurement error in such studies. Using data collected for California Powerline Study (CAPS), we attempt to disentangle the effect of mobility.

54 ENVIRONMENTAL SCIENCES↗