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At least 955 records · Page 53

The Atacama Cosmology Telescope: a measurement of the Cosmic Microwave Background power spectra at 98 and 150 GHz

We present the temperature and polarization angular power spectra of the CMB measured by the Atacama Cosmology Telescope (ACT) from 5400 deg2 of the 2013–2016 survey, which covers >15000 deg2 at 98 and 150 GHz. For this analysis we adopt a blinding strategy to help avoid confirmation bias and, related to this, show numerous checks for systematic error done before unblinding. Using the likelihood for the cosmological analysis we constrain secondary sources of anisotropy and foreground emission, and derive a “CMB-only” spectrum that extends to ℓ=4000. At large angular scales, foreground emission at 150 GHz is ∼1% of TT and EE within our selected regions and consistent with that found by Planck. Using the same likelihood, we obtain the cosmological parameters for ΛCDM for the ACT data alone with a prior on the optical depth of τ=0.065±0.015. ΛCDM is a good fit. The best-fit model has a reduced χ2 of 1.07 (PTE=0.07) with H0=67.9±1.5 km/s/Mpc. We show that the lensing BB signal is consistent with ΛCDM and limit the celestial EB polarization angle to ψP =−0.07ˆ±0.09ˆ. We directly cross correlate ACT with Planck and observe generally good agreement but with some discrepancies in TE. All data on which this analysis is based will be publicly released.

79 ASTRONOMY AND ASTROPHYSICS↗

Spurious Shear in Weak Lensing with LSST

The complete 10-year survey from the Large Synoptic Survey Telescope (LSST) will image {approx} 20,000 square degrees of sky in six filter bands every few nights, bringing the final survey depth to r {approx} 27.5, with over 4 billion well measured galaxies. To take full advantage of this unprecedented statistical power, the systematic errors associated with weak lensing measurements need to be controlled to a level similar to the statistical errors. This work is the first attempt to quantitatively estimate the absolute level and statistical properties of the systematic errors on weak lensing shear measurements due to the most important physical effects in the LSST system via high fidelity ray-tracing simulations. We identify and isolate the different sources of algorithm-independent, additive systematic errors on shear measurements for LSST and predict their impact on the final cosmic shear measurements using conventional weak lensing analysis techniques. We find that the main source of the errors comes from an inability to adequately characterise the atmospheric point spread function (PSF) due to its high frequency spatial variation on angular scales smaller than {approx} 10{prime} in the single short exposures, which propagates into a spurious shear correlation function at the 10{sup -4}-10{sup -3} level on these scales. With the large multi-epoch dataset that will be acquired by LSST, the stochastic errors average out, bringing the final spurious shear correlation function to a level very close to the statistical errors. Our results imply that the cosmological constraints from LSST will not be severely limited by these algorithm-independent, additive systematic effects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SDSS/SEGUE spectral feature analysis for stellar atmospheric parameter estimation

Large-scale and deep sky survey missions are rapidly collecting a large amount of stellar spectra, which necessitate the estimation of atmospheric parameters directly from spectra and make it feasible to statistically investigate latent principles in a large data set. We present a technique for estimating parameters T{sub eff}, log g, and [Fe/H] from stellar spectra. With this technique, we first extract features from stellar spectra using the LASSO algorithm; then, the parameters are estimated from the extracted features using the support vector regression. On a subsample of 20,000 stellar spectra from the Sloan Digital Sky Survey (SDSS) with reference parameters provided by the SDSS/SEGUE Spectroscopic Parameter Pipeline, estimation consistency are 0.007458 dex for log T{sub eff} (101.609921 K for T{sub eff}), 0.189557 dex for log g, and 0.182060 for [Fe/H], where the consistency is evaluated by mean absolute error. Prominent characteristics of the proposed scheme are sparseness, locality, and physical interpretability. In this work, each spectrum consists of 3821 fluxes, and 10, 19, and 14 typical wavelength positions are detected, respectively, for estimating T{sub eff}, log g, and [Fe/H]. It is shown that the positions are related to typical lines of stellar spectra. This characteristic is important in investigating physical indications from analysis results. Then, stellar spectra can be described by the individual fluxes on the detected positions (PD) or local integration of fluxes near them (LI). The aforementioned consistency is the result based on features described by LI. If features are described by PD, consistency is 0.009092 dex for log T{sub eff} (124.545075 K for T{sub eff}), 0.198928 dex for log g, and 0.206814 dex for [Fe/H].

79 ASTRONOMY AND ASTROPHYSICS↗

Design of a Particle Shadow-graph Velocimetry and Size (PSVS) System to Determine Particle Size and Density Distributions in Hanford Nuclear Tank Wastes - 12280

Accurate particle size and density distributions for nuclear tank waste materials are essential information that helps determine the engineering requirements for a host of waste management unit operations (e.g., tank mixing, pipeline transport, and filtration). The most prevalent approach for determining particle size and density distribution is highly laborious and involves identifying individual particles using scanning electron microscope/x-ray diffraction and then acquiring the density of the materials from the technical literature. Other methods simply approximate individual particle densities by assuming chemical composition, rather than obtaining actual measurements of particle density. To overcome these limitations, a Particle Shadow-graph Velocimetry and Size (PSVS) system has been designed to simultaneously obtain particle size and density distributions for a broad range of Hanford tank waste materials existing as both individual particles and agglomerates. The PSVS system uses optical hardware, a temperature-controlled settling column, and particle introduction chamber to accurately and reproducibly obtain images of settling particles. Image analysis software provides a highly accurate determination of both particle terminal velocity and equivalent spherical particle diameter. The particle density is then calculated from Newton's terminal settling theory. The PSVS system was designed to accurately image particle/agglomerate sizes between 10 and 1000 μm and particle/agglomerate densities ranging from 1.4 to 11.5 g/cm{sup 3}, where the maximum terminal velocity does not exceed 10 cm/s. Preliminary testing was completed with standard materials and results were in good agreement with terminal settling theory. Recent results of this method development are presented, as well as experimental design. The primary goal of these PSVS system tests was to obtain accurate and reproducible particle size and velocity measurements to estimate particle densities within 20 percent of direct measured density values. The average percent error observed in particle densities was 4.8, 8.2, and 25.8 percent for S1D3 (high-density soda-lime glass), S3D4 (zirconia), and S1D2 (soda-lime glass) beads, respectively. The maximum measured particle density error observed was 14.5, 21.0, and 58.4, for S1D3, S3D4, and S1D2 beads, respectively. Multiple sources of error can exist that contribute to inaccurate estimates of particle density using the PSVS approach. Two significant influences observed were thermal convective currents in the settling column fluid and non-spherical (irregular) particle shapes in the standard test materials. Experimental results using buoyant beads suggest thermal convective currents can influence the movement of settling particles as much as 4 mm/s. These thermal convective currents are clearly a significant concern for smaller and less-dense particles/agglomerates which have terminal velocities of the same magnitude. Significant effort went into the design and fabrication of a thermal control system for the PSVS settling column. However, small temperature variations (<0.3 deg. C) are difficult to prevent and measure accurately. Therefore, although designing the thermal control system was necessary, it is not considered the only solution to minimize error due to thermal convective currents. The use of small diameter (10 to 27 μm) polyethylene buoyant beads (in low concentrations) during actual settling experiments may be necessary to provide insight into particle-particle interactions and fluid velocity correction factors to account for potential influences from thermal convective currents. Future testing will incorporate the buoyant beads into the analysis technique when the suspension fluid is chemically compatible. The use of the Newton's law to calculate particle/agglomerate densities assumes spherical particle shapes. As the actual particle/agglomerates diverge from spherical, the margin of error increases. The selection of high quality (in density and shape) monodispersed particle standards was a direct attempt to reduce the uncertainties associated with non-spherical or irregular particles and to only observe the PSVS method and analysis error. While investigating the source of data scatter for the S1D3 bead (nominal 700 μm) standard, significant irregular particles where discovered. Yet, a subsequent investigation into the S3D4 bead standard was also conducted and it was determined that 60 percent of the particles had a 0.9 to 0.8 centricity, 32 percent were between 0.8 and 0.7, only 7 percent were between 1.0 and 0.9, and the remaining 1 percent of the particles had centricities between 0.7 and 0.6. Contrast this with the S1D3 bead standard, where 100 percent of particles had centricities between 0.95 and 0.98, upon applying the centricity filter. The influence of the non-spherical shape of the S3D4 bead standard is evident when comparing a 3.9 percent average density error for S1D3 glass bead standard with an 8.3 percent average density error for the S3D4 bead standard. Model corrections for non-spherical shape must be implemented to account for these measurement errors during future method validation and system performance assessments. In addition, further work is needed to resolve the higher than expected velocities for the smaller S1D2 particles. Initial measurements conducted with buoyant beads as fluid velocity tracers indicate that fluid velocities can be subtracted from the increased particle velocities to determine the particle terminal velocity, regardless of the surrounding fluid velocity. However, this approach is in its infancy and will need to be carefully and methodically validated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

MO-FG-BRA-01: Development of An Image-Guided Dosimetric Planning System for Injectable Brachytherapy Using ELP Nanoparticles

Purpose: To develop, validate, and evaluate a methodology for determining dosimetry for intratumoral injections of elastin-like-polypeptide (ELP) brachytherapy nanoparticles. These organic-polymer-based nanoparticles are injectable, biodegradable, and genetically tunable. We present a genetically encoded polymer-solution, composed of novel radiolabeled-ELP nanoparticles that are custom-designed to self-assemble into a local source upon intratumoral injection. Our preliminary results of a small animal study demonstrate 100% tumor response, effective radionuclide retention-rates, strong in vivo stability, and no polymer-induced toxicities. While our approach is therefore highly promising for improved brachytherapy, the current workflow lacks a dosimetry framework. Methods: We are developing a robust software framework that provides image-guided dosimetric-planning capabilities for ELP brachytherapy. The user graphically places ELP injection sites within a µCT-planning-image, and independently defines each injection volume, concentration, and radioisotope to be used. The resulting internal dosimetry is then pre-determined by first modeling post-injection ELP advection-diffusion, and then calculating the resulting dose distribution based on a point- dose-kernel-convolution algorithm. We have experimentally measured ELP steady-state concentrations via µSPECT acquisition, and validated our dose calculation algorithm against Monte Carlo simulations of several radioactivity distributions. Finally, we have investigated potential advantages and limitations of various ELP injection parameters. Results: The µSPECT results demonstrated inhomogeneous steady-state distributions of ELP in tissue, and Monte Carlo radioactivity distributions were designed accordingly. Our algorithm yielded a root-mean-square-error of less than 2% for each distribution tested (average root-mean-square-error was 0.73%). Dose-Volume-Histogram analysis of five different plans showed how strategic injection placement, and an injection volume-tapering technique, could be used to achieve D95% target coverage. Conclusion: We have preliminarily developed a novel planning framework for ELP brachytherapy. Its dosimetry accuracy has been validated against Monte Carlo, and we have started to investigate the potential advantages of injection-based planning. This system, once fully developed, will serve as the technical foundation for our novel approach.

60 APPLIED LIFE SCIENCES↗

GPS Data Filtration Method for Drive Cycle Analysis Applications

When employing GPS data acquisition systems to capture vehicle drive-cycle information, a number of errors often appear in the raw data samples, such as sudden signal loss, extraneous or outlying data points, speed drifting, and signal white noise, all of which limit the quality of field data for use in downstream applications. Unaddressed, these errors significantly impact the reliability ofsource data and limit the effectiveness of traditional drive-cycle analysis approaches and vehicle simulation software. Without reliable speed and time information, the validity of derived metrics for drive cycles, such as acceleration, power, and distance, become questionable. This study explores some of the common sources of error present in raw onboard GPS data and presents a detailedfiltering process designed to correct for these issues. Test data from both light and medium/heavy duty applications are examined to illustrate the effectiveness of the proposed filtration process across the range of vehicle vocations. Graphical comparisons of raw and filtered cycles are presented, and statistical analyses are performed to determine the effects of the proposed filtration processon raw data. Finally, an evaluation of the overall benefits of data filtration on raw GPS data and present potential areas for continued research is presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Full circle mechanical dynamic characterization including experimental modal analysis and finite element analysis

During operation, it was observed that a specific mechanical system experienced undesirable vibration and it became necessary to understand and mitigate this phenomenon. This document investigates the tools, methodology, and results of the dynamic characterization of the system. The characterization makes use of the experimental modal analysis (EMA) methods of single input multiple output (SIMO) and single input single output (SISO). The validity of the theory of reciprocity is confirmed to minimize measurement error, cost, and time of repeat testing. Finite element analysis (FEA) is used in choosing transducer and modal impact locations to adequately characterize the system. Single degree of freedom (SDOF) and multiple degree of freedom (MDOF) curve fitting is used to fully characterize the system’s mode shapes and natural frequencies. The EMA characterization results are used to modify and validate the FEA model so that FEA can be used to model potential structural modifications to the system to mitigate the undesirable vibration. Structural modifications are chosen, implemented, and their effectiveness is quantified using EMA. Finally, a qualitative evaluation of the methodology of FEA validation by EMA and tuning of the model to match the experimental results is discussed.

42 ENGINEERING↗

DETECTION OF GAMMA-RAY POLARIZATION IN PROMPT EMISSION OF GRB 100826A

We report the polarization measurement in prompt {gamma}-ray emission of GRB 100826A with the Gamma-Ray Burst Polarimeter on board the small solar-power-sail demonstrator IKAROS. We detected the firm change of polarization angle (PA) during the prompt emission with 99.9% (3.5{sigma}) confidence level, and the average polarization degree ({Pi}) of 27% {+-} 11% with 99.4% (2.9{sigma}) confidence level. Here the quoted errors are given at 1{sigma} confidence level for the two parameters of interest. The systematic errors have been carefully included in this analysis, unlike other previous reports. Such a high {Pi} can be obtained in several emission models of gamma-ray bursts (GRBs), including synchrotron and photospheric models. However, it is difficult to explain the observed significant change of PA within the framework of axisymmetric jet as considered in many theoretical works. The non-axisymmetric (e.g., patchy) structures of the magnetic fields and/or brightness inside the relativistic jet are therefore required within the observable angular scale of {approx}{Gamma}{sup -1}. Our observation strongly indicates that the polarization measurement is a powerful tool to constrain the GRB production mechanism, and more theoretical works are needed to discuss the data in more detail.

79 ASTRONOMY AND ASTROPHYSICS↗

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.↗

Use of treatment log files in spot scanning proton therapy as part of patient-specific quality assurance

Purpose: The purpose of this work was to assess the monitor unit (MU) values and position accuracy of spot scanning proton beams as recorded by the daily treatment logs of the treatment control system, and furthermore establish the feasibility of using the delivered spot positions and MU values to calculate and evaluate delivered doses to patients. Methods: To validate the accuracy of the recorded spot positions, the authors generated and executed a test treatment plan containing nine spot positions, to which the authors delivered ten MU each. The spot positions were measured with radiographic films and Matrixx 2D ion-chambers array placed at the isocenter plane and compared for displacements from the planned and recorded positions. Treatment logs for 14 patients were then used to determine the spot MU values and position accuracy of the scanning proton beam delivery system. Univariate analysis was used to detect any systematic error or large variation between patients, treatment dates, proton energies, gantry angles, and planned spot positions. The recorded patient spot positions and MU values were then used to replace the spot positions and MU values in the plan, and the treatment planning system was used to calculate the delivered doses to patients. The results were compared with the treatment plan. Results: Within a treatment session, spot positions were reproducible within {+-}0.2 mm. The spot positions measured by film agreed with the planned positions within {+-}1 mm and with the recorded positions within {+-}0.5 mm. The maximum day-to-day variation for any given spot position was within {+-}1 mm. For all 14 patients, with {approx}1 500 000 spots recorded, the total MU accuracy was within 0.1% of the planned MU values, the mean (x, y) spot displacement from the planned value was (-0.03 mm, -0.01 mm), the maximum (x, y) displacement was (1.68 mm, 2.27 mm), and the (x, y) standard deviation was (0.26 mm, 0.42 mm). The maximum dose difference between calculated dose to the patient based on the plan and recorded data was within 2%. Conclusions: The authors have shown that the treatment log file in a spot scanning proton beam delivery system is precise enough to serve as a quality assurance tool to monitor variation in spot position and MU value, as well as the delivered dose uncertainty from the treatment delivery system. The analysis tool developed here could be useful for assessing spot position uncertainty and thus dose uncertainty for any patient receiving spot scanning proton beam therapy.

60 APPLIED LIFE SCIENCES↗

Building a Wide-Area File Transfer Performance Predictor: An Empirical Study

Wide-area data transfer is central to geographically distributed scientific workflows. Faster delivery of data is important for these workflows. Predictability is equally (or even more) important. With the goal of providing a reasonably accurate estimate of data transfer time to improve resource allocation & scheduling for workflows and enable end-to-end data transfer optimization, we apply machine learning methods to develop predictive models for data transfer times over a variety of wide area networks. To build and evaluate these models, we use 201,388 transfers, involving 759 million files totaling 9 PB transferred, over 115 heavily used source-destination pairs (“edges”) between 135 unique endpoints. We evaluate the models for different retraining frequencies and different window size of history data. In the best case, the resulting models have a median prediction error of ≤21% for 50% of the edges, and ≤32% for 75% of the edges. We present a detailed analysis of these results that provides insights into the cause of some of the high errors. We envision that the performance predictor will be informative for scheduling geo-distributed workflows. The insights also suggest obvious directions for both further analysis and transfer service optimization.

Liu, Zhengchun↗

Improving cosmological analyses of HI clustering by reducing stochastic noise

High-number-density tracers of large-scale structure, such as the HI-rich galaxies measured by 21 cm intensity mapping, have low sampling noise, making them particularly promising as cosmological probes. At large scales, this sampling noise can be subdominant to other scale-independent contributions to the power spectrum; such contributions arise from nonlinear bias, and exceed the sampling noise if at least one of the associated bias coefficients is sufficiently large. This has important consequences for cosmological constraints obtained from such tracers, since it indicates that using the power spectrum does not lead to optimal constraints even in the linear regime. In this paper, we provide a conservative estimate of the possible improvement in constraining power of a 21 cm survey if one were to use an optimal analysis strategy (such as field-level analysis), where only the true sampling noise enters the error budget. We find that improvements in uncertainties on some cosmological parameters can be as large as 50%, depending on redshift, foreground cleaning efficiency, scales used in the analysis, and instrumental noise. One byproduct of our work is measurements of bias parameters and stochasticity for neutral hydrogen in the IllustrisTNG simulation over a wide range of redshifts; we provide simple fitting formulas for these measurements. Furthermore, our results motivate further exploration of new optimal analysis techniques and provide important insights into the constraining power of current and future 21 cm surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

ON THE ACCURACY OF THE DIFFERENTIAL EMISSION MEASURE DIAGNOSTICS OF SOLAR PLASMAS. APPLICATION TO SDO/AIA. II. MULTITHERMAL PLASMAS

Differential emission measure (DEM) analysis is one of the most used diagnostic tools for solar and stellar coronae. Being an inverse problem, it has limitations due to the presence of random and systematic errors. We present in this series of papers an analysis of the robustness of the inversion in the case of SDO/AIA observations. We completely characterize the DEM inversion and its statistical properties, providing all the solutions consistent with the data along with their associated probabilities, and a test of the suitability of the assumed DEM model. While Paper I focused on isothermal conditions, we now consider multithermal plasmas and investigate both isothermal and multithermal solutions. We demonstrate how the ambiguity between noises and multithermality fundamentally limits the temperature resolution of the inversion. We show that if the observed plasma is multithermal, isothermal solutions tend to cluster on a constant temperature whatever the number of passbands or spectral lines. The multithermal solutions are also found to be biased toward near-isothermal solutions around 1 MK. This is true even if the residuals support the chosen DEM model, possibly leading to erroneous conclusions on the observed plasma. We propose tools for identifying and quantifying the possible degeneracy of solutions, thus helping the interpretation of DEM inversion.

79 ASTRONOMY AND ASTROPHYSICS↗

BEYONDPLANCK XIII. Intensity foreground sampling, degeneracies, and priors

We present the intensity foreground algorithms and model employed within the BEYONDPLANCK analysis framework. The BEYONDPLANCK analysis is aimed at integrating component separation and instrumental parameter sampling within a global framework, leading to complete end-to-end error propagation in the Planck Low Frequency Instrument (LFI) data analysis. Given the scope of the BEYONDPLANCK analysis, a limited set of data is included in the component separation process, leading to foreground parameter degeneracies. In order to properly constrain the Galactic foreground parameters, we improve upon the previous Commander component separation implementation by adding a suite of algorithmic techniques. These algorithms are designed to improve the stability and computational efficiency for weakly constrained posterior distributions. These are: (1) joint foreground spectral parameter and amplitude sampling, building on ideas from MIRAMARE; (2) component-based monopole determination; (3) joint spectral parameter and monopole sampling; and (4) application of informative spatial priors for component amplitude maps. We find that the only spectral parameter with a significant signal-to-noise ratio using the current BEYONDPLANCK data set is the peak frequency of the anomalous microwave emission component, for which we find $ν$ p = 25.3 ± 0.5 GHz; all others must be constrained through external priors. Future works will be aimed at integrating many more data sets into this analysis, both map and time-ordered based, thereby gradually eliminating the currently observed degeneracies in a controlled manner with respect to both instrumental systematic effects and astrophysical degeneracies. When this happens, the simple LFI-oriented data model employed in the current work will need to be generalized to account for both a richer astrophysical model and additional instrumental effects. This work will be organized within the Open Science-based COSMOGLOBE community effort.

79 ASTRONOMY AND ASTROPHYSICS↗

Silicon Carbide Temperature Monitor Processing Improvements. Status Report

Silicon carbide (SiC) temperature monitors are used as temperature sensors in Advanced Test Reactor (ATR) irradiations at the Idaho National Laboratory (INL). Although thermocouples are typically used to provide real-time temperature indication in instrumented lead tests, other indicators, such as melt wires, are also often included in such tests as an independent technique of detecting peak temperatures incurred during irradiation. In addition, less expensive static capsule tests, which have no leads attached for real-time data transmission, often rely on melt wires as a post-irradiation technique for peak temperature indication. Melt wires are limited in that they can only detect whether a single temperature is or is not exceeded. SiC monitors are advantageous because a single monitor can be used to detect for a range of temperatures that occurred during irradiation. As part of the process initiated to make SiC temperature monitors available at the ATR, post-irradiation evaluations of these monitors have been previously completed at the High Temperature Test Laboratory (HTTL). INL selected the resistance measurement approach for determining irradiation temperature from SiC temperature monitors because it is considered to be the most accurate measurement. The current process involves the repeated annealing of the SiC monitors at incrementally increasing temperature, with resistivity measurements made between annealing steps. The process is time consuming and requires the nearly constant attention of a trained staff member. In addition to the expensive and lengthy post analysis required, the current process adds many potential sources of error in the measurement, as the sensor must be repeatedly moved from furnace to test fixture. This time-consuming post irradiation analysis is a significant portion of the total cost of using these otherwise inexpensive sensors. An additional consideration of this research is that, if the SiC post processing can be automated, it could be performed in an MFC hot cell, further reducing the time and expense of lengthy decontaminations prior to processing. Sections of this report provide a general description of resistivity techniques currently used to infer peak irradiation temperature from silicon carbide temperature monitors along with some representative data, the proposed concepts to improve the process of analyzing irradiated SiC temperature monitors, the completed efforts to prove the proposed concepts, and future activities. The efforts detailed here succeeded in designing and developing a real-time automated SiC resistivity measurement system, and performed two initial test runs. Activities carried out include the assembly and integration of the system hardware; the design and development of a preliminary monitor fixture; the design of a technique to automate the data analysis and processing; the development of the communication, coordination, and user software; and the execution and troubleshooting of test run experiments using the box furnace. Although the automation system performed as required, the designed fixture did not succeed in establishing the needed electrical contacts with the SiC monitor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

LOGISTIC FUNCTION PROFILE FIT: A least-squares program for fitting interface profiles to an extended logistic function

The extended logistic function provides a physically reasonable description of interfaces such as depth profiles or line scans of surface topological or compositional features. It describes these interfaces with the minimum number of parameters, namely, position, width, and asymmetry. Logistic Function Profile Fit (LFPF) is a robust, least-squares fitting program in which the nonlinear extended logistic function is linearized by a Taylor series expansion (equivalent to a Newton-Raphson approach) with no apparent introduction of bias in the analysis. The program provides reliable confidence limits for the parameters when systematic errors are minimal and provides a display of the residuals from the fit for the detection of systematic errors. The program will aid researchers in applying ASTM E1636-10, 'Standard practice for analytically describing sputter-depth-profile and linescan-profile data by an extended logistic function,' and may also prove useful in applying ISO 18516: 2006, 'Surface chemical analysis-Auger electron spectroscopy and x-ray photoelectron spectroscopy-determination of lateral resolution.' Examples are given of LFPF fits to a secondary ion mass spectrometry depth profile, an Auger surface line scan, and synthetic data generated to exhibit known systematic errors for examining the significance of such errors to the extrapolation of partial profiles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analysis of shockless dynamic compression data on solids to multi-megabar pressures: Application to tantalum

Magnetically-driven, planar shockless-compression experiments to multi-megabar pressures were performed on tantalum samples using a stripline target geometry. Free-surface velocity waveforms were measured in 15 cases; nine of these in a dual-sample configuration with two samples of different thicknesses on opposing electrodes, and six in a single-sample configuration with a bare electrode opposite the sample. Details are given on the application of inverse Lagrangian analysis (ILA) to these data, including potential sources of error. The most significant source of systematic error, particularly for single-sample experiments, was found to arise from the pulse-shape dependent free-surface reflected wave interactions with the deviatoric-stress response of tantalum. This could cause local, possibly temporary, unloading of material from a ramp compressed state, and thus multi-value response in wave speed that invalidates the free-surface to in-material velocity mapping step of ILA. By averaging all 15 data sets, a final result for the principal quasi-isentrope of tantalum in stress-strain was obtained to a peak longitudinal stress of 330 GPa with conservative uncertainty bounds of ±4.5% in stress. The result agrees well with a tabular equation of state developed at Los Alamos National Laboratory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗