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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Large energy-spread beam diagnostics through quadrupole scans

The Facility for Advanced Accelerator and Experimental Tests (FACET) is a new user facility at the SLAC National Accelerator Laboratory, servicing next-generation accelerator experiments. The 1.5% RMS energy spread of the FACET beam causes large chromatic aberrations in optics. These aberrations necessitate updated quadrupole scan fits to remain accurate.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Non-Intrusive Measurements Using Femtosecond Laser in Atmospheric Pressure Plasma Jet

Femto-second (fs) lasers offer state-of-the art non-intrusive diagnostic capabilities in plasma flow environments. The diagnostics in plasma flows using a fs-laser that are relevant to this proposal include Two-photon Absorption Laser Induced Fluorescence (TALIF) for measuring the number density of an atomic species, and Femto-second Laser Electronic Excitation Tagging (FLEET) for performing velocity measurements in plasma flows. Various aspects of these diagnostics using fs-lasers are still an active domain of research. The TALIF technique has been used to measure the number density of atomic species in various plasma flow environments like atmospheric pressure plasma jet (APPJ) and arc-jet flows. This technique utilizes a fs-laser to excite an atomic species and the subsequent relaxation process through fluorescence is recorded to make measurements. A narrow band-pass filter is used to isolate the fluorescence signal that is in the infra-red regime. However, broad-band background emissions can potentially pass through the filter and induce noise in the TALIF signal. Particularly, arc-jet plasma flows inherently contain background emissions. In such plasma flow environments, in addition to the filter, the background-subtraction technique will play an important role in reducing the noise that is induced in the number density measurements using TALIF. The proposed research focuses on evaluating the effectiveness of a background-subtraction technique by measuring atomic oxygen using a femtosecond (fs) TALIF in APPJ with induced background emissions and comparing measurements obtained without inducing the emissions. Therefore, by quantifying the changes in the signal-to-noise ratio caused by a background-subtraction technique applied for APPJ, it will enable a better understanding of the uncertainties in the background subtracted fs-TALIF measurements for arc-jet plasma flows. In addition to this, FLEET will be used to obtain velocity in the APPJ, and the impact of background emissions will be analyzed. Under this effort, the experimenters and research personnel will gain the technical know-how in the operational and theoretical aspects of the advanced fs-laser-based diagnostic techniques. The knowledge gained in this process will then also directly be applied to a separate ONR funded project at the Aerodynamics Research Center (ARC), UT Arlington, related to arc-jet flow characterization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2006

Investigation of Tapered Roller Bearing Damage Detection Using Oil Debris Analysis

A diagnostic tool was developed for detecting fatigue damage to tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. This diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests performed by The Timken Company in their Tapered Roller Bearing Health Monitoring Test Rig. Failure progression tests were performed under simulated engine load conditions. Tests were performed on one healthy bearing and three predamaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of debris generated during failure of the bearing. The bearing was removed periodically for inspection throughout the failure progression tests. Results indicate the accumulated oil debris mass is a good predictor of damage on tapered roller bearings. The use of a fuzzy logic model to enable an easily interpreted diagnostic metric was proposed and demonstrated.

Dempsey, Paula J.↗
NASA NTRS2006

Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis

A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.

Dempsey, Paula J.↗
DOE OSTI2016

New compact and efficient local oscillator optic system for the KSTAR electron cyclotron emission imaging system

Electron cyclotron emission imaging (ECEI) diagnostic on Korean Superconducting Tokamak Advanced Research utilizes quasi-optical heterodyne-detection method to measure 2D (vertical and radial) T{sub e} fluctuations from two toroidally separated poloidal cross section of the plasma. A cylindrical lens local oscillator (LO) optics with optical path length (OPL) 2–2.5 m has been used in the current ECEI system to couple the LO source to the 24 vertically aligned array of ECE detectors. For efficient and compact LO optics employing the Powell lens is proposed so that the OPL of the LO source is significantly reduced from ∼2.0 m to 0.4 m with new optics. The coupling efficiency of the LO source is expected to be improved especially at the edge channels. Results from the optical simulation together with the laboratory test of the prototype optics will be discussed in this paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Experimental observation of the geodesic acoustic frequency limit for the NBI-driven Alfvén eigenmodes in TJ-II

We study Alfvén Eigenmodes (AEs) in the TJ-II heliac in hydrogen plasmas heated by hydrogen cofield NBI. Taking advantage of the unique TJ-II flexibility in varying plasma current, we have observed strong variation of the AE frequency from f AE ~ 30 to ~ 220 kHz for selected modes. An advanced heavy ion beam probe diagnostic determines the spatial location and internal amplitudes of the modes. The modes satisfy a local AE dispersion relation including the geodesic acoustic frequency that represents the lowest frequency of the mode. Linear MHD-modeling with STELLGAP and FAR3D codes shows that the calculated temporal evolution of the mode frequency reproduces the observed maxima and minima at the same time intervals with a similar frequency range and the radial profile peaks near the outer edge of the observed one.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Compact in-vacuum gamma-ray spectrometer for high-repetition rate PW-class laser–matter interaction

With the advent of high repetition rate laser facilities, novel diagnostic tools compatible with these advanced specifications are required. This paper presents the design of an active gamma-ray spectrometer intended for these high repetition rate experiments, with particular emphasis on functionality within a PW level laser-plasma interaction chamber’s extreme conditions. The spectrometer uses stacked scintillators to accommodate a broad range of gamma-ray energies, demonstrating its adaptability for various experimental setups. In addition, it has been engineered to maintain compactness, electromagnetic pulse resistance, and ISO-5 cleanliness requirements while ensuring high sensitivity. The spectrometer has been tested in real conditions inside the PW-class level interaction chamber at the BELLA center, LBNL. The paper further details the calibration process, which utilizes a 60 Co radioactive source, and describes the unfolding technique implemented through a stochastic minimization method.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Semantic Interoperability to Enable Smart, Grid-Interactive Efficient Buildings

Achieving a widespread transition to grid-interactive, efficient buildings (GEBs) depends critically on there being sufficient interoperability among connected building systems. While many critical elements already exist at the technical interoperability level (TCP/IP, BACnet, etc.), a lack of interoperability in the semantic level hinders streamlined integration of interdependent applications. Semantics refers to expressing information about “things” in a way that can be consistently understood by applications. Key components of formalized semantics include identifying what a “thing” is (its “type”), defining general information about that “thing” (its characteristics or properties), and defining the appropriate relationships of that “thing” to other “things” (its function or role in a larger system). Although this might seem initially trivial, the success of smart building applications is highly dependent on maintaining consistent self-descriptive notions of the “things”. Without semantic interoperability, it is technically difficult, labor-intensive, and cost-prohibitive to enable three key objectives of GEBs: optimizing performance, automatically identifying and diagnosing faults, and delivering grid services. Industry, academia, and standards bodies have invested effort in developing information models to facilitate semantic interoperability, however, they have not been widely adopted across the U.S. commercial building portfolio. This paper will present a pathway to drive semantic interoperability through a three-pronged approach to be led by the DOE Building Technologies Office in partnership with NIST and multiple national laboratories comprising: 1) industry engagement and coordination across existing efforts; 2) a semantic interoperability standard that empowers building owners to identify and require interoperable attributes when procuring equipment and applications; 3) tools to assist in implementation and a test framework to verify compliance of products with semantic interoperability specifications. This approach is designed to accelerate the timeline for adoption of semantic interoperability specifications. The intent is to reduce soft costs associated with implementing advanced controls, fault detection and diagnostics, and other smart building technologies and use cases as a necessary step in achieving an energy efficient smart grid future.

Bergmann, Harry↗
DOE OSTI2022

Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional Neural Networks

Summary Distributed acoustic sensing (DAS) has been used in the oil and gas industry as an advanced technology for surveillance and diagnostics. Operators use DAS to monitor hydraulic fracturing activities, examine well stimulation efficacy, and estimate complex fracture system geometries. Particularly, low-frequency DAS can detect geomechanical events such as fracture hits because hydraulic fractures propagate and create strain rate variations in the rock. Analysis of DAS data today is mostly done post-job and subject to interpretation methods. However, the continuous and dense data stream generated live by DAS poses the opportunity for more efficient and accurate real-time data-driven analysis. The objective of this study is to develop a machine learning-based workflow that can identify and locate fracture-hit events in simulated strain rate responses correlated with low-frequency DAS data. In this paper, “fracture hit” refers to a hydraulic fracture originating from a stimulated well intersecting an offset well. We start with building a single fracture propagation model to produce strain rate patterns observed at a hypothetical monitoring well. This model is used to generate two sets of strain rate responses with one set containing fracture-hit events. The labeled synthetic data are then used to train a custom convolutional neural network (CNN) model for identifying the presence of fracture-hit events. The same model is trained again for locating the event with the output layer of the model replaced with linear units. We achieved near-perfect predictions for both event classification and localization. These promising results prove the feasibility of using CNN for real-time event detection from fiber-optic sensing data. Additionally, we use edge detection techniques to recognize fracture-hit event patterns in strain rate images. The fracture-hit location can be identified using recognized pixels in the image. The accuracy of edge detection-based location identification is also plausible, but edge detection is dependent on the assumption of pattern shape and image quality, hence it is less robust compared to CNN models. This comparison further supports the need for CNN applications in image-based real-time fiber-optic sensing event detection.

Engineering↗
DOE OSTI2022

Editorial: Particulate Matter Emissions From Conventional and Reformulated Fuel Combustion: Advances in Experiments and Simulations

Particulate matter (PM or soot) emissions generated by combustion of conventional and reformulated fuels adversely impact the environment and human health (Bond et al., 2013; Landrigan et al., 2018; World Health Organization (WHO), 2016), generating public awareness and motivating efforts towards the mitigation of their harmful effects. Soot formation is one of the most complex phenomena in combustion, involving interactions between combustion chemistry, fluid mechanics, mass/heat transport, and particle dynamics, spanning different spatial and temporal scales. A fundamental understanding of soot formation process is thus necessary to achieve a strong reduction of PM emissions and design cleaner and more efficient combustion systems. This has motivated a longstanding and ongoing research activity aimed at improving our understanding of the physical and chemical processes involved in soot formation, well reviewed in these recent works (Wang and Chung, 2019; Michelsen et al., 2020; Martin et al., 2022). Despite the wide interest, the transition from gas-phase molecules to incipient soot particles is still elusive and the successive particle growth and oxidation processes are far from being fully understood, especially in conditions relevant to real-world applications. Recent advances in combustion PM emission diagnostic and computational capabilities helped in improving the predictability of fundamental chemical and aerosol models for practical applications, thus tackling some of the above-mentioned challenges. The aim of this research topic is to display the ongoing research efforts in addressing the existing gaps on particulate formation from various fuel sources and in conditions typical of practical combustion applications (e.g. flames, engines, pool fires), through both experimental and numerical approaches.

42 ENGINEERING↗
DOE OSTI2023

High Speed Data Acquisition for Real Time Feedback in a Light Duty Engine Combustion-Mode Switching Application

The paper describes the integration of a high-speed data acquisition and diagnostics controller used in an advanced engine platform. The controller enables ultra-low emissions and new benchmarks of engine efficiency while running a Gasoline Compression Ignition (GCI) cycle on a 2.2L, 4-cylinder engine. The system enables real-time combustion feedback and vibration analysis in engines. The paper focuses on: (1) the development of an interpolative sampling algorithm for transposition of time acquired data to the crank angle domain using a production crank sensor (60-2 tooth wheel); (2) the control unit, high-speed data acquisition, communication rates between the dedicated data acquisition and base controller to ensure cycle-to-cycle feedback; and, (3) validation exercises using cylinder pressure measurements. Here, the study shows how the algorithm resolves cylinder pressure information over an engine cycle, validating its robustness across acquisition rates of 50 and 200 kHz, with crank angle resolutions of 0.5° and 0.1°. Results show that the 50 kHz, 0.5° hardware yield combustion phasing and torque estimates within 0.1° and 1% torque of those attained with the 200 kHz, 0.1° hardware. Finally, study shows the dedicated controller and communication speeds allow for next-cycle fuel injection correction for speeds above 5000 rpm.

42 ENGINEERING↗
NASA NTRS1993

Ground-based simulation of LEO environment: Investigations of a select LDEF material: FEP Teflon (trademark)

The Long Duration Exposure Facility (LDEF) has produced a wealth of data on materials degradation in the low earth orbit (LEO) space environment and has conclusively shown that surface chemistry (as opposed to surface physics-sputtering) is the key to understanding and predicting the degradation of materials in the LEO environment. It is also clear that materials degradation and spacecraft contamination are closely linked and that the fundamental mechanisms responsible for this linking are in general not well understood especially in the area of synergistic effects. The study of the fundamental mechanisms underlying materials degradation in LEO is hampered by the fact that the degradation process itself is not observed during the actual exposure to the environment. Rather the aftermath of the degradation process is studied, i.e., the material that remains after exposure is observed and mechanisms are proposed to explain the observed results. The EOIM-3 flight experiment is an attempt to bring sophisticated diagnostic equipment into the space environment and monitor the degradation process in real time through the use of mass spectrometry. More experiments of this nature which would include surface sensitive diagnostics (Auger and photoelectron spectroscopes) are needed to truly unravel the basic chemical mechanisms involved in the materials degradation process. Since these in-space capabilities will most likely not be available in the near future, ground-based LEO simulation facilities employing sophisticated diagnostics are needed to further advance the basic understanding of the materials degradation mechanisms. The LEO simulation facility developed at Los Alamos National Laboratory has been used to investigate the atomic oxygen/vacuum ultraviolet (AO/VUV) enhanced degradation of FEP Teflon. The results show that photo-ejection of polymer fragments occur at elevated temperature (200 C), that VUV synergistic rare gas sputtering of polymer fragments occur even at 25 C, and that combined OA/VUV interaction produces a wide variety of gas phase reaction products.

Cross, Jon B.↗
NASA NTRS1999

FDNS CFD Code Benchmark for RBCC Ejector Mode Operation

Computational Fluid Dynamics (CFD) analysis results are compared with benchmark quality test data from the Propulsion Engineering Research Center's (PERC) Rocket Based Combined Cycle (RBCC) experiments to verify fluid dynamic code and application procedures. RBCC engine flowpath development will rely on CFD applications to capture the multi-dimensional fluid dynamic interactions and to quantify their effect on the RBCC system performance. Therefore, the accuracy of these CFD codes must be determined through detailed comparisons with test data. The PERC experiments build upon the well-known 1968 rocket-ejector experiments of Odegaard and Stroup by employing advanced optical and laser based diagnostics to evaluate mixing and secondary combustion. The Finite Difference Navier Stokes (FDNS) code was used to model the fluid dynamics of the PERC RBCC ejector mode configuration. Analyses were performed for both Diffusion and Afterburning (DAB) and Simultaneous Mixing and Combustion (SMC) test conditions. Results from both the 2D and the 3D models are presented.

Holt, James B.↗
NASA NTRS1999

NDE and Advanced Actuators for Space Applications at JPL

Nondestructive Evaluation and Advanced Actuators (NDEAA) are presented. The focus areas are on mechanisms and devices that are driven by acoustic or elastic waves. The topics include: 1) Nondestructive Evaluation; 2) Advanced Actuators; 3) Ultrasonic Medical Diagnostics and Treatment; and 4) Telerobotics.

Bar-Cohen, Yoseph↗
NASA NTRS2000

FDNS CFD Code Benchmark for RBCC Ejector Mode Operation: Continuing Toward Dual Rocket Effects

Computational Fluid Dynamics (CFD) analysis results are compared with benchmark quality test data from the Propulsion Engineering Research Center's (PERC) Rocket Based Combined Cycle (RBCC) experiments to verify fluid dynamic code and application procedures. RBCC engine flowpath development will rely on CFD applications to capture the multi -dimensional fluid dynamic interactions and to quantify their effect on the RBCC system performance. Therefore, the accuracy of these CFD codes must be determined through detailed comparisons with test data. The PERC experiments build upon the well-known 1968 rocket-ejector experiments of Odegaard and Stroup by employing advanced optical and laser based diagnostics to evaluate mixing and secondary combustion. The Finite Difference Navier Stokes (FDNS) code [2] was used to model the fluid dynamics of the PERC RBCC ejector mode configuration. Analyses were performed for the Diffusion and Afterburning (DAB) test conditions at the 200-psia thruster operation point, Results with and without downstream fuel injection are presented.

West, Jeff↗
NASA NTRS2023

An Analysis of Barriers Preventing the Widespread Adoption of Predictive and Prescriptive Maintenance in Aviation

The aviation industry has long recognized the potential benefits of predictive maintenance, a maintenance strategy that leverages sensor and operational data to predict the future degradation of components. Prescriptive maintenance takes this a step further and considers the entire aviation ecosystem to schedule maintenance actions optimally. With the ability to reduce maintenance costs by up to 30%, as reported by the Department of Energy, these maintenance strategies have been identified to be an important investment to reduce a airline costs. However, despite great interest and technological advances in areas such as diagnostics, prognostics, sensing, computation, and machine learning, the adoption of predictive and prescriptive maintenance has not been widely applied in aviation. To shed light on this issue, we conducted an analysis of the barriers preventing or limiting the adoption of predictive and prescriptive maintenance in aviation. Through discussions with subject matter experts across industry, academia, standards bodies, and government, we identified five key challenges: complexity of prediction; validation, safety assurance, and regulatory challenges; cost of adoption; difficulty in quantifying impact and informing decisions; and data availability, quality, and ownership challenges. This study provides a detailed overview of these barriers and areas where stakeholders could invest to overcome them, aiming to support the scaled adoption of predictive and prescriptive maintenance in aviation.

Christopher Teubert↗