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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SCALE Enhancements for Detailed Cask Dose Rate Analysis - Paper 37

The Nuclear Fuels Storage and Transportation Planning Project and the Used Fuel Disposition Campaign, both under the US Department of Energy (DOE) Office of Nuclear Energy, require the ability to predict k{sub eff}, heat generation and temperature distributions, and external dose rates from any combination of commercial spent nuclear fuel assemblies loaded into any type of licensed cask. Work in the Reactor and Nuclear Systems Division at Oak Ridge National Laboratory has begun to develop the UNF-ST[and]DARDS system (Used Nuclear Fuel Storage, Transportation and Disposal Analysis Resource and Data System) that uses many of the nuclear analysis codes from the SCALE package, a comprehensive database of used nuclear fuel inventories from utilities, and a library of model template files to produce complete input files for the various types of UNF computational analyses. UNF-ST[and]DARDS uses the template files and input parameters that are applicable to a safety analysis to assemble and execute a complete input file, collect the output files and relevant information for subsequent calculations, and illustrate calculation results as a function of decay time and other relevant analysis parameters. This paper will focus on the shielding aspects and the ability to predict external dose rates from as-loaded casks. Realistic dose rate values based on actual canister fuel contents may be used in developing appropriate plans, procedures, and methods to keep personnel radiation exposures as low as reasonably achievable during cask repackaging and transportation operations, as well as in performing total system analyses and transportation risk evaluations. The MAVRIC shielding sequence of the SCALE package was created for the US Nuclear Regulatory Commission for analyzing dose rates outside of storage, transfer, or transportation casks loaded with spent nuclear fuel. MAVRIC contains automated variance reduction capabilities based on the CADIS and FW-CADIS methods that are effective for optimizing deep penetration Monte Carlo shielding problems for achieving low relative uncertainties in short computing times. MAVRIC uses the Denovo discrete ordinates code to compute importance maps and biased source terms for the Monaco fixed-source Monte Carlo code, which can use multi-group or continuous-energy cross section data. ORIGEN (Oak Ridge Isotope Generation and Depletion) is the SCALE computer code for calculating time-dependent isotopic concentrations during irradiation and decay for more than 2,200 nuclides that can be produced by nuclear fuel irradiation and activation. A series of SCALE enhancements was implemented to enable automatic decay heat and radiation source term generation and shielding safety analysis of as-loaded casks. The enhancements to SCALE made under this project will be a part of the SCALE 6.2 release expected in fall 2014. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1994

Analysis of small-scale microwave background radiation anisotropy in the presence of foreground contamination

Many of the current round of experiments searching for anisotropies in the microwave background radiation (MBR) are confronting the problem of how to disentangle the cosmic signal from contamination due to Galactic and intergalactic foreground sources. Here we show how commonly used likelihood function techniques can be generalized to account for foreground. Specifically we set some restrictions on the spectrum of foreground contamination but allow the amplitude to vary arbitrarily. The likelihood function thus generalized gives reasonable limits on the MBR anisotropy which, in some cases, are not much less restrictive than what one would get from more detailed modeling of the foreground. Furthermore, the likelihood function is exactly the same as one would obtain by simply projecting out foreground contamination and looking at the reduced data set. We apply this generalized analysis to the recent medium-angle data sets of ACME-HEMT (Gaier et al. 1992; Schuster et al. 1993) and MAX (Meinhold et al. 1993; Gunderson et al. 1993). The resulting analysis constrains the one free parameter in the standard cold dark matter theory to be Q(sub rms-ps) = 18(sub -5 sup +8) microKelvin. This best fit value, although in striking agreement with the normalization from Cosmic Background Explorer (COBE), is not a very good fit, with an overall chi-squared/degrees of freedom = 208/168. We also argue against three commonly used methods of dealing with foreground: (1) ignoring it completely; (2) subtracting off a best-fit foreground and treating the residuals as if uncontaminated; and (3) culling data which appears to be contaminated by foreground.

Dodelson, Scott↗
DOE OSTI2012

System Evaluation and Life-Cycle Cost Analysis of a Commercial-Scale High-Temperature Electrolysis Hydrogen Production Plant

Results of a system evaluation and lifecycle cost analysis are presented for a commercial-scale high-temperature electrolysis (HTE) central hydrogen production plant. The plant design relies on grid electricity to power the electrolysis process and system components, and industrial natural gas to provide process heat. The HYSYS process analysis software was used to evaluate the reference central plant design capable of producing 50,000 kg/day of hydrogen. The HYSYS software performs mass and energy balances across all components to allow optimization of the design using a detailed process flow sheet and realistic operating conditions specified by the analyst. The lifecycle cost analysis was performed using the H2A analysis methodology developed by the Department of Energy (DOE) Hydrogen Program. This methodology utilizes Microsoft Excel spreadsheet analysis tools that require detailed plant performance information (obtained from HYSYS), along with financial and cost information to calculate lifecycle costs. The results of the lifecycle analyses indicate that for a 10% internal rate of return, a large central commercial-scale hydrogen production plant can produce 50,000 kg/day of hydrogen at an average cost of $2.68/kg. When the cost of carbon sequestration is taken into account, the average cost of hydrogen production increases by $0.40/kg to $3.08/kg.

08 HYDROGEN↗
NASA NTRS1995

Wavelet transform analysis of the small-scale X-ray structure of the cluster Abell 1367

We have developed a new technique based on a wavelet transform analysis to quantify the small-scale (less than a few arcminutes) X-ray structure of clusters of galaxies. We apply this technique to the ROSAT position sensitive proportional counter (PSPC) and Einstein high-resolution imager (HRI) images of the central region of the cluster Abell 1367 to detect sources embedded within the diffuse intracluster medium. In addition to detecting sources and determining their fluxes and positions, we show that the wavelet analysis allows a characterization of the sources extents. In particular, the wavelet scale at which a given source achieves a maximum signal-to-noise ratio in the wavelet images provides an estimate of the angular extent of the source. To account for the widely varying point response of the ROSAT PSPC as a function of off-axis angle requires a quantitative measurement of the source size and a comparison to a calibration derived from the analysis of a Deep Survey image. Therefore, we assume that each source could be described as an isotropic two-dimensional Gaussian and used the wavelet amplitudes, at different scales, to determine the equivalent Gaussian Full Width Half-Maximum (FWHM) (and its uncertainty) appropriate for each source. In our analysis of the ROSAT PSPC image, we detect 31 X-ray sources above the diffuse cluster emission (within a radius of 24 min), 16 of which are apparently associated with cluster galaxies and two with serendipitous, background quasars. We find that the angular extents of 11 sources exceed the nominal width of the PSPC point-spread function. Four of these extended sources were previously detected by Bechtold et al. (1983) as 1 sec scale features using the Einstein HRI. The same wavelet analysis technique was applied to the Einstein HRI image. We detect 28 sources in the HRI image, of which nine are extended. Eight of the extended sources correspond to sources previously detected by Bechtold et al. Overall, using both the PSPC and the HRI observations, we detect 16 extended features, of which nine have galaxies coincided with the X-ray-measured positions (within the positional error circles). These extended sources have luminosities lying in the range (3 - 30) x 10(exp 40) ergs/s and gas masses of approximately (1 - 30) x 10(exp 9) solar mass, if the X-rays are of thermal origin. We confirm the presence of extended features in A1367 first reported by Bechtold et al. (1983). The nature of these systems remains uncertain. The luminosities are large if the emission is attributed to single galaxies, and several of the extended features have no associated galaxy counterparts. The extended features may be associated with galaxy groups, as suggested by Canizares, Fabbiano, & Trinchieri (1987), although the number required is large.

Grebeney, S. A.↗
DOE OSTI2017

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42 x compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines.

Biochemistry & Molecular Biology↗
DOE OSTI2015

Past and present cosmic structure in the SDSS DR7 main sample

We present a chrono-cosmography project, aiming at the inference of the four dimensional formation history of the observed large scale structure from its origin to the present epoch. To do so, we perform a full-scale Bayesian analysis of the northern galactic cap of the Sloan Digital Sky Survey (SDSS) Data Release 7 main galaxy sample, relying on a fully probabilistic, physical model of the non-linearly evolved density field. Besides inferring initial conditions from observations, our methodology naturally and accurately reconstructs non-linear features at the present epoch, such as walls and filaments, corresponding to high-order correlation functions generated by late-time structure formation. Our inference framework self-consistently accounts for typical observational systematic and statistical uncertainties such as noise, survey geometry and selection effects. We further account for luminosity dependent galaxy biases and automatic noise calibration within a fully Bayesian approach. As a result, this analysis provides highly-detailed and accurate reconstructions of the present density field on scales larger than ∼ 3 Mpc/h, constrained by SDSS observations. This approach also leads to the first quantitative inference of plausible formation histories of the dynamic large scale structure underlying the observed galaxy distribution. The results described in this work constitute the first full Bayesian non-linear analysis of the cosmic large scale structure with the demonstrated capability of uncertainty quantification. Some of these results will be made publicly available along with this work. The level of detail of inferred results and the high degree of control on observational uncertainties pave the path towards high precision chrono-cosmography, the subject of simultaneously studying the dynamics and the morphology of the inhomogeneous Universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

ThinCurr: An open-source 3D thin-wall eddy current modeling code for the analysis of large-scale systems of conducting structures

In this paper we present a new thin-wall eddy current modeling code, ThinCurr, for studying inductively-coupled currents in 3D conducting structures -- with primary application focused on the interaction between currents flowing in coils, plasma, and conducting structures of magnetically-confined plasma devices. The code utilizes a boundary finite element method on an unstructured, triangular grid to accurately capture device structures. The new code, part of the broader Open FUSION Toolkit, is open-source and designed for ease of use without sacrificing capability and speed through a combination of Python, Fortran, and C/C++ components. Scalability to large models is enabled through use of hierarchical off-diagonal low-rank compression of the inductance matrix, which is otherwise dense. Ease of handling large models of complicated geometry is further supported by automatic determination of supplemental elements through a greedy homology approach. Here, a detailed description of the numerical methods of the code and verification of the implementation of those methods using cross-code comparisons against the VALEN code and Ansys commercial analysis software is shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Chemical Upcycling of Polyethylene, Polypropylene, and Mixtures to High-Value Surfactants

Conversion of plastic wastes to fatty acids is an attractive means to supplement the sourcing of these high-value, high-volume chemicals. We report a method for transforming polyethylene (PE) and polypropylene (PP) at ~80% conversion to fatty acids with number-average molar masses of up to ~700 and 670 daltons, respectively. The process is applicable to municipal PE and PP wastes and their mixtures. Temperature-gradient thermolysis is the key to controllably degrading PE and PP into waxes and inhibiting the production of small molecules. The waxes are upcycled to fatty acids by oxidation over manganese stearate and subsequent processing. PP ..beta..-scission produces more olefin wax and yields higher acid-number fatty acids than does PE ..beta..-scission. We further convert the fatty acids to high-value, large-market-volume surfactants. Industrial-scale technoeconomic analysis suggests economic viability without the need for subsidies.

deconstruction↗
DOE OSTI2013

The MCDB System for Management and Analysis of Petabyte-Scale Uncertain Data

Analysts working with very large data sets often use statistical models to “guess” at unknown, inaccurate, or missing information associated with the data. For example, a distant object viewed through an optical lens will have its position slightly shifted by imperfections in the lens. Thus, rather than considering the object’s observed position to be absolutely correct, it makes sense to take into account the lens’s imperfections to obtain a probabilistic guess as to the object’s true position. For another example, it might be important to associate some sort of error distribution with each of the individual sensors in an array of magnetometers. This error distribution may be complex and include spatially-driven covariances, because errors in nearby sensors are likely to be correlated (caused, for example, by the presence of some nearby, fixed metal object). This project is concerned with the design and implementation of a prototype data management system called the Monte Carlo Database System, or MCDB for short. MCDB allows an expert-level analyst or statistician to attach arbitrary stochastic models to very large data sets in order to “guess” the values for unknown or inaccurate data, such as the actual position of the observed object in the lens example above. When the resulting data set is analyzed, the underlying stochastic models are used to generate hundreds or thousands of possible data set instances, and each of those possible instances is analyzed separately by MCDB. Thus, MCDB does not just give a single answer to the analysis, but it actually gives an empirical distribution of query results that embody the underlying uncertainty, and can in turn be analyzed using standard statistical techniques. The stochastic models in MCDB are implemented as user-defined, external C++ libraries called Variable Generation functions (VG functions for short). Because the VG function interface is exceedingly general, it allows MCDB to be used in a very wide variety of application domains, in conjunction with virtually any stochastic model. Ultimately, we ended up calling the system that we developed over the course of the project SimSQL, to denote the fact that it allowed for stochastic simulation of data. The software developed during the lifetime of the project is available for download from the SimSQL project website: http://cmj4.web.rice.edu/SimSQL/SimSQL.html.

42 ENGINEERING↗
DOE OSTI2026

PERFORMANCE ANALYSIS OF AN ENGINEERING SCALE HYDROTHERMAL LIQUEFACTION SYSTEM

This work evaluates the Modular Hydrothermal Liquefaction System (MHTLS), an engineering-scale, integrated continuous HTL plant operated at the Pacific Northwest National Laboratory (PNNL), for converting realistic wet wastes into energy-dense biocrudes. The production campaigns discussed here processed algae, sewage sludges, lignocellulosic blends, Industrial food waste, and engineered food-waste slurries at 350?°C and around 200?bar, with nominal feed rates of ~12?L?h?¹. We report biocrude yields and composition, establish mass and elemental (C, N) balances, and quantify energy performance via heater duties, heat-exchanger behavior, and system-level efficiencies. Biocrudes contained 76–80?wt?% C (dry, ash-free) with HHVs of 38-41?MJ?kg?¹, substantially higher than feed materials HHVs of 16.6–26.1?MJ?kg?¹ and approaching petroleum fuels. Dry, ash-free biocrude yields of 32–53?wt?% corresponded to 43–71?wt?% carbon yields, with 18–40?wt?% of feed carbon routed to the aqueous phase. Thermal efficiencies were 50-65%, and total energy efficiencies, including reactor heat input, were 35-55%. A counter-current tube-in-tube heat exchanger delivered U values of 200–450?W?m?²?K?¹, with fouling-induced declines impacting heat recovery and heater duty. The analysis highlights three priorities for the process intensification of HTL: robust, fouling-resistant heat recovery, hydrodynamically suitable reactor and heat-exchanger designs, simplified and predictable solids management, and biocrude-water separation.

Biocrude production↗
NASA NTRS1995

Development and Application of the Collaborative Optimization Architecture in a Multidisciplinary Design Environment

Collaborative optimization is a design architecture applicable in any multidisciplinary analysis environment but specifically intended for large-scale distributed analysis applications. In this approach, a complex problem is hierarchically de- composed along disciplinary boundaries into a number of subproblems which are brought into multidisciplinary agreement by a system-level coordination process. When applied to problems in a multidisciplinary design environment, this scheme has several advantages over traditional solution strategies. These advantageous features include reducing the amount of information transferred between disciplines, the removal of large iteration-loops, allowing the use of different subspace optimizers among the various analysis groups, an analysis framework which is easily parallelized and can operate on heterogenous equipment, and a structural framework that is well-suited for conventional disciplinary organizations. In this article, the collaborative architecture is developed and its mathematical foundation is presented. An example application is also presented which highlights the potential of this method for use in large-scale design applications.

Braun, R. D.↗
DOE OSTI2018

Duplications and losses of genes encoding known elements of the stress defence system of the Aspergilli contribute to the evolution of these filamentous fungi but do not directly influence their environmental stress tolerance

The contribution of stress protein duplication and deletion events to the evolution of the Aspergilli was studied. We performed a large-scale homology analysis of stress proteins and generated and analysed three stress defence system models based on Saccharomyces cerevisiae , Schizosaccharomyces pombe and Aspergillus nidulans . Although both yeast-based and A. nidulans -based models were suitable to trace evolutionary changes, the A. nidulans -based model performed better in mapping stress protein radiations. The strong Mantel correlation found between the positions of species in the phylogenetic tree on the one hand and either in the A. nidulans -based or S. cerevisiae -based models on the other hand demonstrated that stress protein expansions and reductions contributed significantly to the evolution of the Aspergilli. Interestingly, stress tolerance attributes correlated well with the number of orthologs only for a few stress proteins. Notable examples are Ftr1 iron permease and Fet3 ferro-O 2 -oxidoreductase, elements of the reductive iron assimilation pathway, in the S. cerevisiae -based model, as well as MpkC, a HogA-like mitogen activated protein kinase in the A. nidulans-based model. In the case of the iron assimilation proteins, the number of orthologs showed a positive correlation with H 2 O 2 -induced stress tolerance while the number of MpkC orthologs correlated positively with Congo Red induced cell wall stress, sorbitol induced osmotic stress and H 2 O 2 induced oxidative stress tolerances. For most stress proteins, changes in the number of orthologs did not correlate well with any stress tolerance attributes. As a consequence, stress tolerance patterns of the studied Aspergilli did not correlate with either the sets of stress response proteins in general or with the phylogeny of the species studied. These observations suggest that stress protein duplication and deletion events significantly contributed to the evolution of stress tolerance attributes of Aspergilli. In contrast, there are other processes, which may counterbalance the effects of stress gene duplications or deletions including (i) alterations in the structures of stress proteins leading to changes in their biological activities, (ii) varying biosynthesis of stress proteins, (iii) rewiring stress response regulatory networks or even (iv) acquiring new stress response genes by horizontal gene transfer. As a result, all these multilevel changes are indispensable for the successful adaptation of filamentous fungi to altering environmental conditions, especially when these organisms are entering new ecological niches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Supporting Co-Design of Extreme-Scale Systems with In Situ Visual Analysis of Event-Driven Simulations (Final Report)

Extreme-scale systems for compute- and data-centric science are pushing the boundaries of system architectures in order to achieve ambitious goals in terms of computing capability, resilience, and power efficiency. Future systems necessitate emerging designs that incorporate new technologies, system organizations, and computer science techniques, and these changes are not yet well understood. Discrete-event-driven simulation of computing system architectures and subsystems has emerged as a productive and cost-effective means to evaluating potential designs, along with capabilities for executing these simulations of extreme-scale systems. However, techniques for analyzing the behavior of these simulations have not kept pace with our ability to perform the simulations, preventing us from extracting the most value from this promising approach. The objective of this project is to support the codesign of extreme-scale system architectures for compute and data-centric science through research and development of novel methods for analysis and visualization of large-scale event-driven simulations.

97 MATHEMATICS AND COMPUTING↗