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The appendices to the previously reported study are presented: statistical data from task rating worksheets; SSD references; survey forms; fourth generation language, a powerful, long-term solution to maintenance cost; task list; methodology; SwRI's instructional systems development model; relevant research; and references.
An important class of techniques for resonant anomaly detection in high energy physics builds models that can distinguish between reference and target datasets, where only the latter has appreciable signal. Such techniques, including Classification Without Labels (CWoLa) and Simulation Assisted Likelihood-free Anomaly Detection (SALAD) rely on a single reference dataset. They cannot take advantage of commonly available multiple datasets and thus cannot fully exploit available information. In this work, we propose generalizations of CWoLa and SALAD for settings where multiple reference datasets are available, building on weak supervision techniques. We demonstrate improved performance in a number of settings with realistic and synthetic data. As an added benefit, our generalizations enable us to provide finite-sample guarantees, improving on existing asymptotic analyses.
In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD models for LRGs, including the base 5-parameter vanilla model and two extensions to it, that we refer to as baseline and extended models. The baseline model is described by the 5 vanilla HOD parameters, an incompleteness factor and a velocity bias parameter, whereas the extended one also includes a galaxy assembly bias and a satellite profile parameter. We utilize the 25 dark matter simulations available in the AbacusSummit simulation suite at z=0.8 and generate mock catalogs for our different HOD models. To test the impact of the HOD modeling in the position of the BAO peak, we run BAO fits for all these sets of simulations and compare the best-fit BAO-scaling parameters α iso and α AP between every pair of HOD models. Furthermore, we do this for both Fourier and configuration spaces independently, using post-reconstruction measurements. We find a 3.3σ detection of HOD systematic for α AP in configuration space with an amplitude of 0.19%. For the other cases, we did not find a 3σ detection, and we decided to compute a conservative estimation of the systematic using the ensemble of shifts between all pairs of HOD models. By doing this, we quote a systematic with an amplitude of 0.07% in α iso for both Fourier and configuration spaces; and of 0.09% in α AP for Fourier space.
Columbia Power LCOE (levelized cost of energy) Model for the Stingray H1 at the DOE Reference Site of Humboldt, CA. The model is integrated with and reports LCOE from DOE Cost Breakdown Structure
Project Design – How do you validate measured Pu model age? There are no certified reference materials (CRMs) that are certified for Pu model age or purification dates. There are no Am isotopic CRMs - IRMM 0243 243 Am spike has 241 Am impurity that can be used; Community working toward "consensus ages." This project executed and evaluated results from a Pu age dating interlaboratory comparison with six IAEA NWAL participant laboratories. It also ran the first quality control evaluation of single-picogram to sub-picogram scale interlaboratory 241 Am assay measurements from cotton swipe matrices. Results are promising, with a majority of 241 Am/ 241 Pu model age results agree to within 1 to 4 years. The calculated 241 Am assay results show interlaboratory variability, expanded percent uncertainties on calculated consensus 241 Am concentrations were: PuAge-S1 = 3.1 %, PuAge-S2 = 23 %, and PuAge-S3 = 26 %. Data can be used to investigate laboratory methods and improve precision and accuracy of 241 Pu and 241 Am assay for future campaigns.
An intercomparison of model stellar atmospheres and observations of real stars can lead to a better understanding of the relationship between the physical properties of stars and their observed radiative flux. In this spirit we have determined wide-band and narrow-band magnitudes and colors for a subset of models of K and M giant and supergiant stars selected from the grid of 40 models by Johnson, Bernat and Krupp (1980) (hereafter referred to as JBK). The 24 models selected have effective temperatures of 4000, 3800, 3600, 3400, 3200, 3000, 2750 and 2500 K and log g = 0, 1 or 2. Emergent energy fluxes (erg/ sq cm s A) were calculated at 9140 wavelengths for each model. These computed flux curves were folded through the transmission functions of Wing's 8-color system (Wing, 1971; White and Wing, 1978) and through Johnson's (1965) wide-band (BVRIJKLM) system. The calibration of the resultant magnitudes was made by using the absolute calibration of the flux curve of Vega by Schild, et al. (1971).
Over the course of more than 70 years, several theoretical models for electric field-enhanced ion diffusion in crystalline insulators have been presented. However, there is no assessment of the validity of these models despite the urge to have a correct description of field-enhanced ion diffusion in several emerging technologies. Herein, an assessment of five models was carried out by computing the field-dependent migration enthalpy ΔH mig (E) for the oxide ion in CeO 2 . The input to these models is the zero-field and zero-temperature migration pathway and/or the activation barrier obtained from an interatomic potential. ΔH mig (E) from these models was compared with reference values obtained from a set of classical molecular-dynamics simulations in the temperature range of 1000 ≤ T ≤ 1600 K and the electric field range of 0 ≤ E ≤ 30 MV/cm. It is revealed that the most successful theoretical models are those that consider local polarization effects induced in the diffusing ion itself and its vicinity. However, all the models did not account for the effect of the electric field and finite temperature on the local polarization, leading to discrepancies between the predicted and the reference ΔH mig (E), particularly at high fields. By comparing results from a rigid-ion potential and a polarizable core-shell potential, it is concluded that an intraionic polarization degree of freedom in the polarizable potential is an important factor in predicting ΔH mig (E), regardless of the field-enhanced diffusion model particularly for low to moderate field. Finally, future more accurate treatments should consider the field- and temperature-dependent interionic and intraionic local polarization effects.
The Structural Dynamics Division at NASA Langley Research Center has started a wind tunnel activity referred to as the Benchmark Models Program. The primary objective of the program is to acquire test data that will be useful for developing and evaluating aeroelastic type CFD codes currently in use of under development. This paper describes the progress achieved in testing the first model in the Benchmark Models Program. Experimental flutter boundaries are presented for a rigid semispan model (NACA 0012 airfoil section) mounted on a flexible mount system. Also, steady and unsteady pressure measurements taken at the flutter condition are presented. The pressure data were acquired over the entire model chord located at the 60 percent span station.
The Waste Isolation Pilot Plant (WIPP) provides for safe, permanent disposal of government-owned transuranic (TRU) and TRU mixed wastes. Receipt and disposal of waste at the WIPP site began in March 1999. The Sandia report, Consideration of Nuclear Criticality When Disposing of Transuranic Waste at the Waste Isolation Pilot Plant, addressed potential nuclear criticality safety issues based on the projected inventory characteristics known at the time [1]. As designs for inventory, waste forms, and disposal packages have changed, new analyses have been performed, and updates have been made to address any potential effects to the WIPP safety basis. New analyses performed include Saylor 2017 [2] and Brickner 2019 [3], which address certain waste containers with specified loadings under post-closure conditions. Both examined several hypothetical scenarios and included analyses to bound (from a criticality potential standpoint) credible configurations that could occur at WIPP during the repository regulatory post-closure disposal time period for feature, event, and process (FEP) considerations—10,000 years. During this post-closure period at WIPP, the screening of FEPs is governed by the risk-based standards and implementing regulations of the US Environmental Protection Agency (EPA) (i.e., 40 CFR 191 and 40 CFR 194, respectively) [4,5]. An FEP screening can be based on either a low-consequence or low-probability rationale. A low-probability rationale includes either (a) a qualitative rationale that the FEP is not credible or (b) a quantitative demonstration that the probability is less than 10-4 in 104 years. In this evaluation, a qualitative lowprobability rationale of not credible is used by demonstrating that bounding configurations of the waste are not critical. The demonstration of subcriticality is through quantitative calculations, but a probability of criticality is not evaluated. Rather, the rationale for this evaluation is that bounding configurations with an effective neutron multiplication factor (keff) well below the upper subcriticality limit (USL) make criticality incredible. Reference [2] documented a nuclear criticality assessment of the WIPP repository for disposal of dilute surplus plutonium materials using the Dilute and Dispose Approach and packaging in criticality control overpacks (CCOs). The CCO is the waste disposal container recently designed to allow for up to 380 fissile gram equivalent (FGE) 239 Pu per drum, which is a higher fissile loading than typical waste containers. The CCO consists of a criticality control container (CCC) positioned by upper and lower plywood spacers within a standard 55 gal drum. The CCC is used to establish a geometry control for fissile materials during transportation and WIPP emplacement operations. The current WIPP waste acceptance criteria for CCO payloads limit beryllium to less than or equal to 1% by weight of the waste contents and require the waste form to be non-machine compacted. Reference [2] considered two scenario progressions—room closure from salt creep, hereafter referred to as the reconfigured dry scenario, and flooding with brine, hereafter referred to as the reconfigured wet scenario. The subsequent drying out of the reconfigured wet scenarios was also considered. For all scenarios, subcriticality was maintained when 50 g of B 4 C (acting as a neutron absorber) per CCC was intermixed within the plutonium disposition waste form. The analysis used a waste form description that limits the amount of moderation that could be present within the waste form (i.e., it limits the amount of water and polyethylene that could be present based on planned processing conditions). This analysis to evaluate increased limits on the amount of moderation that could be present was performed as a companion to Reference [2] to address concerns associated with verifying moisture and/or plastic contents of waste materials following packaging of dilute surplus plutonium in the CCO. To that end, this analysis used the models and methods from Reference [2] to evaluate a more generic base waste form consisting of water and polyethylene that is more similar (and nearly identical) to the generic waste forms utilized in other models/analyses supporting the TRU Package Transporter Model II (TRUPACTII) safety analysis [6] (all are without moderation controls). The waste form in this analysis uses a base mixture of 75% water and 25% polyethylene, the total amount of which is varied to determine the optimum moderation to fissile material (H/Pu) ratio. The fissile loading is maintained at up to 380 FGE 239 Pu (modeled as PuO 2 ) per CCO with an additional 545 g of beryllium (to bound the 1% by weight contents restriction) and 50 g of B 4 C intermixed per CCO. The beryllium content (1% by weight) is based on the total allowed waste weight (this does not include packaging and container weights). Figures ES-1 and ES-2 display summary results, showing that with this model including 50 g of B 4 C per CCO, the system keff remains under 0.85 for all moderator amounts and provides a significant margin against post-closure criticality under postulated bounding conditions for compaction. Figure ES-1 compares an infinite model with a room model at the initial emplacement spacing and under full radial compaction. Full radial compaction places each CCC in direct contact and does not credit any anticipated spacing associated with current post-closure geomechanical modeling of the repository [7]. The effects of variations in the H/Pu ratio were evaluated by varying the amount of the water/polyethylene component of the waste model, with fissile loading maintained at 380 239 Pu FGE. Similarly, Figure ES-2 illustrates how various amounts of B 4 C per CCO influence k eff at different radial compactions, all at the H/Pu ratio of 200 (in the room array model). Therefore, while the results from Saylor 2017 [2] modeled more realistic process limits associated with packaging of dilute surplus plutonium, this analysis demonstrates that limits on moderation (plastic and water content) are not necessary to ensure subcriticality in the WIPP repository, provided the requisite B 4 C absorber is present.
We trained two Random Forest (RF) machine-learning models for cloud mask and cloud thermodynamic phase detection using spectral observations from VIIRS on Suomi NPP (SNPP). Observations from CALIOP were carefully selected to provide reference labels. The two RF models were trained for all-day and daytime-only conditions using a 4-year collocated VIIRS/CALIOP dataset from 2013 to 2016. Due to the orbit difference, the collocated CALIOP and SNPP VIIRS training samples cover a broad viewing zenith angle range, which is a great benefit to overall model performance. The all-day model uses 3 VIIRS infrared (IR) bands (8.6,11, and 12 μm) and the daytime model uses 5 Near-IR (NIR) and Shortwave-IR (SWIR) bands (0.86, 1.24, 1.38, 1.64 and 2.25 μm) together with the 3 IR bands to detect clear, liquid water, and ice cloud pixels. Up to 7 surface types, namely, ocean/water, forest, cropland, grassland, snow/ice, barren/desert, and shrubland, were considered separately to enhance performance for both models. Detection of cloudy pixels and thermodynamic phase with the two RF models were compared against collocated CALIOP products from 2017. It is shown that, with a conservative screening process that excludes the most challenging cloudy pixels for passive remote sensing, the two RF models have high accuracy rates in comparison with the CALIOP reference for both cloud detection and thermodynamic phase. Other existing SNPP VIIRS and Aqua MODIS cloud mask and phase products are also evaluated, with results showing that the two RF models and the MODIS MYD06 optical property phase product are the top 3 algorithms with respect to lidar observations during the daytime. During the nighttime, the RF all-day model works best for both cloud detection and phase, in particular for pixels over snow/ice surfaces. The present RF models can be extended to other similar passive instruments if training samples can be collected from CALIOP or other lidars. However, the quality of reference labels and potential sampling issues that may impact model performance would need further attention.
Mixing models are powerful tools for identifying biogeochemical sources and determining mixing fractions in a sample. However, identification of actual source contributors is often not simple, and source compositions typically vary or even overlap, significantly increasing model uncertainty in calculated mixing fractions. This study compares three probabilistic methods, SIAR [ Parnell et al ., 2010] a pure Monte Carlo technique (PMC), and Stable Isotope Reference Source (SIRS) mixing model, a new technique that estimates mixing in systems with more than three sources and/or uncertain source compositions. In this paper, we use nitrate stable isotope examples (δ 15 N and δ 18 O) but all methods tested are applicable to other tracers. In Phase I of a three-phase blind test, we compared methods for a set of six-source nitrate problems. PMC was unable to find solutions for two of the target water samples. The Bayesian method, SIAR, experienced anchoring problems, and SIRS calculated mixing fractions that most closely approximated the known mixing fractions. For that reason, SIRS was the only approach used in the next phase of testing. In Phase II, the problem was broadened where any subset of the six sources could be a possible solution to the mixing problem. Results showed a high rate of Type I errors where solutions included sources that were not contributing to the sample. In Phase III some sources were eliminated based on assumed site knowledge and assumed nitrate concentrations, substantially reduced mixing fraction uncertainties and lowered the Type I error rate. These results demonstrate that valuable insights into stable isotope mixing problems result from probabilistic mixing model approaches like SIRS. The results also emphasize the importance of identifying a minimal set of potential sources and quantifying uncertainties in source isotopic composition as well as demonstrating the value of additional information in reducing the uncertainty in calculated mixing fractions.
The aim of this study is to evaluate the impact of the bandlike sampling of spaceborne scatterometers on the ability of scatterometer winds to successfully force the mean flow and seasonal cycle of an ocean model in the context of equatorial and tropical dynamics. The equatorial ocean is simulated with a four-layer, primitive equation, reduced gravity model of the Indian Ocean. The variable wind stress used in this study is derived from one year (1988) of 6-hour analyses of the 10-m wind vector over the Indian Ocean performed at the European Centre for Medium-Range Weather Forecasts (ECMWF). It is applied as a forcing at every grid point of the model to drive a reference circulation. Scatterometer winds are simulated from ECMWF winds, using the nominal configurations and orbital parameters of the European Remote Sensing 1 (ERS-1) and NASA Scatterometer (NSCAT) missions. The model is forced in real time under swaths with the raw scatterometer winds of ERS-1 and NSCAT, with a persistence condition (i.e., the wind is kept constsnt until the next passage of the satellite provides a new value). The circulation obtained for each of the scatterometer experiments is compared with the reference circulation. The seasonal circulation of the Indian Ocean with NSCAT winds is very similar to the reference. The perturbations introduced by the bandlike sampling and the persistance condition have an impact similar to that of a small uncorrelated noise added to the reference forcing. The persistence condition for ERS-1 does not give results which are as good as those obtained for NSCAT.
Quantum-chemical computational methods are benchmarked for their ability to describe conical intersections in a series of organic molecules and models of biological chromophores. Reference results for the geometries, relative energies, and branching planes of conical intersections are obtained using ab initio multireference configuration interaction with single and double excitations (MRCISD). They are compared with the results from more approximate methods, namely, the state-interaction state-averaged restricted ensemble-referenced Kohn-Sham method, spin-flip time-dependent density functional theory, and a semiempirical MRCISD approach using an orthogonalization-corrected model. It is demonstrated that these approximate methods reproduce the ab initio reference data very well, with root-mean-square deviations in the optimized geometries of the order of 0.1 Å or less and with reasonable agreement in the computed relative energies. A detailed analysis of the branching plane vectors shows that all currently applied methods yield similar nuclear displacements for escaping the strong non-adiabatic coupling region near the conical intersections. Our comparisons support the use of the tested quantum-chemical methods for modeling the photochemistry of large organic and biological systems.
This work proposes a power control strategy based on the linear quadratic regulator with optimal reference tracking (LQR-ORT) for a three-phase inverter-based generator (IBG) using an LCL filter. The use of an LQR-ORT controller increases robustness margins and reduces the quadratic value of the power error and control inputs during transient response. A model in a synchronous reference frame that integrates power sharing and voltage–current (V–I) dynamics is also proposed. This model allows for analyzing closed-loop eigenvalue location and robustness margins. The proposed controller was compared against a classical droop approach using proportional-resonant controllers for the inner loops. Mathematical analysis and hardware-in-the-loop (HIL) experiments under variations in the LCL filter components demonstrate fulfillment of robustness and performance bounds of the LQR-ORT controller. Experimental results demonstrate accuracy of the proposed model and the effectiveness of the LQR-ORT controller in improving transient response, robustness, and power decoupling.
Abstract Due to the rapidly changing climate, the frequency and severity of extreme weather is expected to increase over the coming decades. As fully‐resolved climate simulations remain computationally intractable, policy makers must rely on coarse‐models to quantify risk for extremes. However, coarse models suffer from inherent bias due to the ignored “sub‐grid” scales. We propose a framework to non‐intrusively debias coarse‐resolution climate predictions using neural‐network (NN) correction operators. Previous efforts have attempted to train such operators using loss functions that match statistics. However, this approach falls short with events that have longer return period than that of the training data, since the reference statistics have not converged. Here, the scope is to formulate a learning method that allows for correction of dynamics and quantification of extreme events with longer return period than the training data. The key obstacle is the chaotic nature of the underlying dynamics. To overcome this challenge, we introduce a dynamical systems approach where the correction operator is trained using reference data and a coarse model simulation nudged toward that reference. The method is demonstrated on debiasing an under‐resolved quasi‐geostrophic model and the Energy Exascale Earth System Model (E3SM). For the former, our method enables the quantification of events that have return period two orders longer than the training data. For the latter, when trained on 8 years of ERA5 data, our approach is able to correct the coarse E3SM output to closely reflect the 36‐year ERA5 statistics for all prognostic variables and significantly reduce their spatial biases.
This report, commissioned by the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), provides a comprehensive set of cost data supporting a cost analysis for the relative economic comparison of options for use in the DOE Nuclear Technology Research and Development (NTRD) Program (previously the Fuel Cycle Research and Development (FCRD) and the Advanced Fuel Cycle Initiative (AFCI)). The report describes the NTRD cost basis development process, reference information on NTRD cost modules, a procedure for estimating fuel cycle costs, economic evaluation guidelines, and a discussion on the integration of cost data into economic computer models. This report contains reference cost data for numerous fuel cycle cost modules (modules A-O) as well as cost modules for a number of reactor types (R modules). The fuel cycle cost modules were developed in the areas of natural uranium mining and milling, thorium mining and milling, conversion, enrichment, depleted uranium disposition, fuel fabrication, interim spent fuel storage, reprocessing, waste conditioning, spent nuclear fuel (SNF) packaging, long-term monitored retrievable storage, managed decay storage, recycled product storage, near surface disposal of low-level waste (LLW), geologic repository and other disposal concepts, and transportation processes for nuclear fuel, LLW, SNF, transuranic, and high-level waste. Since its inception, this report has been periodically updated. The last such internal document was published in August 2015 while the last external edition was published in December of 2009 as INL/EXT-07-12107 and is available on the Web at URL: www.inl.gov/technicalpublications/Documents/4536700.pdf. This current report (Sept 2017) is planned to be reviewed for external release, at which time it will replace the 2009 report as an external publication. This information is used in the ongoing evaluation of nuclear fuel cycles by the NE NTRD program.
A nominal atmospheric model of Mars is presented, with detailed consideration being given to the various sources of variability in the Martian atmosphere. A basic model for the midlatitude summer is outlined for the northern and southern hemispheres. Attention is given to meteorological variability due to winds, diurnal and seasonal pressure variations, temperature changes, and the effects of dust opacity, particularly on temperature stratification. Viking lander IR thermal mapper data are examined in terms of diurnal and latitudinal temperature variations, and cloud and haze formation and locations are discussed. Mass spectrometry of the atmosphere is used to describe the molecular abundances, and water vapor measurements are reviewed. Finally, radio occultation, UV airglow, and mass spectrometry of the Martian upper atmosphere are investigated, along with the temperature structure of the upper atmosphere.
A probabilistic model of brittle fracture is examined with reference to two-dimensional problems. The model is illustrated by using experimental data obtained for 25 macroscopically identical specimens made of short-fiber-reinforced composites. It is shown that the model proposed here provides a predictive formalism for the probability distributions of critical crack depth, critical loads, and crack arrest depths. It also provides similarity criteria for small-scale testing.