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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Fast-RF-Shimming: Accelerate RF shimming in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical diagnostics and advanced research. However, the jump to higher fields introduces complications, particularly transmit radiofrequency (RF) field ($B^{+}_{1}$) inhomogeneities, manifesting as uneven flip angles and image intensity irregularities. These artifacts can degrade image quality and impede broader clinical adoption. Traditional RF shimming methods, such as Magnitude Least Squares (MLS) optimization, effectively mitigate $B^{+}_{1}$ inhomogeneity, but remain time-consuming. Recent machine learning approaches, including RF Shim Prediction by Iteratively Projected Ridge Regression and other deep learning architectures, suggest alternative pathways. Although these approaches show promise, challenges such as extensive training periods, limited network complexity, and practical data requirements persist. In this paper, we introduce a holistic learning-based framework called Fast-RF-Shimming, which achieves a 5000 ​× ​speed-up compared to the traditional MLS method. In the initial phase, we employ random-initialized Adaptive Moment Estimation (Adam) to derive the desired reference shimming weights from multi-channel $B^{+}_{1}$ fields. Next, we train a Residual Network (ResNet) to map $B^{+}_{1}$ fields directly to the ultimate RF shimming outputs, incorporating the confidence parameter into its loss function. Finally, we design Non-uniformity Field Detector (NFD), an optional post-processing step, to ensure the extreme non-uniform outcomes are identified. Comparative evaluations with standard MLS optimization underscore notable gains in both processing speed and predictive accuracy, which indicates that our technique shows a promising solution for addressing persistent inhomogeneity challenges.

Deep learning↗
DOE OSTI2020

Exploring cycling induced crystallographic change in NMC with X-ray diffraction computed tomography

This study presents the application of X-ray diffraction computed tomography for the first time to analyze the crystal dimensions of LiNi 0.33 Mn 0.33 Co 0.33 O 2 electrodes cycled to 4.2 and 4.7 V in full cells with graphite as negative electrodes at 1 μm spatial resolution to determine the change in unit cell dimensions as a result of electrochemical cycling. The nature of the technique permits the spatial localization of the diffraction information in 3D and mapping of heterogeneities from the electrode to the particle level. An overall decrease of 0.4% and 0.6% was observed for the unit cell volume after 100 cycles for the electrodes cycled to 4.2 and 4.7 V. Additionally, focused ion beam-scanning electron microscope cross-sections indicate extensive particle cracking as a function of upper cut-off voltage, further confirming that severe cycling stresses exacerbate degradation. Finally, the technique facilitates the detection of parts of the electrode that have inhomogeneous lattice parameters that deviate from the bulk of the sample, further highlighting the effectiveness of the technique as a diagnostic tool, bridging the gap between crystal structure and electrochemical performance.

25 ENERGY STORAGE↗
NASA NTRS1978

Fuel consumption improvement in current transport engines

A review is conducted of improvements which can be made with respect to the fuel consumption of current engines and new production versions of current engines. A description is presented of an engine diagnostics program which has the objective to identify and quantify the causes and sources of performance deterioration in the JT9D turbofan engine and to develop basic data which will be applied to minimize performance degradation of current and future engines. General areas where performance losses occur are examined, taking into account seals, blades and vanes, and cases. Potential performance improvement concepts are related to improved component aerodynamics, improved flowpath sealing, blade tip clearance control, improved turbine cooling effectiveness, improved turbine materials and coatings, duct and nozzle aerodynamic refinements, nacelle aerodynamic refinements, forced exhaust mixers, advanced nacelle materials, and advanced fuel control.

Hines, R. W.↗
DOE OSTI2024

Final Technical Report - Rapid Surface Microanalysis using a Low Temperature Plasma

This project focused on improving our current understanding and scientific knowledge in the area of plasma-surface interactions and plasma assisted material synthesis related to advanced microelectronics and nanotechnology. Current challenges include: controlling the interaction of Low Temperature Plasma (LTP) with a single layer of atoms to manufacture integrated circuits, continued miniaturization of integrated circuits, LTP processing of material surfaces and thin films to enable industrial scale fabrication of advanced microelectronics, synthesis of new materials, nanomaterials, nanotubes, and complex materials, Technology developed in this subtopic is of value to either (i) enable scans of surfaces (~1 sq. cm area) using various microscopies (electron, optical, other) at high resolution (micron or sub-micron resolution) rapidly (hours or days rather than years to complete a high-resolution scan of such a large surface area), or (ii) enable scans of surfaces (~1 sq. cm area) using various microscopies (electron, optical, other) at relatively low resolution rapidly, then apply algorithms to select spots for micron-scale imaging. Sputtering occurs when particles of a solid material are ejected from its surface by energetic particles from a plasma. While the degradation of the solid material and the subsequent deposition of the ejected material onto vulnerable surfaces are the usual subjects of sputtering studies, plasma science has yet to be combined with sputtering to create new diagnostics devices and systems. Small changes in the design of the plasma discharge device make it possible to create broad plasma beams for rapid scanning or small plasma beams to obtain the distribution of ejected elements with micron resolution. In the high-resolution use, the ion flux is extracted from the gas-discharge plasma and focused by a spherical emission surface to micron sizes onto the target specimen, providing very local sputtering and local elemental analysis. We call this “self-focusing”. The radiation from the excited and ionized sputtered atoms is recorded by a spectrometer through a window and fiberglass cable and analyzed with standard software packages used for optical glow discharge spectroscopy. Computer simulations of beam formation were used to verify and optimize the designs to be tested. A prototype was designed, constructed, and used to start experiments of beam formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1977

Flare heating by energetic nonthermal electrons

A model has been developed which includes, in a self-consistent fashion, the energy degradation and attendant bremsstrahlung emission of a high-energy electron beam, heating of a flare plasma by the beam, and subsequent cooling by thermal conduction and radiation. To assist in the interpretation of experimental diagnostics, the model also characterizes the radiative behavior of iron ions present in the flare plasma. Electron deposition is described by the Fokker-Planck equation for an initial power-law particle distribution. Results are presented for the bremsstrahlung radiation emitted by the incident beam as it impinges on the disturbed atmosphere. A comparison is made between direct beam heating and thermal-conduction heating of the flare plasma. The radiation emitted by several selected spectral lines of Fe ions is determined as a function of time during and after deposition

Davis, J.↗
NASA NTRS2014

End-of-Test Performance and Wear Characterization of NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test

The NASA's Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to quantify the thruster propellant throughput capability. Testing was recently completed in February 2014, with the thruster accumulating 51,184 hours of operation, processing 918 kg of xenon propellant, and delivering 35.5 MN-s of total impulse.As part of the test termination procedure, a comprehensive performance characterization was performed across the entire NEXT throttle table. This was performed prior to planned repairs of numerous diagnostics that had become inoperable over the course of the test. After completion of these diagnostic repairs in November 2013, a comprehensive end-of-test performance and wear characterization was performed on the test article prior to exposure to atmosphere. These data have confirmed steady thruster performance with minimal degradation as well as mitigation of numerous life limiting mechanisms encountered in the NSTAR design. Component erosion rates compare favorably to pretest predictions based on semi-empirical models used for the thruster service life assessment. Additional data relating to ion beam density profiles, facility backsputter rates, facility backpressure effects on thruster telemetry, and modulation of the neutralizer keeper current are presented as part of the end-of-test characterization. Presently the test article for the NEXT LDT has been exposed to atmosphere and placed within a clean room environment, with post-test disassembly and inspection underway.

wear tests↗
NASA NTRS1989

Reusable rocket engine turbopump health monitoring system, part 3

Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms.

Perry, John G.↗
NASA NTRS2023

Automated Fluidics Device for Extraction and Quantification of miRNA Biomarkers From Blood

Radiation Assessment DuRing Exposure And long-Duration Spaceflight (RADREADS) demonstrates space-compatible point-of-care technology for quantitative biological monitoring of blood miRNA biomarkers in response to long-term low dose radiation exposure. This individualized monitoring approach will inform targeted treatment strategies to maximize medical resource utilization by accounting for individual susceptibility to radiation-related illnesses. As human spaceflight progresses beyond Earth’s magnetic shielding, radiation exposure poses a significant risk to astronaut health and safety. Extended operation in this environment comes with an increased risk of radiation exposure, leading to higher risks of radiation sickness, cancer, central nervous system effects, and degenerative diseases. While conventional physical dosimetry techniques capture radiation dose, individualistic susceptibility to radiation damage is varied. Multiple characteristics, including age, body weight, sex, genetics, and immune status, have been found to influence radiosensitivity (Liu et al. 2011, and Bouffler 2016). This differential response necessitates individualized monitoring and targeted treatment strategies to maximize medical resource utilization; however, a practical diagnostic platform for quantifying long-term, low dose radiation-induced tissue damage does not currently exist. MicroRNAs (miRNAs) are a class of small, non-coding RNAs that regulate gene expression by mediating the degradation of messenger RNA. The levels of particular miRNAs are influenced by biological processes such as inflammation and serve as biomarkers for a variety of conditions including cancer (Singh et al. 2017). MicroRNAs are found in various bodily fluids and are amenable to collection via liquid biopsies, providing a minimally invasive and easily quantifiable readout for a variety of radiosensitive reporters. A preliminary signature of 15 spaceflight sensitive miRNA has been identified in rodent and human studies, including miR-21-5p, miR-24-3p, miR-92a-3p, miR-17-5p, miR-16a-3p, miR-34a-3p, and miR-223-3p. These targets generally increased expression with radiation dose and linear energy transfer, though variation between individuals is not yet described. Current gaps in the field include a lack of understanding of longitudinal biological responses to long-term, low dose radiation exposure and the absence of space-compatible point-of-care technology for quantitative biological monitoring. In this body of work, we aim to develop an automated bleed-to-read system to process whole blood for the detection of miRNA biomarkers in order to monitor individualistic responses to radiation exposure. This will be achieved via separating serum (or plasma) from whole blood, followed by extraction, amplification, and quantification of the miRNA using a RT-qPCR reaction. Previously, the WetLab-2 hardware enabled execution of a RT-qPCR reaction aboard ISS; however, it is a manual system that requires crew manipulation and bulky components (Parra et al. 2017). To address these issues, automated fluid handling hardware was developed for each stage of sample preparation. Extraction of total RNA is achieved by sequentially pumping reagents through an off-the-shelf nucleic acid binding column (miRNeasy Serum/Plasma Advanced Kit, Qiagen). This approach eliminates several manual pipetting and centrifuging steps and limits the use of toxic chemicals commonly found in other sample processing techniques. The resulting elution will then be automatically dispensed for RT-qPCR analysis using a compact rotary qPCR (Mic qPCR Cycler, Bio Molecular Systems) that will improve spaceflight compatibility by removing bubbles from the detection region, another challenge highlighted by WetLab-2 (Parra et al. 2017). Efforts are also being made to simplify the RT-qPCR reaction to a 1-step air-dryable mix to improve long-term reagent stability at room temperature and reduce system complexity. By automating the RT-qPCR processes via microfluidic manipulation, RADREADS will reduce crewmember hands-on time and enable the personalized detection of radiation-induced tissue damage during long duration missions. Minimally invasive, longitudinal monitoring of individual’s response to radiation exposure will inform how the physiological system responds to long-term low dose space radiation and enables development of targeted countermeasures by the medical team. Ultimately, this portable technology will require minimal technical expertise and can also be used to monitor miRNA biomarkers associated with other diseases.

Tristen Head↗
DOE OSTI2024

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, and robustness. Inspired by the concept of Edge Artificial Intelligence (Edge AI), we propose a robust approach that enables fast FLI with no degradation of accuracy. This approach couples a recurrent neural network (RNN), which is trained to estimate the fluorescence lifetime directly from raw timestamps without building histograms, to SPAD TCSPC systems, thereby drastically reducing transfer data volumes and hardware resource utilization, and enabling real-time FLI acquisition. We train two variants of the RNN on a synthetic dataset and compare the results to those obtained using center-of-mass method (CMM) and least squares fitting (LS fitting). Results demonstrate that two RNN variants, gated recurrent unit (GRU) and long short-term memory (LSTM), are comparable to CMM and LS fitting in terms of accuracy, while outperforming them in the presence of background noise by a large margin. To explore the ultimate limits of the approach, we derive the Cramer-Rao lower bound of the measurement, showing that RNN yields lifetime estimations with near-optimal precision. To demonstrate real-time operation, we build a FLI microscope based on an existing SPAD TCSPC system comprising a 32 x 32 SPAD sensor named Piccolo. Four quantized GRU cores, capable of processing up to 4 million photons per second, are deployed on the Xilinx Kintex-7 FPGA that controls the Piccolo. Powered by the GRU, the FLI setup can retrieve real-time fluorescence lifetime images at up to 10 frames per second. The proposed FLI system is promising and ideally suited for biomedical applications, including biological imaging, biomedical diagnostics, and fluorescence-assisted surgery, etc.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Optically Excited Lasing in a Cavity‐Based, High‐Current‐Density Quantum Dot Electroluminescent Device

Abstract Laser diodes based on solution‐processable materials can benefit numerous technologies including integrated electronics and photonics, telecommunications, and medical diagnostics. An attractive system for implementing these devices is colloidal semiconductor quantum dots (QDs). The progress towards a QD laser diode has been hampered by rapid nonradiative Auger decay of optical‐gain‐active multicarrier states, fast device degradation at high current densities required for laser action, and unfavorable competition between optical gain and optical losses in a multicomponent device stack. Here we resolve some of these challenges and demonstrate optically excited lasing from fully functional high‐current density electroluminescent (EL) devices with an integrated optical resonator. This advance has become possible due to excellent optical gain properties of continuously graded QDs and a refined device architecture, which allows for highly efficient light amplification in a thin, EL‐active QD layer.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Magellan - Initial analysis of Venus surface modification

Images of the Venus surface provided by the Magellan mission make it possible to see the fine-scale features diagnostic of weathering, erosion, and deposition. These include ejecta deposits extending up to 1000 km to the west of several impact craters, windblown deposits, features containing both obstacles and a source of particulate material, and evidence for degradation by atmosphere-surface interactions and mass movements. Initial Magellan observations pertaining to the nature, rate, and history of surficial processes are analyzed. Emphasis is placed on radar imaging, but results from radiometry and altimetry observations are also discussed.

Arvidson, R. E.↗
DOE OSTI2026

Advancing Battery Manufacturing: Synchrotron Characterization for Industry

Large-scale battery manufacturing requires understanding the fundamental principles of materials and interfaces and relies on advanced techniques for detailed interrogation. Despite advancements in the industrial scale production and their associated quality control tools, challenges such as electrode heterogeneity, internal defects, and largescale material waste (e.g., scrap) can hamper manufacturing. Synchrotron X-ray characterization techniques offer spatial, temporal, and chemical resolution that can provide diagnostic insights for metrology across various manufacturing steps. This review examines the use of synchrotron tools to advance understanding of key steps in the battery manufacturing process. Recent examples demonstrate how synchrotron methods resolve manufacturing challenges and uncover degradation pathways that are otherwise inaccessible. Future directions for advancing battery manufacturing emphasize collaboration between academia and industry through the use of synchrotron X-ray techniques.

Batteries↗
DOE OSTI2025

Impacts of PV Module Connector Failures on Cost and Performance of Utility Scale Photovoltaic Systems

The reliability, cost and performance of electrical connectors are a concern in all types of electrical systems, and demands on connectors used on photovoltaic (PV) systems include that connectors maintain electrical conductivity and physical strength, endure ultraviolet sunlight and high ambient temperature, and resist moisture and chemical intrusion over a very long (>25 year) performance period. Connector failures increase operation and maintenance (O&M) costs and reduce plant production, but connector failure can also cause safety and liability problems, which are of greater concern. This work results from a three-year collaboration between Sandia National Laboratories (SNL), the Electric Power Research Institute (EPRI), and the National Renewable Energy Laboratory (NREL) and funded by the U.S. Department of Energy (DOE) Solar Energy Technology Office (SETO) under Agreements #39035 and #38531 "Connector Reliability Across the US Solar Sector." a multi-pronged investigation of PV connector health across the US (see https://energy.sandia.gov/pvconnectors/). This report presents derivation of a Techno-Economic Analysis (TEA) that models failure modes and frequencies (how often failure occurs), estimates O&M costs and lost production associated with connector failures, and then calculates the effect that PV module connectors can have on Levelized Cost of Energy (LCOE). The model is informed with initial data from quantitative assessment of failure rates, root causes and mechanisms, in-situ diagnostics and data collection, lab-based forensics, and interviews with PV connector manufacturers and plant operators. SNL conducted site inspections at multiple utility-scale sites in different climates and subjected field samples of new, used, and degraded connectors to visual and electrical characterization. EPRI conducted metallurgical analysis of the pin and sleeve conductors to study failure-induced morphological and compositional changes. There is in general a shortage of statistically valid data, but data from PVROM database maintained by SNL was sufficient to ascertain failure rates and lost production as well as provide qualitative insight in its curated maintenance records. This report details the structure of the mathematical model but the sources of data to inform the model will continue to evolve. Analysis of a 100 MW PV plant is provided as an example of the use of the model, with results indicating that connectors are responsible for Annualized O&M Costs of $\$$71,933/year; Annualized Unit O&M Costs of $\$$0.72/kW/year; that a Reserve Account of $\$$187,220 should be available to fund repairs related to connectors; that connectors add $\$$1,494,004 to the Net Present Value of the O&M Costs (project life); and that O&M related to connectors adds about $\$$0.00088/kWh to the Levelized Cost of Energy. The impact of this model is to provide a tool to make the US solar sector more robust by quantifying and monetizing the reliability risks to utility-scale PV systems posed by poorly installed, mismatched and/or poorly designed and manufactured connectors. The TEA provides a model incorporating failure statistics, O&M cost data, and lost production into a single figure of merit, informing decisions and enabling practitioners to optimize cost and performance trade-offs. Stakeholders include connector manufacturers, system designers and equipment specifiers, standards bodies, installers and O&M providers, investors and insurance underwriters. This report supports continued growth of PV predicated on assurances that properly installed and maintained PV system connectors are safe and reliable. The project team is proposing future work including accelerated testing of connectors and expanding the approach taken here to other PV system components, such as TEA for rapid shut-down devices.

14 SOLAR ENERGY↗
DOE OSTI2025

Interface diagnostics platform for thin-film solid-state batteries

Understanding the impedances of battery materials and their interfaces remains a major challenge, usually addressed by electrochemical impedance spectroscopy (EIS) where frequency-dependent complex impedance of full battery cells is measured and then modeled by a network of connected electrical elements. As conventionally applied, this approach produces ambiguity in that (1) multiple different network configurations may fit the data convincingly and (2) the method offers no direct association of the electrical elements with physical features of the battery. Here we present a new methodology that resolves both sources of ambiguity, enabled by expanding the experimental scope to directly inform the configuration of elements and their parameters in the network model. We demonstrate this methodology using thin film fabrication of solid state battery devices patterned by shadow masked sputter deposition, so that diagnostic devices corresponding to individual interface and material components can be fabricated simultaneously with full cell batteries. EIS models for the diagnostic devices can then be connected to form full cell networks whose topology matches the well-known physical configuration of the battery. When connected in this way, the full network model – made from connecting the diagnostic device EIS models – fits the full cell EIS data. For the case of a thin film solid state battery composed of amorphous silicon anode, lithium phosphorus oxynitride (LiPON) solid electrolyte, and lithium vanadium oxide (Li x V 2 O 5 ) cathode, we show that the approach allows us to identify ionic impedance/conductivity of the cathode/electrolyte as a limiting impedance and the anode/electrolyte interface cycling instability as a primary degradation factor.

25 ENERGY STORAGE↗
DOE OSTI2023

Battery state-of-health diagnostics during fast cycling using physics-informed deep-learning

Rapid, in-situ Li-ion battery state-of-health (SOH) quantification is challenging. Li-ion battery aging can vary significantly with chemistry, operating conditions, cycling demands, electrode design, and operation history. As a cell ages, optimal and safe operating conditions need to be adapted to account for battery degradation by tracking critical aging modes such as loss-of-lithium-inventory (LLI), loss-of-active-material (LAM) in either electrode, and/or impedance rise. This manuscript describes a framework for identifying battery aging modes in-operando using fast-rate voltage charge/discharge responses. The framework uses a physically based Li-ion battery model to produce synthetic high-rate responses at aged states. The aging model is calibrated against experimental data from cells with different electrode loadings and cycled under a variety of fast-charging conditions (1 h, 15 min, 10 min, and 7 min charging). The synthetically generated high-rate responses at aged states are then used to train a deep-learning model to identify real cell state-of-health from fast charge/discharge battery voltage responses. The synthetically trained deep-learning model performance is validated by comparing to standard incremental capacity analysis and half-cell measurements. Finally, the framework demonstrates the benefits of using high-rate physics-based models to generate synthetic data for training deep-learning models.

25 ENERGY STORAGE↗
DOE OSTI2020

View factor estimation of hot spot velocities in inertial confinement fusion implosions at the National Ignition Facility

nertial confinement fusion (ICF) experiments at the National Ignition Facility (NIF) suffer from asymmetries in thex-ray drive that degrade capsule performance compared to expectations for a symmetric one-dimensional implosion.Mode 1, or pole-to-pole, drive asymmetry can reduce confinement and implosion efficiency, driving a bulk motion ofthe hot spot that is detectable with neutron diagnostics. Understanding and removing sources of mode 1 asymmetry inICF implosions is important for improving performance, and the three-dimensional nature of the problem makes high-resolution radiation-hydrodynamic modeling extremely computationally expensive. This work describes a reducedorder view factor model that calculates the drive asymmetry induced by beam-to-beam variations in laser delivery andhohlraum diagnostic windows along the equator. Capsule response is estimated by coupling to a Green’s function thatrelates final hot spot velocity to the applied time-varying mode 1 asymmetry. The model makes several predictionsabout the impact of mode 1 drivers such as laser delivery and target misalignment, and achieves good agreementin both magnitude and vector direction for several shots in three families of high-performance platforms. However,notable discrepancies suggest other potential sources of mode 1 asymmetry not captured by the model are also at play

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The ultrafast pixel array camera system and its applications in high energy density physics

Diagnostics in high energy density physics, shock physics, and related fields are primarily driven by a need to record rapidly time-evolving signals in single-shot events. These measurements are often limited by channel count and signal degradation issues on cable links between the detector and digitizer. Here we present the Ultrafast Pixel Array Camera (UPAC), a compact and flexible detector readout system with 32 waveform-recording channels at up to 10 Gsample/s and 1.8 GHz analog bandwidth. The compact footprint allows the UPAC to be directly embedded in the detector environment. A key enabling technology is the PSEC4A chip, an eight-channel switch-capacitor array sampling device with up to 1056 samples/channel. The UPAC system includes a high-density input connector that can plug directly into an application-specific detector board, programmable control, and serial readout, with less than 5 W of power consumption in full operation. We present the UPAC design and characterization, including a measured timing resolution of ~20 ps or better on acquisitions of sub-nanosecond pulses with minimal system calibrations. Example applications of the UPAC are also shown to demonstrate operation of a solid-state streak camera, an ultrafast imaging array, and a neutron time-of-flight spectrometer.

47 OTHER INSTRUMENTATION↗
NASA NTRS1993

A plume spectroscopy system for flight applications

An operational plume spectroscopy system will be an important element of any rocket engine health management system (HMS). The flight capable FPI spectrometer will enable prognosis and response to incipient rocket engine failures as well as diagnosis of wear and degradation for on-condition maintenance. Spectrometer application to development programs, such as the Space Lifter, NASP, and SSTO, will reduce program risks, allow better adherence to schedules and save money by reducing or eliminating redesign and test costs. The diagnostic capability of a proven, calibrated spectrometer will enhance post-burn certification of high value, reusable engines, such as the Space Shuttle Main Engine (SSME), where life and reliability are key cost drivers. This paper describes a prototype FPI spectrometer for demonstration and validation testing on NASA's Technology Test Bed Engine (TTBE) at Marshall Space Flight Center. The TTBE test unit is designed with flight prototype optics and a commercial off-the-shelf data processing system.

Makel, D. B.↗