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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Miniature Time-of-Flight Mass Spectrometer

Major advances must occur to protect astronauts from prolonged periods in near-zero gravity and high radiation associated with extended space travel. The dangers of living in space must be thoroughly understood and methods developed to reverse those effects that cannot be avoided. Six of the seven research teams established by the National Space Biomedical Research Institute (NSBRI) are studying biomedical factors for prolonged space travel to deliver effective countermeasures. To develop effective countermeasures, each of these teams require identification of and quantitation of complex pharmacological, hormonal, and growth factor compounds (biomarkers) in humans and in experimental animals to develop an in-depth knowledge of the physiological changes associated with space travel. At present, identification of each biomarker requires a separate protocol. Many of these procedures are complicated and the identification of each biomarker requires a separate protocol and associated laboratory equipment. To carry all of this equipment and chemicals on a spacecraft would require a complex clinical laboratory; and it would occupy much of the astronauts time. What is needed is a small, efficient, broadband medical diagnostic instrument to rapidly identify important biomarkers for human space exploration. The Miniature Time-Of- Flight Mass Spectrometer Project in the Technology Development Team is developing a small, high resolution, time-of-flight mass spectrometer (TOFMS) to quantitatively measure biomarkers for human space exploration. Virtues of the JHU/APL TOFMS technologies reside in the promise for a small (less than one cubic ft), lightweight (less than 5 kg), low-power (less than 50 watts), rugged device that can be used continuously with advanced signal processing diagnostics. To date, the JHU/APL program has demonstrated mass capability from under 100 to beyond 10,000 atomic mass units (amu) in a very small, low power prototype for biological analysis. Further, the electronic nature of the TOFMS output makes it ideal for rapid telemetry to earth for in-depth analysis by ground support teams.

Potember, Richard S.↗
DOE OSTI2020

Progress on Understanding Rayleigh–Taylor Flow and Mixing Using Synergy Between Simulation, Modeling, and Experiment

Simultaneous advances in numerical methods and computing, theoretical techniques, and experimental diagnostics have all led independently to better understanding of Rayleigh–Taylor (RT) instability, turbulence, and mixing. In particular, experiments have provided significant motivation for many simulation and modeling studies, as well as validation data. Numerical simulations have also provided data that is not currently measurable or very difficult to measure accurately in RT unstable flows. Thus, simulations have also motivated new measurements in this class of buoyancy-driven flows. This overview discusses simulation and modeling studies synergistic with experiments and examples of how experiments have motivated simulations and models of RT instability, flow, and mixing. First, a brief summary of measured experimental and calculated simulation quantities, of experimental approaches, and of issues and challenges in the simulation and modeling of RT experiments is presented. Implicit large-eddy, direct numerical, and large-eddy simulations validated using RT experimental data are then discussed. This is followed by a discussion of modeling using analytical, modal, buoyancy–drag, and turbulent transport models of RT mixing experiments. The discussion will focus on three-dimensional RT mixing arising from multimode perturbations. Finally, this focused review concludes with a perspective on future simulation, modeling, and experimental directions for further research. Research in simulation and modeling of RT unstable flows, coupled with experiments, has made significant progress over the past several decades. This overview serves as an opportunity to both discuss progress and to stimulate future research on simulation and modeling of this unique class of hydrodynamically unstable turbulent flows.

42 ENGINEERING↗
DOE OSTI2023

Data-Driven Approaches for Bead Geometry Prediction Via Melt Pool Monitoring

In the realm of additive manufacturing, the selection of process parameters to avoid over and under deposition entails a time-consuming and resource-intensive trial-and-error approach. Given the distinct characteristics of each part geometry, there is a pressing need for advancing real-time process monitoring and control to ensure consistent and reliable part dimensional accuracy. Here, this research shows that support vector regression (SVR) and convolutional neural network (CNN) models offer a promising solution for real-time process control due to the models’ abilities to recognize complex, non-linear patterns with high accuracy. A novel experiment was designed to compare the performance of SVR and CNN models to indirectly detect bead height from a coaxial image of a melt pool from a single-layer, single bead build. The study showed that both SVR and CNN models trained on melt pool data collected from a coaxial optical camera can accurately predict the bead height with a mean absolute percentage error of 3.67% and 3.68%, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimizing transmit field inhomogeneity of parallel RF transmit design in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) provides a higher signal-to-noise ratio and, thereby, higher spatial resolution. However, UHF MRI introduces challenges such as transmit radiofrequency (RF) field (B+1) inhomogeneities, leading to uneven flip angles and image intensity anomalies. These issues can significantly degrade imaging quality and its medical applications. This study addresses B+1 field homogeneity through a novel deep learning-based strategy. Traditional methods like Magnitude Least Squares (MLS) optimization have been effective but are time-consuming and dependent on the patient’s presence. Recent machine learning approaches, such as RF Shim Prediction by Iteratively Projected Ridge Regression and deep learning frameworks, have shown promise but face limitations like extensive training times and oversimplified architectures. We propose a two-step deep learning strategy. First, we obtain the desired reference RF shimming weights from multi-channel B+1 fields using random-initialized Adaptive Moment Estimation. Then, we employ Residual Networks (ResNets) to train a model that maps B+1 fields to target RF shimming outputs. Our approach does not rely on pre-calculated reference optimizations for the testing process and efficiently learns residual functions. Comparative studies with traditional MLS optimization demonstrate our method’s advantages in terms of speed and accuracy. The proposed strategy achieves a faster and more efficient RF shimming design, significantly improving imaging quality at UHF. This advancement holds potential for broader applications in medical imaging and diagnostics.

Lu, Zhengyi [Vanderbilt University]↗
DOE OSTI2025

Thermonuclear Fusion Verification of Staged Z-Pinch Fusion on a 0.5 MA LTD Pulsed Power Generator (Final Report)

LLNL fielded neutron detectors at UCSD’s CESZAR facility during the experimental campaigns investigating the staged Z-pinch concept. This concept uses high current to compress a cylindrical plasma composed a high atomic number gas, such as argon, surrounding fusion fuel. LLNL analyzed data from the diagnostics and improved the diagnostic setup specific to the experiment. This work helps to advance the mission creating a fusion energy source, which is a benefit to the economy and for energy security.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Incorporating the latest Neutron NDA analysis techniques into INCC6

International Neutron Coincidence Counting (INCC6) is the IAEA’s neutron NDA software. With FY25 SGTech support we implemented self-diagnostic features into INCC6. For FY26 we propose to implement advanced analysis methods that have been splintered into custom software for one-off instruments. Incorporating these capabilities in INCC6 will make them available for any new or existing application on the ubiquitous INCC6 platform, increasing safeguards efficiency and effectiveness.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1986

A flight expert system (FLES) for on-board fault monitoring and diagnosis

The increasing complexity of modern aircraft creates a need for a larger number of caution and warning devices. But more alerts require more memorization and higher work loads for the pilot and tend to induce a higher probability of errors. Therefore, an architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing and recovering from in-flight faults has been developed. A prototype of FLES has been implemented. A sensor simulation model was developed and employed to provide FLES with the airplane status information during the diagnostic process. The simulator is based partly on the Lockheed Advanced Concept System (ACS), a future generation airplane, and partly on the Boeing 737, an existing airplane. A distinction between two types of faults, maladjustments and malfunctions, has led us to take two approaches to fault diagnosis. These approaches are evident in two FLES subsystems: the flight phase monitor and the sensor interrupt handler. The specific problem addressed in these subsystems has been that of integrating information received from multiple sensors with domain knowledge in order to assess abnormal situations during airplane flight. This paper describes the reasons for handling malfunctions and maladjustments separately and the use of domain knowledge in the diagnosis of each.

Ali, M.↗
NASA NTRS1994

CRI planning and scheduling for space

Computer Resources International (CRI) has many years of experience in developing space planning and scheduling systems for the European Space Agency. Activities range from AIT/AIV planning over mission planning to research in on-board autonomy using advanced planning and scheduling technologies in conjunction with model based diagnostics. This article presents four projects carried out for ESA by CRI with various subcontractors: (1) DI, Distributed Intelligence for Ground/Space Systems is an on-going research project; (2) GMPT, Generic Mission Planning Toolset, a feasibility study concluded in 1993; (3) OPTIMUM-AIV, Open Planning Tool for AIV, development of a knowledge based AIV planning and scheduling tool ended in 1992; and (4) PlanERS-1, development of an AI and knowledge-based mission planning prototype for the ERS-1 earth observation spacecraft ended in 1991.

Aarup, Mads↗
NASA NTRS1998

JANNAF 35th Combustion Subcommittee and 17th Propulsion Systems Hazards Subcommittee Meeting: Joint Sessions

This publication is a compilation of 15 unclassified/unlimited technical papers presented at the 1998 meeting of the Joint Army-Navy-NASA-Air Force (JANNAF) Combustion Subcommittee (CS) and Propulsion Systems Hazards Subcommittee (PSHS) held jointly with the Airbreathing Propulsion Subcommittee (APS). The meeting was held on 7 - 11 December 1 998 at Raytheon Systems Company and the Marriott Hotel, Tucson, AZ. Topics covered include advanced ingredients and reaction kinetics in solid propellants and experimental diagnostic techniques.

Fry, Ronald S.↗
NASA NTRS2004

3D MHD Models of Active Region Loops

Present imaging and spectroscopic observations of active region loops allow to determine many physical parameters of the coronal loops, such as the density, temperature, velocity of flows in loops, and the magnetic field. However, due to projection effects many of these parameters remain ambiguous. Three dimensional imaging in EUV by the STEREO spacecraft will help to resolve the projection ambiguities, and the observations could be used to setup 3D MHD models of active region loops to study the dynamics and stability of active regions. Here the results of 3D MHD models of active region loops are presented, and the progress towards more realistic 3D MHD models of active regions. In particular the effects of impulsive events on the excitation of active region loop oscillations, and the generation, propagations and reflection of EIT waves are shown. It is shown how 3D MHD models together with 3D EUV observations can be used as a diagnostic tool for active region loop physical parameters, and to advance the science of the sources of solar coronal activity.

Ofman, Leon↗
NASA NTRS2005

Real-Time Aerodynamic Flow and Data Visualization in an Interactive Virtual Environment

Significant advances have been made to non-intrusive flow field diagnostics in the past decade. Camera based techniques are now capable of determining physical qualities such as surface deformation, surface pressure and temperature, flow velocities, and molecular species concentration. In each case, extracting the pertinent information from the large volume of acquired data requires powerful and efficient data visualization tools. The additional requirement for real time visualization is fueled by an increased emphasis on minimizing test time in expensive facilities. This paper will address a capability titled LiveView3D, which is the first step in the development phase of an in depth, real time data visualization and analysis tool for use in aerospace testing facilities.

Schwartz, Richard J.↗
NASA NTRS2011

Advanced Electrocardiography Can Identify Occult Cardiomyopathy in Doberman Pinschers

Recently, multiple advanced resting electrocardiographic (A-ECG) techniques have improved the diagnostic value of short-duration ECG in detection of dilated cardiomyopathy (DCM) in humans. This study investigated whether 12-lead A-ECG recordings could accurately identify the occult phase of DCM in dogs. Short-duration (3-5 min) high-fidelity 12-lead ECG recordings were obtained from 31 privately-owned, clinically healthy Doberman Pinschers (5.4 +/- 1.7 years, 11/20 males/females). Dogs were divided into 2 groups: 1) 19 healthy dogs with normal echocardiographic M-mode measurements: left ventricular internal diameter in diastole (LVIDd . 47mm) and in systole (LVIDs . 38mm) and normal 24-hour ECG recordings (<50 ventricular premature complexes, VPCs); and 2) 12 dogs with occult DCM: 11/12 dogs had increased M-mode measurements (LVIDd . 49mm and/or LVIDs . 40mm) and 5/11 dogs had also >100 VPCs/24h; 1/12 dogs had only abnormal 24-hour ECG recordings (>100 VPCs/24h). ECG recordings were evaluated via custom software programs to calculate multiple parameters of high-frequency (HF) QRS ECG, heart rate variability, QT variability, waveform complexity and 3-D ECG. Student's t-tests determined 19 ECG parameters that were significantly different (P < 0.05) between groups. Principal component factor analysis identified a 5-factor model with 81.4% explained variance. QRS dipolar and non-dipolar voltages, Cornell voltage criteria and QRS waveform residuum were increased significantly (P < 0.05), whereas mean HF QRS amplitude was decreased significantly (P < 0.05) in dogs with occult DCM. For the 5 selected parameters the prediction of occult DCM was performed using a binary logistic regression model with Chi-square tested significance (P < 0.01). ROC analyses showed that the five selected ECG parameters could identify occult ECG with sensitivity 89% and specificity 83%. Results suggest that 12-lead A-ECG might improve diagnostic value of short-duration ECG in earlier detection of canine DCM as five selected ECG parameters can with reasonable accuracy identify occult DCM in Doberman Pinschers. Future extensive clinical studies need to clarify if 12-lead A-ECG could be useful as an additional screening test for canine DCM.

Spiljak, M.↗
DOE OSTI2025

Single-shot spatiotemporal plasma density measurements with a chirped probe pulse

In this work, we present the development and demonstration of a diagnostic for the measurement of the spatial and temporal evolution of plasma density in a single shot. Single-shot Advanced Plasma Probe HolographIc REconstruction (SAPPHIRE) utilizes a chirped probe pulse, a diffractive optical element, a self-referenced interferometer, and an interference bandpass filter to achieve high-fidelity electron density measurements suitable for underdense plasmas that exhibit cylindrical symmetry. The method overcomes limitations in conventional diagnostics, such as reliance on shot-to-shot reproducibility, while capturing plasma dynamics on picosecond timescales with micron-level spatial resolution. The capabilities of SAPPHIRE are demonstrated through measurements of laser-driven plasma channels in helium–nitrogen gas jets. SAPPHIRE demonstrates the formation and expansion of plasma channels in a single shot and the propagation of supersonic ionization fronts while revealing shot-to-shot variations in the plasma profiles. Experimental results are validated against theoretical models and scaling laws, underscoring the robustness and accuracy of this technique. By enabling ultrafast, high-resolution plasma diagnostics in a single exposure, SAPPHIRE represents a transformative advancement in plasma measurement technology.

Grace, Elizabeth S. [Lawrence Livermore National L↗
DOE OSTI2023

Machine learning in analytical spectroscopy for nuclear diagnostics [Invited]

Analytical spectroscopy methods have shown many possible uses for nuclear material diagnostics and measurements in recent studies. In particular, the application potential for various atomic spectroscopy techniques is uniquely diverse and generates interest across a wide range of nuclear science areas. Over the last decade, techniques such as laser-induced breakdown spectroscopy, Raman spectroscopy, and x-ray fluorescence spectroscopy have yielded considerable improvements in the diagnostic analysis of nuclear materials, especially with machine learning implementations. These techniques have been applied for analytical solutions to problems concerning nuclear forensics, nuclear fuel manufacturing, nuclear fuel quality control, and general diagnostic analysis of nuclear materials. The data yielded from atomic spectroscopy methods provide innovative solutions to problems surrounding the characterization of nuclear materials, particularly for compounds with complex chemistry. Implementing these optical spectroscopy techniques can provide comprehensive new insights into the chemical analysis of nuclear materials. In particular, recent advances coupling machine learning methods to the processing of atomic emission spectra have yielded novel, robust solutions for nuclear material characterization. This review paper will provide a summation of several of these recent advances and will discuss key experimental studies that have advanced the use of analytical atomic spectroscopy techniques as active tools for nuclear diagnostic measurements.

Rao, Ashwin P. (ORCID:0000000319312568)↗
DOE OSTI2025

An Integrated High-Speed Microstructural Characterization Method Using Simultaneous XRD, Stereo-DIC, and PCI

High-speed characterization of the deformation mechanisms in polycrystalline metals requires the quantification of full strain fields and local microstructural evolutions simultaneously. In this paper, we present a novel experimental method to integrate phase-contrast imaging (PCI), stereographic digital image correlation (stereo-DIC), and full-ring X-ray diffraction (XRD) to allow for the simultaneous characterization of polycrystalline metals at 1MHz or higher. A Kolsky bar was integrated into the synchrotron X-ray source in Sector 32 ID-B at the Advance Photon Source (APS) at Argonne National Laboratory. When the sample is dynamically loaded, the diagnostic methods of full-ring XRD, PCI, and stereo-DIC are properly synchronized to record the deformation behavior at both continuum and microstructural scales as a function of the loading history. An advanced high-strength steel (AHSS) is used as a model material to demonstrate the capabilities of this new experimental method.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Cost Benefit Analyses through Integrated Online Monitoring and Diagnostics (Final Report)

The objective of this research is to improve the economic competitiveness of advanced reactors through the optimization of cost and plant performance, which can be achieved by coupling intelligent online monitoring with asset management decision-making. As advanced reactors are early in the development life-cycle, online monitoring systems and associated sensor networks can be incorporated directly into the design without constraints related to retrofitting and system upgrades

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2010

Physics of Solar Prominences: I-Spectral Diagnostics and Non-LTE Modelling

This review paper outlines background information and covers recent advances made via the analysis of spectra and images of prominence plasma and the increased sophistication of non-LTE (i.e. when there is a departure from Local Thermodynamic Equilibrium) radiative transfer models. We first describe the spectral inversion techniques that have been used to infer the plasma parameters important for the general properties of the prominence plasma in both its cool core and the hotter prominence-corona transition region. We also review studies devoted to the observation of bulk motions of the prominence plasma and to the determination of prominence mass. However, a simple inversion of spectroscopic data usually fails when the lines become optically thick at certain wavelengths. Therefore, complex

Labrosse, N.↗