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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

High performance millimeter-wave microstrip circulators and isolators

Millimeter wave systems, phased array antennas, and high performance components all require wideband circulators (and isolators) to perform diplexing and switching, to improve isolation and Voltage Standing Wave Ratio (VSWR), and to construct IMPATT diode reflection amplifiers. Presently, most of the millimeter-wave circulators and isolators are available in the configurations of waveguide or stripline, both of which suffer from the shortcomings of bulky size/weight, narrow bandwidth, and poor compatibility with monolithic millimeter-wave integrated circuits (MMIC). MMW microstrip circulators/isolators can eliminate or improve these shortcomings. Stub-tuned microstrip circulator configuration were developed utilizing the electromagnetic fields perturbation technique, the adhesion problems of microstrip metallization on new ferrite substrate were overcome, the fabrication, assembly, packaging techniques were improved, and then successfully designed, fabricated a Ka band circulator which has isolation and return loss of greater than 16dB, insertion loss less than 0.7dB. To assess the steady and reliable performance of the circulator, a temperature cycling test was done over the range of -20 to +50 C for 3 continuous cycles and found no significant impact or variation of circulator performance.

Shih, Ming↗
NASA NTRS2004

Lithium Polymer Electrolytes and Solid State NMR

Research is being done at the Glenn Research Center (GRC) developing new kinds of batteries that do not depend on a solution. Currently, batteries use liquid electrolytes containing lithium. Problems with the liquid electrolyte are (1) solvents used can leak out of the battery, so larger, more restrictive, packages have to be made, inhibiting the diversity of application and decreasing the power density; (2) the liquid is incompatible with the lithium metal anode, so alternative, less efficient, anodes are required. The Materials Department at GRC has been working to synthesize polymer electrolytes that can replace the liquid electrolytes. The advantages are that polymer electrolytes do not have the potential to leak so they can be used for a variety of tasks, small or large, including in the space rover or in space suits. The polymers generated by Dr. Mary Ann Meador's group are in the form of rod -coil structures. The rod aspect gives the polymer structural integrity, while the coil makes it flexible. Lithium ions are used in these polymers because of their high mobility. The coils have repeating units of oxygen which stabilize the positive lithium by donating electron density. This aids in the movement of the lithium within the polymer, which contributes to higher conductivity. In addition to conductivity testing, these polymers are characterized using DSC, TGA, FTIR, and solid state NMR. Solid state NMR is used in classifying materials that are not soluble in solvents, such as polymers. The NMR spins the sample at a magic angle (54.7') allowing the significant peaks to emerge. Although solid state NMR is a helpful technique in determining bonding, the process of preparing the sample and tuning it properly are intricate jobs that require patience; especially since each run takes about six hours. The NMR allows for the advancement of polymer synthesis by showing if the expected results were achieved. Using the NMR, in addition to looking at polymers, allows for participation on a variety of other projects, including aero-gels and carbon graphite mat en als. The goals of the polymer electrolyte research are to improve the physical properties of the polymers. This includes improving conductivity, durability, and expanding the temperature range over which it is effective. Currently, good conductivity is only present at high temperatures. My goals are to experiment with different arrangements of rods and coils to achieve these desirable properties. Some of my experiments include changing the number of repeat units in the polymer, the size of the diamines, and the types of coil. Analysis of these new polymers indicates improvement in some properties, such as lower glass transition temperature; however, they are not as flexible as desired. With further research we hope to produce polymers that encompass all of these properties to a high degree.

Berkeley, Emily R.↗
NASA NTRS2015

A Case Study on the Application of a Structured Experimental Method for Optimal Parameter Design of a Complex Control System

This report documents a case study on the application of Reliability Engineering techniques to achieve an optimal balance between performance and robustness by tuning the functional parameters of a complex non-linear control system. For complex systems with intricate and non-linear patterns of interaction between system components, analytical derivation of a mathematical model of system performance and robustness in terms of functional parameters may not be feasible or cost-effective. The demonstrated approach is simple, structured, effective, repeatable, and cost and time efficient. This general approach is suitable for a wide range of systems.

Torres-Pomales, Wilfredo↗
NASA NTRS1977

Methods of reducing low frequency cabin noise and sonically induced stresses, based on the intrinsic structural tuning concept

Control of low frequency interior noise has been difficult in all commercial and general aviation aircraft, since the existing sound attenuation techniques are less effective at these frequencies. Therefore low frequency cabin noise and sonically induced stresses can be reduced mainly by a proper design of the fuselage structure. For this purpose, a concept based on intrinsic tuning and damping of fuselage structural elements has been under development at Boeing for the past three years. This paper describes the results of some laboratory and field tests that were conducted for evaluation of the concept.

Sengupta, G.↗
DOE OSTI2025

Controlling beam trajectory and transport in a tapered helical undulator

In this paper we present a detailed discussion of the helical undulator system developed for high extraction efficiency experiments in the tapered-enhanced stimulated superradiant amplification regime. The design is based on permanent magnet technology and comprises two Halbach arrays orthogonally oriented and shifted by 90° with respect to each other. When used in low energy beamlines for THz generation, the electron beam trajectory and transport are particularly sensitive to the undulator off-axis fields so that it becomes important to complement on-axis field measurements with analysis and tuning of the higher-order field components. Here we describe how the pulsed wire measurement technique can be effectively used to retrieve on- and off-axis magnetic field characteristics of the undulator. A simple two-dipole model is developed to guide the final adjustments to the permanent magnet positions along the array to tune the quadrupole and sextupole components of the field.

free-electron lasers↗
NASA NTRSDate not supplied

Semantic Search with Sentence-BERT for Design Information Retrieval

Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval: semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pretrained sBERT model shows excellent out-of-the-box performance, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over the LLIS’s built-in keyword search. Additionally, we demonstrate a use case for the query system by searching for lessons learned relevant to specific requirements from a NASA project as part of a broader knowledge management and retrieval system. Results indicate that applying state-of-the-art natural language processing techniques, especially when fine-tuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.

Hannah S. Walsh↗
DOE OSTI2025

Machine learning for arbitrary single-qubit rotations on an embedded device

Here, in this study, we present a technique for using machine learning (ML) for single-qubit gate synthesis on field-programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first “bootstrap” a model based on simulation with access to the full state vector for measuring gate fidelity. We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements of the devices. We also present techniques for deploying the model on programmable devices with care to reduce the required resources. While the techniques here are applied to a transmon-based computer, many of them are portable to other architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Optimizing Distributed Training on Frontier for Large Language Models

Large language models (LLMs) have demonstrated remarkable success as foundational models, benefiting various downstream applications through fine-tuning. Loss scaling studies have demonstrated the superior performance of larger LLMs compared to their smaller counterparts. Nevertheless, training LLMs with billions of parameters poses significant challenges and requires considerable computational resources. For example, training a one trillion parameter GPT-style model on 20 trillion tokens requires a staggering 120 million exaflops. This research explores efficient distributed training strategies to extract this computation from Frontier, the world's first exascale supercomputer. We enable and investigate various model and data parallel training techniques, such as tensor parallelism, pipeline parallelism, and sharded data parallelism, to facilitate training a trillion-parameter model on Frontier. We empirically assess these techniques and their associated parameters to determine their impact on memory footprint, communication latency, and GPU's computational efficiency. We analyze the complex interplay among these techniques and find a strategy to combine them to achieve high throughput through hyperparameter tuning. We have identified efficient strategies for training large LLMs of varying sizes through empirical analysis and hyperparameter tuning. For 22 Billion, 175 Billion, and 1 Trillion parameters, we achieved GPU throughputs of 38.38%, 36.14%, and 31.96%, respectively. For the training of the 175 Billion parameter model and the 1 Trillion parameter model, we achieved 100% weak scaling efficiency on 1024 and 3072 Mi250X GPUs, respectively. We also achieved strong scaling efficiencies of 89% and 87% for these two models. We trained these models only tens of iterations instead of training till completion.

Yin, Junqi↗
DOE OSTI2024

Rapid curing dynamics of PEG-thiol-ene resins allow facile 3D bioprinting and in-air cell-laden microgel fabrication

Thiol-norbornene photoclick hydrogels are highly efficient in tissue engineering applications due to their fast gelation, cytocompatibility, and tunability. In this work, we utilized the advantageous features of polyethylene glycol (PEG)-thiol-ene resins to enable fabrication of complex and heterogeneous tissue scaffolds using 3D bioprinting and in-air drop encapsulation techniques. We demonstrated that photoclickable PEG-thiol-ene resins could be tuned by varying the ratio of PEG-dithiol to PEG norbornene to generate a wide range of mechanical stiffness (0.5–12 kPa) and swelling ratios. Importantly, all formulations maintained a constant, rapid gelation time (<0.5 s). We used this resin in biological projection microstereolithography (BioPµSL) to print complex structures with geometric fidelity and demonstrated biocompatibility by printing cell-laden microgrids. Moreover, the rapid gelling kinetics of this resin permitted high-throughput fabrication of tunable, cell-laden microgels in air using a biological in-air drop encapsulation apparatus (BioIDEA). We demonstrated that these microgels could support cell viability and be assembled into a gradient structure. This PEG-thiol-ene resin, along with BioPµSL and BioIDEA technology, will allow rapid fabrication of complex and heterogeneous tissues that mimic native tissues with cellular and mechanical gradients. The engineered tissue scaffolds with a controlled microscale porosity could be utilized in applications including gradient tissue engineering, biosensing, and in vitro tissue models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mid-infrared spectroscopy with a broadly tunable thin-film lithium niobate optical parametric oscillator

Mid-infrared spectroscopy, an important technique for sensing molecules, has encountered barriers from sources either limited in tuning range or excessively bulky for widespread use. We present a compact, efficient, and broadly tunable optical parametric oscillator surmounting these challenges. Leveraging dispersion-engineered thin-film lithium niobate-on-sapphire photonics and a singly resonant cavity allows broad, controlled tuning over an octave from 1.5–3.3 µm. The device generates >25mW of mid-infrared light at 3.2 µm with 15% conversion efficiency. The ability to precisely control the device’s mid-infrared emission enables spectroscopy of methane and ammonia, demonstrating our approach’s relevance for sensing. Our work signifies an important advance in nonlinear photonics miniaturization, bringing practical field applications of high-speed, broadband mid-infrared spectroscopy closer to reality.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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.↗
NASA NTRS1993

Quaternion normalization in spacecraft attitude determination

Attitude determination of spacecraft usually utilizes vector measurements such as Sun, center of Earth, star, and magnetic field direction to update the quaternion which determines the spacecraft orientation with respect to some reference coordinates in the three dimensional space. These measurements are usually processed by an extended Kalman filter (EKF) which yields an estimate of the attitude quaternion. Two EKF versions for quaternion estimation were presented in the literature; namely, the multiplicative EKF (MEKF) and the additive EKF (AEKF). In the multiplicative EKF, it is assumed that the error between the correct quaternion and its a-priori estimate is, by itself, a quaternion that represents the rotation necessary to bring the attitude which corresponds to the a-priori estimate of the quaternion into coincidence with the correct attitude. The EKF basically estimates this quotient quaternion and then the updated quaternion estimate is obtained by the product of the a-priori quaternion estimate and the estimate of the difference quaternion. In the additive EKF, it is assumed that the error between the a-priori quaternion estimate and the correct one is an algebraic difference between two four-tuple elements and thus the EKF is set to estimate this difference. The updated quaternion is then computed by adding the estimate of the difference to the a-priori quaternion estimate. If the quaternion estimate converges to the correct quaternion, then, naturally, the quaternion estimate has unity norm. This fact was utilized in the past to obtain superior filter performance by applying normalization to the filter measurement update of the quaternion. It was observed for the AEKF that when the attitude changed very slowly between measurements, normalization merely resulted in a faster convergence; however, when the attitude changed considerably between measurements, without filter tuning or normalization, the quaternion estimate diverged. However, when the quaternion estimate was normalized, the estimate converged faster and to a lower error than with tuning only. In last years, symposium we presented three new AEKF normalization techniques and we compared them to the brute force method presented in the literature. The present paper presents the issue of normalization of the MEKF and examines several MEKF normalization techniques.

Deutschmann, J.↗
NASA NTRS1992

Preliminary burst location calibration results for the BATSE instrument on CGRO

Preliminary results pertaining to burst location using BATSE Large Area Detector measurements of solar flares are presented. These solar flare measurements are currently being used to fine tune the calibration of our data analysis software. The current status of techniques for identifying and eliminating systematic errors from the data analysis tools is discussed. Data revealing the effects of the atmospheric scattering algorithm that will be implemented in the data analysis software are presented.

Pendleton, G. N.↗
NASA NTRS1995

(abstract) Vibration Damping of the Cassini Spacecraft Structure

Cassini will be protected during launch ascent through the atmosphere by a lightweight aluminum payload fairing (PLF). As a result of the extreme noise levels generated by the powerful Titan IV at liftoff, and the acoustic transparency of the PLF, Cassini is predicted to experience severe acoustic levels. Furthermore, the high acoustic levels, coupled with the size and configuration of the spacecraft, will induce intense random vibration on the structure and critical spacecraft components. Efforts to mitigate the vibroacoustic environment by modifying the spacecraft structure were pursued. Preliminary studies indicated that a structural damping treatment using viscoelastic materials (VEMs) represented a viable technique of reducing vibration with minimum impact on weight, cost, and redesign. Tuned Vibration Absorbers (TVAs) - compact, single degree-of-freedom mechanical oscillators in which a VEM serves as the spring and damping element - will be used also. The operating principles, design, and installation of the TVAs are described, the test program is outlined, and test results are presented which show that significant vibration attenuation was achieved.

vibroacoustic environment↗
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↗
NASA NTRS1997

Improvement in Suppression of Pulsed Nd:YAG Laser Light With Iodine Absorption Cells for Filtered Rayleigh Scattering Measurements

Filtered Rayleigh scattering using iodine absorption cells is an effective technique for obtaining density, temperature, and velocity measurements in high speed confined flows. By tuning a single frequency laser to a strong iodine absorption line, stray scattered laser light can be greatly suppressed. For example, the minimum transmission predicted by an iodine absorption model calculation is less than 10(exp -5) at the 18788.44/cm line using a 200 mm absorption cell containing iodine vapor at 0.46 T. Measurements obtained by other researches using a CW Nd:YAG laser agree with the model calculations. However, measurements made by us and by others using Q-switched, injection-seeded, frequency doubled Nd:YAG lasers only show minimum transmission of about 3 x 10(exp -3). This greatly reduces the applicability of the filtered Rayleigh scattering technique using these lasers in experiments having large amounts of stray scattered laser light. The purposes of the present study are to characterize the spectrum of the excess light transmitted by the iodine cell and to make changes to the laser to reduce the transmitted laser light. Transmission data as a function of laser frequency for the iodine absorption line at 18788.44/cm are presented. A planar mirror Fabry-Perot interferometer was used to characterize the frequency spectrum of the light passed through the cell. Measurements taken with the laser tuned to the center of the iodine absorption line show the light transmitted through the iodine cell to have a component with a bandwidth of about 40 GHz. This is probably caused by other modes in the laser that exist in spite of the single frequency injection beam. A second broadband component was also observed, possibly caused by the laser flash lamps or by fluorescence. An intracavity etalon was installed in the laser oscillator cavity to suppress the 40 GHz component. Measurements taken with the etalon tuned to the injection frequency showed a reduction in the transmitted laser light. This improvement allows the iodine cell to block significantly more of the stray laser light in filtered Rayleigh scattering experiments. Examples are given of filtered Rayleigh scattering measurements showing the effect of the etalon on measurements taken in a Mach 3 flow in the NASA Lewis 4 inch by 10 inch supersonic wind tunnel.

Seasholtz, Richard G.↗
NASA NTRS1975

Conclusions from the discussions on observational results of heterodyne spectroscopy in astronomy

Experimental results in astronomy obtained with the aid of infrared heterodyne detection techniques are considered, taking into account the detection of thermal emission with no dispersion at the intermediate frequency and observations involving molecular line detection. The tuning range of a heterodyne spectrometer and of a Fourier transform spectrometer is considered and attention is given to the selection of the appropriate technique for a specific investigative problem.-

Mumma, M.↗