Utilization of NEUP Data for HTGR Thermal-Fluid Code Validation: A New Resource Platform
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22 GENERAL STUDIES OF NUCLEAR REACTORS↗
SEARCH · Engineering Papers
Results for “Verification of data”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Labels as a feature: Network homophily for systematically annotating human GPCR drug-target interactions
Machine learning has revolutionized drug discovery by enabling the exploration of vast, uncharted chemical spaces essential for discovering novel patentable drugs. Despite the critical role of human G protein-coupled receptors in FDA-approved drugs, exhaustive in-distribution drug-target interaction testing across all pairs of human G protein-coupled receptors and known drugs is rare due to significant economic and technical challenges. This often leaves off-target effects unexplored, which poses a considerable risk to drug safety. In contrast to the traditional focus on out-of-distribution exploration (drug discovery), we introduce a neighborhood-to-prediction model termed Chemical Space Neural Networks that leverages network homophily and training-free graph neural networks with labels as features. We show that Chemical Space Neural Networks’ ability to make accurate predictions strongly correlates with network homophily. Thus, labels as features strongly increase a machine learning model’s capacity to enhance in-distribution prediction accuracy, which we show by integrating labeled data during inference. We validate these advancements in a high-throughput yeast biosensing system (3773 drug-target interactions, 539 compounds, 7 human G protein-coupled receptors) to discover novel drug-target interactions for FDA-approved drugs and to expand the general understanding of how to build reliable predictors to guide experimental verification.
Hansson, Frederik G↗
Data Analysis of Energy Code Compliance in Commercial Buildings
What percent of newly constructed commercial buildings comply with the energy code? How much energy and cost could be saved if the compliance increased? Which code requirements have both low compliance rates and high savings potential? These are the questions U.S. Department of Energy (DOE) is trying to answer through its Commercial Energy Code Field Study. Previous commercial studies have been very limited and did not result in a widely accepted and tested methodology. DOE’s goal is to create a standardized methodology that can produce actionable results at a reasonable study cost, that can be used by state and local governments and utilities and provides valuable information to policy makers. The field study team implemented the pilot methodology, compiling a data set of 230 office and retail buildings in two climate zones. The approach is based on identifying lost savings on a total energy cost basis rather than simply counting the quantity of measures that do not meet code. This report is focused on the analysis of the collected data. The primary goal was to analyze the data collected during the field study and determine the actual energy cost impact of each measure in a non-compliance situation. The energy impact results allowed for ranking the measures to identify which have the highest potential for lost savings. These results combined with the time required to verify each measure will allow future compliance verification to focus on measures that had a large impact on energy use over the life of the building and those that have the greatest savings recovery potential per verification hour.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Data Analysis of Energy Code Compliance in Commercial Buildings (Rev. 1)
What percent of newly constructed commercial buildings comply with the energy code? How much energy and cost could be saved if the compliance increased? Which code requirements have both low compliance rates and high savings potential? These are the questions U.S. Department of Energy (DOE) is trying to answer through its Commercial Energy Code Field Study. Previous commercial studies have been very limited and did not result in a widely accepted and tested methodology. DOE’s goal is to create a standardized methodology that can produce actionable results at a reasonable study cost, that can be used by state and local governments and utilities and provides valuable information to policy makers. The field study team implemented the pilot methodology, compiling a data set of 230 office and retail buildings in two climate zones. The approach is based on identifying lost savings on a total energy cost basis rather than simply counting the quantity of measures that do not meet code. This report is focused on the analysis of the collected data. The primary goal was to analyze the data collected during the field study and determine the actual energy cost impact of each measure in a non-compliance situation. The energy impact results allowed for ranking the measures to identify which have the highest potential for lost savings. These results combined with the time required to verify each measure will allow future compliance verification to focus on measures that had a large impact on energy use over the life of the building and those that have the greatest savings recovery potential per verification hour.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
The NASA Carbon Monitoring System Phase 2 synthesis: scope, findings, gaps and recommended next steps
Abstract Underlying policy efforts to address global climate change is the scientific need to develop the methods to accurately measure and model carbon stocks and fluxes across the wide range of spatial and temporal scales in the Earth system. Initiated in 2010, the NASA Carbon Monitoring System is one of the most ambitious relevant science initiatives to date, exploiting the satellite remote sensing resources, computational capabilities, scientific knowledge, airborne science capabilities, and end-to-end system expertise that are major strengths of the NASA Earth Science program. Here we provide a synthesis of ‘Phase 2’ activities (2011–2019), encompassing 79 projects, 482 publications, and 136 data products. Our synthesis addresses four key questions: What has been attempted? What major results have been obtained? What major gaps and uncertainties remain? and What are the recommended next steps? Through this review, we take stock of what has been accomplished and identify future priorities toward meeting the nation’s needs for carbon monitoring reporting and verification.
54 ENVIRONMENTAL SCIENCES↗
Evaluation of a pair-based, joint-likelihood association approach for regional infrasound event identification
SUMMARY A Bayesian framework for the association of infrasonic detections is presented and evaluated for analysis at regional propagation scales. A pair-based, joint-likelihood association approach is developed that identifies events by computing the probability that individual detection pairs are attributable to a hypothetical common source and applying hierarchical clustering to identify events from the pair-based analysis. The framework is based on a Bayesian formulation introduced for infrasonic source localization and utilizes the propagation models developed for that application with modifications to improve the numerical efficiency of the analysis. Clustering analysis is completed using hierarchical analysis via weighted linkage for a non-Euclidean distance matrix defined by the negative log-joint-likelihood values. The method is evaluated using regional synthetic data with propagation distances of hundreds of kilometres in order to study the sensitivity of the method to uncertainties and errors in backazimuth and time of arrival. The method is found to be robust and stable for typical uncertainties, able to effectively distinguish noise detections within the data set from those in events, and can be made numerically efficient due to its ease of parallelization.
58 GEOSCIENCES↗
Field Test Bed for Vadose-Zone Monitoring Approaches - 20404
In the Central Plateau at the U.S. Department of Energy Hanford Site, a large inventory of contaminants resides in unsaturated sediments within the approximately 100-meter-thick vadose zone, posing a potential continuing risk to groundwater. Vadose zone remedies used to address these contaminants will require performance monitoring to provide feedback during implementation and for long-term verification that remedial action objectives have been met. Passive approaches may also need long-term monitoring to demonstrate that the flux of contaminants from the vadose zone to the groundwater are below thresholds established to meet groundwater protection goals. Collection of physical (e.g., groundwater or sediment) samples is a common method for identifying contaminant concentration distributions, but this approach is limited by the number of locations and the frequency with which data can be collected. In situ vadose zone measurements have evolved over the past few years to include key measurements of water content, soil water pressure, temperature, and chemical concentration. However, the current generation of sensors is designed for relatively short-term use in near-surface soils or sediments. Geophysical methods have been evolving but are also limited in that they have not been designed for the specific long-term vadose zone monitoring needs at the Hanford Site. Overall, monitoring under unsaturated conditions can be difficult due to the need to install and maintain instrumentation over a large area and depth and the need to identify preferential flow pathways due to geologic and chemical heterogeneities over long periods. Thus, a vadose zone monitoring test bed was initiated to address these challenges and identify cost-effective approaches for implementation and postclosure monitoring of the deep vadose zone. The monitoring test bed is expected to provide valuable field-scale information for the design of vadose zone monitoring systems. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Evaluation of AI-Enabled Digital Documented Safety Analysis: A Case Study
Safety basis documentation development and review under U.S. Department of Energy (DOE) authorization have emerged as critical constraint throttling deployment of advanced nuclear reactors, with traditional processes demanding extraordinary resource investment that delays the delivery of these technologies. Traditional Documented Safety Analysis (DSA) processes rely on static documents with limited traceability [U.S. DOE]. The regulatory review and engagement processes are similarly constrained, often requiring significant effort and extensive manual verification. The scale of this challenge is exemplified by the U.S. Nuclear Regulatory Commission (NRC) review of the NuScale application, which required over 250,000 staff hours and the evaluation of approximately two million pages of documentation [Bergman 2021]. The volume and complexity of information within nuclear licensing applications or authorization reviews demands innovative approaches to document generation and data management.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
The Short Baseline Neutrino Program at Fermilab
The current status of the Short Baseline Neutrino (SBN) project at Fermilab is reviewed. While the installation of SBND is still in progress, ICARUS has taken its first neutrino data on beam:using both the Booster Neutrino Beam (BNB) and the Neutrino at the Main Injector (NuMI) beam.MicroBooNE has presently completed its data taking and is producing the world’s first high statistics results on neutrino Argon interactions, in both inclusive and exclusive channels. In parallel, the unexpected MiniBooNE “low energy excess” is under investigation, to search for sterile neutrinos.The physics potential for sterile neutrino searches at SBN will be outlined, with emphasis on the Neutrino-4 experiment and the possible ICARUS verification of this claim.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
AMR-Wind: A Performance-Portable, High-Fidelity Flow Solver for Wind Farm Simulations
We present AMR-Wind, a verified and validated high-fidelity computational-fluid-dynamics code for wind farm flows. AMR-Wind is a block-structured, adaptive-mesh, incompressible-flow solver that enables predictive simulations of the atmospheric boundary layer and wind plants. It is a highly scalable code designed for parallel high-performance computing with a specific focus on performance portability for current and future computing architectures, including graphical processing units (GPUs). In this paper, we detail the governing equations, the numerical methods, and the turbine models. Establishing a foundation for the correctness of the code, we present the results of formal verification and validation. The verification studies, which include a novel actuator line test case, indicate that AMR-Wind is spatially and temporally second-order accurate. The validation studies demonstrate that the key physics capabilities implemented in the code, including actuator disk models, actuator line models, turbulence models, and large eddy simulation (LES) models for atmospheric boundary layers, perform well in comparison to reference data from established computational tools and theory. We conclude with a demonstration simulation of a 12-turbine wind farm operating in a turbulent atmospheric boundary layer, detailing computational performance and realistic wake interactions.
17 WIND ENERGY↗
Monitoring, Reporting, and Verification Considerations for Carbon Dioxide Removal
The project investigates Measurement, Reporting, and Verification (MRV) methods for Enhanced Weathering and Marine Carbon Dioxide Removal (mCDR) technologies. Enhanced Weathering accelerates natural mineral processes to capture CO2, while mCDR leverages oceanic processes for carbon sequestration. The study focuses on developing standardized MRV protocols, assessing environmental impacts, and evaluating the scalability and economic feasibility of these carbon sequestration methods. The goal is to ensure reliable and transparent data for validating and improving CO2 removal technologies.
Priyadarshini↗
Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant (Presentation)
Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizable. To address this challenge, this study aims to develop a financial model that quantifies the risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of value at risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and assess the potential reduction in investor risk exposure. This paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verifying the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. This paper’s results present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Verification of Coupled Hydraulic Fracturing Simulators Using Laboratory-Scale Experiments
In this work, we aim to verify the predictions of the numerical simulators, which are used for designing field-scale hydraulic stimulation experiments. Although a strong theoretical understanding of this process has been gained over the past few decades, numerical predictions of fracture propagation in low-permeability rocks still remains a challenge. Against this background, we performed controlled laboratory-scale hydraulic fracturing experiments in granite samples, which not only provides high-quality experimental data but also a well-characterized experimental set-up. Using the experimental pressure responses and the final fracture sizes as benchmark, we compared the numerical predictions of two coupled hydraulic fracturing simulators—CSMP and GEOS. Both the simulators reproduced the experimental pressure behavior by implementing the physics of Linear Elastic Fracture Mechanics (LEFM) and lubrication theory within a reasonable degree of accuracy. The simulation results indicate that even in the very low-porosity (1–2 %) and low-permeability (10 -18 m 2 - 10 -19 m 2 ) crystalline rocks, which are usually the target of EGS, fluid-loss into the matrix and unsaturated flow impacts the formation breakdown pressure and the post-breakdown pressure trends. Therefore, underestimation of such parameters in numerical modeling can lead to significant underestimation of breakdown pressure. The simulation results also indicate the importance of implementing wellbore solvers for considering the effect of system compressibility and pressure drop due to friction in the injection line. The varying injection rate as a result of decompression at the instant of fracture initiation affects the fracture size, while the entry friction at the connection between the well and the initial notch may cause an increase in the measured breakdown pressure.
15 GEOTHERMAL ENERGY↗
Cyber‐physical system testbed for power system monitoring and wide‐area control verification
The electric power system is intrinsically a cyber‐physical system (CPS) with power flowing inthe physical system and information flowing in the cyber‐network. Testbeds arecrucial for understanding the cyber‐physical interactions and provideenvironments for prototyping novel applications. This study proposes afour‐layer architecture for CPS testbeds with emphases on communication networkemulation and networked physical components. A configurable software‐definednetwork is employed to bridge physical components with wide‐area applicationsfor closed‐loop control. In order to distribute physically coupled devices intomultiple software simulations, this study proposes a data broker setup based ona distributed messaging environment to achieve low‐latency data streaming. Thedecoupled design with data streaming allows for building testbed components asmodules and running them in a distributed manner. Case studies verify the databroker setup for low‐latency sensing and actuation, as well as the communicationemulation setup for the desired network latency. Also illustrated is a replayattack scenario using synchrophasors in the Western Electricity CoordinatingCouncil (WECC) 181‐bus system for demonstrating the closed‐loop cyber‐physicalsimulation capability of the testbed.
Cui, Hantao↗
Quantifying deformation during Zry-4 burst testing: a comparison of BISON and a combined in-situ digital image correlation and infrared thermography method
The development and verification of nuclear fuel-cladding performance codes require extensive testing to establish empirical correlations, necessitating more accelerated testing methods that can replace large validation studies. Here, in the present work, a technique was developed and implemented to experimentally quantify the relationship between temperature, cladding internal pressure, and strain in-situ during a burst test, with the specific aim of generating data for code validation and model refinement. Digital image correlation was used to measure hoop, axial, and radial strain, and infrared thermography to quantify axial temperature gradients. Several key experimental modifications to traditional LOCA burst testing were necessary, but are shown to effectively have little impact on burst temperatures. The time/temperature dependent pressure and time/spatially dependent thermal gradient data were used with BISON to simulate cladding burst and strain rates. Although the measured DIC strains reach appreciable amounts at slightly lower temperatures than BISON simulated strains, there is good agreement between the measured and simulated strains in terms of magnitude and rates leading up to burst. However, in the few seconds prior to and during burst, the BISON simulated strains are significantly lower than the measured strains, indicating the potential for model improvement. The combined experiment and simulation technique may be applied to any new cladding concept to accelerate fuel qualification.
36 MATERIALS SCIENCE↗
NucMesh: nuclear reactor geometry creation and mesh generation module in NEMoSys
NucMesh is a parameterized geometry and mesh generator for nuclear reactors developed within the Nuclear Energy Modeling System NEMoSys at Illinois Rocstar. NEMoSys is a platform developed for mesh generation, adaptive refinement, and solution verification. NucMesh is implemented to be generalized and extensible with a robust computer aided design engine and multiple mesh generation algorithms for unstructured triangular, quad-dominant, and structured quadrilateral meshing. In this paper, we present the geometric and meshing features of NucMesh. Geometrically objects are constructed bottom-to-top and overlaps are addressed automatically. A sophisticated object tracking algorithm prevents data from being lost for segmented objects. We discuss the primitive objects of circle and polygons that constitute the module and show how they are used with example inputs. Arrays of primitives and arrays of arrays are utilized to build large assemblies of objects. The concept of saved objects is discussed to demonstrate how repetitive objects can be reused easily and augmented in place. Three dimensional meshes can be obtained through mesh extrusion where all materials and side sets are extended to three dimensions. We show that side sets can be defined nearly anywhere within the geometry and can then be applied to the mesh. Finally, example reactor meshes are demonstrated for the Idaho National Laboratory Advanced Test Reactor and Los Alamos National Lab Empire reactor, both of which use control drums that NucMesh handles easily. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Materials Development and Advanced Process Simulation for Additive Manufacturing with Fiber-Reinforced Thermoplastics (Final Technical Report)
DuPont, Local Motors, and the Composites Manufacturing and Simulation Center (CMSC) at Purdue worked together to advance process simulation capabilities for Additive Manufacturing (AM) and develop printable short fiber reinforced semi-crystalline engineering thermoplastics suitable for vehicle components. DuPont provided one candidate thermoplastic material, which was evaluated against the following three criteria: 1) Printability using extrusion additive manufacturing processes. 2) Suitability for vehicle applications based on mechanical coupon screening tests. 3) Predictive capability of process simulations. Indiana Manufacturing Institute provided modeling and simulation technology and access to Purdue’s lab scale AM printer. Local Motors provided mechanical property requirements and printed demonstration prototype components using their Thermwood Large Scale Additive Manufacturing (LSAM) printer. To meet the performance and cost requirements of the automotive industry, high fiber content semi-crystalline engineering materials are required. Printing experience and property data for a 50% by weight short glass fiber reinforced material were gathered. Further, material properties required for simulating the printing process with the glass-fiber reinforced material were characterized. Knowledge was acquired with regards to the processability and performance of this thermoplastic material. Predictions of part deformation and crystallinity level were verified against experimental observations. Any significant results other than verification of simulation, e.g., novel material identified here would be impactful.
36 MATERIALS SCIENCE↗
HPC-Enabled Optimization of High Temperature Heat Exchangers (CRADA Final Report)
This project was a collaborative effort between Lawrence Livermore National Security, LLC (LLNS) as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Materials Sciences, LLC, to develop a technology for design and optimization of heat exchangers using powerful desktop and laptop computers. The project was originally designated as a 12-month project, and consisted of 3# major tasks and the following 8# major deliverables: 1) CFD models of 3D heat exchangers based on existing and new geometry. 2) Validation against experimental data provided by MSC and published in the literature. 3) CFD models of 3D unit cells based on TPMS. 4) Surrogate models capable of delivering the gradients of the homogenized properties with respect to the parametrization. 5) 3D design methodology using TO algorithms. 6) Conventional reference and topology optimized designs. 7) 3D optimized designs stored in a 3D printer build format. 8) Verification of the improved performance. All of the deliverables for this project were successfully completed with two no-cost time extensions.
36 MATERIALS SCIENCE↗