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At least 325 records · Page 18

Data-driven Vulnerability Analysis of Networked Pipeline System

This paper introduces an attack generation framework for evaluating the vulnerability of nonlinear networked pipeline systems. The vulnerability analysis is formulated as determining the presence of feasible attack sets, defined by boundary functions representing the effectiveness and stealthiness of attack signals with respect to the objective and attack detection module. The framework utilizes three data-driven models, including two discriminative models that learn the boundary functions and a generative model that produces elements of the feasible attack set. A new loss function ensures successful attack generation with high probability.

03 NATURAL GAS↗

Critical review of functionalized silica sorbent strategies for selective extraction of rare earth elements from acid mine drainage

We report the ubiquitous and growing global reliance on rare earth elements (REEs) for modern technology and the need for reliable domestic sources underscore the rising trend in REE-related research. Adsorption-based methods for REE recovery from liquid waste sources are well-positioned to compete with those of solvent extraction, both because of their expected lower negative environmental impact and simpler process operations. Functionalized silica represents a rising category of low cost and stable sorbents for heavy metal and REE recovery. These materials have collectively achieved high capacity and/or high selective removal of REEs from ideal solutions and synthetic or real coal wastewater and other leachate source. These sorbents are competitive with conventional materials, such as ion exchange resins, activated carbon; and novel polymeric materials like ion-imprinted particles and metal organic frameworks (MOFs). This critical review first presents a data mining analysis for rare earth element recovery publications indexed in Web of science, highlighting changes in REE recovery research foci and confirming the sharply growing interest in functionalized silica sorbents. A detailed examination of sorbent formulation and operation strategies to selectively separate heavy (HREE), middle (MREE), and light (LREE) REEs from the aqueous sources is presented. Selectivity values for sorbents were largely calculated from available figure data and gauged the success of the associated strategies, primarily: (1) silane-grafted ligands, (2) impregnated ligands, and (3) bottom-up ligand/silica hybrids. These were often accompanied by successful co-strategies, especially bite angle control, site saturation, and selective REE elution. Recognizing the need to remove competing fouling metals to achieve purified REE “baskets,” we highlight techniques for eliminating these species from acid mine drainage (AMD) and suggest a novel adsorption-based process for purified REE extraction that could be adapted to different water systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

pyNuMAD v.0.1

SAND2024-08606O The pyNuMAD software is used for managing wind turbine blade model data. pyNuMAD specializes in defining the geometry, materials, and boundary conditions for structural analysis of wind turbine blades. This includes loading in data files and providing an interface for users to make updates to the model. The software also features meshing functionality, which takes the blade model and creates a shell or brick mesh for use in finite element analysis. A typical user workflow might be: load in blade information from a yaml file, make adjustments to the blade properties, update the blade based on the adjustments, create a mesh of the blade, export this blade to another software for structural analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Paquette, Joshua↗

Comparison of PsbQ and Psb27 in photosystem II provides insight into their roles

Photosystem II (PSII) catalyzes the oxidation of water at its active site that harbors a high-valent inorganic Mn 4 CaO x cluster called the oxygen-evolving complex (OEC). Extrinsic subunits generally serve to protect the OEC from reductants and stabilize the structure, but diversity in the extrinsic subunits exists between phototrophs. Recent cryo-electron microscopy experiments have provided new molecular structures of PSII with varied extrinsic subunits. We focus on the extrinsic subunit PsbQ, that binds to the mature PSII complex, and on Psb27, an extrinsic subunit involved in PSII biogenesis. PsbQ and Psb27 share a similar binding site and have a four-helix bundle tertiary structure, suggesting they are related. Here, we use sequence alignments, structural analyses, and binding simulations to compare PsbQ and Psb27 from different organisms. We find no evidence that PsbQ and Psb27 are related despite their similar structures and binding sites. Evolutionary divergence within PsbQ homologs from different lineages is high, probably due to their interactions with other extrinsic subunits that themselves exhibit vast diversity between lineages. This may result in functional variation as exemplified by large differences in their calculated binding energies. Psb27 homologs generally exhibit less divergence, which may be due to stronger evolutionary selection for certain residues that maintain its function during PSII biogenesis which is consistent with their more similar calculated binding energies between organisms. Previous experimental inconsistencies, low confidence binding simulations, and recent structural data suggest that Psb27 is likely to exhibit flexibility that may be an important characteristic of its activity. Furthermore, the analysis provides insight into the functions and evolution of PsbQ and Psb27, and an unusual example of proteins with similar tertiary structures and binding sites that probably serve different roles.

59 BASIC BIOLOGICAL SCIENCES↗

RNA language models predict mutations that improve RNA function

Structured RNA lies at the heart of many central biological processes, from gene expression to catalysis. RNA structure prediction is not yet possible due to a lack of high-quality reference data associated with organismal phenotypes that could inform RNA function. We present GARNET (Gtdb Acquired RNa with Environmental Temperatures), a new database for RNA structural and functional analysis anchored to the Genome Taxonomy Database (GTDB). GARNET links RNA sequences to experimental and predicted optimal growth temperatures of GTDB reference organisms. Using GARNET, we develop sequence- and structure-aware RNA generative models, with overlapping triplet tokenization providing optimal encoding for a GPT-like model. Leveraging hyperthermophilic RNAs in GARNET and these RNA generative models, we identify mutations in ribosomal RNA that confer increased thermostability to the Escherichia coli ribosome. The GTDB-derived data and deep learning models presented here provide a foundation for understanding the connections between RNA sequence, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗

Resolving Atomic-Scale Structure and Chemical Coordination in High-Entropy Alloy Electrocatalysts for Structure–Function Relationship Elucidation

The recent breakthrough in confining five or more atomic species in nanocatalysts, referred to as high-entropy alloy nanocatalysts (HEAs), has revealed the possibilities of multielemental interactions that can surpass the limitations of binary and ternary electrocatalysts. The wide range of potential surface configurations in HEAs, however, presents a significant challenge in resolving active structural motifs, preventing the establishment of structure-function relationships for rational catalyst design and optimization. Here, we present a methodology for creating sub-5 nm HEAs using an aqueous-based peptide-directed route. Using a combination of pair distribution function and X-ray absorption spectroscopy, HEA structure models are constructed from reverse Monte Carlo modeling of experimental data sets and showcase a clear peptide-induced influence on atomic-structure and chemical miscibility. Coordination analysis of our structure models facilitated the construction of structure-function correlations applied to electrochemical methanol oxidation reactions, revealing the complex interplay between multiple metals that leads to improved catalytic properties. Our results showcase a viable strategy for elucidating structure-function relationships in HEAs, prospectively providing a pathway for future materials design.

36 MATERIALS SCIENCE↗

FRAM Isotopic Analysis of High-Resolution CZT Data

H3D Inc. has introduced a new type of CZT detectors that has resolution several times better than that of a typical, single crystal CZT detector. The better resolution has made it easier for software codes to analyze its spectra for isotopic composition of nuclear materials. The Fixed-energy Response-function Analysis with multiple efficiency (FRAM) is one of such software codes. The good peak resolution of the H3D CZT detectors allows the current FRAM v.6.1 and earlier to successfully analyze uranium spectra with minimal modification of the parameter sets and get reasonable results. (A parameter set governs how an analysis is performed.) The exceptionally large high-energy tail of the peaks makes it difficult to achieve good uranium results and impossible to successfully analyze plutonium spectra. The FRAM code needed to be modified to better fit the high-energy tail of the peaks in order to analyze plutonium data and to get better uranium analysis results. Results of this modification, encoded in beta version FRAM v.7.0i, are reported herein.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hyper Suprime-Cam Year 3 results: Cosmology from galaxy clustering and weak lensing with HSC and SDSS using the minimal bias model

Here, we present cosmological parameter constraints from a blind joint analysis of three two-point correlation functions measured from the Year 3 Hyper Suprime-Cam (HSC-Y3) imaging data, covering about 416 deg 2 , and the SDSS DR11 spectroscopic galaxies spanning the redshift range [0.15, 0.70]. We subdivide the SDSS galaxies into three luminosity-cut, and therefore nearly volume-limited samples separated in redshift, each of which acts as a large-scale structure tracer characterized by the measurement of the projected correlation function, w p ⁡(R). We also use the measurements of the galaxy-galaxy weak-lensing signal Δ⁢Σ⁡(R) for each of these SDSS samples which act as lenses for a secure sample of source galaxies selected from the HSC-Y3 shape catalog based on their photometric redshifts. We combine these measurements with the cosmic shear correlation functions, ξ ± ⁡($\vartheta$) measured for our HSC source sample. We model these observables with the minimal bias model of the galaxy clustering observables in the context of a flat Λ⁢CDM cosmology. We use conservative scale cuts, R >12 and 8⁢ℎ -1 Mpc for Δ⁢Σ and w p , respectively, where the minimal bias model is valid, in addition to conservative prior on the residual bias in the mean redshift of the HSC photometric source galaxies. We present various validation tests of our model as well as analysis methods. Our baseline analysis yields S 8 = $0.77⁢5^{+0.043}_{-0.038}$ (68% C.I.) for the Λ⁢CDM model, after marginalizing over uncertainties in other parameters. Our value of S 8 is consistent with that from the Planck 2018 data, but the credible interval of our result is still relatively large. We show that various internal consistency tests based on different splits of the data are passed. Our results are statistically consistent with those of a companion paper, which extends this analysis to smaller scales with an emulator-based halo model, using Δ⁢Σ⁡(R) and w p ⁡(R) down to R >3 and 2⁢ℎ -1 Mpc, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

Driving mode analysis—How uncertain functional inputs propagate to an output

Abstract Driving mode analysis elucidates how correlated features of uncertain functional inputs jointly propagate to produce uncertainty in the output of a computation. Uncertain input functions are decomposed into three terms: the mean functions, a zero‐mean driving mode, and zero‐mean residual. The random driving mode varies along a single direction, having fixed functional shape and random scale. It is uncorrelated with the residual, and under linear error propagation, it produces an output variance equal to that of the full input uncertainty. Finally, the driving mode best represents how input uncertainties propagate to the output because it minimizes expected squared Mahalanobis distance amongst competitors. These characteristics recommend interpretation of the driving mode as the single‐degree‐of‐freedom component of input uncertainty that drives output uncertainty. We derive the functional driving mode, show its superiority to other seemingly sensible definitions, and demonstrate the utility of driving mode analysis in an application. The application is the simulation of neutron transport in criticality experiments. The uncertain input functions are nuclear data that describe how Pu reacts to bombardment by neutrons. Visualization of the driving mode helps scientists understand what aspects of correlated functional uncertainty have effects that either reinforce or cancel one another in propagating to the output of the simulation.

97 MATHEMATICS AND COMPUTING↗

Sensitivity analyses of a homogeneous model and a RZ model of the MYRRHA reactor in its critical configuration

Two homogenized models of the MYRRHA (Multi-purpose hybrid Research Reactor for High-tech Applications) reactor in its critical configuration are presented in this study. Both models will be verified by comparing the main reactor parameters (K{sub eff}, β{sub eff} and Λ) with those of the heterogeneous model and a sensitivity analysis will be performed. A sensitivity analysis of some important parameters related to reactivity, namely the vacuum coefficient, the Doppler and the power peaking factors, is also presented. The study of the vacuum coefficient has been carried out by analyzing two possible scenarios: 50% vacuum in the coolant (lead bismuth eutectic) and 100%, obtaining a list of the 10 reactions and nuclides that most affect the k{sub eff} value. With respect to the Doppler coefficient, it will be seen that a 300 degree increase in fuel temperature (starting at 800 K) results in a reduction of the total reactivity of the system by 134 pcm.. Finally, the map of the power peaking factors will be shown, as well as a sensitivity analysis. For making the sensitivity calculations Serpent-2 reactor physics Monte Carlo code has been used and JEFF-3.3 library has been chosen in order to continue with the OECD/NEA WPEC SG46 work evaluating the nuclear data of this library. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Amplitude analysis of the ${D}_s^{+}$ → π - π + π + decay

A Dalitz plot analysis of the ${D}_s^{+}$ → π - π + π + decay is presented. The analysis is based on proton-proton collision data recorded by the LHCb experiment at a centre of-mass energy of 8 TeV and corresponding to an integrated luminosity of 1.5 fb -1 . The resonant structure of the decay is obtained using a quasi-model-independent partial-wave analysis, in which the π + π - S-wave amplitude is parameterised as a generic complex function determined by a fit to the data. The S-wave component is found to be dominant, followed by the contribution from spin-2 resonances and a small contribution from spin-1 resonances. The latter includes the first observation of the ${D}_s^{+}$ → ω(782)π + channel in the ${D}_s^{+}$ → π - π + π + decay. The resonant structures of the ${D}_s^{+}$ → π - π + π + and ${D}^{+}$ → π - π + π + decays are compared, providing information about the mechanisms for the hadron formation in these decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

WI Fast Stats: a collection of web apps for the visualization and analysis of WI Fast Plants data

WI Fast Stats is an integrated animated web page which serves as a medium to a collection of R-developed web apps that provide Data Visualization and Data Analysis tools for WI Fast Plants data. Each web app corresponds to an educational unit linked to a specific WI Fast Plants webinar and it serves two main functions: 1) K-16 teachers attending the WI Fast Plants webinar will learn how to design Data Science exercises through the web app for their students and 2) students can use the web app independently to learn about visualization and analysis via the publicly available sample datasets and educational materials.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental validation of a co-simulation architecture for modeling whole-building and detailed electrical distribution performance

This article presents an experimental validation of a co-simulation architecture for simultaneously modeling whole-building energy performance and detailed building electrical distribution system performance. The co-simulation architecture consists of a whole-building energy model (EnergyPlus®) embedded within a Modelica-based building electrical distribution system library called the Building Electrical Efficiency Analysis Model (BEEAM) using the Functional Mock-up Interface standard. We validate the model using experimental data collected at a full-scale test cell within Lawrence Berkeley National Laboratory’s FLEXLAB® facility. In conclusion, we show that the co-simulation model accurately predicts the electrical, mechanical, and thermal performance of the test cell for typical loads with both an AC and a DC electrical distribution topology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Methanol adsorption and dissociation on GaP(110) studied by ambient pressure X-ray photoelectron spectroscopy

Ambient pressure X-ray photoelectron spectroscopy (AP-XPS) was used to investigate methanol (CH 3 OH) adsorption and reaction on the GaP(110) surface. Exposure of CH 3 OH to GaP(110) at room temperature led to the formation of at least four different surface species as indicated by analysis of C 1s and O 1s XPS features. By combining AP-XPS data with density functional theory calculations, the surface species were identified as methoxy (CH 3 O*), formaldehyde (CH 2 O*), and paired methanol (p-CH 3 O*H) and methoxy (p-CH 3 O*) species, where “paired” means that they belong to a hydrogen-bonded methoxy-methanol complex. Asterisk * here indicates an adsite. The formation of CH 2 O* via the dehydrogenation of CH 3 O* was shown to be limited by the availability of vacant phosphorus (P) sites on GaP(110). With an increase in CH 3 OH pressure, the fractional coverage of CH 3 O* species reached 0.55, and the surface P sites were completely saturated with hydrogen. Under a constant CH 3 OH pressure of 0.5 Torr, the surface concentration of the paired species and of CH 2 O* remained constant until 400 K. At higher temperatures, thermally driven reactions led to a significant increase in the concentration of surface CH x * species, which suggests that C-O bond cleavage of the CH 3 O group is the dominant decomposition mechanism on GaP(110). In conclusion, based on the reactivity of GaP(110) toward CH 3 OH dehydrogenation, elevated temperatures and CH 3 OH pressures may be used to functionalize this surface.

36 MATERIALS SCIENCE↗

Random Knotting in Fractal Ring Polymers

Many ring polymer systems of physical and biological interest exhibit both pronounced topological effects and nontrivial self-similarity, but the relationship between these two phenomena has not yet been clearly established. Here, we use theory and simulation to formulate such a connection by studying a fundamental topological property—the random knotting probability—for ring polymers with varying fractal dimension, d f . Using straightforward scaling arguments, we generalize a classic mathematical result, showing that the probability of a trivial knot decays exponentially with chain size, N, for all fractal dimensions: P 0 (N) ∝ exp(–N/N 0 ). However, no such simple considerations can account for the dependence of the knotting length, N 0 , on d f , necessitating a more involved analytical calculation. This analysis reveals a complicated double-exponential dependence, which is well supported by numerical data. By contrast, functional forms typical of simple scaling theories fail to adequately describe the observations. These findings are equally valid for two-dimensional ring polymer systems, where “knotting” is defined as the intersection of any two segments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Statistical analysis for the neutrinoless double-β-decay matrix element of 48 Ca

Neutrinoless double-β-decay (0⁢vββ) nuclear matrix elements (NME) are the object of many theoretical calculation methods, and are very important for analysis and guidance of a large number of experimental efforts. However, there are large discrepancies between the NME values provided by different methods. Here, in this paper, we propose a statistical analysis of the 48 Ca 0v⁢ββ NME using the interacting shell model, emphasizing the range of the NME probable values and their correlations with observables that can be obtained from the existing nuclear data. Based on this statistical analysis with three independent effective Hamiltonians, we propose a common probability distribution function for the 0⁢vββ NME, which has a range of (0.45–0.95) at 90% confidence level, and a mean value of 0.68.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

2024 Workshop - Remote Sensing and Fluxes Upscaling for Real-world Impact - Tutorial v1

The software-tutorial was developed within the 2024 Remote Sensing and Fluxes Upscaling for Real-world Impact workshop as part of the hands-on session. The workshop was supported by AmeriFlux, National Ecological Observatory Network (NEON) and CarbonDew. The software provides basic tools to perform the following tasks: - gather remote sensing images using Google Earth Engine API; - gather flux data; - perform basic functions, such as plotting time-series, perform QA of the data, compute vegetation indices; - perform correlation analysis between flux data and remote sensing data; - perform flux predictions based on remote sensing data integrated in different modalities.

Falco, Nicola [Lawrence Berkeley National Laborato↗

Model for the Softening Factor within Stages of Work Hardening

A formulation for a dimensionless coefficient c b is derived that represents a scale of microstructural softening for alloys which follow Kocks-Mecking (K-M) work hardening behavior. The variation of the true plastic strain ε p between the proportional limit σ y and the strength σ u at the instability is determined using the Considère criterion. Parameterization of the model is limited to variables expressly measured within tensile experiments. Further development is now made for the softening factor c bi through the individual and sequential stages 3 and 4 of plastic deformation during K-M work hardening Q behavior. Application is shown for tensile test results of Ti-6Al-4V made by different additively manufactured (AM) processes. It is found that the variation in plastic strain as a function of c bi produces a continuous curve representative of the alloy system. The results of data analysis indicate that Θ o3 and c b3 increase, while Θ o4 and c b4 decrease, as the total plastic strain ε p increases. Furthermore, formulations derived for K-M stages 3 and 4 enable the evaluation of other material parameters such as the activation volume ν* for the onset of plastic deformation. This activation volume is found to be near constant, at a ν*-value of 0.353±0.036 nm 3 as computed using a strain-rate sensitivity of strength exponent m of 0.014, irrespective of the AM method used to produce the Ti-6Al-4V alloy.

36 MATERIALS SCIENCE↗