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At least 649 records · Page 36

A review on the sizing and selection of control valves for thermal hydraulics for reactor system applications

This study presents an overview regarding how to model/size, choose, and maintain control valves (CVs) for a reactor system thermal hydraulics experimentation—specifically simulating pipe break(s) and a loss of coolant accident (LOCA) analysis. In a thermal hydraulics test loop, CVs modulate fluid flow according to the control signal generated by the controller to control the process parameter. The selection of a CV in industrial applications involves many factors, including process diversity, safety, and reliability. Further, the key issues and challenges for performing proper mathematical modeling, installation, servicing, and calibration are also discussed for the benefit of operators and end-users. Additionally, this research includes case studies illustrating major plant-level accidents associated with the malfunctioning of valves. Therefore, the study will serve as a knowledge base or reference guide for young professionals and operators who wish to better understand process control applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Optimization and active stabilization of a far-infrared laser for NSTX-U high poloidal wavenumber scattering diagnostics

The far-infrared (FIR) laser output beam power and profile are important parameters in the laser-aided diagnostics, directly influencing the spatial resolution and signal-to-noise ratio of measurements. Here, this work focuses on developing a systematic control method to enhance FIR laser beam quality through optimized mirror alignment and real-time feedback-based precision cavity length tuning. A 150 W CO 2 laser, aligned with the waveguide axis using a HeNe reference laser, serves as the pump source. The sensitivity of FIR beam intensity to pump gas pressure and thermal expansion is investigated, revealing that even a 1 µm cavity expansion can significantly degrade output power stability to about two-thirds of its original value. To address this, a feedback control module has been designed and implemented for active cavity length adjustment, stabilizing the output power at ∼30 mW. In addition, maintaining a high formic acid gas pressure ($>$190 mTorr) within the cavity ensures reliable operation. The optimized FIR laser will be deployed on the National Spherical Torus eXperiment-U high poloidal wavenumber scattering system for studying electron-scale turbulence in tokamak plasmas.

Xu, Xinhang [Univ. of California, Davis, CA (Unite↗

Fiber-optic links based on silicon photonics for high-speed readout of trackers

We propose to use silicon photonics technology to build radiation-hard fiber-optic links for high-bandwidth readout of tracking detectors. The CMOS integrated silicon photonics was developed by Luxtera and commercialized by Molex. The commercial off-the-shelf (COTS) fiber-optic links feature moderate radiation tolerance insufficient for trackers. A transceiver contains four RX and four TX channels operating at 10 Gbps each. The next generation will likely operate at 25 Gbps per channel. The approach uses a standard CMOS process and single-mode fibers, providing low power consumption and good scalability and reliability.

47 OTHER INSTRUMENTATION↗

Environmental Influence on Module Delamination Rate

Here, this study begins to investigate the role of environmental factors, such as temperature and humidity, on the delamination kinetics of the ethylene vinyl acetate (EVA)/silicon-photovoltaic (Si-PV) cell interface. A fracture mechanics approach based on a single cantilever beam technique is employed to measure the delamination rate as a function of applied driving force. To glean insight into the mechanisms of bonding and degradation at this interface, and the effect of manufacturing variability and quality, we consider a high-quality pristine EVA and two EVAs formulated with reduced amounts of its adhesion promoter, silane. Results indicate that a bulk change in the viscoelastic properties of the EVA dominates the delamination kinetics at high driving forces and low humidity and the effect of a chemical reaction only becomes apparent at higher humidity and lower driving forces. These findings suggest that only interfacial phenomenon of susceptible, degraded material may have to be considered to adequately model PV module delamination failure.

14 SOLAR ENERGY↗

A Custom High-Throughput Optical Mapping Instrument for Accelerated Stress Testing of PV Module Materials

The performance and integrity of photovoltaic (PV) modules and materials may be assessed through optical characterizations. We have developed a custom optical mapping instrument (OMI) to improve measurement throughput time, facilitate automated measurements, allow for localized specimen examination, obtain spatial information relative to commercial benchtop spectrophotometer instruments, and provide automated data analysis. Both the key components and the methods used to improve the measurements are described. The measurement precision for the OMI is benchmarked for hemispherical transmittance relative to a previous round-robin study for commercial spectrophotometers. In addition to the unique instrument developed in this study, new insights have emerged from the examination of specimens from previous experiments, including: the depletion of the UV absorber is revealed for specimens beyond a certain size after artificial ultraviolet (UV) weathering; an optical degradation by internal haze formation is confirmed following Damp Heat (85 °C/85% relative humidity) testing; the better uniformity of the wear pattern for falling sand abrasion is used to select the DIN 52348 fixture over the ASTM D968 fixture; and the greater local (in the order of millimeters) heterogeneity of surface contamination in the soiling-prone location of Dubai relative to Kuwait. The results of the UV study have already been used to improve the standardized weathering of encapsulants. The example for Damp Heat testing is given to increase awareness of a degradation believed to be ubiquitously occurring in safety and design-type qualification testing of PV modules.

14 SOLAR ENERGY↗

Design of a Two-Body Wave Energy Converter Featuring Controllable Geometry

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continue to prove themselves as a promising modern renewable energy field. A wave energy converter (WEC) concept currently being explored is the variable-geometry WEC (VGWEC), which aims to add an extra control option to WEC design. VGWECs attempt to incorporate controllable geometric features to adjust the floating body hydrodynamics to favor either power absorption, load shedding, or other operational goals. These variable geometry components have been proposed to be controlled on a sea-state-to-sea-state or wave-to-wave time scale depending on the force (or torque) and bandwidth limitations of the actuators required to manipulate just the controllable geometric hull features. Having control over both the WEC geometry components and the power takeoff (PTO) offers the potential to improve overall system performance and reliability if a cost-effective solution can be found for a given WEC architecture. This paper will present the recent developments and results of a VGWEC concept that incorporates variable-geometry modules into a two-body WEC. In the proposed VGWEC concept, the variable-geometry modules consist of air-inflatable bags in the surface float and a water inflatable ring in the subsurface body. The surface float is tethered directly to the subsurface body through tether lines, each connected to a separate PTO. Adjusting the geometry of both the surface and subsurface bodies along with the PTO coefficients can maximize power in design sea states while reducing motion response and PTO forces when transitioning to sea states where rated power is reached and load shedding is prioritized. The ability to transition between operating condition is expected to increase the sea state operational map and power capacity.

geometry control↗

A New Drug Discovery Platform: Application to DNA Polymerase Eta and Apurinic/Apyrimidinic Endonuclease 1

The ability to quickly discover reliable hits from screening and rapidly convert them into lead compounds, which can be verified in functional assays, is central to drug discovery. The expedited validation of novel targets and the identification of modulators to advance to preclinical studies can significantly increase drug development success. Our SaXPyTM (“SAR by X-ray Poses Quickly”) platform, which is applicable to any X-ray crystallography-enabled drug target, couples the established methods of protein X-ray crystallography and fragment-based drug discovery (FBDD) with advanced computational and medicinal chemistry to deliver small molecule modulators or targeted protein degradation ligands in a short timeframe. Our approach, especially for elusive or “undruggable” targets, allows for (i) hit generation; (ii) the mapping of protein–ligand interactions; (iii) the assessment of target ligandability; (iv) the discovery of novel and potential allosteric binding sites; and (v) hit-to-lead execution. These advances inform chemical tractability and downstream biology and generate novel intellectual property. We describe here the application of SaXPy in the discovery and development of DNA damage response inhibitors against DNA polymerase eta (Pol η or POLH) and apurinic/apyrimidinic endonuclease 1 (APE1 or APEX1). Notably, our SaXPy platform allowed us to solve the first crystal structures of these proteins bound to small molecules and to discover novel binding sites for each target.

59 BASIC BIOLOGICAL SCIENCES↗

A preliminary user-friendly, digital console for the control room parameters supervision in old-generation Nuclear Plants

Improvements in the awareness of a system status is an essential requirement to achieve safety in every kind of plant. In particular, in the case of Nuclear Power Plants (NPPs), a progress is crucial to enhance the Human Machine Interface (HMI) in order to optimize monitoring and analyzing processes of NPP operational states. Firstly, as old-fashioned plants are concerned, an upgrading of the whole console instrumentation is desirable in order to replace an analog visualization with a full-digital system. In this work, we present a novel instrument able to interface the control console of a nuclear reactor, developed by using CompactRio, a National Instruments embedded architecture and its dedicated programming language. This real-time industrial controller composed by a real-time processor and FPGA modules has been programmed to visualize the parameters coming from the reactor, and to storage and reproduce significant conditions anytime. This choice has been made on the basis of the FPGA properties: high reliability, determinism, true parallelism and re-configurability, achieved by a simple programming method, based on LabVIEW real-time environment. The system architecture exploits the FPGA capabilities of implementing custom timing and triggering, hardware-based analysis and co-processing, and highest performance control algorithms. Data stored during the supervisory phase can be reproduced by loading data from a measurement file, re-enacting worthwhile operations or conditions. The system has been thought to be used in three different modes, namely Log File Mode, Supervisory Mode and Simulation Mode. The proposed system can be considered as a first step to develop a more complete Decision Support System (DSS): indeed this work is part of a wider project that includes the elaboration of intelligent agents and meta-theory approaches. A synoptic has been created to monitor every kind of action on the plant through an intuitive sight. Furthermore, another important aim of this work is the possibility to have a front panel available on a web interface: CompactRio acts as a remote server and it is accessible on a dedicated LAN. This supervisory system has been tested and validated on the basis of the real control console for the 1-MW TRIGA reactor RC-1 at the ENEA, Casaccia Research Center. In this paper we show some results obtained by recording each variable as the reactor reaches its maximum level of power. The choice of a research reactor for testing the developed system relies on its training and didactic importance for the education of plant operators: in this context a digital instrument can offer a better user-friendly tool for learning and training. It is worthwhile to remark that such a system does not interfere with the console instrumentation, the latter continuing to preserve the total control. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NJOY21: Making NJOY Suitable for the 21. Century - 14409

NJOY has a long history of nuclear data processing. NJOY began as a successor to MINX (Multigroup Interpretation of Nuclear X-Sections), a Los Alamos code and was first publicly released in the summer of 1977. The initial version included modules such as RECONR for resonance reconstruction on a union energy grid, BROADR for Doppler broadening plus a new Multigroup averaging program, GROUPR and an associated output module, DTR. Soon thereafter the HEATR, ERRORR, and THERMR modules were added to NJOY. By the mid 1980's, NJOY had a worldwide user community. The current version of NJOY2012 was released in December 2012. NJOY2012 builds on the success of more than 45 years of nuclear data processing at Los Alamos National Laboratory. NJOY2012 was rewritten using Fortran 90/95, utilizing among other things the concepts of public and private variables, eliminating common blocks in lieu of Fortran modules and taking advantage of allocatable arrays. A new version of NJOY is being developed at Los Alamos National Laboratory; NJOY21: NJOY for the 21. Century. NJOY21 uses modern programming standards of quality, reliability, and maintainability. It is being designed from the ground up to utilize modern methods of interacting with computer codes by providing an interactive and scripting (e.g., Python) interface. This will allow scientists the ability to more easily work with the results of the various steps in the processing of nuclear data. NJOY21 will continue the legacy of NJOY by providing a trusted and verified processing code that is fast, flexible, easy to use and customize and capable of handling both modern and established nuclear data formats. This paper introduces NJOY21 by first relating the history of NJOY; the majority of the paper will discuss NJOY21. NJOY21 will take advantage of the many decades of nuclear data processing experience that is contained in NJOY2012 and previous versions of NJOY and extend the capabilities and convenience of processing nuclear data. We will discuss how NJOY21 will remain backwards compatible with NJOY2012 - i.e., how current NJOY2012 input decks will continue to work with NJOY21. We will also discuss the verification and validation of the NJOY21 code base. Finally we will discuss new features in NJOY21 that do not exist in NJOY2012. These features include changes in how a scientist can interact with NJOY to process and verify and validate nuclear data; and the ability to read and write new nuclear data formats. (authors)

42 ENGINEERING↗

Nanostructured double-layer FeO as nanotemplate for tuning adsorption of titanyl phthalocyanine molecules

The growth, structure of Pt(111) supported double-layer FeO and the adsorption of titanyl phthalocyanine (TiOPc) molecules with tunable site and orientation were presented. According to the atomic-resolution STM image, the structure was rationalized as (8√3 × 8√3) R30°/Pt(111) nanostructure constructed by Fe species coordinated with different number of oxygen on top of non-rotated (8 × 8) FeO /Pt(111) structure. Due to the modulation of the stacking of Fe atoms in the second layer relative to the O atoms in the second layer and the underlying layer, the interface and total dipole moment periodically vary within (8√3 × 8√3) R30°/Pt(111) structure. The resulted periodically distributed dipole-dipole interaction benefits the growth of TiOPc molecules with area-selective sites and molecular orientations. Thus, this study provides a reliable method to govern the adsorption process of the polar molecules for potential applications in future functional molecular devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Exploring Capability of Multimodal Foundation Model for Image-based Fault Detection of Photovoltaic Modules

Multimodal Foundation Model (MFM), like ChatGPT and Gemini, have emerged as powerful tools for their exceptional natural language processing capabilities and their emerging potential in image analysis. This paper investigates the application of MFMs for photovoltaic (PV) fault detection through image analysis, focusing on ChatGPT 4.0 and Gemini 1.5 Pro. Three types of PV images and the corresponding common PV faults are detected: bird droppings using visible images, cell cracks via electroluminescence (EL) images, and hotspots using infrared (IR) images. Among the two models, Gemini 1.5 Pro demonstrated superior performance, achieving near-perfect results with an average F1 score of 0.97, consistently outperforming ChatGPT 4.0 in accuracy and reliability. Unlike traditional machine learning (ML) models, MFMs can operate in a zero shot manner that does not require additional training by the user, and the input images are not limited by size, angle, scope, or PV technology. The strong adaptability and user-friendliness make MFM a promising tool for analyzing PV images and advancing health monitoring for PV modules.

Li, Baojie↗

Activation Energy Determination for Photovoltaic Encapsulant Discoloration by Indoor Accelerated UV Testing

A novel methodology for determining the activation energy of photovoltaic encapsulant discoloration using an indoor accelerated ultraviolet (UV) stress test while simultaneously maintaining multiple module temperatures in a single weathering chamber is presented. The testing was performed on some fresh mini-modules with a glass/EVA/cell/EVA/backsheet construction. The short-circuit current degradation from individual cells was used to quantify transmittance losses due to discoloration. Activation energy determined using indoor accelerated UV test data and Modified Arrhenius model ranges from 26 to 44 kJ/mol (0.27 to 0.46 eV). Activation energy was also determined from the outdoor field degradation data by employing different physical models that consider the individual or combined effects of key environmental factors. The approach here is instrumental to evaluating the reliability studies on encapsulant degradation mechanisms using relatively less time and resources.

14 SOLAR ENERGY↗

Physics-Based Analysis of Cell Imbalances and Aging in Lithium-Ion Battery Modules and Packs

Lithium-ion battery (LIB) packs are a key solution for grid-scale energy storage, enabling grid resilience and supporting critical infrastructure. LIB modules and packs experience current imbalances and uneven cell aging due to various design and operational factors, and require a battery management system (BMS) to continuously monitor and control. In this context, a physics-based modeling framework for LIB modules and packs (liionpack) was enhanced to identify design and control strategies that minimize current imbalance and improve module/pack operation. Simulations of an 8-cell parallel-connected module demonstrate that reducing current imbalance leads to more uniform cell aging and improved module/pack-level degradation predictions. The analysis shows that current imbalance are affected by the electrical resistances. Terminal location significantly affects imbalance, with opposite-end terminal connections at intermediate branches minimizing the imbalance, and the pack circuit construction influences the accuracy of physics-based analysis at the pack scale. This framework enables design optimization of modules and packs through a fast and easy evaluation of pack performance and aging, and supports the development of aging-informed balancing strategies compatible with BMS implementation. Thereby, offering practical pathways to improve reliability and cycle life predictions in large-scale battery energy storage systems.

Ayalasomayajula, Surya Mitra [Oak Ridge National L↗

A Massively Parallel Solver for the Mechanical Harmonic Analysis of Accelerator Cavities

ACE3P is a 3D massively parallel simulation suite that developed at SLAC National Accelerator Laboratory that can perform coupled electromagnetic, thermal and mechanical study. Effectively utilizing supercomputer resources, ACE3P has become a key simulation tool for particle accelerator R and D. A new frequency domain solver to perform mechanical harmonic response analysis of accelerator components is developed within the existing parallel framework. This solver is designed to determine the frequency response of the mechanical system to external harmonic excitations for time-efficient accurate analysis of the large-scale problems. Coupled with the ACE3P electromagnetic modules, this capability complements a set of multi-physics tools for a comprehensive study of microphonics in superconducting accelerating cavities in order to understand the RF response and feedback requirements for the operational reliability of a particle accelerator. (auth)

43 PARTICLE ACCELERATORS↗

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

59 BASIC BIOLOGICAL SCIENCES↗

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

Lindsey, Jack W. (ORCID:0000000309307327)↗

Vibrationally resolved NEXAFS at C and N K-edges of pyridine, 2-fluoropyridine and 2,6-difluoropyridine: A combined experimental and theoretical assessment

In the present work, the near edge X-ray absorption spectroscopy (NEXAFS) spectra at both C and N K-edges of pyridine, 2-fluoropyridine, and 2,6-difluoropyridine have been studied both experimentally and theoretically. From an electronic point of view, both transition potential density functional theory and time-dependent density functional theory approaches lead to reliable results provided that suitable basis sets and density functionals are employed. In this connection, the global hybrid B3LYP functional in conjunction with the EPR-III basis set appears particularly suitable after constant scaling of the band positions. For the N K-edge, vertical energies obtained at these levels and broadened by symmetric Gaussian distributions provide spectra in reasonable agreement with the experiment. Vibronic contributions further modulate the band-shapes leading to a better agreement with the experimental results, but are not strictly necessary for semi-quantitative investigations. On the other hand, vibronic contributions are responsible for strong intensity redistribution in the NEXAFS C K-edge spectra, and their inclusion is thus mandatory for a proper description of experiments. In this connection, the simple vertical gradient model is particularly appealing in view of its sufficient reliability and low computational cost. For more quantitative results, the more refined vertical Hessian approach can be employed, and its effectiveness has been improved thanks to a new least-squares fitting approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗