SEARCH · Engineering Papers

Results for “model diagnostics and development”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36

All sources NASA NTRS DOE OSTI

NASA NTRS2011

SPoRT's Participation in the GOES-R Proving Ground Activity

The next generation geostationary satellite, GOES-R, will carry two new instruments with unique atmospheric and surface observing capabilities, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), to study short-term weather processes. The ABI will bring enhanced multispectral observing capabilities with frequent refresh rates for regional and full disk coverage to geostationary orbit to address many existing and new forecast challenges. The GLM will, for the first time, provide the continuous monitoring of total lightning flashes over a hemispherical region from space. NOAA established the GOES-R Proving Ground activity several years ago to demonstrate the new capabilities of these instruments and to prepare forecasters for their day one use. Proving Ground partners work closely with algorithm developers and the end user community to develop and transition proxy data sets representing GOES-R observing capabilities. This close collaboration helps to maximize refine algorithms leading to the delivery of a product that effectively address a forecast challenge. The NASA Short-term Prediction Research and Transition (SPoRT) program has been a participant in the NOAA GOES-R Proving Ground activity by developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the SPoRT program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. Participation in the Proving Ground activities extends SPoRT s activities and taps its experience and expertise in diagnostic weather analysis, short-term weather forecasting, and the transition of research and experimental data to operational decision support systems like NAWIPS, AWIPS, AWIPS2, and Google Earth. Recent SPoRT Proving Ground activities supporting the development and use of a pseudo GLM total lightning product and the transition of the AWG s Convective Initiation (CI) product, both of which were available in AWIPS and AWIPS II environments, by forecasters during the Hazardous Weather Testbed (HWT) Spring Experiment. SPoRT is also providing a suite of SEVIRI and MODIS RGB image products, and a high resolution composite SST product to several National Centers for use in there ongoing demonstration activities. Additionally, SPoRT has involved numerous WFOs in the evaluation of a GOES-MODIS hybrid product which brings ABI-like data sets in front of the forecaster for everyday use. An overview of this activity will be presented at the conference.

Jedlovec, Gary↗

NASA NTRS1997

Using Cross-Correlations of SEUs and AP8 as a Diagnostic Tool

Timely data on low altitude energetic protons is very important for predicting the effect on humans and satellites. Because of the high bioeffectivity of protons in tissue, determination of the geographical location of the south Atlantic anomally (SAA) would be especially useful for reducing the risk associated with extravehicular activities. Because the AP8 model was developed with an epoch several decades old, the location of the south Atlantic anomally is incorrectly positioned in the model. The lack of extensive present-epoch energetic proton data at low altitude has prevented the update of the AP8 proton model. While there are studies in progress which are attempting to update the model at low altitude by using the path-integrated column density of the residual atmosphere as an organizing parameter, success in those studies will be defined by consistency in organization of old data. New data will still be required to provide a good present epoch model. As an alternative to using instrumental measurements of proton fluxes, background effects, proxy data sets such as SEUs, anomalies in instruments, enhanced background in shielded sensors believed to be induced by high energy protons, and dosimeter data in which key parameters (energy, efficiency, geometric factor, shielding, etc.) are poorly known can also be used. This in situ data is not as precise as direct measurement of the proton flux as geometric factor and shielding etc. are not calibrated, but these factors do not affect determination of the location of the SAA.

Vampola, A. L.↗

DOE OSTI2023

A bi-level data-driven framework for fault-detection and diagnosis of HVAC systems

Long-term operation of heating, ventilation, and air conditioning (HVAC) systems will eventually lead to a range of HVAC system failures, resulting in excessive energy consumption and maintenance costs. Here, to avoid HVAC malfunctioning, fault detection diagnostic (FDD) is utilized as a common practice. Machine learning methods have lately received considerable interest for FDD analysis of HVAC systems due to their high detection accuracy. Meanwhile, HVAC malfunctions are regarded as rare occurrences, hence normal operating data samples are much more accessible than data samples in faulty and malfunctioning conditions. The dominating frequency of normal operation in HVAC datasets has also led to heavily biased classification algorithms within the literature. Moreover, the focus of previous literature has been on increasing the accuracy of the models which leads to a high number of false positives (misleading alarms) in the system. In order to enhance the performance of diagnostic procedures and fill the mentioned gaps, this study proposes a novel data-driven framework. A bi-level machine learning framework is developed for diagnosing faults in air handling units (AHUs) and rooftop units (RTUs) based on principal component analysis (PCA), time series anomaly detection, and random forest (RF). It is shown that PCA can reduce the dataset dimension with one principal component accounting for 95% of data variance. Also, the random forest could classify the faults with 89% precision for single-zone AHU, 85% precision for RTU, and 79% for multi-zone AHU. By proposing this framework, three persistent challenges are addressed: (I) minimizing false positives; (II) accounting for data imbalance; and (III) normal condition monitoring of equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Three-dimensional hot-spot x-ray emission tomography from cryogenic deuterium–tritium direct-drive implosions on OMEGA

A three-dimensional model of the hot-spot x-ray emission has been developed and applied to the study of low-mode drive asymmetries in direct-drive inertial confinement fusion implosions on OMEGA with cryogenic deuterium–tritium targets. Here, the steady-state model assumes an optically thin plasma and the data from four x-ray diagnostics along quasi-orthogonal lines of sight are used to obtain a tomographic reconstruction of the hot spot. A quantitative analysis of the hot-spot shape is achieved by projecting the x-ray emission into the diagnostic planes and comparing this projection to the measurements. The model was validated with radiation-hydrodynamic simulations assuming a mode-2 laser illumination perturbation resulting in an elliptically shaped hot spot, which was accurately reconstructed by the model using synthetic x-ray images. This technique was applied to experimental data from implosions in polar-direct-drive illumination geometry with a deliberate laser-drive asymmetry, and the hot-spot emission was reconstructed using spherical-harmonic modes of up to ℓ = 3. A 10% stronger drive on the equator relative to that on the poles resulted in a prolate-shaped hot spot at stagnation with a large negative A 2,0 coefficient of A 2,0 = –0.47 ± 0.03, directly connecting the modal contribution of the hot-spot shape with the modal contribution in laser-drive asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Measurement of Stark-split beam and carbon charge exchange emissions for simultaneous B-field and temperature/rotation analysis at DIII-D

A set of two newly designed, single-channel Czerny–Turner spectrometers has been deployed at the DIII-D tokamak for measurements of the motional Stark effect (MSE) split beam emission and the C6+ (CVI) carbon charge exchange recombination (CER) emission at high spectral (δλ = 0.13 nm) and temporal (1–5 kHz) resolution. High throughput optics (f/# = 2.8) allow for good signal-to-noise at high time resolution using fast EMCCD detectors. The MSE emission allows for spectral fitting of the magnitude and direction of the local B-field, while the carbon emission yields local ion temperature and toroidal rotation information. To reduce so-called Doppler broadening of the MSE emission, a new channel-specific variable lens-masking approach has been developed. Experimental data collected from the 2023 DIII-D experimental campaign demonstrate the signal quality and instrument fidelity for both diagnostic measurements. Moreover, initial CER data analysis shows a clear evolution of the toroidal rotation during edge localized modes. Initial progress on the advanced MSE model, including a new validated ray-trace model of the DIII-D collection optics, is shown via sensitivity analysis.

Instruments & Instrumentation↗

DOE OSTI2024

A Gaussian process guide for signal regression in magnetic fusion

Extracting reliable information from diagnostic data in tokamaks is critical for understanding, analyzing, and controlling the behavior of fusion plasmas and validating models describing that behavior. Recent interest within the fusion community has focused on the use of principled statistical methods, such as Gaussian process regression (GPR), to attempt to develop sharper, more reliable, and more rigorous tools for examining the complex observed behavior in these systems. While GPR is an enormously powerful tool, there is also the danger of drawing fragile, or inconsistent conclusions from naive GPR fits that are not driven by principled treatments. Here we review the fundamental concepts underlying GPR in a way that may be useful for broad-ranging applications in fusion science. We also revisit how GPR is developed for profile fitting in tokamaks. We examine various extensions and targeted modifications applicable to experimental observations in the edge of the DIII-D tokamak. Finally, we discuss best practices for applying GPR to fusion data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗

NASA NTRS2012

Qualification of a Null Lens Using Image-Based Phase Retrieval

In measuring the figure error of an aspheric optic using a null lens, the wavefront contribution from the null lens must be independently and accurately characterized in order to isolate the optical performance of the aspheric optic alone. Various techniques can be used to characterize such a null lens, including interferometry, profilometry and image-based methods. Only image-based methods, such as phase retrieval, can measure the null-lens wavefront in situ - in single-pass, and at the same conjugates and in the same alignment state in which the null lens will ultimately be used - with no additional optical components. Due to the intended purpose of a Dull lens (e.g., to null a large aspheric wavefront with a near-equal-but-opposite spherical wavefront), characterizing a null-lens wavefront presents several challenges to image-based phase retrieval: Large wavefront slopes and high-dynamic-range data decrease the capture range of phase-retrieval algorithms, increase the requirements on the fidelity of the forward model of the optical system, and make it difficult to extract diagnostic information (e.g., the system F/#) from the image data. In this paper, we present a study of these effects on phase-retrieval algorithms in the context of a null lens used in component development for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. Approaches for mitigation are also discussed.

Bolcar, Matthew R.↗

DOE OSTI2024

Heavy ion beam probe for Wendelstein 7-X measurement capabilities as projected through its design

A heavy ion beam probe (HIBP) diagnostic is being developed for studies of plasma equilibrium and turbulence in the optimized Wendelstein 7-X (W7-X) stellarator. Operation of W7-X has experimentally demonstrated that its optimized magnetic field results in improved neoclassical particle confinement and, as a result, turbulence is the predominant cause of energy transport. The HIBP will have the unique ability to provide experimental data needed to complement models of both neoclassical and turbulent transport. It will acquire direct measurements in the W7-X plasma interior of the electric potential (needed for understanding ambipolar particle flux) and fluctuations of electron density and potential (needed for understanding turbulence). The HIBP for W7-X will inject singly charged ion beams with energies of up to 2 MeV and is designed to access the upper cross section of the W7-X plasma. We use trajectory simulations to illustrate the plasma coverage that the diagnostic can achieve in the reference magnetic configurations of W7-X. We calculate beam signal levels, discuss anticipated measurement sensitivity of broadband fluctuations of electron density and plasma potential, and show how they depend on plasma density. We also discuss the diagnostic sensitivity to equilibrium plasma potential.

Instruments & Instrumentation↗

NASA NTRS2002

One-Dimensional Spontaneous Raman Measurements of Temperature Made in a Gas Turbine Combustor

The NASA Glenn Research Center is working with the aeronautics industry to develop highly fuel-efficient and environmentally friendly gas turbine combustor technology. This effort includes testing new hardware designs at conditions that simulate the high-temperature, high-pressure environment expected in the next-generation of high-performance engines. Glenn has the only facilities in which such tests can be performed. One aspect of these tests is the use of nonintrusive optical and laser diagnostics to measure combustion species concentration, fuel/air ratio, fuel drop size, and velocity, and to visualize the fuel injector spray pattern and some combustion species distributions. These data not only help designers to determine the efficacy of specific designs, but provide a database for computer modelers and enhance our understanding of the many processes that take place within a combustor. Until recently, we lacked one critical capability, the ability to measure temperature. This article summarizes our latest developments in that area. Recently, we demonstrated the first-ever use of spontaneous Raman scattering to measure combustion temperatures within the Advanced Subsonics Combustion Rig (ASCR) sector rig. We also established the highest rig pressure ever achieved for a continuous-flow combustor facility, 54.4 bar. The ASCR facility can provide operating pressures from 1 to 60 bar (60 atm). This photograph shows the Raman system setup next to the ASCR rig. The test was performed using a NASA-concept fuel injector and Jet-A fuel over a range of air inlet temperatures, pressures, and fuel/air ratios.

Hicks, Yolanda R.↗

NASA NTRSDate not supplied

The ZBOT-NC Experiment - Effects of Non-Condensable Gases on Propellant Tank Pressurization and Pressure Control

Introduction Integral to all phases of NASA’s projected planetary expeditions is affordable and reliable cryogenic fluid storage for use in propellant or life support systems. It is greatly advantageous to develop innovative vent-less pressure control designs based on cooling/mixing of the bulk tank fluid to allow storage of the cryogenic fluid with zero or reduced boil-off. The presence of noncondensable gases, can interfere with the condensation at the interface impacting tank pressure control during subcooled jet mixing especially in microgravity. The Zero-Boil-Off Tank (ZBOT) Experiments are a series of small-scale experiments aboard the International Space Station (ISS) that use a transparent volatile simulant fluid in a transparent sealed tank to delineate various fundamental fluid flow, heat and mass transport, and phase change phenomena associated with storage tank pressurization and pressure control in microgravity. The ZBOT-1 experiment was performed on the ISS 2017-2018 timeframe and collected data to validate a state-of-the-art CFD model for tank pressurization and pressure control for a pure system. The ZBOT-NC Experiment is the second experiment in the series to be performed on the International Space Station (ISS) in 2025. Its goal is to investigate the effects of noncondensable gases on interfacial evaporation and condensation during self -pressurization and jet-mixing pressure control in microgravity for a two-component system. Materials & Methods In this work, we will describe the detailed features of the ZBOT-NC experimental hardware and Diagnostics that includes nonintrusive Quantum Dot Thermometry (QDT) for whole field temperature measurement. All microgravity pressurization and pressure control tests will be performed for both the pure and the two-components systems with Xenon and Neon as the two noncondensable gases spanning small and large molecular weights and sizes. The two-phase CFD model that is developed as part of the project will be also presented and discussed. Results Ground-based pressurization and jet mixing experiments and CFD simulation results are compared to each other to validate both the fidelity of the CFD model predictions and the accuracy of the QDT measurement. Model simulations for noncondensable gas effects will also be compared against large Cryogenic LH2-GHe experiments to indicate the noncondensable gas effects on tank pressure control during jet mixing in 1G. Finally, CFD results will be presented to predict the effects of the noncondensable gas during subcooled jet mixing during the ZBOT-NC in advance of the microgravity experiment in 2015.

Evaporation Condensation↗

NASA NTRSDate not supplied

The Zero-Boil-Off Tank Experiment: the Effects of Non-Condensable Gases on Pressurization and Pressure Control of Propellant Tanks in Microgravity

Evaporation Condensation↗

DOE OSTI2022

Experimental Investigation of Cavitation-Induced Erosion Using X-Ray Imaging and Tomography

High injection pressure in diesel engines can lead to cavitation-induced erosion in injector nozzles. One important factor affecting the severity of erosion is the fuel and its properties. Traditionally, modeling and simulation studies have used single-component representations of fuels, but realistic fuels feature a multitude of components and can even include volatile additives such as water and alcohol. To provide realistic benchmarks and comparisons, experimental measurements quantifying erosion characteristics were made using ultra-low sulfur diesel (ULSD) and two alternative diesel fuels (ADF). X-ray imaging and computed tomography were used to investigate cavitation-induced erosion onset and progression. Hard X-ray tomography revealed injector internal geometry, including details such as surface marks from the manufacturing process and erosion patterns from repeated injections. Erosion progression was measured using X-ray tomography and imaging performed between injections. The critical erosion site was found to be similar across different fuel blends, while the erosion rate and incubation time were sensitive to the fuel blend. The injector geometry and the erosion characteristics were also prepared for numerical model development and validation.

42 ENGINEERING↗

DOE OSTI2026

Overview of the KSTAR experiments and future plan

The Korea Superconducting Tokamak Advanced Research (KSTAR) device has recently entered a new phase of operation following the installation of a tungsten mono-block divertor, providing a unique platform to investigate high-performance, long-pulse plasma scenarios for future reactors. The 2023–2024 experimental campaigns demonstrated significant progress in commissioning the tungsten divertor, developing plasma operation scenarios, and achieving real-time control. Comparative studies revealed increased core radiation losses and associated performance degradation relative to the carbon divertor environment. Alleviation strategies, such as optimized neutral beam injection timing, boron powder seeding, and impurity control through gas puffing, were shown to reduce tungsten accumulation and extend high-performance phases, including record H-mode operation exceeding 100 s. International collaboration enabled the first demonstration of high poloidal beta scenarios with an internal transport barrier on KSTAR. Advances in control included upgraded real-time resonant magnetic perturbation schemes and disruption forecasting. Furthermore, divertor detachment control using a new surrogate-model-based approach with real-time radiation imaging demonstrated active impurity and heat flux management. Supported by enhanced heating, current drive, and diagnostic systems, these achievements offer valuable insights into tungsten impurity behavior, transport physics, and control strategies for future reactors including ITER. Planned upgrades toward a full-tungsten wall and ITER-aligned real-time plasma control will further establish KSTAR as a leading experimental platform for developing operational scenarios required to achieve steady-state, burning plasma conditions.

KSTAR↗

NASA NTRS2012

On-Line, Real-Time Diagnostics of a Single Fluid Atomization System

A drop tube-Impulse Atomization technique was used to produce copper droplets. In this method, energy is transferred to a liquid by plunger movement resulting in spherical droplets emanating from orifices. A mathematical model of the evolution of droplet velocity and temperature at various heights for different sized droplets was developed. A two-color pyrometer, DPV-2000, and a shadowgraph were used to measure droplets radiant energy, diameter and velocity. The temperature values from the model were used to assess the two color pyrometer assumption over the temperature range of measurement. The DVP 2000 measurements were found to be dependent of droplet size wavelength and position of droplets below the atomizing nozzle. By calibrating the instrument for effective emissivity over the range of measurements, the thermal history of droplets may be recorded using a single color pyrometer approach.

DelshadKhatibi, P.↗

DOE OSTI2022

Exploratory Precipitation Metrics: Spatiotemporal Characteristics, Process-Oriented, and Phenomena-Based

Abstract Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Soft X-ray measurements of transport and MHD activity in the core and edge NSTX plasma (Final Technical Report)

A comprehensive suite of innovative diagnostic instrumentation and techniques has been developed by the Johns Hopkins collaboration for measurements of transport and MHD activity in the core and edge of the National Spherical Torus Experiment (NSTX) at the Princeton Plasma Physics Laboratory (PPPL). These include ultrafast multi-energy poloidal soft X-ray arrays, high spatial resolution multi-energy tangential soft X-ray arrays, high spectral resolution transmission grating imaging VUV spectrometers and ultrafast bolometric arrays, which measure over a broad range of spatial, spectral, and temporal scales the emission from ohmic, RF, and beam driven NSTX plasmas. The instrumentation was designed to fulfill the specific measurement needs of the Spherical Torus (ST) magnetic fusion concept and is accompanied by a comprehensive set of numerical tools for data analysis and modeling, aimed at determining as many as possible plasma parameters and at extracting as much as possible physics information from NSTX experiments. The Johns Hopkins diagnostics have been and continue to be instrumental for essentially all the NSTX experiments. In addition, our own research and experiments using these diagnostics has led over the years to fundamental conclusions for the ST fusion physics, such as the establishment of near neoclassical impurity transport in the NSTX core and edge plasma, and the critical role of the Global Alfven Eigenmode (GAE) MHD activity for the ST core electron thermal transport. The Johns Hopkins Diagnostics continue to be operational on the upgraded NSTX-U and will provide key plasma information in its upcoming high field, current and power experimental campaigns. The present report summarizes the main technical characteristics and measurement capabilities of the diagnostic instrumentation and methods developed within our research and describes a key physics result achieved during this research. Success in our research was made possible also by the excellent support and cooperation of the NSTX research team and of PPPL researchers, who are warmly acknowledged here.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Simulating energetic particle losses in JET plasmas with a reverse integration biasing scheme

We report that an integrated energetic particle transport model has been constructed in JET plasmas constrained by experimental fast ion loss measurements. The model incorporates a synthetic fast ion loss detector identical to JET’s thin-foil Faraday cup fast ion loss detector array. The loss model combines analyses from the TRANSP and ORBIT-kick codes with enhanced features for producing the synthetic diagnostic. Extensions to the ORBIT code framework allow a full-orbit representation within the vacuum region that can map particles directly to an installed detector geometry. Since synthetic fast ion loss detectors are plagued by weak loss statistics, a novel reverse integration biasing scheme has been implemented to boost computational efficiency. The model is validated against experimental loss measurements induced by long-lived kink modes and is found to be in good agreement. This confirms the development of a fully integrated transport/loss model which can be quantitatively verified against experiment allowing for future validation and predictive studies. The model is particularly useful for more complicated plasma scenarios that involve multiple fast ion species such as JET’s 2021 DT-campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗