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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

The Apollo Alpha Spectrometer.

Located in the Science Instrument Module of Apollo 15 and 16, the Alpha Particle Spectrometer was designed to detect and measure the energy of alpha particles emitted by the radon isotopes and their daughter products. The spectrometer sensor consisted of an array of totally depleted silicon surface barrier detectors. Biased amplifier and linear gate techniques were utilized to reduce resolution degradation, thereby permitting the use of a single 512 channel PHA. Sensor identification and in-flight radioactive calibration were incorporated to enhance data reduction.

Jagoda, N.↗
NASA NTRS1982

Photothermal characterization of encapsulant materials for photovoltaic modules

A photothermal test matrix and a low cost testing apparatus for encapsulant materials of photovoltaic modules were defined. Photothermal studies were conducted to screen and rank existing as well as future encapsulant candidate materials and/or material formulations in terms of their long term physiochemical stability under accelerated photothermal aging conditions. Photothermal characterization of six candidate pottant materials and six candidate outer cover materials were carried out. Principal products of photothermal degradation are identified. Certain critical properties are also monitored as a function of photothermal aging.

Liang, R. H.↗
DOE OSTI2025

XFEM Development for Modeling Crack Growth in Prototypical Welded Components

Nuclear power plant components are subjected to harsh operating environments that can lead to multiple degradation mechanisms in which fracture can play a prominent role. Predicting crack growth is important for assessing the integrity of welded components. The extended finite element method (XFEM) is an important tool for modeling such crack growth, and XFEM capabilities have been developed within the MOOSE framework. This report documents work in the MOOSE XFEM module to model fractures in three-dimensional representations of components using a topologically two-dimensional mesh to define cutting planes. Crack growth algorithms have been implemented to evolve the cutting mesh based on equations for stress corrosion cracking. Additionally, several usability and robustness improvements have been developed to enable three-dimensional fracture simulations. The cutting algorithms were demonstrated on a three-dimensional model of a prototypical reactor component undergoing stress corrosion cracking driven by idealized weld residual stresses. This is an incremental step toward using this capability to model more complex components with residual stresses computed through welding process simulations.

42 - ENGINEERING↗
NASA NTRS1972

Concepts for application of 500- to 2500-We Brayton power systems for shuttle-launched missions

A mini-Brayton power system in the power range of 500 to 2500 We utilizing the multihundred Watt isotope heat source was studied for use in shuttle-launched experiments. The system consists of a single closed gas loop containing a single-shaft, gas cooled, compressor-alternator turbine assembly; a heat source heat exchanger assembly; a startup battery package; an electrical control module; a recuperator; a gas radiator; and a multifoil superinsulation system. The basic configuration and major nuclear payloads for shuttle integration are discussed. It is concluded that mini-Brayton systems have low isotope inventories and high electrical output per thermal input, and have the capability of flying all earth orbital and interplanetary missions with little degradation in performance.

Block, H. B.↗
NASA NTRS1981

A modified adaptive delta modulator

This paper presents the results of a study in data compression of adaptive delta modulated video signals. The Song mode ADM is first investigated at a sampling rate of 16 Mbits/s and shown not to produce enough redundancy to warrant entropy encoding. A modified adaptive delta modulator algorithm is presented that operates at a sampling rate of 16 Mbits/s and does produce sufficient redundancy to yield a 40-50 percent data compression by using a simple code on 4 bit data blocks. Other techniques such as field interpolation and direct substitution are shown to increase the possible data compression further without noticeable degradation in the two input images used in this investigation. The effects of channel errors in the transmission of packet video over a computer network are considered. A leaky integrator is used to reduce the effects of channel errors in the data bits. It is shown that the effects of channel errors can be reduced by field interpolating those packets that can be shown to contain errors.

Barba, J.↗
NASA NTRS1982

Application of MMIC modules in future multiple beam satellite antenna systems

Multiple beam antenna systems for advanced communication satellites operating in the 30/20 GHz frequency bands (30 GHz uplink, 20 GHz downlink) were developed. Up to twenty 0.3 deg HPBW fixed spot beams and six 0.3 deg HPBW scanning spot beams will be required. Array-fed dual reflector antenna systems in which monolithic microwave integrated circuit (MMIC) phase shift and amplifier modules are used with each radiating element of the feed array for beam pointing and power gain were developed. The feasibility of distributed power amplification and beam pointing with MMIC modules in the elements of an array and to develop a data base for future development were demonstrated. The technical discussion centers around the potential advantages of ""monolithic'' antennas for specific applications as compared to systems using high powered TWT's. These include: reduced losses in the beam forming network; advantage of space combining and graceful degradation; dynamic control of beam pointing and illumination contour; and possibilities for cost and weight reduction.

Smetana, J.↗
NASA NTRS1987

Oxygen interaction with space-power materials

Data from the space shuttle flights have established that many materials experience relatively rapid degradation when exposed to the low Earth orbit ambient atmosphere, which is predominately atomic oxygen. While much was learned from samples flown on the shuttle, laboratory simulations of the shuttle environment are necessary for a detailed understanding of the various interactions which contribute to the observed degradations. These laboratory experiments are particularly important for predicting the deterioration to be expected for materials aboard orbiting power systems, which will be exposed for long periods of time and could have components operating at very high temperatures. By using a mass spectrometer to synchronously detect molecules emitted from the surface as a result of amplitude modulated oxygen ion bombardment, quantum yields were obtained as a function of ion energy. A technique was developed to obtain preliminary yield data by slowly scanning the mass setting of the mass spectrometer; measurements were extended down to zero modulation frequency; yield data was obtained for the insulating materials (Nomex, Kevlar, and Teflon) used in the construction of electrodynamic tethers; a heated sample holder was constructed to investigate the effect of sample temperature on quantum yields; and the instrumentation was developed to observe the mass spectrometer signal as a function of time during and following bombardment of the sample by a brief (approximately 1 millisecond) pulse of ions.

Eck, T. G.↗
DOE OSTI2024

Crystalline Si Surface Passivation with Nafion for Bulk Defects Detection with Electron Paramagnetic Resonance

Here, in monocrystalline Si (c-Si) solar cells, identification and mitigation of bulk defects are crucial to achieving a high photoconversion efficiency. To spectroscopically detect defects in the c-Si bulk, it is desirable to passivate the surface defects. Passivation of the c-Si surface with dielectrics such as Al 2 O 3 and SiNx requires deposition at elevated temperatures, which can influence defects in the bulk. Herein, we report on the passivation of different Czochralski (Cz) Si wafer surfaces by an organic copolymer, Nafion. We test the efficacy of the surface passivation at temperatures ranging from 6 to 473 K to detect bulk defects using electron paramagnetic resonance (EPR) spectroscopy. By comparing with state-of-the-art passivation layers, including Al 2 O 3 and liquid HF/HCl, we found that at room temperature, Nafion can provide comparable passivation of n-type Cz Si with an implied open-circuit voltage (iV oc ) of 713 mV and a recombination current prefactor J o of 5 fA/cm 2 . For p-type Cz Si, we obtained an iV oc of 682 mV with a J o of 22.4 fA/cm 2 . Scanning electron microscopy and photoluminescence reveal that Nafion can also be used to passivate the surface of c-Si solar cell fragments scribed from a solar cell module by using a laser. Consistent with previous studies, analysis of the EPR spectroscopy data confirms that the H-terminated surface is necessary, and fixed negative charge in Nafion is responsible for the field-effect passivation. While the surface passivation quality was maintained for almost 24 h, which is sufficient for spectroscopic measurements, the passivation degraded over longer durations, which can be attributed to surface SiO x growth. These results show that Nafion is a promising room-temperature surface passivation technique to study bulk defects in c-Si.

14 SOLAR ENERGY↗
DOE OSTI2025

GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics

Data package for Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon This data is published under a CC0 license. The authors encourage data reuse and request attribution by referencing the below citations for the data packages and associated manuscript. Please cite as: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics. [Data Set] PNNL DataHub. doi: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. MSV000097435: GLBRC soil yearlong incubation 13C-SIP-Lipidomics [Data Set] MassIVE. doi:10.25345/C57659T3K Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon. In Prep This data package consists of compound-specific 13C SIP-lipidomics data from a yearlong tracer incubation experiment designed to investigate microbial lipid persistence in switchgrass bioenergy crop soils. In order to explore how lipid structure may modulate the persistence of C in soil lipids, we leveraged soils from two sites (Michigan - sandy texture, Wisconsin - silty texture) operated by the U.S. Department of Energy-funded Great Lakes Bioenergy Research Center (GLBRC). These sites had comparable climates, identical management practices, but contrasting soil textures, allowing us to assess the variability of lipid accrual or degradation in soils as well as provide insight regarding the degree to which edaphic properties may regulate the retention of soil lipids. Untargeted lipidomics analyses were performed to identify 13C-labeled lipids in the soil microbiome after long-term incubation. Soils were supplemented with 100 micrograms glucose per gram dry soil (99 atom % 13C or natural abundance for paired control) and incubated; samples were collected two months and one year after glucose addition. Lipid extracts (MPLEx) were analyzed by LC-MS/MS and identified using LIQUID. Calculation of isotopic enrichment of lipids was performed by targeted approach using TarMet to quantify lipid isotopologues and IsoCorrectoR to correct for natural abundance isotopes. Contents: Data package contents reported here are the first version and contain downstream analysis files for the raw LC-MS mass spectrometry files (.mzXML) deposited at the MassIVE database repository under accession MSV000097435 (80 experimental runs; 5.85 GB) | MassIVE DOI: 10.25345/C57659T3K. Support files include the additional data download 'Read Me' file containing data descriptor information. Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. Data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location. Available Data Downloads (0.3 GB): "GLBRC soil yearlong incubation 13C-SIP-Lipidomics_readme.txt" - 'Read Me' data package content file (txt) "GLBRC_DataPackage_analysis files" - Data processing files (Rmd) and saved intermediate data processing outputs (rds, csv, xlsx) "GLBRC_13C_lipidomics_dataset.xlsx" - processed data in tabular format (xlsx) Linked Software: LIQUID LC-MS Analysis Software | 10.5281/zenodo.6459462 Lipid Mini-On Software Tools | 10.5281/zenodo.1492803 pmartR Omics Statistical Software | 10.5281/zenodo.6108667 xcms (v4.3.3) TarMet (v1.1.1) IsoCorrectoR (1.24.0) Funding Acknowledgments: This research was supported by an Early Career Research Program award funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (OBER) Genomic Science program under FWP 68292, FWP 07880 and EMSL Exploratory Research Project 51095. A portion of this work was performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by OBER and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated by Battelle for the DOE under Contract DE-AC05-76RLO1830.

Rempfert, Kaitlin R [Pacific Northwest National La↗
NASA NTRS1991

A distributed fault-detection and diagnosis system using on-line parameter estimation

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

Guo, T.-H.↗
NASA NTRS2001

Application of Physiological Self-Regulation and Adaptive Task Allocation Techniques for Controlling Operator Hazardous States of Awareness

Prinzel, Hadley, Freeman, and Mikulka found that adaptive task allocation significantly enhanced performance only when used at the endpoints of the task workload continuum (i.e., very low or high workload), but that the technique degraded performance if invoked during other levels of task demand. These researchers suggested that other techniques should be used in conjunction with adaptive automation to help minimize the onset of hazardous states of awareness (HSA) and keep the operator 'in-the-loop.' The paper reports on such a technique that uses psychophysiological self-regulation to modulate the level of task engagement. Eighteen participants were assigned to three groups (self-regulation, false feedback, and control) and performed a compensatory tracking task that was cycled between three levels of task difficulty on the basis of the electroencephalogram (EEG) record. Those participants who had received self-regulation training performed significantly better and reported lower NASA-TLX scores than participants in the false feedback and control groups. Furthermore, the false feedback and control groups had significantly more task allocations resulting in return-to-manual performance decrements and higher EEG difference scores. Theoretical and practical implications of these results for adaptive automation are discussed.

Prinzel, Lawrence J., III↗
DOE OSTI2023

GBT20, a 20.48 Gbps PAM4 Optical Transmitter Module for Particle Physics Experiments

We present a pluggable radiation-tolerant 4-level Pulse-Amplitude-Modulation (PAM4) optical transmitter module called GBT20 (Giga-Bit Transmitter at 20 Gbps) for particle-physics experiments. GBT20 has an OSFP or firefly connector to input 16-bit data each at 1.28 Gbps. The GBT20 drives a VCSEL die with an LC lens or a VCSEL TOSA and interfaces an optical fiber with a standard LC connector. The minimum module, including the host connector, occupies 41 mm x 13 mm x 6 mm. At 20.48 Gbps, the minimum Transmitter Dispersion Eye Closure Quaternary (TDECQ) is around 0.7 dB. The power consumption is around 164 mW in the low-power mode. The SEE cross-section is below 7.5x10^(-14) cm^2. No significant performance degrades after a TID of 5.4 kGy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Characterization of Interconnects

Combined-accelerated stress testing (C-AST) simultaneously combines stress factors of the natural environment (including UV radiation, temperature, humidity, electrical current, and external mechanical force) into a single test that requires fewer modules, fewer chambers, and makes it possible to discover weaknesses in new designs that are not known a-priori. C-AST reduces risk, accelerates time to market, and improves bankability by reducing costly overdesign using test levels not exceeding those seen in the natural environment. This project seeks to evaluate strengths and weaknesses of modern cell interconnect designs with combined-accelerated stress testing (C-AST) to screen multiple climates along with finite element and failure analysis to determine the potential for a 50-year life. Supporting this, we seek to develop methods of characterization to assess the degradation of interconnects, enable predictive rate models with material forensics and FEA and show C-AST's ability to find interconnect failures and benchmark it relative to other accelerated stress test methods like temperature cycling and cyclic dynamic mechanical loading. Examples of modern interconnect designs covered are Canadian Solar Hetero Technology ribbon enabling closer cell interconnections, SmartWire (eg. Meyer-Berger technology), and shingled cells with new interconnect materials.

C-AST↗
NASA NTRS1983

Photothermal degradation of ethylene/vinylacetate copolymer

Photothermal degradation studies were conducted on a 'stabilized' formulation of ethylene/vinyl acetate copolymer (EVA) in the temperature range 25-105 C under three different oxygen environments (in open air, with limited access to O2, and in a dark closed stagnant oven). These studies were performed in order to evaluate the utility of EVA as an encapsulation material for photovoltaic modules. Results showed that at low temperature (25 C), slow photooxidation of the polymer occurred via electronic energy transfer involving the UV absorber incorporated in the polymer. However, no changes in the physical properties of the bulk polymer were detected up to 1500 hours of irradiation. At elevated temperatures, leaching and evaporation of the additives occurred, which ultimately resulted in the chemical crosslinking of the copolymer and the formation of volatile photoproducts such as acetic acid.

Liang, R. H.↗
NASA NTRS1998

Optical Channelizer Evaluation Using Empirical Data and Simulation

Westinghouse Electric Corporation Division under NASA contract NAS3-25865 developed a proof-of-concept (POC) multichannel demultiplexer implemented as an acousto-optic radiofrequency (RF) with a spectrum analyzer. A detailed analysis of the experimental results indicate that the expected degradation caused by the acousto-optical channelizer is approximately 2.0 dB degradation at 10(exp -5) bit-error rate (BER) and 3.0 dB degradation at 10(exp -8) BER. This degradation may be quite acceptable when considering the excellent volume, mass, and power characteristics of acousto-optical channelizing relative to other technologies. In addition, system performance can be greatly improved by using digital pulse shaping in the modem and increasing the channel spacing from 40 to 45 kHz for 64 kbps quadrature phase-shift keying (QPSK) modulation.

Ivancic,William D.↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, G. C.↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗