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At least 1,657 records · Page 92

Hybrid AI-ML and FE-based Digital Twin Predictive Modeling Framework for a PWR Coolant System Components: Updates on Multi-Time-Series-3D-Location Dependent Usages Factor Prediction

The long-term operation (LTO) of nuclear power plants (NPP) beyond their original design life of 40 years can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition, the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Requiring frequent NDE inspections may lead to frequent NPP shutdowns which can lead to power outages and additional NDE inspection cost-related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing a more digital approach such as using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. The DT framework is based on limited experimental data, Artificial-intelligence (AI)-Machine-Learning (ML) and multiphysics-computationalmechanics such as finite element- (FE) based models. Given the real-time thermal-hydraulic process measurements from several existing plant sensors, the overall goal of the DT framework is to predict the cumulative usages factors or equivalent fatigue lives in real time and at any random 3D location of the components. This includes inaccessible locations such as inside the thickness or location of a component. This prediction can be at thousands to millions of 3D point clouds or locations like conventional FE-based models, but without running an FE model in real time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Twinac: initiation of a community-driven accelerator digital twin framework

We present the initiation of a community-driven framework for the integration of accelerator digital twins into control systems: Twinac. Few facilities have fully integrated accelerator digital twins like at Cornell’s CHESS. Many facilities have active research to employ surrogate models to aid in operational decisions like at Argonne’s ALS, MSU’s FRIB, SLAC’s LCLS-II, and Fermilab’s FAST/IOTA, PIP-II, and main complex. To lower the barrier to entry for all accelerator facilities to build and benefit from a digital twin of their own accelerators, we propose the following software framework. Twinac will provide the capability to compose one’s own digital twin using reusable components engineered at other facilities. With this model in place, Twinac will also support tools for (1) predictive maintenance systems; (2) discovery of correlated but uncontrolled environmental factors, like seasonal temperature variations causing performance changes on power supplies, magnets, etc.; and (3) prototyping and updating sophisticated optimization and controls algorithms. The Twinac framework will enable sharing and simplified deployment of modeled components and control algorithms at all facilities. With an inter-facility team to build and support the Twinac framework, it will be easy to publish and try out the latest advancements at one’s own facility.

Miceli, Tia [Fermilab]↗

Model Evaluation Protocol for Fire Models Involving Fuels at Liquefied Natural Gas Facilities.

This document provides a description of the model evaluation protocol (MEP) for pool fires, jet fires, and fireballs involving liquefied natural gas (LNG), refrigerant fluids, and byproducts at LNG facilities. The purpose of the MEP is to provide procedures regarding the assessment of a model's suitability to predict heat flux from fires. Three components, namely, a scientific assessment, model verification, and model validation comprise the MEP. The evaluation of a model satisfying these three components is to be documented in the form of a model evaluation report (MER). Discussion of models for the prediction of fire, detailed information on each of the three MEP components, the MEP procedure regarding new versions of previously approved models, and the format of the model evaluation report (MER) are provided.

03 NATURAL GAS↗

Model Evaluation Protocol for Fire Models Involving Fuels at Liquefied Natural Gas Facilities (Version 2)

This document provides a description of the model evaluation protocol (MEP) for pool fires, jet fires, and fireballs involving liquefied natural gas (LNG) and processing fuels at LNG facilities. The purpose of the MEP is to provide procedures regarding the assessment of a model’s suitability to predict heat flux from fires. Three components, namely, a scientific assessment, model verification, and model validation comprise the MEP. The evaluation of a model satisfying these three components is to be documented in the form of a model evaluation report (MER). Discussion of models for the prediction of fire, detailed information on each of the three MEP components, the MEP procedure regarding new versions of previously approved models, and the format of the model evaluation report (MER) are provided.

03 NATURAL GAS↗

Precision measurement of the W boson mass using the full CDF Run II data set

The mass of the W boson, a mediator of the weak force between elementary particles, is tightly constrained by the symmetries of the standard model of particle physics. After the observation of the Higgs boson, the last missing component of the model, the measurement of the W boson mass provides a stringent test of the model. A measurement of the W boson mass is presented, which used data corresponding to 8.8 fb$^{-1}$ of integrated luminosity, collected in proton-antiproton collisions at a 1.96 TeV center-of-mass energy with the CDF II detector at the Fermilab Tevatron collider. A sample of approximately 4 million W boson candidates was used to obtain a Wboson mass of 80433.5±6.4$_{stat}$ ±6.9$_{syst}$ = 80433.5±9.4 MeV, the precision of which exceeds that of all previous measurements combined. This measurement is in significant tension with the standard model expectation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

Credibility↗

Finite Element Model Development For Aircraft Fuselage Structures

The ability to extend the valid frequency range for finite element based structural dynamic predictions using detailed models of the structural components and attachment interfaces is examined for several stiffened aircraft fuselage structures. This extended dynamic prediction capability is needed for the integration of mid-frequency noise control technology. Beam, plate and solid element models of the stiffener components are evaluated. Attachment models between the stiffener and panel skin range from a line along the rivets of the physical structure to a constraint over the entire contact surface. The finite element models are validated using experimental modal analysis results.

Buehrle, Ralph D.↗

Effect of an isotropic nonequilibrium plasma on electron temperature measurements.

The electron temperatures that would be determined (using the conventional single-temperature analysis) by the electrostatic probe, the diffuse resonance, and the radar backscatter techniques in an isotropic two-temperature plasma are presented. Plasma models corresponding to the addition of a minor component of energetic electrons and models corresponding to a process that cools a fraction of the ionospheric electrons are considered. The diffuse resonance temperature is found to lie between the probe and radar backscatter temperatures. The isotropic models corresponding to the addition of energetic electrons cannot support the reported discrepancies between radio wave and probe electron temperature measurements. Temperature differences similar to the observed differences can be produced by models with a fraction of the electrons at a temperature cooler than that of the main component of electrons. These models, however, are difficult to explain in terms of present understanding of the ionospheric plasma.

Benson, R. F.↗

Energy Exascale Earth System Model v2.0

First release of version 2 of the Energy Exascale Earth System Model. The atmosphere component remains EAM. Major changes since version 1 include: all column-physics parameterizations are computed on a separate grid that has approximately half the number of points of the dynamics grid, a new nonhydrostatic dynamical core (running in hydrostatic mode) with semi-Lagrangian tracer transport, CLUBB updated from v1 to v2, a new convective trigger (dCAPE/ULL) based on the dynamic Convective Available Potential Energy (CAPE) (dCAPE) and the Unrestricted Launch Level (ULL) concepts is used in ZM. minimum cloud droplet number changed, gravity wave drag energy conservation fixed and new tunings used, dust emission size distribution changed to emit more coarse dust particles The land component is still ELM. Major changes since version 1 include: using SNICAR-AD for radiation in snow to match the sea-ice model and fixing bugs in snow compaction and water state calculation. The ocean component remains MPAS-ocean. Major change since version 1 include: Redi isopycnal mixing has been updated, tested, and tuned in combination with the Gent-McWilliams parameterization, a sign error was fixed in the 3rd-order flux routines, the mesh used in low-resolution coupled cases was modified and the time steps adjusted, new regionally refined meshes were created, one focused on North America and another on the Southern Ocean, including ice shelf cavities. The sea-ice component remains MPAS-seaice. Major changes since version 1 include: A new heat- and freshwater-conserving coupling of frazil ice, turning off of SSH filtering, addition of SNICAR-AD and snow grain aging. The land-ice component remains MPAS-Albany-landIce (MALI) and is a static ice sheet. There is more out-of-the-box support for cryosphere configurations including the new regionally refined configuration around Antarctica with ice shelf cavities. The river model is MOSART. The half-degree river mesh was redone so it no longer treats Black and Caspian seas as ocean. The coupler remains cpl7/MCT. Major changes since version 1 include handling of ice shelf melt fluxes (heat / freshwater exchange with the ocean), and data icebergs. All components allow regional refinement of their meshes and two separate example of refinement, one in and around North America and one around Antarctica and the Southern Ocean, are provided.

E3SM Project, DOE↗

System Testing of Ground Cooling System Components

This internship focused primarily upon software unit testing of Ground Cooling System (GCS) components, one of the three types of tests (unit, integrated, and COTS/regression) utilized in software verification. Unit tests are used to test the software of necessary components before it is implemented into the hardware. A unit test determines that the control data, usage procedures, and operating procedures of a particular component are tested to determine if the program is fit for use. Three different files are used to make and complete an efficient unit test. These files include the following: Model Test file (.mdl), Simulink SystemTest (.test), and autotest (.m). The Model Test file includes the component that is being tested with the appropriate Discrete Physical Interface (DPI) for testing. The Simulink SystemTest is a program used to test all of the requirements of the component. The autotest tests that the component passes Model Advisor and System Testing, and puts the results into proper files. Once unit testing is completed on the GCS components they can then be implemented into the GCS Schematic and the software of the GCS model as a whole can be tested using integrated testing. Unit testing is a critical part of software verification; it allows for the testing of more basic components before a model of higher fidelity is tested, making the process of testing flow in an orderly manner.

Unit Test↗

Characterization of damped structural connections for multi-component systems

The inability to model connections adequately has historically limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Lawrence, Charles↗

Characterization of damped structural connections for multi-component systems

The inability to model connections adequately has historically limited the ability to predict overall system dynamic response. Connections between structural components are often mechanically complex and difficult to accurataely model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. This study explores combining Component Mode Synthesis methods for coupling structural components with Parameter Identification procedures for improving the analytical modeling of the connections. Improvements in the connection stiffness and damping properties are computed in terms of physical parameters so the physical characteristics of the connections can be better understood, in addition to providing improved input for the system model.

Lawrence, Charles↗

NRAP-Open-IAM: Open Wellbore Component (V.2.0)

The Open Wellbore component of NRAP-Open-IAM is applicable to the calculation of Area of Review at a carbon storage site and fast estimation of dense gas dispersion from multiple continuous CO 2 surface leakage sources for risk assessment. The Open Wellbore Component of NRAP-Open-IAM is a lookup table model based on the drift-flux approach. The National Research Assessment Partnership’s second-generation integrated assessment model, NRAP-Open-IAM, is open-source software written in Python for use in performance and quantitative risk assessment of geologic carbon storage (GCS) systems. The look-up table for open well leakage is an updated version the previous model which provides finer resolution of reservoir depth and more accurate fluid properties than the previous open well look-up table, especially in calculating the gas (CO 2 -rich) phase properties. The component model input parameters include the reservoir transmissivity, aquifer transmissivity, brine salinity, well radius, and well top and bottom depths. The reservoir transmissivity and brine salinity were set to values consistent with the reservoir component, and the well top and bottom depths varied with location. The possible outputs from the Open Wellbore component are leakage rates of CO 2 and brine to either an aquifer or atmosphere, depending on the depth of the well top. Several python test scripts are presented that demonstrate that the Open Wellbore component works correctly. Use of the open wellbore model in NRAP-Open-IAM may result in a large CO 2 leakage rates, comparable to the leakage rates of CO 2 blow out.

54 ENVIRONMENTAL SCIENCES↗

The Static and Dynamic Rotary Stability Derivatives at Subsonic Speeds of an Airplane Model Having Wing and Tail Surfaces Swept Back 45 degrees

Wind-tunnel measurements were made of the static and dynamic rotary stability derivatives of an airplane model having sweptback wing and tail surfaces. The Mach number range of the tests was from 0.23 to 0.94. The components of the model were tested in various combinations so that the separate contribution to the stability derivatives of the component parts and the interference effects could be determined. Estimates of the dynamic rotary derivatives based on some of the simpler existing procedures which utilize static force data were found to be in reasonable agreement with the experimental results at low angles of attack. The results of the static and dynamic measurements were used to compute the short-period oscillatory characteristics of an airplane geometrically similar to the test model. The results of these calculations are compared with military flying qualities requirements.

Lopez, Armando E.↗

Solving Seismic Wave Equations on Variable Velocity Models With Fourier Neural Operator

Here, in the study of subsurface seismic imaging, solving the acoustic wave equation is a pivotal component in existing models. The advancement of deep learning (DL) enables solving partial differential equations (PDEs), including wave equations, by applying neural networks to identify the mapping between the inputs and the solution. This approach can be faster than traditional numerical methods when numerous instances are to be solved. Previous works that concentrate on solving the wave equation by neural networks consider either a single velocity model or multiple simple velocity models, which is restricted in practice. Instead, inspired by the idea of operator learning, this work leverages the Fourier neural operator (FNO) to effectively learn the frequency domain seismic wavefields under the context of variable velocity models. We also propose a new framework paralleled FNO (PFNO) for efficiently training the FNO-based solver given multiple source locations and frequencies. Numerical experiments demonstrate the high accuracy of both FNO and PFNO with complicated velocity models in the OpenFWI datasets. Furthermore, the cross-dataset generalization test verifies that PFNO adapts to out-of-distribution velocity models. Finally, PFNO admits higher computational efficiency on large-scale testing datasets than the traditional finite-difference method. The aforementioned advantages endow the FNO-based solver with the potential to build powerful models for research on seismic waves.

58 GEOSCIENCES↗

Hypersonic research engine/aerothermodynamic integration model, experimental results. Volume 1: Mach 6 component integration

The NASA Hypersonic Research Engine (HRE) Project was initiated for the purpose of advancing the technology of airbreathing propulsion for hypersonic flight. A large component (inlet, combustor, and nozzle) and structures development program was encompassed by the project. The tests of a full-scale (18 in. diameter cowl and 87 in. long) HRE concept, designated the Aerothermodynamic Integration Model (AIM), at Mach numbers of 5, 6, and 7. Computer program results for Mach 6 component integration tests are presented.

Andrews, E. H., Jr.↗

A Reference Architecture for Space Information Management

We describe a reference architecture for space information management systems that elegantly overcomes the rigid design of common information systems in many domains. The reference architecture consists of a set of flexible, reusable, independent models and software components that function in unison, but remain separately managed entities. The main guiding principle of the reference architecture is to separate the various models of information (e.g., data, metadata, etc.) from implemented system code, allowing each to evolve independently. System modularity, systems interoperability, and dynamic evolution of information system components are the primary benefits of the design of the architecture. The architecture requires the use of information models that are substantially more advanced than those used by the vast majority of information systems. These models are more expressive and can be more easily modularized, distributed and maintained than simpler models e.g., configuration files and data dictionaries. Our current work focuses on formalizing the architecture within a CCSDS Green Book and evaluating the architecture within the context of the C3I initiative.

information systems↗