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At least 415 records · Page 23

Aerial Data and Processed Models of Port Arthur Coastal Neighborhood and Pleasure Island Golf Course, June 2024

Our Co-design team is from the University of Texas, working on a Department of Energy-funded project focused on the Beaumont-Port Arthur area. As part of this project, we will be developing climate-resilient design solutions for areas of the region. More on www.caee.utexas.edu.We captured aerial photos in the Port Arthur Coastal Neighborhood Community and the Golf Course on Pleasure Island, Texas, in June 2024.Aerial photos taken were through DroneDeploy autonomous flight, and models were processed through the DroneDeploy engine as well. All aerial photos are in .JPG format and contained in zipped files for each area.The processed data package includes 3D models, geospatial data, mappings, and point clouds. Please be aware that DTM, Elevation toolbox, Point cloud, and Orthomosaic use EPSG: 6588. And 3D Model uses EPSG: 3857.For using these data:- The Adobe Suite gives you great software to open .Tif files.- You can use LASUtility (Windows), ESRI ArcGIS Pro (Windows), or Blaze3D (Windows, Linux) to open a LAS file and view the data it contains.- Open an .OBJ file with a large number of free and commercial applications. Some examples include Microsoft 3D Builder, Apple Preview, Blender, and Autodesk.- You may use ArcGIS, Merkaartor, Blender (with the Google Earth Importer plug-in), Global Mapper, and Marble to open .KML files.- The .tfw world file is a text file used to georeference the GeoTIFF raster images, like the orthomosaic and the DSM. You need suitable software like ArcView to open a .TFW file.This dataset provides researchers with sufficient geometric data and the status quo of the land surface at the locations mentioned above. This dataset could streamline researchers' decision-making processes and enhance the design as well.

2D mapping↗

A Combined Computer Vision and Deep Learning Approach for Rapid Drone-Based Optical Characterization of Parabolic Troughs

Optical accuracy is a primary driver of parabolic trough concentrating solar power (CSP) plant performance, but can be damaged by wind loads, gravity, error during installation, and regular plant operation. Collecting and analyzing optical measurements over an entire operating parabolic trough plant is difficult, given the large scale of typical installations. Distant Observer, a software tool developed at the National Renewable Energy Laboratory, uses images of the absorber tube reflected in the collector mirror to measure both surface slope in the parabolic mirror and offset of the absorber tube from the ideal focal point. This technology has been adapted for fast data collection using low-cost commercial drones, but until recently still required substantial human labor to process large amounts of data. A new method leveraging advanced deep learning and computer vision tools can drastically reduce the time required to process images. This new method addresses the primary analysis bottleneck, identifying featureless, reflective mirror corner points to a high degree of accuracy. Recent work has shown promising results using computer vision methods. The combined deep learning and computer vision approach presented here proved highly effective and has the potential to further automate data collection and analysis, making the tool more robust. The method presented in this paper automatically identified 74.3% of mirror corners within 2 pixels of their manually marked counterparts and 91.9% within 3 pixels. This level of accuracy is sufficient for practical Distant Observer analysis within a target uncertainty. A commercial drone collected video of over 100 parabolic trough modules at an operating CSP plant to demonstrate the deep learning and computer vision method's usefulness in processing large amounts of data. These troughs were successfully analyzed using Distant Observer, paired with the new deep learning and computer vision algorithm, and can provide plant operators and trough designers with valuable insight about plant performance, operating strategies, and plant-wide optical error trends.

computer vision↗

Controlling Preferred Grain Orientation in Vapor-Deposited Metal-Halide Perovskite Thin Films

Metal-halide perovskites are promising semiconductor materials for light-absorber layers in solar cells due to their optimized band gap, defect tolerance, and relative ease of synthesis. In this work, we demonstrate the viability of vapor transport deposition (VTD), a solvent-free processing method, to realize polycrystalline films of both lead iodide (PbI 2 ) and methylammonium lead iodide (MAPbI 3 ) perovskites showing preferential crystallographic orientation. Notable is the difference in perovskite film texturing observed for sequentially and co-deposited VTD films of MAPbI 3 , as well as the lack of strong preferential orientation in solution-processed MAPbI 3 films. While sequential deposition of the perovskite precursors PbI 2 and methylammonium iodide (MAI) leads to a MAPbI 3 film with a limited preferential grain orientation, co-deposited MAPbI 3 films mirror the orientation of excess PbI 2 present in the film. The latter is confirmed by the similar dependence of preferential orientation for PbI 2 and co-deposited MAPbI 3 on underlayer roughness, as well as the emergence of preferential orientation in MAPbI 3 only when excess PbI 2 is present. Both MAPbI 3 and PbI 2 films show a strong preferred lattice orientation on smooth substrates, while on rougher substrates, this orientation is disrupted. Furthermore, these results are interpreted as excess PbI 2 frustrating the diffusion of MAI in the film, which would otherwise disrupt the preferred orientation, pointing to a notable difference in lattice orientation arising from processing technique and conditions.

Deposition↗

Technology Applicable to Remote Hazardous Constituents and Waste Stream Grouping

Originally, Rocky Flats transuranic (TRU) waste was managed from waste streams that were composed of similar chemical constituents and were generated from identical processes. Early waste processing at Idaho National Laboratory (INL) maintained the Rocky Flats record until INL began generating their own item description codes (IDCs). Ultimately TRU waste management at INL was driven to combine wastes from all IDCs that were assigned by Rocky Flats to a summary category group regardless of whether the chemical constituents in the waste were known or not. At this point, the Waste Isolation Pilot Plant (WIPP) certified program requirements to process the TRU waste according to waste streams was nearly eliminated. In April 2018, operations in the Sludge Repackage Project (SRP) area were halted by a radiological materials release accident in which drums containing waste experienced a loss of containment after over-pressurization occurred. Four SRP drums, repackaged in the Accelerated Retrieval Project (ARP) V area, had an adverse, delayed chemical reaction event occur when prohibited materials from one container were mixed with chemically-incompatible materials from other containers in the repackaging process. This incident was the direct result of processing unknowns under a protocol where the components of the waste were added to incompatible materials resulting in a run-away reaction. After a Difficult Waste Team (DWT) and Los Alamos National Laboratory – Carlsbad Operations (LANL-CO) subject matter expert (SME) visit in September 2019, it was determined by the team that all of the work observed on the September visit was performed upstream of the certified program and that the Visual Examination (VE) and other methods typically used by the certified program were being used for Acceptable Knowledge (AK) augmentation. This augmentation was needed in order to determine what the constituents in the waste might be, and is based primarily on collections of VE results. The waste at INL that is being processed in what is considered to be the Priority 2 (yellow) and Priority 3 (red) lists either needs AK to be completed before certified characterization can occur or is waiting to be processed because the waste has been mixed with unknown wastes resulting in a lack of information that could have impact of the ability to certify and ship the waste to the WIPP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Why are Lead Iodide‐Based Perovskite Precursor Inks Yellow?

A challenge faced by metal halide perovskite (MHP) photovoltaics is scaling up solution deposition processes to realize rapid and inexpensive manufacturing. The challenge lies in completely understanding and controlling solution speciation, nucleation, and self-assembly of iodoplumbate complexes during solvent evaporation as the liquid transforms into gels and solids. An accurate description of solution species, at all points in the transformation, is a prerequisite to design robust and reliable processes. Here, in this study, the common assumption that initial monoplumbate solution species typically invoked (e.g., [PbI 6 ] 4− ) are certainly not the origin of optical absorbance at >400 nm wavelengths is disproved, as are many large particles of common “intermediate” iodoplumbate phases with face- or edge-sharing connectivity. Instead, a new perspective is offered, involving (partially) corner-sharing iodo(poly)plumbates (>1 Pb 2+ per complex) that experience highly dynamic chemical environments. It is outlined how the MHP field would benefit by elucidating these phenomena. Future work is required to determine the size and kinetic behavior of polyplumbate species, and contextualize these findings in relation to broader trends in materials chemistry beyond MHPs. Ultimately, a complete explanation for the solution speciation, optical absorbance signatures, and the color of MHP precursor inks remains an open challenge to the community.

14 SOLAR ENERGY↗

Definition of fragmentation functions and the violation of sum rules

We point out a problem with the formulation and derivations of sum rules for quark fragmentation functions that impacts their validity in QCD, but which potentially points toward an improved understanding of final states in inclusive hard processes. Fragmentation functions give the distribution of final-state hadrons arising from a parton exiting a hard scattering, and the sum rules for momentum, electric charge, etc. express conservation of these quantities. The problem arises from a mismatch between the quark quantum numbers of the initial quark and the fact that all observed final-state hadrons are confined bound states with color zero. We point that, in a confining theory like QCD, the Wilson line in the operator definition of a fragmentation function entails that the final state in a fragmentation function includes a bound state in the external field generated by the Wilson line. We justify this with the aid of general features of string hadronization. The anomalous bound states are restricted to fractional momentum z = 0 . They tend to invalidate sum rules like the one for charge conservation when applied to the fragmentation functions inferred from experimental data but not the momentum sum rule. We propose to exploit our ideas in future studies as a way to relate the fragmentation functions extracted from inclusive cross sections to more detailed nonperturbative descriptions of final state hadronization. We also describe scenarios wherein the traditional sum rules might remain approximately valid with a reasonably high degree of accuracy. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Verification of EvaluateFLux Utility Program

The EvaluateFlux program is a post-processing utility program for DIF3D, specifically DIF3D-VARIANT which handles Cartesian and hexagonal geometries. The EvaluateFlux program was developed to allow users to obtain flux and power traverses through the geometry domain, and its initial purpose was to facilitate foil analysis by evaluating the flux solution from DIF3D-VARIANT and combining it with foil cross section data. The EvaluateFlux program can calculate the neutron flux, as well as the reaction rates, at any user provided evaluation point. It does this by identifying the spatial mesh associated with the evaluation point and then evaluates the polynomial based neutron flux moments stored in the NHFLUX file at that point. The output of EvaluateFlux varies depending on the input setup. The maximum output includes the neutron flux and microscopic and macroscopic reaction rates at each evaluation point. The purpose of this work is to verify the outputs of EvaluateFlux. Simple models that have hand calculatable results are first defined and used to verify the EvaluateFlux outputs. More complex cases are then added where a duplicate program of EvaluateFlux that uses PrintTables outputs of the binary files is used to verify the EvaluateFlux outputs. In those complex cases, hand calculations of selected evaluation points were also displayed to confirm the software verification. For all the tests done, the hand calculations agreed well with those calculated by EvaluateFlux. For the larger complex problems, the duplicate program that can process hundreds of evaluation points was able to identify that zero points within some meshes have large errors. This aspect was attributed to the truncation error on the input provided to the duplicate program and is not a concern for the accuracy of the EvaluateFlux software.

97 MATHEMATICS AND COMPUTING↗

Verification of the EvaluateFlux Utility Program

The EvaluateFlux program is a post-processing utility program for DIF3D, specifically DIF3D-VARIANT which handles Cartesian and hexagonal geometries. The EvaluateFlux program was developed to allow users to obtain flux and power traverses through the geometry domain, and its initial purpose was to facilitate foil analysis by evaluating the flux solution from DIF3D-VARIANT and combining it with foil cross section data. The EvaluateFlux program can calculate the neutron flux, as well as the reaction rates, at any user provided evaluation point. It does this by identifying the spatial mesh associated with the evaluation point and then evaluates the polynomial based neutron flux moments stored in the NHFLUX file at that point. The output of EvaluateFlux varies depending on the input setup. The maximum output includes the neutron flux and microscopic and macroscopic reaction rates at each evaluation point. The purpose of this work is to verify the outputs of EvaluateFlux. Simple models that have hand calculatable results are first defined and used to verify the EvaluateFlux outputs. More complex cases are then added where a duplicate program of EvaluateFlux that uses PrintTables outputs of the binary files is used to verify the EvaluateFlux outputs. In those complex cases, hand calculations of selected evaluation points were also displayed to confirm the software verification. For all the tests done, the hand calculations agreed well with those calculated by EvaluateFlux. For the larger complex problems, the duplicate program that can process hundreds of evaluation points was able to identify that zero points within some meshes have large errors. This aspect was attributed to the truncation error on the input provided to the duplicate program and is not a concern for the accuracy of the EvaluateFlux software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Material and Design Optimization of Printed Melt Wire Arrays

Recent work conducted by the Advanced Sensors and Instrumentation (ASI) program at Idaho National Laboratory resulted in the establishment of in-house capabilities for fabricating and testing new advanced manufactured sensors for measuring irradiation temperatures inside a nuclear test reactor. Though current methods of real-time temperature monitoring (e.g., thermocouples) can still be used, the complexity of the feedthroughs and attachments needed for collecting real time measurements greatly increases the experiment-related costs. On the other hand, passive monitoring techniques can be used for collecting post irradiation temperature measurements by inferring reactor temperatures, based on the melting points of well-characterized materials (i.e., standard melt wires). However, challenges have arisen due to the limited space available for including instrumentation in experiments. To resolve this issue, the ASI program expanded its temperature detection capabilities to include advance manufactured melt wires for post-irradiation temperature measurements. These melt wires can determine reactor temperatures while also accommodating space limitations in irradiation experiments. To improve performance reliability and enhance melt wire readability following irradiation, FY-22 efforts have focused on optimizing the materials used in the encapsulation and printed melt wire array. This report details the design and fabrication tasks, along with the subsequent x ray computed tomography (XCT) evaluation process. The melt wire array consisted of indium with a melting point of 157°C, indium/silver (96/4 at%) with a melting point of 219°C, and tin with a melting point of 230°C. The encapsulation disc was made of vanadium due to its low activation properties and radiation resistance when deployed in nuclear reactors. Additionally, the melt wire design consisted of a ceramic sublayer (alumina disc) to further enhance the XCT post melting images of the printed melt wires. However, when sealing the vanadium container, all three melt wires melted, reflecting the temperature limitations that must be considered when employing metal containers in the sealing process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Unraveling the impact of initial choices and in-loop interventions on learning dynamics in autonomous scanning probe microscopy

The current focus in Autonomous Experimentation (AE) is on developing robust workflows to conduct the AE effectively. This entails the need for well-defined approaches to guide the AE process, including strategies for hyperparameter tuning and high-level human interventions within the workflow loop. This paper presents a comprehensive analysis of the influence of initial experimental conditions and in-loop interventions on the learning dynamics of Deep Kernel Learning (DKL) within the realm of AE in scanning probe microscopy. We explore the concept of the “seed effect,” where the initial experiment setup has a substantial impact on the subsequent learning trajectory. Additionally, we introduce an approach of the seed point interventions in AE allowing the operator to influence the exploration process. Using a dataset from Piezoresponse Force Microscopy on PbTiO 3 thin films, we illustrate the impact of the “seed effect” and in-loop seed interventions on the effectiveness of DKL in predicting material properties. The study highlights the importance of initial choices and adaptive interventions in optimizing learning rates and enhancing the efficiency of automated material characterization. This work offers valuable insights into designing more robust and effective AE workflows in microscopy with potential applications across various characterization techniques.

47 OTHER INSTRUMENTATION↗

Gaussian Process Emulators for Volcanic Ash Dispersion Model Tephra2

It is necessary to predict volcanic ash deposition since falling ash is harmful to human activities. Because simulators built for this purpose are computationally expensive, it is popular to use statistical emulators for geophysical hazard analyses, where a large number of simulations are required. Gaussian stochastic process emulators are able to approximate expensive simulations in an accurate and efficient way. Using a relatively small number of simulation runs, a well-trained emulator can accurately predict simulation outputs at massive new input points in a few seconds. Under different explosive eruption conditions, we constructed Gaussian stochastic process emulators for Tephra2, a simulation tool for estimating the accumulation of volcanic ash over a region. Historical wind records are used as input wind data, without assuming a Gaussian wind speed profile or common wind direction among elevations. While there are several inputs for Tephra2, we use no more than three physically motivated variables as emulator inputs to reduce the computational cost of emulations. The emulator outputs predict the mass of tephra per unit area at 50281 grid points around a predetermined vent location.

58 GEOSCIENCES↗

Task-oriented machine learning surrogates for tipping points of agent-based models

We present a machine learning framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale approach, for the construction of different types of effective reduced order models from detailed agent-based simulators and the systematic multiscale numerical analysis of their emergent dynamics. The specific tasks of interest here include the detection of tipping points, and the uncertainty quantification of rare events near them. Our illustrative examples are an event-driven, stochastic financial market model describing the mimetic behavior of traders, and a compartmental stochastic epidemic model on an Erdös-Rényi network. We contrast the pros and cons of the different types of surrogate models and the effort involved in learning them. Importantly, the proposed framework reveals that, around the tipping points, the emergent dynamics of both benchmark examples can be effectively described by a one-dimensional stochastic differential equation, thus revealing the intrinsic dimensionality of the normal form of the specific type of the tipping point. This allows a significant reduction in the computational cost of the tasks of interest.

97 MATHEMATICS AND COMPUTING↗

Clean Energy Manufacturing: Renewable Energy Technology Benchmarks

The manufacturing of clean energy technologies has become a global enterprise. An analysis of four clean energy technology manufacturing processes—wind turbine components, crystalline silicon solar photovoltaic modules, light-duty vehicle lithium-ion battery cells, and light-emitting diodes—was conducted to provide a reference point for comparison over time as this sector evolves. The manufacturing supply chain analysis included processing of raw materials, making required subcomponents, and assembling final products, using benchmarks that crossed 12 economies: Brazil, Canada, China, Germany, India, Japan, Malaysia, Mexico, South Korea, Republic of China (Taiwan), the United Kingdom, and the United States. Larger economies, with extensive manufacturing supply chains and high prevailing wages, tend to retain more value added from clean energy manufacturing than small economies. Manufacturing of clean energy technologies drives extensive trade among economies to support the widely distributed supply chain links. Production of wind turbine components and photovoltaic modules is more centralized than production of light-emitting diodes and lithium-ion battery cells. Across the four clean energy technologies evaluated, there was generally an excess of manufacturing capacity relative to global supply.

benchmarks↗

Digital Signal Processing of Radar Pulse Echoes

Modern high-performance radar systems are employing ever-more Digital Signal Processing (DSP), replacing ever-more formerly analog components. Precisely predicting the performance of digital filters and correlators requires an awareness of some of the finer points and characteristics of digital filters. We examine a representative radar receiver DSP chain that is processing a Linear Frequency Modulated (LFM) chirp.

47 OTHER INSTRUMENTATION↗

The eROSITA Final Equatorial-Depth Survey (eFEDS)

Aims. The eROSITA Final Equatorial-Depth Survey (eFEDS), executed during the performance verification phase of the Spectrum-Roentgen-Gamma (SRG)/eROSITA telescope, was completed in November 2019. One of the science goals of this survey is to demonstrate the ability of eROSITA to detect samples of clusters and groups at the final depth of the eROSITA all-sky survey. Methods. Because of the sizeable (≈26" HEW FOV average) point-spread function of eROSITA, high-redshift clusters of galaxies or compact nearby groups hosting bright active galactic nuclei (AGN) can be misclassified as point sources by the source detection algorithms. A total of 346 galaxy clusters and groups in the redshift range of 0.1 < z < 1.3 were identified based on their red sequenc in the eFEDS point source catalog. Results. We examine the multiwavelength properties of these clusters and groups to understand the potential biases in our selection process and the completeness of the extent-selected sample. We find that the majority of the clusters and groups in the point source sample are indeed underluminous and compact compared to the extent-selected sample. Their faint X-ray emission, well below the flux limit of the extent-selected eFEDS clusters, and their compact X-ray emission are likely to be the main reason for this misclassification. In the sample, we confirm that 10% of the sources host AGN in their brightest cluster galaxies (BCGs) through optical spectroscopy and visual inspection. By studying their X-ray, optical, infrared, and radio properties, we establish a method for identifying clusters and groups that host AGN in their BCGs. We successfully test this method on the current point source catalog through the Sloan Digital Sky Survey optical spectroscopy and find eight low-mass clusters and groups with active radio-loud AGN that are particularly bright in the infrared. They include eFEDS J091437.8+024558, eFEDS J083520.1+012516, and eFEDS J092227.1+043339 at redshifts 0.3-0.4. Conclusions. This study helps us to characterize and understand our selection process and assess the completeness of the eROSITA extent-selected samples. The method we developed will be used to identify high-redshift clusters, AGN-dominated groups, and low-mass clusters that are misclassified in the future eROSITA all-sky survey point source catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗

Monolayer TiS 2 Nanosheets on Au(111)–Structural Characterization and Effect of Edge Stability for Shape Control

Transition metal dichalcogenides are promising alternatives to noble metal catalysts, e.g., for (photo-)activation of greenhouse gases or hydrogenations. Herein, a direct synthetic route for 2D TiS 2 nanosheets on Au(111) by titanium deposition in the presence of a mild, organic, non-oxidizing sulfur source is presented. High-resolution scanning tunneling microscopy (STM) is used to gain atomic-level insights into the TiS 2 nanosheet morphology. In contrast to the literature, this protocol gains mostly hexagonal and truncated triangular nanosheets with an increased edge contrast in STM, analog to metallic edge states in MoS 2 . Synchrotron-based photoelectron spectroscopy allows insights into compositional details, specifically to distinguish different S sites on the TiS 2 sheets and other S species on the sample. Further, a minimum size is identified (9 S atoms side length), which underlines the importance of moiré reconstructions for stress relief. The TiS 2 sheets coexist with [Au]Ti 1 S 3 clusters, in which a single gold atom is alloyed into the surface and capped by three S atoms. Together with the finding of a critical sheet size, this points toward on-surface Ostwald ripening as a relevant process in the sheet formation. Ab-initio calculations (density functional theory) underscore that the chemical potential of S is an essential descriptor to maintain shape control.

2D nanomaterials↗

Highly accelerated life testing (HALT): A review from a statistical perspective

Despite its use in one form or another for at least four decades, HALT and related techniques [e.g., highly accelerated-stress screening (HASS) and stress audits (HASA)] are not well understood within the statistical community and remain controversial. This largely reflects a conflict in motivation between engineers, testing under harsh conditions to discover and eliminate failure modes, and statisticians, taking a more cautious approach to develop quantitative estimates of parameters such as mean time between failures (MTBF). Here, this review article will clarify HALT concepts and methods and explain where it fits within the universe of methods that involve the application of accelerating factors to compress the time required to evaluate or enhance product reliability. A major distinction is between methods such as HALT, a high-stress test-analyze-fix-test iterative process directed at improving reliability by discovering and fixing weak points in a design, and quantitative accelerated life testing (QALT), whose goal is the estimation of product life for a fixed design. We discuss methods such as physics of failure that offer some hope of bridging the gap between the qualitative nature of HALT, and purely quantitative statistical methods. We present a variety of engineering applications of HALT including metal fatigue, piping and pressure vessels, structural damage, radiation damage, and rotating machinery. We also discuss potential synergies between HALT and QALT, such as rapid identification, through HALT, of failure modes requiring quantitative analysis. For further study, extensive references to the applicable literature are provided as well as an appendix that describes related methods.

97 MATHEMATICS AND COMPUTING↗

Exploratory Investigation of Coal in Nonequilibrium Plasma

Coal is an abundant natural resource and there is motivation to find new uses for it that do not intrinsically involve combustion. One approach is to explore new ways of processing coal, and in this work, we focus on the transformation of coal in a nonequilibrium plasma generated from an equimolar mixture of nitrogen and hydrogen. The outcome of the nonequilibrium plasma reaction is fundamentally different than a thermal control reaction carried out using the same gas composition, pressure, and temperature range. The nonequilibrium plasma produces a gas mixture that is enriched in acetylene and its derivatives. Furthermore, when compared to the thermal control experiment, the solid char byproduct of the nonequilibrium plasma has a very reactive surface and is spontaneously combustible at ambient temperature. Experiments performed to characterize the reaction kinetics of coal in the plasma suggest that the mechanism proceeds through a sequential process by which the coal particle temperature rises to a point where devolatilization can occur, the devolatilization reaction happens, followed by parallel reactions of released organic vapors in the plasma phase and surface activation. In conclusion, the reaction rate appears to be limited by the time it takes for the coal particle temperature to rise, consistent with previous results reported for reactions of coal in thermal plasma.

Acetylene↗