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At least 955 records · Page 53

Exploration of High-Dimensional Scalar Function for Nuclear Reactor Safety Analysis and Visualization

The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user’s guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving dataset from a nuclear reactor safety simulation.

97 MATHEMATICS AND COMPUTING↗

Exploration of high-dimensional scalar function for nuclear reactor safety analysis and visualization

The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user's guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving data from a nuclear reactor safety simulation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Analysis of diagnostic calorimeter data by the transfer function technique

This paper describes the analysis procedure applied to the thermal measurements on the rear side of a carbon fibre composite calorimeter with the purpose of reconstructing the energy flux due to an ion beam colliding on the front side. The method is based on the transfer function technique and allows a fast analysis by means of the fast Fourier transform algorithm. Its efficacy has been tested both on simulated and measured temperature profiles: in all cases, the energy flux features are well reproduced and beamlets are well resolved. Limits and restrictions of the method are also discussed, providing strategies to handle issues related to signal noise and digital processing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fueling the Future with Fungal Genomes

Genomes of fungi relevant to energy and environment are in focus of the JGI Fungal Genomic Program. One of its projects, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts and pathogens) and biorefinery processes (cellulose degradation and sugar fermentation) by means of genome sequencing and analysis. New chapters of the Encyclopedia can be opened with user proposals to the JGI Community Science Program (CSP). Another JGI project, the 1000 fungal genomes, explores fungal diversity on genome level at scale and is open for users to nominate new species for sequencing. Over 400 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics will lead to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such ‘parts’ suggested by comparative genomics and functional analysis in these areas are presented here.

Grigoriev, Igor V.↗

Fungal Genomics for Energy and Environment

Genomes of fungi relevant to energy and environment are in focus of the Fungal Genomic Program at the US Department of Energy Joint Genome Institute (JGI). One of its projects, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts) by means of genome sequencing and analysis. New chapters of the Encyclopedia can be opened with user proposals to the JGI Community Sequencing Program (CSP). Another JGI project, the 1000 fungal genomes, explores fungal diversity on genome level at scale and is open for users to nominate new species for sequencing. Over 200 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics leads to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such parts suggested by comparative genomics and functional analysis in these areas are presented here.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-Wide Analysis of Sorghum GT47 Family Reveals Functional Divergences of MUR3-Like Genes

Sorghum (Sorghum bicolor) is an important bioenergy crop. Its biomass mainly consists of the cellulosic and non-cellulosic polysaccharides, both which can be converted to biofuels. The biosynthesis of non-cellulosic polysaccharides involves several glycosyltransferases (GT) families including GT47. However, there was no systemic study on GT47 family in sorghum to date. Here, we identified 39 sorghum GT47 family members and showed the functional divergences of MURUS3 (MUR3) homologs. Sorghum GT47 proteins were phylogenetically clustered into four distinct subfamilies. Within each subfamily, gene structure was relatively conserved between the members. Ten gene pairs were identified from the 39 GT47 genes, of which two pairs might be originated from tandem duplication. 25.6% (10/39) of sorghum GT47 genes were homologous to Arabidopsis MUR3, a xyloglucan biosynthesis gene in primary cell walls. SbGT47_2, SbGT47_7, and SbGT47_8, three most homologous genes of MUR3, exhibited different tissue expression patterns and were selected for complementation into Arabidopsis mur3-3. Physiological and cell wall analyses showed that SbGT47_2 and SbGT47_7 may be two functional xyloglucan galactosyltransferases in sorghum. Further studies found that MUR3-like genes are widely present in the seed plants but not in the chlorophytic alga Chlamydomonas reinhardtii. Our results provide novel information for evolutionary analysis and functional dissection of sorghum GT47 family members.

59 BASIC BIOLOGICAL SCIENCES↗

Investigating biofilm structure using x-ray microtomography and gratings-based phase contrast

Direct examination of natural and engineered environments has revealed that the majority of microorganisms in these systems live in structured communities termed biofilms. To gain a better understanding for how biofilms function and interact with their local environment, fundamental capabilities for enhanced visualization, compositional analysis, and functional characterization of biofilms are needed. For pore-scale and community-scale analysis (100’s of nm to 10’s of microns), a variety of surface tools are available. However, understanding biofilm structure in complex three-dimensional (3-D) environments is considerably more difficult. X-ray microtomography can reveal a biofilm’s internal structure, but the obtaining sufficient contrast to image low-Z biological material against a higher-Z substrate makes detecting biofilms difficult. Here we present results imaging Shewanella oneidensis biofilms on a Hollow-fiber Membrane Biofilm Reactor (HfMBR), using the x-ray microtomography system at sector 2-BM of the Advanced Photon Source (APS), at energies ranging from 13-15.4 keV and pixel sizes of 0.7 and 1.3 μm/pixel. We examine the use of osmium (Os) as a contrast agent to enhance biofilm visibility and demonstrate that staining improves imaging of hydrated biofilms. We also present results using a Talbot interferometer to provide phase and scatter contrast information in addition to absorption. Talbot interferometry allows imaging of unstained hydrated biofilms with phase contrast, while absorption contrast primarily highlights edges and scatter contrast provides little information. However, the gratings used here limit the spatial resolution to no finer than 2 μm, which hinders the ability to detect small features. Future studies at higher resolution or higher Talbot order for greater sensitivity to density variations may improve imaging.

Environmental Molecular Sciences Laboratory↗

Binding Geometries of Silicate Species on Ferrihydrite Surfaces

Silicate sorption on ferrihydrite surfaces, as monomers, oligomers, and polymers, strongly affects ferrihydrite crystallinity, thermodynamic stability, and surface reactivity. How these silicate species bind on ferrihydrite surfaces is, however, not well understood. We have determined silicate binding geometries using a combination of X-ray absorption spectroscopy (XAS), differential atomic pair distribution function (d-PDF) analysis, and density functional theory (DFT) calculations. Silicon K-edge absorption pre-edges and DFT-predicted energies indicate that silicate forms monomeric monodentate–mononuclear (MM) complexes at low silicate sorption loadings. With increasing silicate loading, the pre-edge peak shifts to higher energies, suggesting changes in the silicate binding geometry toward multidentate complexation. The d-PDF analysis determines the Si–Fe interatomic distance to be ~3.25 Å for the high-loading samples. The DFT calculations indicate that such distance corresponds to an oligomer in the bidentate–binuclear (BB) binding geometry. The transition of the silicate sorption geometry accompanied by polymerization can affect stability of ferrihydrite and its adsorption and redox reactivity and increase the degree of Si isotopic fractionation upon silicate sorption on Fe oxides. MM monomeric complexes and BB oligomeric complexes should be used for surface complexation models predicting silicate sorption on Fe oxide surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantitative proteomic analyses of the response of acidophilic microbial communities to different pH conditions

Extensive genomic characterization of multi-species acid mine drainage microbial consortia combined with laboratory cultivation has enabled the application of quantitative proteomic analyses at the community level. In this study, quantitative proteomic comparisons were used to functionally characterize laboratory-cultivated acidophilic communities sustained in pH 1.45 or 0.85 conditions. The distributions of all proteins identified for individual organisms indicated biases for either high or low pH, and suggests pH-specific niche partitioning for low abundance bacteria and archaea. Although the proteome of the dominant bacterium, Leptospirillum group II, was largely unaffected by pH treatments, analysis of functional categories indicated proteins involved in amino acid and nucleotide metabolism, as well as cell membrane/envelope biogenesis were overrepresented at high pH. Comparison of specific protein abundances indicates higher pH conditions favor Leptospirillum group III, whereas low pH conditions promote the growth of certain archaea. Thus, quantitative proteomic comparisons revealed distinct differences in community composition and metabolic function of individual organisms during different pH treatments. Proteomic analysis revealed other aspects of community function. Different numbers of phage proteins were identified across biological replicates, indicating stochastic spatial heterogeneity of phage outbreaks. Additionally, proteomic data were used to identify a previously unknown genotypic variant of Leptospirillum group II, an indication of selection for a specific Leptospirillum group II population in laboratory communities. Our results confirm the importance of pH and related geochemical factors in fine-tuning acidophilic microbial community structure and function at the species and strain level, and demonstrate the broad utility of proteomics in laboratory community studies.

54 ENVIRONMENTAL SCIENCES↗

Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small-Angle X-ray Scattering Analysis

The combination of in situ pair distribution function (PDF) analysis and small-angle X-ray scattering (SAXS) enables analysis of the formation mechanism of metal oxido nanoclusters and cluster–solvent interactions as they take place. Herein, we demonstrate the method for the formation of clusters with a [Bi 38 O 45 ] core. Upon dissolution of crystalline [Bi 6 O 5 (OH) 3 (NO 3 ) 5 ]∙3 H 2 O in DMSO, an intermediate rapidly forms, which slowly grows to stable [Bi 38 O 45 ] clusters. To identify the intermediate, we developed an automated modeling method, where smaller [Bi x O y ] structures based on the [Bi 38 O 45 ] framework are tested against the data. [Bi 22 O 26 ] was identified as the main intermediate species, illustrating how combined PDF and SAXS analysis is a powerful tool to gain insight into nucleation on an atomic scale. PDF also provides information on the interaction between nanoclusters and solvent, which is shown to depend on the nature of the ligands on the cluster surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defect accumulation in swift heavy ion-irradiated CeO 2 and ThO 2

Here, neutron total scattering was used to investigate defect accumulation mechanisms in CeO 2 and ThO 2 irradiated with 2.2 GeV Au ions. Pair distribution function (PDF) analysis was applied to characterize the local structural evolution and irradiation-induced defects as a function of irradiation fluence. CeO 2 exhibits a greater amount of disorder than ThO 2 under the same irradiation conditions. The local structures of the two materials evolve differently as a function of ion fluence, even if similar defects are produced. The PDF analysis indicates that oxygen dimer and/or peroxide defects with distances of ~1.45 Å are formed in CeO 2 , while irradiation-induced defects in ThO 2 result in a change in the mean O–Th–O bond angle and a distortion of local ThO 8 polyhedra. Understanding how bound oxygen defects, such as peroxide, affect bulk oxygen transport in CeO 2 will aid in better predicting and improving properties of fluorite structure materials for fast ion conductor applications.

36 MATERIALS SCIENCE↗

Emphanitic anharmonicity in PbSe at high temperature and anomalous electronic properties in the Pb Q ( Q = S , Se , Te ) system

Here, the temperature dependence of the local structure of PbSe has been investigated using pair distribution function (PDF) analysis of x-ray and neutron powder diffraction data and density functional theory (DFT) calculations. Observation of non-Gaussian PDF peaks at high temperature indicates the presence of significant anharmonicity, which can be modeled as Pb off-centering along [100] directions that grows on warming similar to the behavior seen in PbTe and PbS and sometimes called emphanisis. Interestingly, the emphanitic response is smaller in PbSe than in both PbS and PbTe indicating a nonmonotonic response with chalcogen atomic number in the PbQ (Q = S, Se, Te) series. The DFT calculations indicate a correlation between band gap and the amplitude of [100] dipolar distortion, suggesting that emphanisis may be behind the anomalous composition and temperature dependencies of the band gaps in this series.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Analysis and selection of optimal function implementations in massively parallel computer

An apparatus, program product and method optimize the operation of a parallel computer system by, in part, collecting performance data for a set of implementations of a function capable of being executed on the parallel computer system based upon the execution of the set of implementations under varying input parameters in a plurality of input dimensions. The collected performance data may be used to generate selection program code that is configured to call selected implementations of the function in response to a call to the function under varying input parameters. The collected performance data may be used to perform more detailed analysis to ascertain the comparative performance of the set of implementations of the function under the varying input parameters.

97 MATHEMATICS AND COMPUTING↗

Modeling the dynamics of phospholipids in the fluid phase of liposomes

Here, we present the derivation of a new model to describe neutron spin echo spectroscopy and quasi-elastic neutron scattering data on liposomes. We compare the new model with existing approaches and benchmark it with experimental data. The analysis indicates the importance of including all major contributions in the modeling of the intermediate scattering function. Simultaneous analysis of the experimental data on lipids with full contrast and tail contrast matched samples reveals highly confined lipid tail motion. A comparison of their dynamics demonstrates the statistical independence of tail-motion and height–height correlation of the membrane. A more detailed analysis indicates that the lipid tail relaxation is confined to a potential with cylindrical symmetry, in addition to the undulation and diffusive motion of the liposome. Despite substantial differences in the chemistry of the fatty acid tails, the observation indicates a universal behavior. The analysis of partially deuterated systems confirms the strong contribution of the lipid tail to the intermediate scattering function. Within the time range from 5 to 100 ns, the intermediate scattering function can be described by the height–height correlation function. The existence of the fast-localized tail motion and the contribution of slow translational diffusion of liposomes determine the intermediate scattering function for t < 5 ns and t > 100 ns, respectively. Taking into account the limited time window lowers the bending moduli by a factor of 1.3 (DOPC) to 2 (DMPC) compared to the full range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the Chemical Kinetics of Minimalist Functional Group Gasoline Surrogates

We report surrogate mixtures are routinely used for understanding gasoline fuel combustion in engine simulations. The general trend in surrogate formulation has been to increase the number of fuel components in a mixture to better emulate real fuel properties. Recently, a new surrogate design strategy based on functional group analysis of real gasolines was proposed using a minimal number of species [minimalist functional group (MFG)-approach]. MFG surrogates (having just one or two components) could experimentally capture the ignition delay time (IDT), threshold sooting index, and smoke point of different gasoline fuels with hundreds of components. However, other combustion characteristics were not explored, and kinetic modeling of MFG surrogates was not reported. These aspects are addressed in this paper, where the combustion behavior of MFG surrogates for various gasolines was assessed by simulating IDT, jet-stirred reactor oxidation, and premixed laminar flame speeds using chemical kinetic modeling. MFG simulations were compared with experimental data of the real gasolines as well as with the more complex multicomponent (five to nine species) surrogates. This study reveals that binary MFG surrogate mixtures are capable of accurately simulating the combustion behavior of more complex gasoline fuels with hundreds of components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An iterative forward analysis technique to determine the equation of state of dynamically compressed materials

Here, we developed an iterative forward analysis (IFA) technique with the ability to use hydrocode simulations as a fitting function for analysis of dynamic compression experiments. The IFA method optimizes over parameterized quantities in the hydrocode simulations, breaking the degeneracy of contributions to the measured material response. Velocity profiles from synthetic data generated using a hydrocode simulation are analyzed as a first-order validation of the technique. We also analyze multiple magnetically driven ramp compression experiments on copper and compare with more conventional techniques. Excellent agreement is obtained in both cases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Cluster spin glass correlations and dynamics in Zn 0.5⁢ Mn 0.5⁢ Te

Here, we present a combined magnetometry, muon spin-relaxation (𝜇⁢SR), and neutron-scattering study of the insulating spin glass Zn 0.5 ⁢Mn 0.5 ⁢Te, for which magnetic Mn 2+ and nonmagnetic Zn 2+ ions are randomly distributed on a face-centered cubic lattice. The magnetometry and 𝜇⁢SR results confirm a spin freezing transition around 𝑇 𝑓 ≈ 23 K, with the spin-fluctuation rate decreasing gradually and somewhat inhomogeneously through the sample volume as the temperature decreases toward 𝑇 𝑓 . Characteristic spin-correlation times well above 𝑇 𝑓 are on the order of 10 −10 s, much slower than typically observed in canonical spin glasses but in line with expectations for a cluster spin glass. Using magnetic pair distribution function (mPDF) analysis and reverse Monte Carlo (RMC) modeling of the magnetic diffuse neutron-scattering data, we show that the spin-glass ground state consists of clusters of spins exhibiting short-range-ordered type-III antiferromagnetic correlations with a locally ordered moment of 3.1⁢(1)⁢𝜇 B between nearest-neighbor spins. The type-III correlations decay exponentially as a function of spin separation distance with a correlation length of approximately 5 Å. The diffuse magnetic scattering and corresponding mPDF show no significant changes across 𝑇 𝑓 , indicating that the dynamically fluctuating short-range spin correlations in the paramagnetic state retain the same basic type-III configuration that characterizes the spin-glass state; the only change apparent from the neutron-scattering data is a gradual reduction of the correlation length and locally ordered moment with increasing temperature. Taken together, these results paint a unique and detailed picture of the local magnetic structure and dynamics in Zn 0.5 ⁢Mn 0.5⁢ Te and provide strong evidence that this material is best described as a cluster spin glass. In addition, this work showcases a statistical method for extracting diffuse scattering signals from neutron powder diffraction data, which we developed to facilitate the mPDF and RMC analysis of the neutron data. This method has the potential to be broadly useful for neutron powder diffraction experiments on a variety of materials with short-range atomic or magnetic order.

magnetism↗