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Results for “Model validation”

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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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Convolutional Neural Networks for Heat Flux Model Validation on NSTX-U

To demonstrate the use of embedded thermocouples in new National Spherical Tokamak eXperiment Upgrade (NSTX-U) graphite plasma-facing components (PFCs), a convolutional neural network (CNN) has been trained using the ANSYS simulations to predict the scrape-off layer (SOL) heat flux width, λ q , given various machine operational parameters and diagnostic data as inputs. Here, the proof-of-concept CNN was trained on the thermocouple data generated by the approximated NSTX-U heat loads applied to real PFC designs in ANSYS. Once trained, the CNN is capable of high precision reconstruction of parameterized heat flux profiles expected in NSTX-U. In addition, to test the system's ability to cope with noise and systematic error, pseudonoise was injected into the simulated data. CNN can accurately predict the incident heat flux despite this noise and error.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Zr Extrusion – Direct Input for Models & Validation

As we examine differences in the high strain rate, high strain tensile response of high purity, highly textured Zr as a function of loading direction, temperature and extrusion velocity with primarily post mortem characterization techniques, we have also developed a technique for characterizing the in-situ extrusion process. This particular measurement is useful for partitioning energy of the system during the extrusion process: friction, kinetic energy, and temperature

36 MATERIALS SCIENCE↗
DOE OSTI2020

Phase Contrast Imaging Diagnostic on DIII-D (1994-2007); Phase Contrast Imaging Diagnostic on DIII-D and Alcator C-Mod (2007-2010); Experimental Study of Waves, Turbulence and Transport, and Model Validation with Phase Contrast Imaging on DIII-D and Alcator C-Mod (2010-2012); Phase Contrast Imaging Diagnostic Upgrade on DIII-D for Measuring High-k Turbulence and Alfven modes (2021-2016); Phase Contrast Imaging Diagnostic Upgrade on DIII-D for Full Multi-Scale Measurements (2016-2020) (Final Report)

This report describes the first twenty-five years of development and use of the Phase Contrast Imaging (PCI) diagnostic for measuring plasma fluctuations on the DIII–D tokamak. One of the key challenges in moving tokamak technology forward to the stage of a nuclear reactor remains understanding how energy and particles are transported across the magnetic field by the action of turbulence and waves, and PCI provides a highly flexible and capable measurement of these fluctuations. The PCI diagnostic uses a laser beam to probe the plasma and optical filtering to produce an amplitude variation on a linear detector array which provides an image of the density waves in the plasma. The PCI covers an exceptional range in frequency and wavelength of the measured fluctuations, allowing observation of plasma-sized magnetohydrodynamic (MHD) modes and ion- and electron-scale turbulence. Modulation of the beam amplitude allows measurement of radio frequency (RF) waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Instrumented Photovoltaic Modules for Environmental Characterization and Simulation Model Validation

Photovoltaic modules are subjected to various mechanical stressors in their deployment environments, ranging from installation handling to wind and snow loads. Damage incurred during these mechanical events has the potential to initiate subsequent degradation mechanisms, reducing useful module lifespan. Thus, characterizing the mechanical state of photovoltaic modules is pertinent to the development of reliable packaging designs. In this work, photovoltaic modules with strain gauges directly incorporated into the module laminate were fabricated and subjected to mechanical loading to characterize internal strains within the module when under load. These experimental measurements were then compared against results obtained by high-fidelity finite-element simulations. The simulation results showed reasonable agreement in the strain values over time; however, there were large discrepancies in the magnitudes of these strains. Both the instrumentation technique and the finite-element simulations have areas where they can improve. These areas of improvement have been documented. Despite the observed discrepancies between the experimental and simulated results, the module instrumentation proved to be a useful gauge in monitoring and characterizing the mechanical state. With some process improvements, this method could potentially be applied to other environments that a photovoltaic module will encounter in its lifetime that are known to cause damage and degrade performance.

14 SOLAR ENERGY↗