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At least 955 records · Page 53

Myna

The additive manufacturing (AM) community has been developing digital factory tools over the past decade to better leverage the multi-modal process data coming out of the advanced manufacturing process. As a result, numerous databases of additive manufacturing process data exist in the literature and in the archival storage of disparate research groups. While some efforts have been made to create a standard ontology for storing and sharing AM data, in practice a variety of data structures are used to store AM build data, even within a single institution. This causes many problems for maintainability and extensibility when attempting to integrate computational modeling tools with experimental data to either validate models or to provide further insight into results and trends. Myna is a Python-based framework that aims to decrease the effort needed to connect individual computational models to the variety of AM process data that exist in different research groups and institutions. This type of software is sometimes referred to as "middleware" or “glueware,” in that it connects disparate databases and applications into a single computational ecosystem. Instead of maintaining unique interfaces between each application and each database, developers can create a single interface from each application to Myna and thereby gain access to the implemented database connections. Similarly, developing a database connection in Myna provides access to the developed simulation applications. This framework greatly simplifies the maintainability of model applications that rely on experimental data. Using external simulation tools, users will also be able to run pre-configured workflows using the built-in workflow manager. Several examples of input files are provided with Myna for different workflows, including melt pool geometry predictions and detailed melt pool and solidification microstructure predictions.

Knapp, GerryL. [Oak Ridge National Laboratory (ORN↗

Particle Engulfment and Pushing By Solidifying Interfaces - Recent Theoretical and Experimental Developments

The objective of the work on Particle Engulfment and Pushing by Solidifying Interfaces (PEP) include: 1) to obtain fundamental understanding of the physics of particle pushing and engulfment, 2) to develop mathematical models to describe the phenomenon, and 3) to perform critical experiments in the microgravity environment of space to provide benchmark data for model validation. Successful completion of this project will yield vital information relevant to a diverse area of terrestrial applications. With PEP being a long term research effort, this report will focus on advances in the theoretical treatment of the solid/liquid interface interaction with an approaching particle, experimental validation of some aspects of the developed models, and the experimental design aspects of future experiments to be performed on board the International Space Station.

Stefanescu, D. M.↗

The 0.125 degree finite-volume General Circulation Model on the NASA Columbia Supercomputer: Preliminary Simulations of Mesoscale Vortices

The NASA Columbia supercomputer was ranked second on the TOP500 List in November, 2004. Such a quantum jump in computing power provides unprecedented opportunities to conduct ultra-high resolution simulations with the finite-volume General Circulation Model (fvGCM). During 2004, the model was run in realtime experimentally at 0.25 degree resolution producing remarkable hurricane forecasts [Atlas et al., 2005]. In 2005, the horizontal resolution was further doubled, which makes the fvGCM comparable to the first mesoscale resolving General Circulation Model at the Earth Simulator Center [Ohfuchi et al., 2004]. Nine 5-day 0.125 degree simulations of three hurricanes in 2004 are presented first for model validation. Then it is shown how the model can simulate the formation of the Catalina eddies and Hawaiian lee vortices, which are generated by the interaction of the synoptic-scale flow with surface forcing, and have never been reproduced in a GCM before.)

Shen, B.-W.↗

Phase Change Processes for Thermal Management Systems and Science Investigations

This white paper focuses on the scientific rationale and motivation for deploying phase change processes-based spacecraft thermal management systems for space missions [1,2]. Phase change processes need to be implemented in the design of various life support systems, sub-critical cryogenic and thermal control systems, taking advantage of the latent heat of phase change so as to significantly increase the heat transfer rate per unit fluid mass. Experimental data are critical to understanding gravitational effects on complex phase change processes using novel materials and working fluids. Experimental data can be acquired by either designing new testing platforms or performing experiments with simulant fluids on existing microgravity platforms. With the acquired data, theoretical flow physics models and numerical simulations can then be validated for use under long-duration microgravity conditions. The acquired data and validated models will enable the deployment of game-changing thermal management systems with remarkably improved efficiency and stability in heat acquisition, transport, and rejection for long-duration space missions.

Fluid mechanics↗

Wind Energy High-Fidelity Model Verification and Validation Roadmap

The development of a next generation high-fidelity modeling code for wind plant applications is one of the central focus areas of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative. The code is based on a highly scalable framework, currently called Nalu-Wind. One key aspect of the model development is a coordinated formal validation program undertaken specifically to establish the predictive capability of Nalu-Wind for wind plant applications. The purpose of this document is to define the verification and validation (V&V) plan for the A2e high-fidelity modeling capability. It summarizes the V&V framework, identifies code capability users and use cases, describes model validation needs, and presents a timeline to meet those needs.

17 WIND ENERGY↗

MASK4 Test Campaign for Sandia WaveBot Device

This data and report details the findings from a wave tank test focused on production of useful work of a wave energy converter (WEC) device. The experimental system and test were specifically designed to validate models for power transmission throughout the WEC system. Additionally, the validity of co-design informed changes to the power take-off (PTO) were assessed and shown to provide the expected improvements in system performance. These data describe the "MASK4" wave tank test of the Sandia WaveBot device. The WaveBot device has been tested a number of times in different permutations at the US Navy's Maneuvering and Sea Keeping (MASK) basin. Each test in this series is referred to as MASK1, MASK2, etc. The WaveBot device was first tested in one degree of freedom (heave) in 2016. This MASK1 test focused primarily on system identification and modeling. After MASK1, major modifications were performed to improve the overall real-time control and measurement system, improve the heave drive train, and add surge and pitch degrees of freedom. The second set of testing, which was broken up in to two stages: MASK2A and MASK2B, focused on bench testing and closed-loop control performance as well as nonlinear modeling. MASK3 then focused on multi-input, multi-output modeling and control for maximization of electrical power. The attached report presents the results from MASK4, which focuses on detailed modeling of the power conversion chain and validation co-design principles by way of the introduction of a magnetic spring. The test log, report, and data from the MASK4 test of the WaveBot augmented with a tunable magnetic spring. Processing codes can be found at the Github link below.

16 TIDAL AND WAVE POWER↗

Characteristics of Cryogenic Hydrogen Releases Under Unignited and Ignited Conditions

Hydrogen is increasingly being used in the public sector as a fuel for vehicles. Due to the high density of hydrogen in its liquid phase, fueling stations that receive deliveries of and store hydrogen as a liquid are more practical for high volume stations. There is a critical need for validated models to assess the risk at hydrogen fueling stations with cryogenic hydrogen on-site. In this work, a cryogenic hydrogen release experiment generated controlled releases of cryogenic hydrogen in the laboratory. We measured the maximum ignition distance, flame length and the radiative heat flux and developed correlations to calculate the ignition ditance and the radiative heat flux. We also measured the concentration and temperature fields of releases under unignited conditions and used these measurements to validate a model for these cryogenic conditions. This study provides critical information on the development of models to inform the safety codes and standards of hydrogen infrastructure.

08 HYDROGEN↗

Rainier Mesa CAU Infiltration Model using INFILv3

The outline of this presentation are: (1) Model Inputs - DEM, Precipitation, Air temp, Soil props, Surface geology, Vegetation; (2) Model Pre-processing - Runoff Routing and sinks, Slope and Azimuth, Soil Ksat reduction with slope (to mitigate bathtub ring), Soil-Bedrock Interface permeabilities; (3) Model Calibration - ET using PEST, Chloride mass balance data, Streamflow using PEST; (4) Model Validation - Streamflow data not used for calibration; (5) Uncertainty Analysis; and (6) Results. Conclusions are: (1) Average annual infiltration rates =11 to 18 mm/year for RM domain; (2) Average annual infiltration rates = 7 to 11 mm/year for SM domain; (3) ET = 70% of precipitation for both domains; (4) Runoff = 8-9% for RM; and 22-24% for SM - Apparently high average runoff is caused by the truncation of the lowerelevation portions of watersheds where much of the infiltration of runoff waters would otherwise occur; (5) Model results are calibrated to measured ET, CMB data, and streamflow observations; (6) Model results are validated using streamflow observations discovered after model calibration was complete; (7) Use of soil Ksat reduction with slope to mitigate bathtub ring was successful (based on calibration results); and (8) Soil-bedrock K{_}interface is innovative approach.

54 ENVIRONMENTAL SCIENCES↗

Solar Sail Models and Test Measurements Correspondence for Validation Requirements Definition

Solar sails are being developed as a mission-enabling technology in support of future NASA science missions. Current efforts have advanced solar sail technology sufficient to justify a flight validation program. A primary objective of this activity is to test and validate solar sail models that are currently under development so that they may be used with confidence in future science mission development (e.g., scalable to larger sails). Both system and model validation requirements must be defined early in the program to guide design cycles and to ensure that relevant and sufficient test data will be obtained to conduct model validation to the level required. A process of model identification, model input/output documentation, model sensitivity analyses, and test measurement correspondence is required so that decisions can be made to satisfy validation requirements within program constraints.

Ewing, Anthony↗

Application of BISON to UO 2 MiniFuel fission gas release analysis

There has been a recent push to accelerate fuel qualification by developing revolutionary capabilities to reduce irradiation periods, and thereby, reduce the time required to qualify a new fuel system. One such capability is the MiniFuel irradiation capsule designed to miniaturize fuel samples and irradiate “mini” fuel samples under isothermal temperature conditions. MiniFuel allows steady-state irradiations to decouple the traditionally coupled fission rate (i.e., power) and temperature parameters to understand and generate microstructures observed in fuel operated in a commercial reactor. Furthermore, this process offers the possibility to gather in situ data as well as postirradiation or transient data such as thermal conductivity, specific heat, fission gas diffusion and release, etc. However, accelerating fuel qualification is not solely reliant on generating large amounts of data but also on developing an informed test matrix designed to rapidly generate impactful data. Additionally, this process is reliant on fuel performance codes, such as BISON, to evaluate MiniFuel irradiations using existing material models. This process pinpoints model/data gaps, identifies desired irradiation conditions, and subsequently supports model validation and development. This work describes the use of BISON to perform a number of sensitivity studies designed to understand conditions that lead to fission gas release (FGR) under steady-state isothermal irradiation conditions and temperature transient conditions. The model is applied to a UO 2 MiniFuel example and shows an overall good qualitative agreement with experimental FGR annealing tests under different temperature conditions. It also accounts well for microstructural effects on FGR. When quantitatively compared with FGR data from previously irradiated 103 MWd/kgU UO 2 discs under thermal annealing, the model shows a less satisfactory agreement with the experimental data. Finally, a UO 2 MiniFuel test matrix is proposed to help to extend the model's operational range and validate the new FGR model capabilities to higher burnups and transient conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Spatiotemporal Downscaling Model for Solar Irradiance Forecast Using Nearest-Neighbor Random Forest and Gaussian Process

Accurate solar photovoltaic (PV) capacity estimation requires high-resolution, site-specific solar irradiance data to account for localized variability. However, global datasets, such as the National Solar Radiation Database (NSRDB), provide regional averages that fail to capture the fine-scale fluctuations critical for large-scale grid integration. This limitation is particularly relevant in the context of increasing distributed energy resources (DERs) penetration, such as rooftop PV. Additionally, it is critical to the implementation of the U.S. Federal Energy Regulatory Commission (FERC) Order 2222, which facilitates DER participation in U.S. bulk power markets. To address this challenge, this study evaluates Nearest-Neighbor Random Forest (NNRF) and Nearest-Neighbor Gaussian Process (NNGP) models for spatiotemporal downscaling of global solar irradiance data. By leveraging historical irradiance and meteorological data, these models incorporate spatial, temporal, and feature-based correlations to enhance local irradiance predictions. The NNRF model, a machine-learning approach, prioritizes computational efficiency and predictive accuracy, while the NNGP model offers a level of interpretability and prediction uncertainty by numerically quantifying correlations and dependencies in the data. Model validation was conducted using day-ahead predictions. The results showed that the average Goodness of Fit (GoF) of the NNRF model of 90.61% across all eight sites outperformed the GoF of the NNGP of 85.88%. Additionally, the computational speed of NNRF was 2.5 times faster than the NNGP. Finally, the NNGP displayed polynomial scaling while the NNRF scaled linearly with increasing number of nearest neighbors. Additional validation of the model on five sites in Puerto Rico further confirmed the superiority of the NNRF model over the NNGP model. These findings highlight the robustness and computational efficiency of NNRF for large-scale solar irradiance downscaling, making it a strong candidate for improving PV capacity estimation and real-time electricity market integration for DERs.

Asiedu, Shadrack (ORCID:0009000646004826)↗

Augmented Method to Improve Thermal Data for the Figure Drift Thermal Distortion Predictions of the JWST OTIS Cryogenic Vacuum Test

The JWST Optical Telescope Element (OTE) assembly is the largest optically stable infrared-optimized telescope currently being manufactured and assembled, and is scheduled for launch in 2018. The JWST OTE, including the 18 segment primary mirror, secondary mirror, and the Aft Optics Subsystem (AOS) are designed to be passively cooled and operate near 45K. These optical elements are supported by a complex composite backplane structure. As a part of the structural distortion model validation efforts, a series of tests are planned during the cryogenic vacuum test of the fully integrated flight hardware at NASA JSC Chamber A. The successful ends to the thermal-distortion phases are heavily dependent on the accurate temperature knowledge of the OTE structural members. However, the current temperature sensor allocations during the cryo-vac test may not have sufficient fidelity to provide accurate knowledge of the temperature distributions within the composite structure. A method based on an inverse distance relationship among the sensors and thermal model nodes was developed to improve the thermal data provided for the nanometer scale WaveFront Error (WFE) predictions. The Linear Distance Weighted Interpolation (LDWI) method was developed to augment the thermal model predictions based on the sparse sensor information. This paper will encompass the development of the LDWI method using the test data from the earlier pathfinder cryo-vac tests, and the results of the notional and as tested WFE predictions from the structural finite element model cases to characterize the accuracies of this LDWI method.

Thermal Modeling↗

Frontiers in the Simulation of Dislocations

Dislocations play a vital role in the mechanical behavior of crystalline materials during deformation. To capture dislocation phenomena across all relevant scales, a multiscale modeling framework of plasticity has emerged, with the goal of reaching a quantitative understanding of microstructure–property relations, for instance, to predict the strength and toughness of metals and alloys for engineering applications. This review describes the state of the art of the major dislocation modeling techniques, and then discusses how recent progress can be leveraged to advance the frontiers in simulations of dislocations. Furthermore, the frontiers of dislocation modeling include opportunities to establish quantitative connections between the scales, validate models against experiments, and use data science methods (e.g., machine learning) to gain an understanding of and enhance the current predictive capabilities.

36 MATERIALS SCIENCE↗

On-Road Validation of a Simplified Model for Estimating Real-World Fuel Economy

On-road fuel economy is known to vary significantly between individual trips in real-world driving conditions. This work introduces a methodology for rapidly simulating a specific vehicle's fuel economy over the wide range of real-world conditions experienced across the country. On-road test data collected using a highly instrumented vehicle is used to refine and validate this modeling approach. Here, model accuracy relative to on-road data collection is relevant to the estimation of 'off-cycle credits' that compensate for real-world fuel economy benefits that are not observed during certification testing on a chassis dynamometer.

33 ADVANCED PROPULSION SYSTEMS↗

Pre-engineering Spaceflight Validation of Environmental Models and the 2005 HZETRN Simulation Code

The HZETRN code has been identified by NASA for engineering design in the next phase of space exploration highlighting a return to the Moon in preparation for a Mars mission. In response, a new series of algorithms beginning with 2005 HZETRN, will be issued by correcting some prior limitations and improving control of propagated errors along with established code verification processes. Code validation processes will use new/improved low Earth orbit (LEO) environmental models with a recently improved International Space Station (ISS) shield model to validate computational models and procedures using measured data aboard ISS. These validated models will provide a basis for flight-testing the designs of future space vehicles and systems of the Constellation program in the LEO environment.

Nealy, John E.↗

Validating Finite Element Models of Assembled Shell Structures

The validation of finite element models of assembled shell elements is presented. The topics include: 1) Problems with membrane rotations in assembled shell models; 2) Penalty stiffness for membrane rotations; 3) Physical stiffness for membrane rotations using shell elements with 6 dof per node; and 4) Connections avoiding rotations.

membrane rotations↗

Open-Source Suite for Advanced Synchrophasor Analysis

The paper presents the results of the development of the open-source suite of applications for synchrophasor analysis. The suite includes several software tools for oscillation analysis, power plant model validation, and frequency response analysis using synchrophasor measurements. All tools are based on the common framework and data sources. The developed tools have been used by the Bonneville Power Administration and other utilities for synchrophasor analysis. The paper includes several use cases based on the actual system PMU data.

PMU, model validation, Oscillation Modes, Open Sou↗

Open Source Suite for Advanced Synchrophasor Analysis

The report presents the results of the development of the open-source suite of applications for synchrophasor analysis. The suite includes several software tools for oscillation analysis, power plant model validation, and frequency response analysis using synchrophasor measurements. All tools are based on the common framework and data sources. The developed tools have been used by different electrical utilities for synchrophasor analysis. The report includes several use cases based on the actual system PMU data.

20 FOSSIL-FUELED POWER PLANTS↗