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At least 91 records · Page 5

Requirements for Cataloging Hanford Geophysical Datasets

Environmental management activities at the Hanford Site produce extensive data about site conditions, contaminants, cleanup, and more. Managing and archiving that data requires a high degree of collaboration among site contractors and a high level of awareness by project managers and staff. Part of that effort is developing a Hanford Environmental Information and Data Index (HEIDI) to organize the data and maximize its value by making it findable and available for reuse. The objective is to catalog the disparate data sets collected to address the evolving needs of planning, executing, and documenting cleanup over several decades up to the present day, including links to active data sources when available. A properly implemented data catalog makes finding environmental datasets related to an area or theme a routine, reliable process, without requiring the searcher to have special knowledge that a data set exists and where it may be stored. In this project, a working group, including the U.S. Department of Energy, the Hanford Site contractors, and Pacific Northwest National Laboratory staff, identified needs and requirements for handling complex site data. Geophysical data was chosen as a test case because it can be large and complex and often involves multiple processing steps to extract the information incorporated into deliverables. The ability to document those steps was one of the requirements identified for the catalog. In addition to developing requirements, other activities included selecting a metadata schema and initial testing with the objective of determining whether the workflow and capabilities of selected data catalog software platforms were sufficient to implement and impose the identified requirements. This initial testing involved running the default catalog instance using the software platform of interest and altering the configuration to achieve each requirement, if possible. Where configuration alone was insufficient, the possibility of modifying the software by changing the code was examined, but not implemented. A follow-on task is planned to reprogram the code as necessary to implement requirements in a prototype catalog.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A variational framework for residual-based adaptivity in neural PDE solvers and operator learning

Residual-based adaptive strategies are widely used in scientific machine learning yet remain largely heuristic. We introduce a variational framework that formalizes these methods through convex transformations of the residual, where different transformations correspond to distinct objective functionals. For instance, exponential weights target uniform error minimization, while linear weights recover quadratic error minimization. This perspective reveals adaptive weighting as a means of selecting sampling distributions that optimize a primal objective, directly linking discretization choices to error metrics. This principled approach yields three key benefits: it enables systematic design of adaptive schemes, reduces discretization error by lowering estimator variance, and enhances learning dynamics by improving gradient signal-to-noise ratio. Extending the framework to operator learning, we demonstrate substantial performance gains across diverse optimizers and architectures. Our results provide a theoretical perspective for residual-based adaptivity and establish a foundation for principled discretization and training.

97 MATHEMATICS AND COMPUTING↗

Inner versus Outer Sphere Metal-Monoamide Complexation: Ramifications for Tetravalent & Hexavalent Actinide Selectivity

Extraction of tetravalent and hexavalent plutonium by straight and branched chained monoamides was studied using UV-Vis spectroscopy. It was determined that predominantly anionic, outer sphere species are, formed, in all instances instead of Pu4+ recovery by acyl branched monoamides. Distribution values calculated from UV-Vis analysis were compared to tracer level LSC measurements, and were found to agree. Distribution values of hexavalent Am were also assessed. Good distribution values were achieved with straight monoamides and bis-2-ethyl hexyl phosphoric acid.

actinide separation, amide extractant↗

Recommended Nuclear Data for the Production of Selected Therapeutic Radionuclides

Increasing interest in the treatment of human disease by means of targeted radionuclide-based therapies requires an accurate understanding of achievable yields and quantification of realisable degrees of purity. Important studies within a more extensive Coordinated Research Project of the International Atomic Energy Agency (IAEA CRP) have included in-depth assessments and evaluations of all available measured cross-section data for ten nuclear reactions leading to the formation of 131 Cs, 131 Ba, 225 Ac, 225 Ra, 227 Th, 227 Ac, 230 U and 230 Pa for various on-going and proposed therapeutic applications in nuclear medicine. Equivalent studies were also undertaken of possible reactions to produce the 178W /low-spin 178m Ta generator system that has been clinically applied in diagnosis by means of SPECT - these particular cross-section studies and recommendations are included in this paper for completeness. All available measured data have been critically reviewed and assessed to produce statistically consistent datasets. Selected datasets have been fitted by a least-squares method with Padé approximations of variable order to evaluate the production cross sections and corresponding uncertainties. New measurements have been made in some instances, and reported data have been adjusted to accommodate new nuclear decay or monitor reaction data which altered the original reported quantities adversely. Insufficient measured data are available in many cases to permit a reliable evaluation of cross sections, and these instances are discussed. Finally, recommended therapeutic radionuclide production reaction data and their uncertainties are available on the Web page of the IAEA Nuclear Data Section at www-nds.iaea.org/radionuclides/ and also at the IAEA medical portal www-nds.iaea.org/medportal/.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Using Receiver Operating Characteristic Curves to Optimize Discovery-Based Software with Comprehensive Two-Dimensional Gas Chromatography with Time-of-Flight Mass Spectrometry

We report a quantitative approach to optimize implementation of discovery-based software for comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC – TOFMS). The software performs a tile-based Fisher ratio (F-ratio) analysis, and facilitates a supervised non-targeted analysis based upon the experimental design to aid in the discovery of analytes whose variances are statistically different between sample classes. The quantitative approach for software optimization uses receiver operating characteristic (ROC) curves. The area under the curve (AUC) of each ROC curve serves as a quantitative metric to optimize two key algorithm parameters: the signal-to-noise ratio (S/N) threshold of the baseline corrected and normalized data prior to calculating F-ratios at each m/z mass channel, and the number of these F-ratios per m/z to include in the calculation of the average F-ratio of a tile. A total of 25 combinations of S/N threshold by number of m/z were studied. Fifty analytes were spiked into a diesel fuel at two concentration spike levels to produce two sample classes that should in principle produce 50 positive instances in the ROC curves (30 native/20 non-native compounds, at spike levels of 200/20 and100/10 ppm native/non-native, respectively). The “sweet spot” for F-ratio analysis was determined to be a S/N threshold of 10 coupled with a maximum of the 10 most chemically selective m/z (requiring a minimum of 3 m/z), corresponding to a ~ 21% improvement in the discovery rate of true positives relative to prior studies. Furthermore, it was observed that optimization of these software parameters did not depend upon a priori determination of the statistically correct number of positive instances in the sample classes. The AUC metric appears to be suitable for the evaluation of all data analysis methods that utilize the proper experimental design.

3D-GS/TOFMS, Data discovery, ROC curves, Fisher ra↗

Discriminating electromagnetic radiation based on angle of incidence

The present invention provides systems, articles, and methods for discriminating electromagnetic radiation based upon the angle of incidence of the electromagnetic radiation. In some cases, the materials and systems described herein can be capable of inhibiting reflection of electromagnetic radiation (e.g., the materials and systems can be capable of transmitting and/or absorbing electromagnetic radiation) within a given range of angles of incidence at a first incident surface, while substantially reflecting electromagnetic radiation outside the range of angles of incidence at a second incident surface (which can be the same as or different from the first incident surface). A photonic material comprising a plurality of periodically occurring separate domains can be used, in some cases, to selectively transmit and/or selectively absorb one portion of incoming electromagnetic radiation while reflecting another portion of incoming electromagnetic radiation, based upon the angle of incidence. In some embodiments, one domain of the photonic material can include an isotropic dielectric function, while another domain of the photonic material can include an anisotropic dielectric function. In some instances, one domain of the photonic material can include an isotropic magnetic permeability, while another domain of the photonic material can include an anisotropic magnetic permeability. In some embodiments, non-photonic materials (e.g., materials with relatively large scale features) can be used to selectively absorb incoming electromagnetic radiation based on angle of incidence.

Hamam, Rafif E.↗

IMS observations of infrasound and acoustic-gravity waves produced by the January 2022 volcanic eruption of Hunga, Tonga: A global analysis

The 15 January 2022 Hunga, Tonga, volcano's explosive eruption produced the most powerful blast recorded in the last century, with an estimated equivalent TNT yield of 100–200 megatons. The blast energy was propagated through the atmosphere as various wave types. The most prominent wave was a long-period (>2000 s) surface-guided Lamb wave with energy comparable to that of the 1883 Krakatoa Lamb wave; both were clearly observed by pressure sensors (barometers) worldwide. Internal gravity, acoustic-gravity, and infrasound waves were captured in great detail by the entire infrasound component of the International Monitoring System (IMS). For instance, infrasound waves (<300 s period) were seen to circumnavigate Earth up to eight times. Atmospheric waves captured by the IMS infrasound network and selected barometers near the source provide insight on Earth's impulse response at planetary scales.

58 GEOSCIENCES↗

Next generation experimental data access at NSLS-II

The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.

36 MATERIALS SCIENCE↗

Properties of F Stars with Stable Radial Velocity Timeseries: A Useful Metric for Selecting Low-jitter F Stars

In a companion paper, we have conducted an in-depth analysis of radial velocity jitter of over 600 stars, examining the astrophysical origins including stellar granulation, oscillation, and magnetic activity. In this paper, we highlight a subsample of those stars, specifically the main sequence and “retired” F stars—which we refer to as “MSRF” stars—that show low levels of RV jitter (<10 m s{sup −1}). We describe the observational signatures of these stars that allow them to be identified in radial velocity planet programs, for instance, those performing follow-up of transiting planets discovered by TESS. We introduce a “jitter metric” that combines the two competing effects of RV jitter with age: activity and convection. Using thresholds in the jitter metric, we can select both “complete” and “pure” samples of low jitter F stars. We also provide recipes for identifying these stars using only Gaia colors and magnitudes. Finally, we describe a region in the Gaia color–magnitude diagram where low jitter F stars are most highly concentrated. By fitting a ninth-order polynomial to the Gaia main sequence, we use the height above the main sequence as a proxy for evolution, allowing for a crude selection of low jitter MSRF stars when activity measurements are otherwise unavailable.

79 ASTRONOMY AND ASTROPHYSICS↗

Multiplex growth rate phenotyping of synthetic mutants in selection to engineer glucose and xylose co‐utilization in Escherichia coli

ABSTRACT Engineering the simultaneous consumption of glucose and xylose sugars is critical to enable the sustainable production of biofuels from lignocellulosic biomass. In most major industrial microorganisms glucose completely inhibits the uptake of xylose, limiting efficient sugar mixture conversion. In E . coli removal of the major glucose transporter PTS allows for glucose and xylose co‐consumption but only after prolonged adaptation, which is an effective process but hard to control and prone to co‐evolving undesired traits. Here we synthetically engineer mutants to target sugar co‐consumption properties; we subject a PTS − mutant to a short adaptive step and subsequently either delete or overexpress key genes previously suggested to affect sugar consumption. Screening the co‐consumption properties of these mutants individually is very laborious. We show we can evaluate sugar co‐consumption properties in parallel by culturing the mutants in selection and applying a novel approach that computes mutant growth rates in selection using chromosomal barcode counts obtained from Next‐Generation Sequencing. We validate this multiplex growth rate phenotyping approach with individual mutant pure cultures, identify new instances of mutants cross‐feeding on metabolic byproducts, and, importantly, find that the rates of glucose and xylose co‐consumption can be tuned by altering glucokinase expression in our PTS − background. Biotechnol. Bioeng. 2017;114: 885–893. © 2016 Wiley Periodicals, Inc.

Groot, Joost↗

Decomposing a renewable energy design and dispatch model

We address a mixed-integer linear programming model which selects a cost-minimizing set of available technologies with which to design a renewable energy system and prescribe their associated dispatch decisions. Realistically sized instances of such models pose computational challenges. To this end, we develop a Lagrangian heuristic based on a decomposition methodology which partitions the model into blocks and optimizes these more manageable, smaller subproblems. It also provides a lower bound to assess solution quality. In conclusion, we apply this methodology to the National Renewable Energy Laboratory's Renewable Energy Integration and Optimization (REopt TM ) model to generate near-optimal solutions to realistic instances containing, on average, approximately 300,000 variables and at least as many constraints, with a mean 30% optimality gap improvement using a five-minute solution time limit, compared to directly solving the original monolith.

97 MATHEMATICS AND COMPUTING↗

Assessment of the analysis capability for core-wide PWR pellet-clad interaction screening of Watts Bar Unit 1

This report illustrates the application of the Virtual Environment for Reactor Applications simulation environment to pressurized water reactor core-wide pellet-clad interaction screening, with emphasis on the multi-dimensional analysis capabilities of the BISON fuel performance code. The Virtual Environment for Reactor Applications codes utilized in this effort include the BISON fuel performance code and the VERA-CS sub-element, which combines the MPACT neutron transport code and the COBRA-TF thermal-hydraulics code. The target reactor for this work is Watts Bar Unit 1, cycle 6 and cycle 7, selected on the basis that pellet-clad interaction failures had occurred during power start up in both cycles, despite the moderate power levels. These instances of failure at Watts Bar Unit 1 offered an interesting test of the code’s veracity and a particularly challenging condition for this assessment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Biomass Demineralization: A Critical Need for Future Biorefineries

Biomass contains up to 14 essential elements that serve as nutrients for plant growth and development, including photosynthesis and enzyme functionalities. These elements in different chemical forms (e.g., minerals) constitute the inorganic fraction of biomass and can cause operational issues in thermal and biochemical biomass conversion technologies. In biomass gasification and pyrolysis processes, for instance, inorganics can cause fouling, tar formation, and corrosion. In catalytic and biochemical processes, inorganics can poison catalysts, alter biochemical pathways, and modify product yields and selectivity. This review provides an overview of the inorganic content in biomass feedstocks, the critical role inorganics play in plant biochemistry, the effect that inorganics have in various thermochemical and biochemical biomass conversion technologies, and different approaches to remove them from biomass. We provide recommendations for future research, focusing on developing technologies to effectively remove inorganics from biomass, using the inorganics to improve soil quality and for alternative applications, and designing biorefineries to convert demineralized biomass obtained from diverse sources.

09 - BIOMASS FUELS↗

Model for mapping settlements

A programmable media includes a graphical processing unit in communication with a memory element. The graphical processing unit is configured to detect one or more settlement regions from a high resolution remote sensed image based on the execution of programming code. The graphical processing unit identifies one or more settlements through the execution of the programming code that executes a multi-instance learning algorithm that models portions of the high resolution remote sensed image. The identification is based on spectral bands transmitted by a satellite and on selected designations of the image patches.

97 MATHEMATICS AND COMPUTING↗

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bias. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Reference 2 (at the end of the article).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Designing Sites in Heterogeneous Catalysis: Are We Reaching Selectivities Competitive With Those of Homogeneous Catalysts?

A critical review of different prominent nanotechnologies adapted to catalysis is provided, with focus on how they contribute to the improvement of selectivity in heterogeneous catalysis. Ways to modify catalytic sites range from the use of the reversible or irreversible adsorption of molecular modifiers to the immobilization or tethering of homogeneous catalysts and the development of well-defined catalytic sites on solid surfaces. The latter covers methods for the dispersion of single-atom sites within solid supports as well as the use of complex nanostructures, and it includes the post-modification of materials via processes such as silylation and atomic layer deposition. All these methodologies exhibit both advantages and limitations, but all offer new avenues for the design of catalysts for specific applications. Because of the high cost of most nanotechnologies and the fact that the resulting materials may exhibit limited thermal or chemical stability, they may be best aimed at improving the selective synthesis of high value-added chemicals, to be incorporated in organic synthesis schemes, but other applications are being explored as well to address problems in energy production, for instance, and to design greener chemical processes. Finally, the details of each of these approaches are discussed, and representative examples are provided. We conclude with some general remarks on the future of this field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Workshop on Incomplete Network Data Held at Sandia National Labs – Livermore

While network analysis is applied in a broad variety of scientific fields (including physics, computer science, biology, and the social sciences), how networks are constructed and the resulting bias and incompleteness have drawn more limited attention. For example, in biology, gene networks are typically developed via experiment -- many actual interactions are likely yet to be discovered. In addition to this incompleteness, the data-collection processes can introduce significant bias into the observed network datasets. For instance, if you observe part of the World Wide Web network through a classic random walk, then high degree nodes are more likely to be found than if you had selected nodes at random. Unfortunately, such incomplete and biasing data collection methods must be often used.

97 MATHEMATICS AND COMPUTING↗