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At least 631 records · Page 35

Modeling Grid Data Flows for Transmission and Distribution Operations: Review, Design, Next Steps

Operational scenarios of the power grids grow multifold to accommodate the diverse needs of both the utilities and end consumers, and the various other stakeholders in-between. To comprehensively model and apply analytics to support objectives and business functions of grid sectors, a reliable approach to characterize and design data flows is crucial. The flows bridge business functions with communications protocols, stakeholders such as the grid actors, and data interfaces comprising different data objects. Additionally, constraints applied to the flow such as cybersecurity, trust, privacy, and ownership among others intersect these entities, requiring the delineation of their interactions under different scenarios. This paper aims to not only highlight relevant research in the space of grid data flows, but also proposes, for the transmission-distribution sector, a novel modeling approach that marries the aforementioned entities: objectives, business functions, data interfaces, communication protocols, data stakeholders, and flow constraints. It elaborates on the design philosophy and the significance of each entity within the model and applies it to an example function of fault location, isolation and service restoration (FLISR). Finally, the next steps to extend the application of this data flow model for other practical operational scenarios are discussed.

Sundararajan, Aditya [ORNL] (ORCID:000000033577854↗

Implementing a Hardware Testbed Using 3-Level ANPC Software Defined Inverters for Fault Analysis of a Transmission Network

In this paper, we propose the implementation of a hardware testbed using 3-level active neutral point clamped (ANPC) software-defined inverters for fault analysis. A test case transmission network equipped with two grid forming (GFM) inverters and four resistive loads is considered in this research. Firstly, grid forming control laws including PI feedback control and droop control are implemented to operate the inverters in parallel. Then, we implement a fault ride-through (FRT) logic and perform a simulation of the test system by applying a three-phase fault. Simulation results show the effectiveness of the fault recovery algorithm upon clearance of the fault. Finally, a 3-level ANPC software-defined inverter is programmed with required control laws and characterized through various lab experiments.

3-level ANPC inverter↗

A Two-Stage Quantum Reinforcement Learning Method for Multi-Objective Transmission Switching

Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale increases, finding feasible solutions becomes increasingly challenging due to the problem's nonlinearity and high computational complexity. To address these challenges, this paper proposes a two-stage quantum reinforcement learning method that leverages potential quantum advantages for MO-TS. In the first stage, candidate switching lines are identified using a graph-theoretical approach to reduce the problem's dimensionality. The second stage introduces a quantum-classical reinforcement learning framework, where a learnable measurement-based CNN-ResVQC architecture is developed to effectively reduce the input dimension for quantum processing, mitigate vanishing gradients, and enhance trainability while improving the quantum circuit's flexibility in modeling complex decision policies for MO-TS. Numerical studies on IEEE 14-bus, 57-bus, and 118-bus systems demonstrate that the proposed algorithm achieves superior training stability and faster convergence with approximately 1% of the network parameters required by classical algorithms, highlighting its effectiveness, efficiency, and scalability. Furthermore, the practicality is validated through its stable convergence under three common quantum noise channels.

99 GENERAL AND MISCELLANEOUS↗

Implications of gnomonic distortion on electron backscatter diffraction and transmission Kikuchi diffraction

The effect of gnomonic distortion on orientation indexing of electron backscatter diffraction patterns is explored through simulation of electron diffraction patterns for sample-to-detector geometries associated with transmission Kikuchi diffraction (TKD) and electron backscatter diffraction (EBSD). Simulated data were analysed by computing a similarity index for both Hough transformed data and simulated patterns to determine the sensitivity of each method for detecting subtle differences in the effect of gnomonic distortions on electron diffraction patterns. These results indicate that the increased gnomonic distortions in electron diffraction patterns for a TKD geometry enhance the sensitivity for detecting subtle differences in interband angles. Additionally, the utilisation of a Hough transform-based indexing approach further enhances the sensitivity.

36 MATERIALS SCIENCE↗

High‐speed 4‐dimensional scanning transmission electron microscopy using compressive sensing techniques

Abstract Here we show that compressive sensing allows 4‐dimensional (4‐D) STEM data to be obtained and accurately reconstructed with both high‐speed and reduced electron fluence. The methodology needed to achieve these results compared to conventional 4‐D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide dataset shows that it is possible to recover over 25 dB peak signal‐to‐noise ratio in the recovered phase using 0.3% of the total data. Lay abstract : Four‐dimensional scanning transmission electron microscopy (4‐D STEM) is a powerful technique for characterizing complex nanoscale structures. In this method, a convergent beam electron diffraction pattern (CBED) is acquired at each probe location during the scan of the sample. This means that a 2‐dimensional signal is acquired at each 2‐D probe location, equating to a 4‐D dataset. Despite the recent development of fast direct electron detectors, some capable of 100kHz frame rates, the limiting factor for 4‐D STEM is acquisition times in the majority of cases, where cameras will typically operate on the order of 2kHz. This means that a raster scan containing 256^2 probe locations can take on the order of 30s, approximately 100‐1000 times longer than a conventional STEM imaging technique using monolithic radial detectors. As a result, 4‐D STEM acquisitions can be subject to adverse effects such as drift, beam damage, and sample contamination. Recent advances in computational imaging techniques for STEM have allowed for faster acquisition speeds by way of acquiring only a random subset of probe locations from the field of view. By doing this, the acquisition time is significantly reduced, in some cases by a factor of 10‐100 times. The acquired data is then processed to fill‐in or inpaint the missing data, taking advantage of the inherently low‐complex signals which can be linearly combined to recover the information. In this work, similar methods are demonstrated for the acquisition of 4‐D STEM data, where only a random subset of CBED patterns are acquired over the raster scan. We simulate the compressive sensing acquisition method for 4‐D STEM and present our findings for a variety of analysis techniques such as ptychography and differential phase contrast. Our results show that acquisition times can be significantly reduced on the order of 100‐300 times, therefore improving existing frame rates, as well as further reducing the electron fluence beyond just using a faster camera.

Robinson, Alex W.↗

Simplex‐based model for nanoparticle grain identification in four‐dimensional scanning transmission electron microscopy data

Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four-dimensional scanning transmission electron microscopy (4D-STEM) datasets. We propose a simplex-based model (SBM) in which each simplex vertex represents the diffraction pattern (DP) of a pure grain, and the simplex edges and interior represent overlapping grains. Our SBM grain identification algorithm operates on the Bragg disk (BD) data matrix distilled from the 4D-STEM data to identify the grain membership at each scan position, together with a BD feature matrix whose columns represent the DPs for each constituent grain, which is important for identifying the crystal structure of each grain. We solve the model using a two-stage algorithm. In Stage 1, we adapt a linear mixing algorithm to estimate an initial BD feature matrix whose columns represent DPs of potentially overlapping grains. Our Stage 2 algorithm incorporates sparsity considerations to transform the initial BD feature matrix so that its columns represent DPs of pure grains. Using simulated datasets with various grain configurations, we demonstrate that SBM recovers both the BD feature matrix and membership maps more accurately than existing methods, even when a grain lacks any pure region and completely overlaps with other grains.

4D-STEM segmentation↗

Reliability-Informed Economic and Energy Evaluation for Bi-Level Design for Remanufacturing: A Case Study of Transmission and Hydraulic Manifold

Abstract Design for remanufacturing (DfRem) is one attractive strategy that encourages the reuse of a product and extends the product's life cycle. Traditional design processes often only consider product reliability at an early design stage. However, from the perspective of environmental sustainability, it is becoming increasingly important to evaluate the long-term economic and environmental impacts of design decisions during early-stage design. We propose a bi-level DfRem framework consisting of system-level reusability allocation and component-level design tradeoff analysis, considering reliability and product warranty policy. First, a system-level reusability allocation problem aims at a theoretical exploration of the design space where all the components comprising the system are allocated certain reuse rates to achieve target energy savings with minimum cost. Following the theoretical exploration at the system level, a component-level analysis looks at practical design options for each component and trades-off between the overall cost and energy consumption for multiple remanufacturing cycles. Both levels of the framework require modeling component reuse for multiple remanufacturing cycles, which we achieve by using a branched power-law model that provides probabilistic scenarios of reusing the component or replacing it with a new part. We demonstrate the utility of this framework with the case study of an infinitely variable transmission (IVT) used by some agricultural machines manufactured by John Deere and show snapshots of a prototype software tool that we developed for easy use by designers.

Engineering↗

A System-Level Cost Modeling Framework for Design for Remanufacturing: A Case Study of an Agricultural Machine Transmission

Remanufacturing offers significant environmental and economic benefits by restoring end-of-life products to as-new conditions. Although extensive research has been conducted on the topic, the adoption of remanufacturing practices remains limited across various industries. A primary barrier to broader implementation is the substantial upfront investment required, which necessitates reliable cost modeling to justify potential future savings. Most existing models treat components independently and ignore inter-component dependencies. We develop a probabilistic, system-level cost modeling framework that integrates reliability, reusability, and a dependency matrix to capture cascading effects across components over multiple life cycles. Our model identifies those critical components that maximize remanufacturing benefits across a product's many lives. A toy example and an industry case study (John Deere PowrQuad transmission subassembly) illustrate how design alternatives affect cumulative cost. Using a Monte Carlo simulation (MCS) to perform life cycle cost analysis on the system with different design changes, we show the normalized average cost savings after three remanufacturing cycles. Accounting for dependencies meaningfully alters cost projections and ignoring them underestimates accumulated cost by up to 20% in our examples. Furthermore, the results of our study confirm that accounting for component interdependencies is necessary to produce cost estimates that meet industry standards.

Life Cycle Analysis and Design↗

TRIZ-Based Design Improvement for Facilitating Transmission Control Unit Remanufacturing

Design for Remanufacturing (DfRem) centers on enhancing product design and operations to facilitate remanufacturing while increasing both economic and environmental sustainability. DfRem requires a comprehensive understanding of product characteristics, production conditions, and operational constraints. Thus, DfRem requires a systematic methodology to identify and implement alternative designs. Among many critical steps in remanufacturing, disassembly is essential because it directly supports remanufacturing by separation of product components for cleaning, inspection, and other subsequent process steps. This study proposes a TRIZ-based framework to improve product design for disassembly in support of remanufacturing. The framework is applied to a transmission control unit (TCU) case study. The current TCU design prevents remanufacturing due to the sealant-based component joinery, which complicates disassembly and risks damaging the printed circuit board (PCB). After defining technical contradictions for the TCU product design and reviewing the suggested TRIZ principles to solve the conflicts, a cantilever snap-fit design alternative is developed. The economic feasibility of the snap-fit design is assessed by comparing the current and snap-fit design costs for three life cycles. The cost analysis demonstrates that the cost of the snap-fit design remains the same as the current design. Additionally, the snap-fit design offers substantial cost savings for three life cycles compared to the current design. We demonstrate how snap-fit design supports both environmental and economic sustainability.

42 ENGINEERING↗

Plasma-free hydrogenation of oxygen-terminated polycrystalline diamond as determined by circular transmission line measurements (CTLM)

Here, we developed a process to fully hydrogen-terminate diamond by annealing in forming gas. The surface was characterized using circular transmission line measurements (CTLMs) to evaluate the onset and degree of hydrogen termination. No hydrogenation occurred at temperatures at or below 500 °C. Hydrogenation occurs after annealing for 5 min at temperatures between 600 and 1000 °C, with complete hydrogenation achieved at 1000 °C, which showed the same sheet resistance as diamond terminated in a hydrogen plasma. Annealing at temperatures lower than 1000 °C resulted in only partial hydrogenation but can be compensated by increasing the anneal time. At temperatures exceeding 1100 °C, the sheet resistance suddenly and drastically increases, indicating instability of a hydrogen-terminated diamond surface at elevated temperatures under forming gas. The activation energy was determined to be 1.20eV. SEM inspection showed that annealing in hydrogen produced significantly reduced surface roughness compared to diamond surfaces hydrogenated in a H 2 plasma.

36 MATERIALS SCIENCE↗

Scanning transmission x-ray microscopy (STXM) of plutonium oxide

Scanning transmission x-ray microscopy was used to examine plutonium oxide particles formed by the corrosion of δ-phase plutonium alloy under high-humidity conditions. O K-edge spectra collected from eight distinct particles displayed significant spectral differences, revealing heterogeneity in oxidation states within a single sample batch. Here, this variation suggests complex chemical environments and formation histories, which are important considerations for nuclear forensic investigations. These findings highlight both the potential of synchrotron-based x-ray microscopy for nondestructive, high-resolution analysis of nuclear materials and the need for expanded reference datasets to improve the interpretation and forensic utility of such measurements.

organic↗

Binary pseudo-random array for calibration of interferometers with transmission spheres and cylinders

Binary pseudo-random array (BPRA) “white noise” artifacts are highly effective for characterizing the instrument transfer function (ITF) of surface topography metrology tools and wavefront measurement instruments. These BPRA artifacts feature all spatial frequencies within the instrument bandpass equally, resulting in a power spectral density with a white-noise-like character. This characteristic allows for direct ITF determination with uniform sensitivity across the entire spatial frequency range. We have developed a novel BPRA calibration standard that combines the diffractive pattern of a reflection computer-generated hologram (CGH) with the white noise generating BPRA pattern. By integrating these technologies using the same lithographic techniques, the resulting calibration sample enables ITF characterization of a Fizeau interferometer with a transmission sphere, or any nulling optic.

Munechika, K↗

Two Sides of a Coin: a Zika Virus Mutation Selected in Pregnant Rhesus Macaques Promotes Fetal Infection in Mice but at a Cost of Reduced Fitness in Nonpregnant Macaques and Diminished Transmissibility by Vectors

Although Zika virus infection of pregnant women can result in congenital Zika syndrome, the factors that cause the syndrome in some but not all infected mothers are still unclear. We identified a mutation that was present in some ZIKV genomes in experimentally inoculated pregnant rhesus macaques and their fetuses. Although we did not find an association between the presence of the mutation and fetal death, we performed additional studies with ZIKV with the mutation in nonpregnant macaques, pregnant mice, and mosquitoes. We observed that the mutation increased the ability of the virus to infect mouse fetuses but decreased its capacity to produce high levels of virus in the blood of nonpregnant macaques and to be transmitted by mosquitoes. This study shows that mutations in mosquito-borne viruses like ZIKV that increase fitness in pregnant vertebrates may not spread in outbreaks when they compromise transmission via mosquitoes and fitness in nonpregnant hosts.

59 BASIC BIOLOGICAL SCIENCES↗

Microstructural Study of Hydration of C 3 S in the Presence of Calcium Nitrate Using Scanning Transmission X-Ray Microscopy (STXM)

Calcium nitrate (CN) is used widely as an effectively inorganic setting accelerator and antifreeze admixture in concrete structures. In this paper, the multiscale investigation of CN on the hydration of C 3 S was studied by scanning transmission X-ray microscopy (STXM) combined with near-edge X-ray absorption fine structure (NEXAFS), 29 Si MAS NMR, calorimetry, scanning electron microscope, and N 2 absorption. It was concluded that the calcium silicate hydrate (C-S-H) surrounds the unhydrated C 3 S at 1-day hydrated C 3 S in the presence of calcium nitrate, while portlandite is partly in transformation and is formed partly. Based on Ca L 3 , 2 -edge NEXAFS spectra for 1-day hydrated C 3 S particle, calcium nitrate does not change the structure of the asymmetrically 7-fold coordination of calcium in the C-S-H. Calcium nitrate can accelerate the hydration of C 3 S to some extent and polymerization of the silicate chains within C-S-H considerably at early age, resulting in the increasing specific surface area.

Li, Qinfei↗

Fault Diagnosis of Double Pitch Time-Sharing Meshing Toothed Conveyor Chain Transmission System Based on Neural Network

With the rapid development of industry, the production and demand of automobiles have increased significantly. The generation of cars often requires tens of thousands of processes, consisting of hundreds of assembly lines to complete. Chain conveyors are widely used in the transportation of automobile assembly lines. The existing conveyor chains are roller chains. With the improvement of the requirements for conveyor reliability, synchronization, and environmental friendliness, the characteristics of roller conveyor chains restrict the further development of chain conveyors. It is urgent to study a new conveyor chain system to improve the synchronization, reliability, and environmental friendliness of chain conveyors on hundreds of assembly lines. In this paper, the mathematical modeling, meshing analysis, reliability, and environmental friendliness of the parameters of the components of the double pitch time-sharing meshing toothed conveyor chain system are studied. In addition, a novel fault diagnosis method of double pitch time-sharing meshing toothed conveyor chain transmission system based on neural network model is proposed in this paper.

Ding, Song↗

Common Electric Power Transmission System Model JSON Schema Specification

The Common Electric Power Transmission System Model (CTM) is an intuitive, extensible, language-agnostic, and error-resistant specification of electric power network components parameter names and units, and relation between components, intended for use by the research community developing new computational methods for power systems operations and simulation. Power system datasets following the CTM specification can be read as dictionaries and manipulated in that form in most programming languages (e.g., Python, Julia, C++). This standard data structure in CTM makes it easy to work in multiple power systems domains (e.g., economic operation, reliability assessment, electricity markets, stability assessment, etc.) without requiring conversions between use-case-specific file formats with information loss in the process. This repository specifies CTM as a JSON Schema, provides documentation, derivate (code-generated) implementations of CTM, and example data and usage of the schema for important use cases.

Aravena Solis, Ignacio↗

Jupyter notebooks for analyzing transmission SAXS/WAXS from beamline 7.3.3 during operando membrane fouling experiments v1.0

This software consists of python-based Jupyter Notebooks for processing transmission x-ray scattering images collected at beamline 7.3.3 at the Advanced Light Source. The measurements considered in these analyses are collected during membrane fouling experiments, where contaminants in the water deposit on/attach to the membrane surface. This software is used to elucidate the mechanisms of membrane fouling that occur during these operando membrane fouling experiments, but the analyses provided in these scripts can be extended to other scientific cases.

Landsman, Matthew [Lawrence Berkeley National Labo↗

BSMV-mediated genome editing exhibits host-specific heritability: germline transmission in barley and somatic edits in Nicotiana benthamiana

Plant RNA virus–mediated guide RNA (gRNA) delivery represents a transformative advance in genome editing technologies. Unlike conventional transformation methods that rely on labor-intensive tissue culture and regeneration for each individual gRNA delivery, viral vectors can rapidly and systemically transmit gRNAs into pre-established Cas-expressing plants, providing an accelerated route for functional genomics and trait discovery directly in planta . However, key design parameters, including subgenomic promoter choice, transcript architecture, and their effects on viral fitness and editing outcomes, remain to be elucidated for most viral platforms. We developed five Barley stripe mosaic virus (BSMV) vectors, each with distinct subgenomic promoter elements to drive single gRNA expression. These were initially evaluated in Cas9-expressing transgenic Nicotiana benthamiana plants targeting the Phytoene desaturase ( PDS ) gene to compare their editing efficiencies. Single gRNAs expressed under the duplicated γb subgenomic promoter or when fused directly to the γb genome achieved the highest mutation frequencies (up to 90% at 60 days post-inoculation), whereas β1- and β2-driven sgRNAs produced delayed and reduced editing. Thus, promoter selection critically determines gRNA accumulation and the efficacy of BSMV-mediated genome editing. The top-performing design was then applied to Cas9-expressing barley ( Hordeum vulgare ) targeting HvCMF7 (conferring green-white variegation) and HvGW2.1 (impacts grain width and weight). BSMV spread systemically throughout barley, inducing somatic and heritable mutations at frequencies up to 100%, with virus-free edited progeny. In contrast, despite robust somatic editing in N. benthamiana, no heritable mutations were detected indicating species-dependent limitations in germline transmission. Our systematic comparison of subgenomic promoter architectures establishes clear design principles for optimizing viral vector–mediated delivery. Promoter choice and transcript structure critically shape editing efficiency and viral stability. The host-specific boundary for germline editing, defined by efficient heritable editing in barley but not N. benthamiana , highlights where BSMV offers advantages and where alternative vectors or hybrid strategies are required, guiding rational platform selection for diverse crop species and applications. Collectively, these findings establish BSMV as a promising next-generation vector for rapid, tissue culture–free, and transformation-independent genome editing in cereals and other recalcitrant monocots.

barley↗