SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This document is the final technical report for the UC Davis project DE-SC00023500, detailing the development and implementation of a Fast Recurrent Neural Network (FRNN) software. The software was designed to enable predictive, real-time control of plasma instabilities within the DIII-D Plasma Control System (PCS).
Understanding complex physical systems often requires integrating data from multiple diagnostics, each with limited resolution or coverage. We present a machine learning framework that reconstructs synthetic high-temporal-resolution data for a target diagnostic using information from other diagnostics, without direct target measurements during the inference. This multimodal super-resolution technique improves diagnostic robustness and enables monitoring even in case of measurement failures or degradation. Applied to fusion plasmas, our method targets edge-localized modes (ELMs), which can damage plasma-facing materials. By reconstructing super-resolution Thomson Scattering data from complementary diagnostics, we uncover fine-scale plasma dynamics and validate the role of resonant magnetic perturbations (RMPs) in ELM suppression through magnetic island formation. The approach provides new observation supporting the plasma profile flattening due to these islands. Our results demonstrate the framework’s ability to generate high-fidelity synthetic diagnostics, offering a powerful tool for ELM control development in future reactors like ITER. The approach is broadly transferable to other domains facing sparse, incomplete, or degraded diagnostic data, opening new avenues for discovery.
We present a synthetic soft x-ray (SXR) forward-modeling framework that characterizes the emissivity structure of rotating magnetic islands in the Lithium Tokamak eXperiment-β across space and time. Magnetic islands associated with tearing modes produce modulations in line-integrated SXR brightness. Traditional tomographic methods struggle to resolve these structures in devices with limited sightlines, resulting in an under-determined inversion problem, or otherwise necessitate equilibrium reconstruction data, preventing their use in active control. Our approach removes this challenge by combining a fully three-dimensional ray-tracing model with a time-dependent emissivity prescription of a $m/n$ = 2/1 magnetic island. The model is validated through helical island geometry, rotation measured by magnetic diagnostics, and equilibrium constraints from PSI-Tri reconstructions. Synthetic brightness signals are generated for each photodiode sightline from a modeled emissivity profile and directly compared with experimental data from a tangential midplane SXR array. By fitting the synthetic diagnostic output to the observed brightness across time, we simultaneously infer key geometric parameters-such as island radial location, island width, and rotation frequency-without requiring full tomographic reconstruction, all with an average absolute deviation of less than 3%. This work demonstrates that forward modeling with a single tangential array can extract key island parameters in a spherical tokamak, providing a computationally efficient alternative to conventional SXR tomography and providing a pathway toward real-time magnetic-island characterization in future devices.
In this work, gyrokinetic simulations are performed with the CGYRO code (Candy et al 2016 J. Comput. Phys. 324 73–93) for a negative triangularity H-mode plasma in ASDEX Upgrade, and compared with experimental measurements. The PORTALS framework (Rodriguez-Fernandez et al 2024 Nucl. Fusion 64 076034) is used to accelerate the prediction of kinetic profiles for this plasma, using surrogate modeling and Bayesian optimization. Ion heat flux, electron heat flux, and electron particle flux are simultaneously matched across the simulated radial regime of the plasma (normalized radius $r/a = 0.35-0.90$), and the resulting ion temperature, electron temperature, and electron density profiles match well with the experimental profile data within this radial range. A synthetic Correlation Electron Cyclotron Emission diagnostic is applied to find well-matched electron temperature fluctuation properties between simulation and experiment. The flux-matched profiles provide a basis for investigation of the turbulence nature across the plasma radius, revealing the dominance of Trapped Electron Mode turbulence at $r/a = 0.35$, the dominance of Ion Temperature Gradient turbulence at $r/a = 0.55$, 0.75, and 0.83, and an instability boundary at $r/a = 0.90$.
Statistical uncertainties in determining the temperatures of hot (0.5-10 keV) coronal plasmas are investigated. The statistical presicion of various spectral temperature diagnostics is established by analyzing synthetic ASCA solid-state imaging spectrometer (SIS) CCD spectra. The diagnostics considered are the ratio of hydrogen-like to helium-like line complexes of Z greater than or = 14 elements, line-free portions of the continuum, and the entire spectrum. While fits to the entire spectrum yield the highest statistical precision, it is argued that fits to the line-free continuum are less susceptible to atomic data uncertainties but lead to a modest increase in statistical uncertainty over full spectral fits. Temperatures deduced from line ratios can have similar accuracy, but only over a narrow range of temperatures. Convenient estimates of statistical accuracies for the various temperature diagnostics are provided which may be used in planning ASCA SIS observations.
A laser absorption spectroscopy (LAS) diagnostic was used to obtain measurements of temperature, pressure, CO, and CO 2 at 500 kHz or 1 MHz in post-detonation fireballs produced by hemispherical samples of pentaerythritol tetranitrate (PETN). A quantum-cascade laser was scanned over multiple CO absorption transitions near 2008.5 cm −1 at 1 MHz, while an interband-cascade laser was scanned over a CO 2 absorption transition near 2394.8 cm −1 at 500 kHz. Light from each laser was combined onto a single path and passed through a detonation chamber approximately 83 mm above the 12-mm diameter hemispherical PETN charge. The CO and CO 2 absorption signals were post-processed to obtain time histories of temperature, pressure, species column pressures (P CO L, P CO2 L), and species column mole fractions (X CO L, X CO2 L). Additionally, schlieren imaging was performed simultaneously at 500 kHz to aid interpretation of the LAS measurements. Experimental and synthetic (i.e., CFD based) LAS measurements were compared to evaluate the accuracy of the CFD model and its ability to model the turbulent afterburning of the detonation products in air. In general, the experimental measurements exhibit reasonable agreement with the synthetic measurements at early times; thereby supporting the accuracy of the CFD model. Periods of disagreement between experimental and synthetic measurements at later times are most likely due to a reflected shock and detonator cavity jetting, which are not accounted for in the CFD model.
We formulate a theory of Thomson scattering (TS) from inhomogeneous plasmas using a ray-tracing approach. The scattered radiation is described within the eikonal approximation, including convective gain arising from scattering instabilities driven by the TS probe laser. In the limit of a weak probe and vanishing gain, the theory recovers the standard TS cross section and scattered power due to volumetric particle noise. The ray-tracing formalism is implemented in a TS fitting framework, enabling accurate analysis of inhomogeneous plasmas whose background profiles can be provided by large-scale hydrodynamic simulations or experimental diagnostics. Here, several examples of synthetic TS spectra are presented, and further extensions of the theory are discussed.
In inertial confinement fusion experiments at the National Ignition Facility, asymmetries are probed by a variety of neutron diagnostics, including neutron imaging systems, real-time neutron activation diagnostics (RTNADs), and neutron spectrometers. It is often useful to generate synthetic data based on these diagnostics to validate and tune models. However, current methods of doing so using Monte Carlo particle tracing are time-consuming. In this paper, an ultra-fast method is presented for generating synthetic neutron images, RTNAD data, and spectrometry data using line integrals and 3D convolutions. While it does not contain as much physics as particle tracing codes, it is thousands of times faster and produces nearly identical data. This enables analysis techniques that depend on generating large amounts of synthetic data, which will prove very useful for the study of asymmetries going forward.
The paper addresses the concept of synthetic satellite imagery as a visualization and diagnostic tool for understanding satellite sensors of the future and to detail preliminary results on the quality of soundings from the current sensors. Preliminary results are presented on the quality of soundings from the combination of the High-Resolution Infrared Radiometer Sounder and the Advanced Microwave Sounding Unit. Results are also presented on the first Observing System Simulation Experiment using this data in a mesoscale numerical prediction model.
The properties of clouds that may be observed by satellite instruments, such as optical depth and cloud top pressure, are only loosely related to the way clouds m-e represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between simulator output and observations can be interpreted unambiguously as model error. But simulators may themselves be restricted by limited information available from the host model or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail data sets developed for comparison with global models using ISCCP and MODIS simulators, In nature MODIS observes less mid-level doudines!> than ISCCP, consistent with the different methods used to determine cloud top pressure; aspects of this difference are reproduced by the simulators running in a climate modeL But stark differences between MODIS and ISCCP observations of total cloudiness and the distribution of cloud optical thickness can be traced to different approaches to marginal pixels, which MODIS excludes and ISCCP treats as homogeneous. These pixels, which likely contain broken clouds, cover about 15 k of the planet and contain almost all of the optically thinnest clouds observed by either instrument. Instrument simulators can not reproduce these differences because the host model does not consider unresolved spatial scales and so can not produce broken pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by excluding ambiguous observations.
The properties of clouds that may be observed by satellite instruments, such as optical depth and cloud top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between simulator output and observations can be interpreted unambiguously as model error. But simulators may themselves be restricted by limited information available from the host model or by internal assumptions. This work examines the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. We focus on the stark differences between MODIS and ISCCP observations of total cloudiness and the distribution of cloud optical thickness can be traced to different approaches to marginal pixels, which MODIS excludes and ISCCP treats as homogeneous. These pixels, which likely contain broken clouds, cover about 15% of the planet and contain almost all of the optically thinnest clouds observed by either instrument. Instrument simulators can not reproduce these differences because the host model does not consider unresolved spatial scales and so can not produce broken pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by excluding ambiguous observations.
Hierarchical neural posterior estimation has its place Hierarchical Bayesian Modeling (HBM) combined with MCMC algorithms has been shown to provide more robust and accurate inference for real-world phenomena in which nature takes a nested form. However, MCMC-based inference can be computationally expensive, and its performance often suffers for complex posterior geometries. These costs are especially pertinent for HBM. Studies have recently demonstrated the potential for a flexible, expressive, and amortized hierarchical neural posterior estimator (HNPE) built on Normalizing Flows. These studies have mostly been performed on simple datasets, or they focus on a single parameter from each level of the hierarchy. A systematic study analyzing how both hierarchical methods compare for more complex and realistic datasets is necessary before applying HNPE for scientific measurements. Here, we re-explore the theory behind HNPE and conduct comparative numerical experiments of HNPE and MCMC-based HBM methods on real and synthetic data, including strong gravitational lensing simulations. In particular, we use a suite of diagnostics to show trade-offs in terms of accuracy, precision, time to train or sample, reproducibility, and the need for expert domain knowledge. Especially for higher dimensional and complex posteriors, HNPE is expected to drastically improve on time for inference, accuracy, and precision with an upfront training time cost.
The integrity and precision of nuclear data are crucial for a broad spectrum of applications, from national security and nuclear reactor design to medical diagnostics, where the associated uncertainties can significantly impact outcomes. A substantial portion of uncertainty in nuclear data originates from the subjective biases in the evaluation process, a crucial phase in the nuclear data production pipeline. Recent advancements indicate that automation of certain routines can mitigate these biases, thereby standardizing the evaluation process and enhancing reproducibility. This research aims to provide a methodology, framework, and metrics for the validation of automated nuclear data evaluation software leveraging high-quality synthetic data that closely mimic real experimental observables. An introduced error metric provides a scale and intuitive measure of the evaluation quality by quantifying the estimate’s accuracy and performance across the specified energy range. Synthetic data provides access to experimental observables and underlying resonance parameters, enabling comparison of different evaluations. The methodology is demonstrated using Ta-181 isotope data in the resolved resonance region. The Automated Resonance Identification Subroutine (ARIS), which operates without prior resonance information, was used to test and showcase the framework’s capabilities utilizing the proposed error metrics. The results demonstrate the effectiveness of the proposed approach and framework for optimizing software parameters and testing hypotheses through “what-if” controlled experiments, such as modifying assumptions about experimental conditions or average resonance parameters.
Recent measurements have shown that the quiet unstructured solar corona observed at the solar limb is close to isothermal, at a temperature that does not appear to change over wide areas or with time. Some in dividual active loop structures have also been found to be nearly iso thermal both along their axis and across their cross-section. Even a complex active region observed at the solar limb has been found to be composed of three distinct isothermal plasmas. If confirmed, these r esults would pose formidable challenges to the current theoretical understanding of the thermal structure and heating of the solar corona. For example, no current theoretical model can explain the excess dens ities and lifetimes of many observed loops if the loops are in fact i sothermal. All of these measurements are based on the so-called emiss ion measure (EM) diagnostic technique that is applied to a set of opt ically thin lines under the assumption of isothermal plasma. It provi des simultaneous measurement of both the temperature and EM. However, no study has ever been carried out to quantify the uncertainties in the technique and to rigorously assess its ability to discriminate bet ween isothermal and multithermal plasmas. Such a study is the topic o f the present work. We define a formal measure of the uncertainty in the EM diagnostic technique that can easily be applied to real data. We here apply it to synthetic data based on a variety of assumed plas ma thermal distributions, and develop a method to quantitatively asse ss the degree of multithermality of a plasma.
Major research advances in heat transfer and fluid dynamics are outlined, with particular reference to relevant energy problems. Of significant importance are such topics as synthetic fuels in combustion, turbulence models, combustion modeling, numerical methods for interacting boundary layers, and light-scattering diagnostics for gases. The discussion covers thermal convection, two-phase flow and boiling heat transfer, turbulent flows, combustion, and aerospace heat transfer problems. Other areas discussed include compressible flows, fluid mechanics and drag, and heat exchangers. Featured topics comprise heat and salt transfer in double-diffusive systems, limits of boiling heat transfer in a liquid-filled enclosure, investigation of buoyancy-induced flow stratification in a cylindrical plenum, and digital algorithms for dynamic analysis of a heat exchanger. Individual items are announced in this issue.
The pursuit of inertial confinement fusion ignition target designs requires precise experimental validation of the conditions within imploding capsules, in particular the density and temperature of the compressed shell. Previous work has identified x-ray Thomson scattering (XRTS) as a viable diagnostic tool for inferring the in-flight compressed deuterium-tritium shell conditions during capsule implosions (Poole et al 2022 Phys. Plasmas 29 072703). However, this study focused on one-dimensional simulations, which do not account for the growth of hydrodynamic instabilities. In this work, two-dimensional DRACO simulations incorporating intermediate-mode perturbations up to Legendre mode l = 50 were used to generate synthetic XRTS spectra with the SPECT3D code. The analysis employed Markov-Chain Monte Carlo techniques to infer plasma conditions from these spectra. The results demonstrate that the XRTS diagnostic platform can effectively discern the in-flight compressed shell conditions for targets with varying adiabats, even in the presence of intermediate-mode perturbations. This work underscores the potential of XRTS for realistic inertial confinement fusion experiments, providing a robust method for probing the complex dynamics of fusion implosions.
Quantifying performance improvements on the OMEGA laser facility requires robust inference of established no-alpha performance metrics, which requires, at minimum, a model to infer the shocked fuel mass and pressure of the confined fusion plasma. In this work, we describe the methodology used to infer performance metrics on OMEGA and present the current state-of-the art model used to infer these metrics from OMEGA experiments. In particular, since neutron images of cryogenic implosions are not available on OMEGA at present, we present how x-ray sizes are determined on OMEGA using a Gaussian Process regression model and how the neutron production region's size is inferred from them. As a result, we end by benchmarking the model using synthetic data and 1-D LILAC simulations and test its experimental self-consistency across available x-ray diagnostic channels.
The role of synthetic instruments (SIs) for Component-Level Electronic-Assembly Repair (CLEAR) is to provide an external lower-level diagnostic and functional test capability beyond the built-in-test capabilities of spacecraft electronics. Built-in diagnostics can report faults and symptoms, but isolating the root cause and performing corrective action requires specialized instruments. Often a fault can be revealed by emulating the operation of external hardware. This implies complex hardware that is too massive to be accommodated in spacecraft. The SI strategy is aimed at minimizing complexity and mass by employing highly reconfigurable instruments that perform diagnostics and emulate external functions. In effect, SI can synthesize an instrument on demand. The SI architecture section of this document summarizes the result of a recent program diagnostic and test needs assessment based on the International Space Station. The SI architecture addresses operational issues such as minimizing crew time and crew skill level, and the SI data transactions between the crew and supporting ground engineering searching for the root cause and formulating corrective actions. SI technology is described within a teleoperations framework. The remaining sections describe a lab demonstration intended to show that a single SI circuit could synthesize an instrument in hardware and subsequently clear the hardware and synthesize a completely different instrument on demand. An analysis of the capabilities and limitations of commercially available SI hardware and programming tools is included. Future work in SI technology is also described.