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Pyrolysis_Molecular_Beam_Mass_Spectrometry_Analysis_of_hybrid_cross_of_Populus_tremula_x_P_alba_717-1B4_and_overexpression_of_a_lectin_receptor-like_kinase_(PtLecRLK1)

Stem tissues from the hybrid poplarPopulus tremula × P. albaclone 717-1B4 and from lectin receptor-like kinase overexpression lines PP7 and PP19 were individually colonized with the ectomycorrhizal fungiLaccaria bicolorstrain S238N,Hyaloscypha finlandicastrain PMI746, orUmbelopsis vinaceastrain PMI3018, as well as with a mixed fungal inoculum; non-inoculated plants served as controls. Plants were grown in a greenhouse at Oak Ridge National Laboratory and harvested in January 2025. Stem samples were analyzed using Pyrolysis–Molecular Beam Mass Spectrometry (Py-MBMS). Stems were harvested, debarked, dried, milled, destarched and ethanol extracted prior to analysis. Py-MBMS analysis was conducted using approximately 4 mg of wood from biomass and each sample was analyzed in duplicate. A Frontier PY2020 unit pyrolyzed samples at 500°C for 30 s in 80 µL deactivated stainless steel cups. An Extrel Super-Sonic MBMS Model Max 1000 was used to collect mass spectral data fromm/z30 to 450 at 17 eV and processed using Merlin Automation software (V3). Spectral ion intensities were normalized to the total ion chromatogram signal for each sample for analysis of spectral variance. Lignin content (wt %) was estimated based on relative responses from standards of known Klason lignin content using mean-normalized ion intensities ofm/z120, 124 (G), 137 (G), 138 (G), 150 (G), 152, 154 (S), 164 (G), 167 (S), 168 (S), 178 (G), 180, 181, 182 (S), 194 (S), 208 (S) and 210 (S) where G indicates guaiacyl-derived ions, S indicates syringyl-derived ions, and other ions either derive from other lignin monomers or multiple sources. Ratios of S and G lignin monomer units (S/G) were obtained by dividing the sum of S-based ions by the sum of G-based ions using mean-normalized ion intensities.

CBI↗

Variability of pigment biomass in the California Current system as determined by satellite imagery. I - Spatial variability

Spatial variability of chlorophyll in the California Current system was analyzed using Coastal Zone Color Scanner (CZCS) imagery. A total of 48 images were analyzed to produce seasonal averages and variances, gradients, and power spectra. Roughly one third to one half of the variance in pigment biomass can be explained by consistent, large-scale gradients. In general, biomass is higher in the north and in nearshore areas. Nearshore areas also have proportionally more small-scale variability than the areas offshore. Slopes of the power spectra for nearshore areas are about -2.2 (for spatial scales of 10-100 km), while slopes for offshore areas are about -3. In addition, the power spectra show evidence of a change in slope at about 10 km, with slopes of about -1 for shorter-length scales. This may indicate that biological processes dominate the smaller scales, while mesoscale eddies and geostrophic currents dominate the larger scales.

Smith, Raymond C.↗

SeaWiFS Technical Report Series. Volume 29: SeaWiFS CZCS-type pigment algorithm

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission will provide operational ocean color that will be superior to the previous Coastal Zone Color Sensor (CZCS) proof-of-concept mission. an algorithm is needed that exploits the full functionality of SeaWiFS whilst remaining compatible in concept with algorithms used for the CZCS. This document describes the theoretical rationale of radiance band-radio methods for determining chlorophyll alpha and other important biogeochemical parameters, and their implementation for the SeaWiFS mission. Pigment interrelationships are examined to explain the success of the CZCS algorithms. In the context where chlorophyll alpha absorbs only weakly at 520 nm, the success of the 520 nm to 550 nm CZCS band ratio needs to be explained. This is explained by showing that in pigment data from a range of oceanic provinces chlorophyll alpha (absorbing at less than 490 nm), carotenoids (absorbing at greater than 460 nm), and total pigment are highly correlated. Correlations within pigment groups particularly photoprotectant and photosynthetic carotenoids are less robust. The sources of variability in optical data re examined using the NIMBUS Experiment Team (NET) bio-optical data set and bio-optical model. In both the model and NET data, the majority of the variance in the optical data is attributed to variability in pigment (chlorophyll alpha, and total particulates, with less than 5% of the variability resulting from pigment assemblage. The relationships between band ratios and chlorophyll is examined analytically, and a new formulation based on a dual hyperbolic model is suggested which gives a better calibration curve than the conventional log-log linear regression fit. The new calibration curve shows that 490:555 ratio is the best single-band ratio and is the recommended CZCS-type pigment algorithm. Using both the model and NET data, a number of multiband algorithms are developed; the best of which is an algorithm based on the 443:555 and 490:555 ratios. From model data, the form of potential algorithms for other products, such as total particulates and dissolved organic matter (DOM), are suggested.

Hooker, Stanford B.↗

Variance and Predictability of Precipitation at Seasonal-to-Interannual Timescales

A series of atmospheric general circulation model (AGCM) simulations, spanning a total of several thousand years, is used to assess the impact of land-surface and ocean boundary conditions on the seasonal-to-interannual variability and predictability of precipitation in a coupled modeling system. In the first half of the analysis, which focuses on precipitation variance, we show that the contributions of ocean, atmosphere, and land processes to this variance can be characterized, to first order, with a simple linear model. This allows a clean separation of the contributions, from which we find: (1) land and ocean processes have essentially different domains of influence, i.e., the amplification of precipitation variance by land-atmosphere feedback is most important outside of the regions (mainly in the tropics) that are most affected by sea surface temperatures; and (2) the strength of land-atmosphere feedback in a given region is largely controlled by the relative availability of energy and water there. In the second half of the analysis, the potential for seasonal-to-interannual predictability of precipitation is quantified under the assumption that all relevant surface boundary conditions (in the ocean and on land) are known perfectly into the future. We find that the chaotic nature of the atmospheric circulation imposes fundamental limits on predictability in many extratropical regions. Associated with this result is an indication that soil moisture initialization or assimilation in a seasonal-to-interannual forecasting system would be beneficial mainly in transition zones between dry and humid regions.

Koster, Randal D.↗

SeaWiFS Technical Report Series: The SeaWiFS CZCS-Type Pigment Algorithm - Volume 29

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission will provide operational ocean color that will be superior to the previous Coastal Zone Color Sensor (CZCS) proof-of-concept mission. An algorithm is needed that exploits the full functionality of SeaWiFS whilst remaining compatible in concept with algorithms used for the CZCS. This document describes the theoretical rationale of radiance band-ratio methods for determining chlorophyll-a and other important biogeochemical parameters, and their implementation for the SeaWIFS mission. Pigment interrelationships are examined to explain the success of the CZCS algorithms. In the context where chlorophyll-a absorbs only weakly at 520 nm, the success of the 520 nm to 550 nm CZCS band ratio needs to be explained. This is explained by showing that in pigment data from a range of oceanic provinces chlorophyll-a (absorbing at less than 490 nm), carotenoids (absorbing at greater than 460 nm), and total pigment are highly correlated. Correlations within pigment groups particularly photoprotectant and photosynthetic carotenoids are less robust. The sources of variability in optical data are examined using the NIMBUS Experiment Team (NET) bio-optical data set and bio-optical model. In both the model and NET data, the majority of the variance in the optical data is attributed to variability in pigment (chlorophyll-a), and total particulates, with less than 5% of the variability resulting from pigment assemblage. The relationships between band ratios and chlorophyll is examined analytically, and a new formulation based on a dual hyperbolic model is suggested which gives a better calibration curve than the conventional log-log linear regression fit. The new calibration curve shows the 490:555 ratio is the best single-band ratio and is the recommended CZCS-type pigment algorithm. Using both the model and NET data, a number of multiband algorithms are developed; the best of which is an algorithm based on the 443:555 and 490:555 ratios. From model data, the form of potential algorithms for other products, such as total particulates and dissolved organic matter (DOM), are suggested.

Hooker, Stanford B.↗

Fisher for complements: extracting cosmology and neutrino mass from the counts-in-cells PDF

In this work, we comprehensively analyse the cosmology dependence of counts-in-cells statistics. Furthermore, we focus on the shape of the one-point probability distribution function (PDF) of the matter density field at mildly non-linear scales. Based on large-deviation statistics, we parametrize the cosmology dependence of the matter PDF in terms of the linear power spectrum, the growth factor, the spherical collapse dynamics, and the non-linear variance. We extend our formalism to include massive neutrinos, finding that the total matter PDF is highly sensitive to the total neutrino mass Mν and can disentangle it from the clustering amplitude σ 8 . Additionally, using more than a million PDFs extracted from the Quijote simulations, we determine the response of the matter PDF to changing parameters in the νΛCDM model and successfully cross-validate the theoretical model and the simulation measurements. We present the first νΛCDM Fisher forecast for the matter PDF at multiple scales and redshifts, and its combination with the matter power spectrum. We establish that the matter PDF and the matter power spectrum are highly complementary at mildly non-linear scales. The matter PDF is particularly powerful for constraining the matter density Ωm, clustering amplitude σ 8 and the total neutrino mass Mν. Adding the mildly non-linear matter PDF to the mildly non-linear matter power spectrum improves constraints on Ω m by a factor of 5 and σ 8 by a factor of 2 when considering the three lowest redshifts. In our joint analysis of the matter PDF and matter power spectrum at three redshifts, the total neutrino mass is constrained to better than 0.01 eV with a total volume of 6 (Gpc h -1 ) 3 . We discuss how density-split statistics can be used to translate those encouraging results for the matter PDF into realistic observables in galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Independent pixel and Monte Carlo estimates of stratocumulus albedo

Monte Carlo radiative transfer methods are employed here to estimate the plane-parallel albedo bias for marine stratocumulus clouds. This is the bias in estimates of the mesoscale-average albedo, which arises from the assumption that cloud liquid water is uniformly distributed. The authors compare such estimates with those based on a more realistic distribution generated from a fractal model of marine stratocumulus clouds belonging to the class of 'bounded cascade' models. In this model the cloud top and base are fixed, so that all variations in cloud shape are ignored. The model generates random variations in liquid water along a single horizontal direction, forming fractal cloud streets while conserving the total liquid water in the cloud field. The model reproduces the mean, variance, and skewness of the vertically integrated cloud liquid water, as well as its observed wavenumber spectrum, which is approximately a power law. The Monte Carlo method keeps track of the three-dimensional paths solar photons take through the cloud field, using a vectorized implementation of a direct technique. The simplifications in the cloud field studied here allow the computations to be accelerated. The Monte Carlo results are compared to those of the independent pixel approximation, which neglects net horizontal photon transport. Differences between the Monte Carlo and independent pixel estimates of the mesoscale-average albedo are on the order of 1% for conservative scattering, while the plane-parallel bias itself is an order of magnitude larger. As cloud absorption increases, the independent pixel approximation agrees even more closely with the Monte Carlo estimates. This result holds for a wide range of sun angles and aspect ratios. Thus, horizontal photon transport can be safely neglected in estimates of the area-average flux for such cloud models. This result relies on the rapid falloff of the wavenumber spectrum of stratocumulus, which ensures that the smaller-scale variability, where the radiative transfer is more three-dimensional, contributes less to the plane-parallel albedo bias than the larger scales, which are more variable. The lack of significant three-dimensional effects also relies on the assumption of a relatively simple geometry. Even with these assumptions, the independent pixel approximation is accurate only for fluxes averaged over large horizontal areas, many photon mean free paths in diameter, and not for local radiance values, which depend strongly on the interaction between neighboring cloud elements.

Cahalan, Robert F.↗

Neural Network (NN) Retrievals of Stratocumulus Cloud Properties Using Multiangle Polarimetric Observations During ORACLES

The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign is taking place in the SouthEast Atlantic during the Austral Spring for three consecutive years from 20162018. The study area encompasses one of the Earths three semipermanent subtropical Stratocumulus (Sc) cloud decks,and experiences very large aerosol optical depths, mainly biomass burning, originating from Africa. Over time, cloud optical depth (COD), lifetime and cloud microphysics (number concentration, effective radii Reff and precipitation) are expected to be influenced by indirect aerosol effects. These changes play a key role in the energetic balance of the region, and are part of the core investigation objectives of the ORACLES campaign, which acquires measurements of clean and polluted scenes of above cloud aerosols (ACA). Simultaneous retrievals of aerosol and cloud optical properties are being developed (e.g. MODIS, OMI), butstill challenging, especially for passive, single viewing angle instruments. By comparison, multiangle polarimetric instruments like RSP (Research Scanning Polarimeter) show promise for detection and quantification of ACA, however, there are no operational retrieval algorithms available yet. Here we describe anew algorithm to retrieve cloud and aerosol optical properties from observations by RSP flown on the ER2and P3 during the 2016 ORACLES campaign. The algorithm is based on training a NN, and is intended to retrieve aerosol and cloud properties simultaneously. However, the first step was to establish the retrievalscheme for low level Sc cloud optical properties. The NN training was based on simulated RSP total and polarized radiances for a range of COD, Reff, and effective variances, spanning 7 wavelength bands and 152 viewing zenith angles. Random and correlated noise were added to the simulations to achieve a morerealistic representation of the signals. Before introducing the input variables to the network, the signals are projected on a principle component plane that retains the maximal signal information but minimizes the noise contribution. We will discuss parameter choices for the network and present preliminary results of cloudretrievals from ORACLES, compared with standard RSP low-levelcloud retrieval method that has been validated against in situ observations.

Cloud-aerosol↗

Turbulent Transport in the Gray Zone: A Large Eddy Model Intercomparison Study of the CONSTRAIN Cold Air Outbreak Case

To quantify the turbulent transport at gray zone length scales between 1 and 10 km the Lagrangian evolution of the CONSTRAIN cold air outbreak (CAO) case was simulated with seven large eddy models. The case is characterized by rather large latent and sensible heat fluxes, and a rapid deepening rate of the boundary layer. In some models the entrainment velocity exceeds 4 cm/s. A significant fraction of this growth is attributed to a strong longwave radiative cooling of the inversion layer. The evolution and the timing of the breakup of the stratocumulus cloud deck differ significantly among the models. Sensitivity experiments demonstrate that a decrease in the prescribed cloud droplet number concentration, and the inclusion of ice microphysics, both act to speed up the thinning of the stratocumulus by enhancing the production of precipitation. In all models the formation of mesoscale fluctuations is clearly evident in the cloud fields but also in the horizontal wind velocity. Resolved vertical fluxes remain important for scales up to 10 km. The simulation results show that the resolved vertical velocity variance gradually diminishes with a coarsening of the horizontal mesh, but the total vertical fluxes of heat, moisture, and momentum are only weakly affected. This is a promising result as it demonstrates the potential use of a mesh size dependent turbulent length scale for convective boundary layers at gray zone model resolutions.

gray zone↗

A generalized approximate control variate framework for multifidelity uncertainty quantification

We describe and analyze a variance reduction approach for Monte Carlo (MC) sampling that accelerates the estimation of statistics of computationally expensive simulation models using an ensemble of models with lower cost. These lower cost models — which are typically lower fidelity with unknown statistics — are used to reduce the variance in statistical estimators relative to a MC estimator with equivalent cost. We derive the conditions under which our proposed approximate control variate framework recovers existing multifidelity variance reduction schemes as special cases. We demonstrate that existing recursive/nested strategies are suboptimal because they use the additional low-fidelity models only to efficiently estimate the unknown mean of the first low-fidelity model. As a result, they cannot achieve variance reduction beyond that of a control variate estimator that uses a single low-fidelity model with known mean. However, there often exists about an order-of-magnitude gap between the maximum achievable variance reduction using all low-fidelity models and that achieved by a single low-fidelity model with known mean. We show that our proposed approach can exploit this gap to achieve greater variance reduction by using non-recursive sampling schemes. The proposed strategy reduces the total cost of accurately estimating statistics, especially in cases where only low-fidelity simulation models are accessible for additional evaluations. Several analytic examples and an example with a hyperbolic PDE describing elastic wave propagation in heterogeneous media are used to illustrate the main features of the methodology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Noise and error analysis and optimization in particle-based kinetic plasma simulations

In this paper we analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We begin by describing kernel density estimation for continuous values of the spatial variable x, expressing the kernel in a form in which its shape and width are represented separately. The covariance matrix of the noise in the density is computed, first for uniform true density. The bandwidth of the covariance matrix C(x,y) is related to the width of the kernel. A feature that stands out is the presence of constant negative terms in the elements of the covariance matrix both on and off-diagonal. These negative correlations are related to the fact that the total number of particles is fixed at each time step; they also lead to the property ∫C(x,y)dy = 0. We investigate the effect of these negative correlations on the electric field computed by Gauss's law, finding that the noise in the electric field is related to a process called the Ornstein-Uhlenbeck bridge, leading to a covariance matrix of the electric field with variance significantly reduced relative to that of a Brownian process. For non-constant density, p(x), still with continuous x, we analyze the total error in the density estimation and discuss it in terms of bias-variance optimization (BVO). For some characteristic length l, determined by the density and its second derivative, and kernel width h, having too few particles within h leads to too much variance; for h that is large relative to l, there is too much smoothing of the density. The optimum between these two limits is found by BVO. For kernels of the same width, it is shown that this optimum (minimum) is weakly sensitive to the kernel shape. Next, we repeat the analysis for x discretized on a grid. In this case the charge deposition rule is determined by a particle shape. An important property to be respected in the discrete system is the exact preservation of total charge on the grid; this property is necessary to ensure that the electric field is equal at both ends, consistent with periodic boundary conditions. We find that if the particle shapes satisfy a partition of unity property, the particle charge deposited on the grid is conserved exactly. Further, if the particle shape is expressed as the convolution of a kernel with another kernel that satisfies the partition of unity, then the particle shape obeys the partition of unity. This property holds for kernels of arbitrary width, including widths that are not integer multiples of the grid spacing. Furthermore, we show results relaxing the approximations used to do BVO optimization analytically, by doing numerical computations of the total error as a function of the kernel width, on a grid in x. The comparison between numerical and analytical results shows good agreement over a range of particle shapes. We discuss the practical implications of our results, including the criteria for design and implementation of computationally efficient particle shapes that take advantage of the developed theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Conditional H I Mass Functions and the H I -to-halo Mass Relation in the Local Universe

We present a new H I mass estimator that relates log 10 (M HI /M * ) to a linear combination of four galaxy properties: stellar surface mass density, color index u - r, stellar mass, and concentration index, with the scatter of individual galaxies around the mean H I mass modeled with a Gaussian distribution function. We calibrate the estimator using the xGASS sample, including both H I detection and nondetection, and constrain the model parameters through Bayesian inferences. Tests with mock catalogs demonstrate that our estimator provides unbiased H I masses for optical samples like SDSS. We apply our estimator to the SDSS spectroscopic sample to estimate the H I mass function (HIMF) of local galaxies, as well as the conditional H I mass function in galaxy groups and the H I –halo mass relation. Our HIMF agrees with the ALFALFA measurements at M HI ≳ 5 × 10 9 M ⊙ , but with higher amplitude and a steeper slope at lower masses. We show that this discrepancy is caused primarily by the cosmic variance, which is corrected for the SDSS sample but not for ALFALFA. The total CHIMFs for all halo masses can be described by a single Schechter function, while those of central galaxies show a double-Gaussian profile. The total H I mass in a group increases monotonically with halo mass, but for central galaxies, the H I mass shows weak dependence on halo mass when M h ≳ 10 12 M ⊙ . The observed H I –halo mass relation is not reproduced by current hydrodynamic simulations and semianalytic models of galaxy formation.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling bidirectional reflectance of forests and woodlands using Boolean models and geometric optics

Geometric-optical discrete-element mathematical models for forest canopies have been developed using the Boolean logic and models of Serra. The geometric-optical approach is considered to be particularly well suited to describing the bidirectional reflectance of forest woodland canopies, where the concentration of leaf material within crowns and the resulting between-tree gaps make plane-parallel, radiative-transfer models inappropriate. The approach leads to invertible formulations, in which the spatial and directional variance provides the means for remote estimation of tree crown size, shape, and total cover from remotedly sensed imagery.

Strahler, Alan H.↗

Temporal deposition of copper and zinc in the sediments of metal removal constructed wetlands

The objective of this study was to explore the effects of time, seasons, and total carbon (TC) on Copper (Cu) and Zinc (Zn) deposition in the surface sediments. This study was performed at the H-02 constructed wetland on the Savannah River Site (Aiken, SC, USA). Covering both warm (April-September) and cool (October-March) seasons, several sediment cores were collected twice a year from the H-02 constructed wetland cells from 2007 to 2013. Total concentrations of Cu and Zn were measured in the sediments. Concentrations of Cu and Zn (mean ± standard deviation) in the surface sediments over 7 years of operation increased from 6.0 ± 2.8 and 14.6 ± 4.5 mg kg -1 to 139.6 ± 87.7 and 279.3 ± 202.9 mg kg -1 dry weight, respectively. The linear regression model explained the behavior and the variability of Cu deposition in the sediments. On the other hand, using the generalized least squares extension with the linear regression model allowed for unequal variance and thus produced a model that explained the variance properly, and as a result, was more successful in explaining the pattern of Zn deposition. Total carbon significantly affected both Cu ( p = 0.047) and Zn ( p < 0.001). Time effect on Cu deposition was statistically significant ( p = 0.013), whereas Zn was significantly affected by the season ( p = 0.009).

54 ENVIRONMENTAL SCIENCES↗

Determination of the major groups of phytoplankton pigments from the absorption spectra of total particulate matter

The contributions of detrital particles and phytoplankton to total light absorption are retrieved by nonlinear regression on the absorption spectra of total particles from various oceanic regions. The model used explains more than 96% of the variance in the observed particle absorption spectra. The resulting absorption spectra of phytoplankton are then decomposed into several Gaussian bands reflecting absorption by phytoplankton pigments. Such a decomposition, combined with high-performance liquid chromatography data on phytoplankton pigment concentrations, allows the computation of specific absorption coefficients for chlorophylls a, b, and c and carotenoids. The spectral values of these in vivo absorption coefficients are then discussed, considering the effects of secondary pigments which were not measured quantitatively. We show that these coefficients can be used to reconstruct the absorption spectra of phytoplankton at various locations and depths. Discrepancies that do occur at some stations are explained in terms of particle size effect. These coefficients can be used to determine the concentrations of phytoplankton pigments in the water, given the absorption spectrum of total particles.

Hoepffner, Nicolas↗

Software Estimates Costs of Testing Rocket Engines

Simulation-Based Cost Model (SiCM) is a computer program that simulates pertinent aspects of the testing of rocket engines for the purpose of estimating the costs of such testing during time intervals specified by its users. A user enters input data for control of simulations; information on the nature of, and activity in, a given testing project; and information on resources. Simulation objects are created on the basis of this input. Costs of the engineering-design, construction, and testing phases of a given project are estimated from numbers and labor rates of engineers and technicians employed in each phase, the duration of each phase; costs of materials used in each phase; and, for the testing phase, the rate of maintenance of the testing facility. The three main outputs of SiCM are (1) a curve, updated at each iteration of the simulation, that shows overall expenditures vs. time during the interval specified by the user; (2) a histogram of the total costs from all iterations of the simulation; and (3) table displaying means and variances of cumulative costs for each phase from all iterations. Other outputs include spending curves for each phase.

Source record↗

Software Estimates Costs of Testing Rocket Engines

Simulation-Based Cost Model (SiCM), a discrete event simulation developed in Extend , simulates pertinent aspects of the testing of rocket propulsion test articles for the purpose of estimating the costs of such testing during time intervals specified by its users. A user enters input data for control of simulations; information on the nature of, and activity in, a given testing project; and information on resources. Simulation objects are created on the basis of this input. Costs of the engineering-design, construction, and testing phases of a given project are estimated from numbers and labor rates of engineers and technicians employed in each phase, the duration of each phase; costs of materials used in each phase; and, for the testing phase, the rate of maintenance of the testing facility. The three main outputs of SiCM are (1) a curve, updated at each iteration of the simulation, that shows overall expenditures vs. time during the interval specified by the user; (2) a histogram of the total costs from all iterations of the simulation; and (3) table displaying means and variances of cumulative costs for each phase from all iterations. Other outputs include spending curves for each phase.

Smith, C. L.↗

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗