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At least 991 records · Page 55

Feasibility and Prospects of the High Resolution Rapid Refresh Model For Dynamic Line Rating

The ampacity of transmission lines is defined as the maximum amount of current the conductor can safely carry. It is necessary for transmission line operators to apply ampacity limits due to the thermal properties of the conductor. Dynamic Line Rating (DLR) is a technology and technique that uses the environmental conditions or a set of the conditions to calculate the ampacity of the conductor. The way the DLR is calculated has depended upon some amount of physical technology to implement the solution. The High Resolution Rapid Refresh (HRRR) Model is an atmospheric model that may provide enough resolution to perform dynamic line rating without any hardware at all. The objective is to use this model to perform Dynamic Line Rating. This will solve two of the most pervasive problems in Dynamic Line Rating, how to instrument a transmission line hundreds of miles long and then how to predict near future ampacity sufficient for transmission operators to effectively use, This technique will use the Idaho National Laboratory site as the test location for analysis. The High Resolution Rapid Refresh model is a reliable, freely available, and well-maintained weather forecasting model for the entire United States of America. The model provides enough special resolution that additional local weather monitoring devices at location are not necessary to conduct dynamic line rating. The HRRR ratings are lower on average than the locally measured ratings which allows for an additional margin of safety. The adoption of using purely digital methods for dynamic line rating could allow for wide scale adoption of the technology with very little overhead expenditure of implementation.

17 WIND ENERGY↗

Transformative remedial action scheme tool (TRAST)

Techniques and apparatuses are described that enable transformative Remedial Action Scheme (RAS) analyses and methodologies for a bulk electric power system, including methods of designing, reviewing, revising, testing, implementing, verifying, or validating a RAS. An improved RAS improves operation of the power system, including performance, reliability, control, and asset utilization. The example methodologies discussed—also referred to as a transformative Remedial Action Scheme tool (TRAST)—provide an end-to-end solution for adaptively setting RAS parameters based on realistic and near real-time operation conditions to improve power grid reliability and grid asset utilization, by leveraging utility data analysis and employing dynamic simulations and machine learning to significantly simplify and shorten the entire RAS process.

Fan, Xiaoyuan↗

EnergyPlus Model Context Protocol Server (EnergyPlus-MCP) v0.1

EnergyPlus-MCP is the first open-source Model Context Protocol server specifically designed for EnergyPlus building energy simulation. This innovative software enables AI assistants and other applications to interact programmatically with EnergyPlus through a standardized, secure interface, eliminating traditional technical barriers in building energy modeling. The software provides specialized tools across five functional domains: server management, model configuration and loading, comprehensive building component inspection, systematic model modification, and simulation execution with results visualization. Key features include automated HVAC system discovery and topology mapping, advanced schedule analysis, intelligent model validation, and interactive visualization capabilities. EnergyPlus-MCP's layered architecture ensures robust separation between protocol communication and domain expertise, enabling scalable deployment across organizations, educational institutions, and research teams. Unlike direct LLM approaches that suffer from inconsistent results and security gaps, EnergyPlus-MCP provides validated, reliable interactions while maintaining scientific rigor. This democratizes sophisticated building energy analysis, making EnergyPlus accessible to broader audiences through conversational interfaces and streamlined workflows.

Li, Han [Lawrence Berkeley National Laboratory (LB↗

TU-C-BRE-01: KEYNOTE PRESENTATION - Emerging Frontiers in IMRT QA

As IMRT treatment processes advance and mature, so must the quality assurance processes being used to validate their delivery. In some respects, treatment delivery advancements (e.g. VMAT) have out-paced QA advancements. The purpose of this session is to describe new processes that are being implemented to bring IMRT QA up-to-date with the treatment delivery advances. It would explore emerging IMRT QA paradigms, including requirements-based IMRT QA which necessitates definition of delivery errors (e.g. patient dose error, leaf positioning error) and development of processes to ensure reliable error detection. Engineeringbased QA approaches, including use of IMRT treatment delivery process trees, fault tree analysis and failure modes effects analysis would be described. Approaches to detect errors such as (1) during treatment delivery validation using exit fluence detectors (e.g. EPIDs); (2) analysis of treatment delivery via use of machine parameter log files; (3) dose recalculation using (3a) treatment planning system; (3b) record-and-verify; or (3c) entrance and exit fluence measurement parameters would be explained. The relative advantages and disadvantages of each method would be discussed. Schemes for error classification and root cause analysis would be described – steps which are essential for future error prevention. For each QA method, testing procedures and results would be presented indicating the types of errors that can be detected, those that cannot be detected, and the reliability of the error detection method (for example determined via ROC analysis). For speakers, we are seeking to engage non-commercially biased experts. Those listed below are a sub-sample of possible qualified individuals.

60 APPLIED LIFE SCIENCES↗

Understanding GPU Memory Corruption at Extreme Scale: The Summit Case Study

GPU memory corruption and in particular double-bit errors (DBEs) remain one of the least understood aspects of HPC system reliability. Albeit rare, their occurrences always lead to job termination and can potentially cost thousands of node-hours, either from wasted computations or as the overhead from regular checkpointing needed to minimize the losses. As supercomputers and their components simultaneously grow in scale, density, failure rates, and environmental footprint, the efficiency of HPC operations becomes both an imperative and a challenge. We examine DBEs using system telemetry data and logs collected from the Summit supercomputer, equipped with 27,648 Tesla V100 GPUs with 2nd-generation high-bandwidth memory (HBM2). Using exploratory data analysis and statistical learning, we extract several insights about memory reliability in such GPUs. We find that GPUs with prior DBE occurrences are prone to experience them again due to otherwise harmless factors, correlate this phenomenon with GPU placement, and suggest manufacturing variability as a factor. On the general population of GPUs, we link DBEs to short- and long-term high power consumption modes while finding no significant correlation with higher temperatures. We also show that the workload type can be a factor in memory’s propensity to corruption.

Oles, Vlad↗

Performance Modelling and Yearlong Outdoor Degradation Analysis of a GaAs//Si Tandem Module

Silicon-based tandem photovoltaic cells and modules are forecasted to enter mass production around the year 2026. Previous research efforts on tandem photovoltaic technology have focused heavily on increasing cell efficiencies. However, for successful large-scale deployment of tandem modules, reliability and long-term durability will be equally important. Outdoor performance data beyond the one-year mark enable sophisticated degradation analysis and help build confidence in the reliability and durability of this new technology.

degradation rate↗

HAPPA: A Modular Platform for HPC Application Resilience Analysis with LLMs Embedded

High-performance computing (HPC) systems are increasingly vulnerable to soft errors, which pose significant challenges in maintaining computational accuracy and reliability. Predicting the resilience of HPC applications to these errors is crucial for robust code protection and detailed resilience analysis. In this study, we present HAppA, a modular platform designed for HPC Application Resilience Analysis. Embedding Large Language Models (LLMs), HAppA addresses understanding the context information of long code sequences typical in HPC applications. HAppA implements a novel code representation module that chunks the code into fixed-size segments and aggregates the embeddings of these segments. Three aggregation methods have been explored: MeanPooling, MaxPooling, and LSTM-based techniques. We built a DAtaset for REsilience analysis using Fault Injection (FI), named DARE. Using our DARE dataset, HAppA is trained for regression prediction tasks. Our evaluation results demonstrate the predictive accuracy of HAppA compared to other models, particularly noting that the LSTM-based aggregation method -- HAppA-LSTM -- achieves a mean squared error (MSE) of 0.078 for SDC prediction, surpassing the existing state-of-the-art PARIS model, which recorded an MSE of 0.1172. Additionally, HAppA with the KeyBERT model extracts a list of keywords representing the source code. A comprehensive importance analysis of these keywords further elucidates the code patterns contributing to the error rate. These findings highlight the effectiveness of HAppA in analyzing the resilience of HPC applications and establish a new benchmark for predictive accuracy in resilience.

Jiang, Hailong [Kent State University]↗

MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8) for advanced open-source tritium transport and fuel cycle modeling

Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Updates on MURAVES Project at Mt. Vesuvius

The MUon RAdiography of VESuvius (MURAVES) project aims to employ muography imaging techniques to investigate the internal structure of the summit of Mount Vesuvius, an active volcano located near Naples, Italy. This paper reports recent advancements in data analysis and simulation tools that significantly improve the quality and reliability of the experiment’s results. A new track selection method, referred to as the Golden Selection, has been developed to identify high-quality muon tracks by applying an improved χ 2 -based criterion. This method enhances the signal-to-background ratio and improves the resolution of the resulting muographic images. Moreover, the simulation framework has been upgraded through the integration of the MULDER (MUon simuLation for DEnsity Reconstruction) library, which consolidates the functionalities of previously used libraries into a single, unified platform. MULDER enables efficient and accurate modeling of muon flux variations induced by topographical features. A good agreement is observed between the simulated and measured muon flux maps, validating the effectiveness of the new analysis and simulation approaches.

Cosmic rays↗

Accurate atmospheric parameters at moderate resolution using spectral indices: Preliminary application to the marvels survey

Studies of Galactic chemical, and dynamical evolution in the solar neighborhood depend on the availability of precise atmospheric parameters (effective temperature T {sub eff}, metallicity [Fe/H], and surface gravity log g) for solar-type stars. Many large-scale spectroscopic surveys operate at low to moderate spectral resolution for efficiency in observing large samples, which makes the stellar characterization difficult due to the high degree of blending of spectral features. Therefore, most surveys employ spectral synthesis, which is a powerful technique, but relies heavily on the completeness and accuracy of atomic line databases and can yield possibly correlated atmospheric parameters. In this work, we use an alternative method based on spectral indices to determine the atmospheric parameters of a sample of nearby FGK dwarfs and subgiants observed by the MARVELS survey at moderate resolving power (R ∼ 12,000). To avoid a time-consuming manual analysis, we have developed three codes to automatically normalize the observed spectra, measure the equivalent widths of the indices, and, through a comparison of those with values calculated with predetermined calibrations, estimate the atmospheric parameters of the stars. The calibrations were derived using a sample of 309 stars with precise stellar parameters obtained from the analysis of high-resolution FEROS spectra, permitting the low-resolution equivalent widths to be directly related to the stellar parameters. A validation test of the method was conducted with a sample of 30 MARVELS targets that also have reliable atmospheric parameters derived from the high-resolution spectra and spectroscopic analysis based on the excitation and ionization equilibria method. Our approach was able to recover the parameters within 80 K for T {sub eff}, 0.05 dex for [Fe/H], and 0.15 dex for log g, values that are lower than or equal to the typical external uncertainties found between different high-resolution analyses. An additional test was performed with a subsample of 138 stars from the ELODIE stellar library, and the literature atmospheric parameters were recovered within 125 K for T {sub eff}, 0.10 dex for [Fe/H], and 0.29 dex for log g. These precisions are consistent with or better than those provided by the pipelines of surveys operating with similar resolutions. These results show that the spectral indices are a competitive tool to characterize stars with intermediate resolution spectra.

79 ASTRONOMY AND ASTROPHYSICS↗

Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with a better control over the spurious fragments in the image.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

In-Vehicle Assessment of Human Exposure to EMFs from 25-kW WPT System Based on Near-Field Analysis

Wireless power transfer (WPT) technology has the potential to be a convenient and reliable charging method for the light and heavy duty electric vehicles. However, the loosely coupling between the two sides results in strong near-electromagnetic fields (EMFs) around the system, which may have the possibility to impact human safety if the standard limits are exceeded. Therefore, comprehensive tests are necessary to ensure the electromagnetic fields are with in safe limits. Consequently, this paper presents a test methodology for the near-field from a 25 kW WPT system from Momentum Dynamics, which is installed in a heavy duty electric shuttle at the National Renewable Energy Laboratory (NREL). The paper describes in detail the measuring device, test setup and conditions. The misalignments between the two systems' sides are considered during the measurements. Test results for the regions of concern around and inside the bus are presented and compared with the reference levels defined by the international standards, including ICNIRP 2010 and IEEE C95.1. In addition, a finite-element model is developed for the wireless coupler and analyzed at the same conditions as the tests. Comparative analysis is presented between the simulated and experimental results. The measurements at the test points show adherence to the standard limits for the general public and occupational exposure.

33 ADVANCED PROPULSION SYSTEMS↗

Thermomechanical analysis and microstructural characterization of high performance concretes

Ultra-high performance concrete (UHPC) is a family of emerging materials for buildings and constructions. Behaviors of UHPCs at high temperatures are very important to their reliability and safety. In the current study, two UHPC materials were studied using the thermomechanical analysis (TMA) technique between room temperature and 800oC. Both reversible and irreversible phase transformations were observed from the TMA results, which were likely due to the - quartz transformation, and the decarburization and the dehydroxylation transitions, respectively. Thermal expansion coefficients exhibited significant variations in different temperature regimes. Postmortem SEM examinations revealed extensive cracking in the heated samples. In addition, micro-porosities were observed in the C-S-H phase as a result of phase changes during heating.

Ren, Fei↗

Hybrid Geo-Solar GeoVision Case Study Analysis: CSP power plant with geothermal boiler feedwater heating

While stand-alone geothermal power plants provide reliable 24/7 baseload operation, most systems are subject to slow resource decline, and air-cooled plant performance suffers in hot weather. Stand-alone solar thermal power plants operate using a consistent, albeit intermittent, solar resource that requires thermal storage for reliability. Hybrid geothermal-solar power plants offer a number of potential advantages including boosted power generation during daylight hours when demand is typically greatest, the ability to share a common power block, and no requirement for thermal storage. The GeoVision hybrid systems analysis focused on aspects of hybrid technology that can increase the utilization of geothermal energy. Important aspects of the hybrid systems analysis therefore include evaluating conditions where hybrid technologies could decrease the costs of geothermal power generation and/or increase the viability of low temperature geothermal resources.

14 SOLAR ENERGY↗

Advanced Composite Wind Turbine Blade Design Based on Durability and Damage Tolerance

The objective of the program was to demonstrate and verify Certification-by-Analysis (CBA) capability for wind turbine blades made from advanced lightweight composite materials. The approach integrated durability and damage tolerance analysis with robust design and virtual testing capabilities to deliver superior, durable, low weight, low cost, long life, and reliable wind blade design. The GENOA durability and life prediction software suite was be used as the primary simulation tool. First, a micromechanics-based computational approach was used to assess the durability of composite laminates with ply drop features commonly used in wind turbine applications. Ply drops occur in composite joints and closures of wind turbine blades to reduce skin thicknesses along the blade span. They increase localized stress concentration, which may cause premature delamination failure in composite and reduced fatigue service life. Durability and damage tolerance (D&DT) were evaluated utilizing a multi-scale micro-macro progressive failure analysis (PFA) technique. PFA is finite element based and is capable of detecting all stages of material damage including initiation and propagation of delamination. It assesses multiple failure criteria and includes the effects of manufacturing anomalies (i.e., void, fiber waviness). Two different approaches have been used within PFA. The first approach is Virtual Crack Closure Technique (VCCT) PFA while the second one is strength-based. Constituent stiffness and strength properties for glass and carbon based material systems were reverse engineered for use in D&DT evaluation of coupons with ply drops under static loading. Lamina and laminate properties calculated using manufacturing and composite architecture details matched closely published test data. Similarly, resin properties were determined for fatigue life calculation. The simulation not only reproduced static strength and fatigue life as observed in the test, it also showed composite damage and fracture modes that resemble those reported in the tests. The results show that computational simulation can be relied on to enhance the design of tapered composite structures such as the ones used in turbine wind blades. A computational simulation for durability, damage tolerance (D&DT) and reliability of composite wind turbine blade structures in presence of uncertainties in material properties was performed. A composite turbine blade was first assessed with finite element based multi-scale progressive failure analysis to determine failure modes and locations as well as the fracture load. D&DT analyses were then validated with static test performed at Sandia National Laboratories. The work was followed by detailed weight analysis to identify contribution of various materials to the overall weight of the blade. The methodology ensured that certain types of failure modes, such as delamination progression, are contained to reduce risk to the structure. Probabilistic analysis indicated that composite shear strength has a great influence on the blade ultimate load under static loading. Weight was reduced by 12% with robust design without loss in reliability or D&DT. Structural benefits obtained with the use of enhanced matrix properties through nanoparticles infusion were also assessed. Thin unidirectional fiberglass layers enriched with silica nanoparticles were applied to the outer surfaces of a wind blade to improve its overall structural performance and durability. The wind blade was a 9-meter prototype structure manufactured and tested subject to three saddle static loading at Sandia National Laboratory (SNL). The blade manufacturing did not include the use of any nano-material. With silica nanoparticles in glass composite applied to the exterior surfaces of the blade, the durability and damage tolerance (D&DT) results from multi-scale PFA showed an increase in ultimate load of the blade by 9.2% as compared to baseline structural performance (without nano). The use of nanoparticles lead to a delay in the onset of delamination. Load-displacement relationships obtained from testing of the blade with baseline neat material were compared to the ones from analytical simulation using neat resin and using silica nanoparticles in the resin. Multi-scale PFA results for the neat material construction matched closely those from test for both load displacement and location and type of damage and failure. AlphaSTAR demonstrated that wind blade structures made from advanced composite materials can be certified with multi-scale progressive failure analysis by following building block verification approach.

17 WIND ENERGY↗

In-Vehicle Assessment of Human Exposure to Electromagnetic Fields from 25-kW Wireless Power Transfer System Based on Near-Field Analysis

Wireless power transfer (WPT) technology has the potential to be a convenient and reliable charging method for the light and heavy duty electric vehicles. However, the loose coupling between the two sides results in strong near-electromagnetic fields (EMFs) around the system, which may have the possibility to impact human safety if the standard limits are exceeded. Therefore, comprehensive tests are necessary to ensure the electromagnetic fields are with in safe limits. This paper presents a test methodology for the near-field from a 25-kW WPT system from Momentum Dynamics, which is installed in a heavy-duty electric shuttle at the National Renewable Energy Laboratory (NREL). The paper describes in detail the measuring device, test setup, and conditions.

30 DIRECT ENERGY CONVERSION↗

Emerging Tools to Support DILI Assessment in Clinical Trials with Abnormal Baseline Serum Liver Tests or Pre-existing Liver Diseases

Abstract Based on the late Dr. Hyman Zimmerman’s observation that hepatocellular drug-induced liver injury (DILI) leading to jaundice carries a ≥ 10% fatality risk (coined as Hy’s law by others), evaluation of Drug-Induced Serious Hepatotoxicity (eDISH) continues to play a central role in the assessment of a study drug’s liability for acute hepatocellular DILI. The eDISH identifies drugs in clinical trials with DILI fatality (death or transplant) risk that may be unacceptable in a post-market setting. As a two-dimensional graph that plots peak total bilirubin (TB) versus peak serum aminotransferase levels for each patient during study drug or comparator treatment, eDISH identifies potential cases of acute, modest, and serious hepatocellular DILI for in-depth analysis of liver tests (LT) and clinical course so that the likelihood of causal association with the study drug can be determined. Unfortunately, the generalizable utility of this tool only pertains to trials enrolling patients with normal or near normal (NNN) baseline (BL) serum LTs. The eDISH does not necessarily apply to trials of patients with abnormal baseline (ABN-BL) LTs that often coincide with underlying liver disorders. Because drug development programs being reviewed by the FDA increasingly target liver disorders, we are often challenged to evaluate DILI risk in trials of patients with ABN-BL LTs. Also, the high background prevalence of metabolic dysfunction associated steatotic liver disease (MASLD) means patients with LTs above NNN may need to be enrolled in trials treating non-liver disorders to reflect the target population. Such study populations create challenges for industry and regulators because eDISH may not reliably categorize or identify potential cases of DILI for further analysis, as it so efficiently does in NNN-BL trials. We describe the main functionalities of eDISH in NNN-BL trials to understand what should be emulated by new tools or eDISH modifications. We then discuss non-eDISH–based plots that may be useful in ABN-BL trials.

Amirzadegan, Jasmine↗

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗