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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Measurement of heat pump processes induced by laser radiation

A series of experiments was performed in which a suitably tuned CO2 laser, frequency doubled by a Tl3AsSe37 crystal, was brought into resonance with a P-line or two R-lines in the fundamental vibration spectrum of CO. Cooling or heating produced by absorption in CO was measured in a gas-thermometer arrangement. P-line cooling and R-line heating could be demonstrated, measured, and compared. The experiments were continued with CO mixed with N2 added in partial pressures from 9 to 200 Torr. It was found that an efficient collisional resonance energy transfer from CO to N2 existed which increased the cooling effects by one to two orders of magnitude over those in pure CO. Temperature reductions in the order of tens of degrees Kelvin were obtained by a single pulse in the core of the irradiated volume. These measurements followed predicted values rather closely, and it is expected that increase of pulse energies and durations will enhance the heat pump effects. The experiments confirm the feasibility of quasi-isentropic engines which convert laser power into work without the need for heat rejection. Of more immediate potential interest is the possibility of remotely powered heat pumps for cryogenic use, such applications are discussed to the extent possible at the present stage.

Garbuny, M.↗
NASA NTRS1987

Performance analysis of parallel branch and bound search with the hypercube architecture

With the availability of commercial parallel computers, researchers are examining new classes of problems which might benefit from parallel computing. This paper presents results of an investigation of the class of search intensive problems. The specific problem discussed is the Least-Cost Branch and Bound search method of deadline job scheduling. The object-oriented design methodology was used to map the problem into a parallel solution. While the initial design was good for a prototype, the best performance resulted from fine-tuning the algorithm for a specific computer. The experiments analyze the computation time, the speed up over a VAX 11/785, and the load balance of the problem when using loosely coupled multiprocessor system based on the hypercube architecture.

Mraz, Richard T.↗
NASA NTRS1998

Toward a More Robust Pruning Procedure for MLP Networks

Choosing a proper neural network architecture is a problem of great practical importance. Smaller models mean not only simpler designs but also lower variance for parameter estimation and network prediction. The widespread utilization of neural networks in modeling highlights an issue in human factors. The procedure of building neural models should find an appropriate level of model complexity in a more or less automatic fashion to make it less prone to human subjectivity. In this paper we present a Singular Value Decomposition based node elimination technique and enhanced implementation of the Optimal Brain Surgeon algorithm. Combining both methods creates a powerful pruning engine that can be used for tuning feedforward connectionist models. The performance of the proposed method is demonstrated by adjusting the structure of a multi-input multi-output model used to calibrate a six-component wind tunnel strain gage.

Stepniewski, Slawomir W.↗
NASA NTRS2004

Robust local search for spacecraft operations using adaptive noise

Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.

planning↗
NASA NTRS2005

Local oscillator chain for 1.55 to 1.75 THz with 100-(mu)W peak power

We report on the design and performance of a fix-tuned x2x 3x 3 frequency multiplier chain that covers 1.55-1.75 THz. The chain is nominally pumped with 100 mW at W-band. At 120 K the measured output power is larger than 4 (mu)W across the band with a peak power of 100 (mu) W at 1.665 THz. A similar chain operated at room temperature produced a peak power of 21 (mu)W. These power levels now make it possible to deploy multipixel heterodyne imaging arrays in this frequency range.

frequency multiplier↗
NASA NTRS2005

Attitude and position estimation on the Mars Exploration Rovers

NASA/JPL 's Mars Exploration Rovers acquire their attitude upon command and autonomously propagate their attitude and position. The rovers use accelerometers and images of the sun to acquire attitude, autonomously searching the sky for the sun with a pointable camera. To propagate the attitude and position the rovers use either accelerometer and gyro readings or gyro readings and wheel odometiy, depending on the nature of the movement ground operators are commanding. Where necessary, visual odometry is performed on images to fine tune the position updates, particularly in high slip environments. The capability also exists for visual odometry attitude updates. This paper describes the techniques used by the rovers to acquire and maintain attitude and position knowledge, the accuracy which is obtainable, and lessons learned after more than one year in operation.

attitude estimation↗
NASA NTRS2013

Low Profile Tunable Dipole Antenna Using BST Varactors for Biomedical Applications

In this paper a 2.4 GHz low profile (lambda/47) tunable dipole antenna is evaluated in the presence of a human core model (HCM) body phantom. The antenna uses a frequency selective surface (FSS) with interdigital barium strontium titanate (BST) varactor-tuned unit cells and its performance is compared to a similar low profile antenna that uses an FSS with semiconductor varactor diodes. The measured data of the antenna demonstrate tunability from 2.2 GHz to 2.55 GHz in free space and impedance match improvement in the presence of a HCM at different distances. This antenna has smaller size, lower cost and less weight compared to the semiconductor varactor diode counterpart.

frequency selective surfaces↗
NASA NTRS2013

Low Profile Tunable Dipole Antennas Using BST Varactors for Biomedical Applications

In this presentation a 2.4 GHz low profile (lambda45) tunable dipole antenna is evaluated in the presence of a human core model (HCM) body phantom. The antenna uses a frequency selective surface (FSS) with interdigital barium strontium titanate (BST) varactor-tuned unit cells and its performance is compared to a similar low profile antenna that uses an FSS with semiconductor varactor diodes. The measured data of the antenna demonstrate tunability from 2.2 GHz to 2.55 GHz in free space and impedance match improvement in the presence of a HCM at different distances. This antenna has smaller size, lower cost and less weight compared to the semiconductor varactor diode counterpart.

Tunable Dipole Antennas↗
NASA NTRS2012

Model-Based Control of an Aircraft Engine using an Optimal Tuner Approach

This paper covers the development of a model-based engine control (MBEC) method- ology applied to an aircraft turbofan engine. Here, a linear model extracted from the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS40k) at a cruise operating point serves as the engine and the on-board model. The on-board model is up- dated using an optimal tuner Kalman Filter (OTKF) estimation routine, which enables the on-board model to self-tune to account for engine performance variations. The focus here is on developing a methodology for MBEC with direct control of estimated parameters of interest such as thrust and stall margins. MBEC provides the ability for a tighter control bound of thrust over the entire life cycle of the engine that is not achievable using traditional control feedback, which uses engine pressure ratio or fan speed. CMAPSS40k is capable of modeling realistic engine performance, allowing for a verification of the MBEC tighter thrust control. In addition, investigations of using the MBEC to provide a surge limit for the controller limit logic are presented that could provide benefits over a simple acceleration schedule that is currently used in engine control architectures.

Connolly, Joseph W.↗
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↗
NASA NTRS2012

International Space Station Major Constituent Analyzer On-Orbit Performance

The Major Constituent Analyzer is a mass spectrometer based system that measures the major atmospheric constituents on the International Space Station. A number of limited-life components require periodic changeout, including the ORU 02 analyzer and the ORU 08 Verification Gas Assembly. Over the past two years, two ORU 02 analyzer assemblies have operated nominally while two others have experienced premature on-orbit failures. These failures as well as nominal performances demonstrate that ORU 02 performance remains a key determinant of MCA performance and logistical support. It can be shown that monitoring several key parameters can maximize the capacity to monitor ORU health and properly anticipate end of life. Improvements to ion pump operation and ion source tuning are expected to improve lifetime performance of the current ORU 02 design.

Gardner, Ben D.↗
NASA NTRS1983

New auto-tuning technique for the hydrogen maser

Auto-tuning of the maser cavity compensates for cavity pulling effect, and other sources of contribution to the long term frequency drift. Schemes previously proposed for the maser cavity auto-tuning can have adverse effects on the performance of the maser. A new scheme is proposed based on the phase relationship between the electric and the magnetic fields inside the cavity. This technique has the desired feature of auto-tuning the cavity with a very high sensitivity and without disturbing the maser performance. Some approaches for the implementation of this scheme and possible areas of difficulty are examined.

Sydnor, R. L.↗
NASA NTRS1964

Nylon Sleeve for Cavity Amplifier Holds Tuning Despite Heat

The problem: Detuning of cavity amplifiers with change in temperature. This results in deterioration of the performance of the amplifier at its design frequency. In cavity amplifiers and filters it is desirable that constant performance be maintained regardless of thermal changes. These changes often cause an "off resonance shift" in a cavity filter and a deterioration of performance in a cavity amplifier. The solution: Mount the tuning probe in a nylon sleeve. Thermal expansion and contraction of the nylon nullifies unwanted capacitive and inductive changes in the resonant elements.

Derr, Lloyd↗
NASA NTRS1987

Interior noise reduction by alternate resonance tuning

Existing interior noise reduction techniques for aircraft fuselages perform reasonably well at higher frequencies, but are inadequate at low frequencies, particularly with respect to the low blade passage harmonics with high forcing levels found in propeller aircraft. A method is studied which considers aircraft fuselages lined with panels alternately tuned to frequencies above and below the frequency that must be attenuated. Adjacent panel would oscillate at equal amplitude, to give equal acoustic source strength, but with opposite phase. Provided these adjacent panels are acoustically compact, the resulting cancellation causes the interior acoustic modes to be cut off, and therefore be nonpropagating and evanescent. This interior noise reduction method, called Alternate Resonance Tuning (ART), is being investigated theoretically and experimentally. Progress to date is discussed.

Bliss, Donald B.↗
NASA NTRS1989

Aircraft interior noise reduction by alternate resonance tuning

Existing interior noise reduction techniques for aircraft fuselages perform reasonably well at higher frequencies, but are inadequate at lower, particularly with respect to the low blade passage harmonics with high forcing levels found in propeller aircraft. A method is being studied which considers aircraft fuselages lines with panels alternately tuned to frequencies above and below the frequency to be attenuated. Adjacent panels would oscillate at equal amplitude, to give equal source strength, but with opposite phase. Provided these adjacent panels are acoustically compact, the resulting cancellation causes the interior acoustic modes to become cut off and therefore be non-propagating and evanescent. This interior noise reduction method, called Alternate Resonance Tuning (ART), is currently being investigated both theoretically and experimentally. This new concept has potential application to reducing interior noise due to the propellers in advanced turboprop aircraft as well as for existing aircraft configurations. This program summarizes the work carried out at Duke University during the third semester of a contract supported by the Structural Acoustics Branch at NASA Langley Research Center.

Bliss, Donald B.↗
NASA NTRSDate not supplied

LSKnowledge: Nexus for Transformative Scientific Discoveries and Enhanced Information Retrieval in NASA Life Sciences Portal

We stand at the brink of an extraordinary transformation in the field of AI, driven by the convergence of generative AI and semantic technologies (e.g., knowledge graphs). This fusion holds immense potential and could redefine the future of scientific exploration, particularly in the realm of life sciences research. In this context, we shed light on the pivotal roles that Large Language Models (LLMs) and semantic technologies will play in advancing research, unearthing and comprehending life sciences information through innovative approaches, and empowering researchers to extract insights from NASA's extensive Life Sciences Data Archive. Within the NASA Life Sciences Portal (NLSP), the integration of LLMs and semantic technologies unlocks several advanced capabilities. First and foremost, it equips scientists with sophisticated tools to manage the ever-expanding wealth of scientific literature and data. Furthermore, it facilitates the creation of knowledge graphs that visually represent intricate relationships among biological entities, enabling comprehensive systems-level analysis. Additionally, the fusion of generative AI (including LLMs) and semantic technology can significantly benefit NASA's life sciences research by enhancing information retrieval and hypothesis generation. These tools enhance natural language understanding, facilitating knowledge discovery within NLSP. The overarching vision is to establish a cohesive knowledge ecosystem within NLSP, harnessing the power of LLMs and semantic technologies to synthesize and cross-reference data from diverse missions, disciplines, and research domains. This holistic approach ultimately deepens our understanding of how space environments impact life sciences data. To advance this initiative, we have launched LSKnowledge, aimed at enhancing the information retrieval capabilities of NLSP. In the short term, our primary goal is to develop a robust semantic search system. This system will empower HRP (Human Research Program) researchers to navigate NLSP data repositories more efficiently and precisely, catalyzing the process of hypothesis formation and scientific breakthroughs. To achieve this, we have employed pre-trained LLMs as part of a semantic search tool that can rank and highlight the most relevant records for user queries. To assess the tool's performance, we have curated a set of approximately 200 queries from subject matter experts (SMEs) and manually ranked the top records retrieved by both the current search system and the new semantic search, using SME judgments as the gold standard for relevancy. Herein, we present the results of our comparative analysis and illustrate how these findings have informed the fine-tuning of the system for enhanced performance. In the long term, our objectives include 1) retrieving publicly available information and integrating it with NLSP data to provide more precise answers to user queries, and 2) incorporating non-textual information from the NLSP database into our approach. In conclusion, the fusion of LLMs and semantic technologies within NLSP represents a pioneering stride towards reshaping the landscape of scientific discovery. This synergy not only equips researchers with powerful tools to navigate the burgeoning sea of information but also facilitates a deeper understanding of complex biological relationships, all while accelerating hypothesis generation and knowledge discovery. Through our initiative, LSKnowledge, we are committed to continually refining and expanding these capabilities, with the aim of not only enhancing information retrieval but also integrating diverse data sources to provide more precise insights. In the grand vision, NLSP strives to become the cornerstone of a comprehensive knowledge ecosystem, unraveling the enigmatic intricacies of life sciences phenomena in the context of space environments.

Life Sciences↗
NASA NTRS1990

Aircraft interior noise reduction by alternate resonance tuning

Existing interior noise reduction techniques for aircraft fuselages perform reasonably well at higher frequencies, but are inadequate at lower frequencies, particularly with respect to the low blade passage harmonics with high forcing levels found in propeller aircraft. A method is being studied which considers aircraft fuselage lined with panels alternately tuned to frequencies above and below the frequency that must be attenuated. Adjacent panels would oscillate at equal amplitude, to give equal source strength, but with opposite phase. Provided these adjacent panels are acoustically compact, the resulting cancellation causes the interior acoustic modes to become cutoff, and therefore be non-propagating and evanescent. This interior noise reduction method, called Alternate Resonance Tuning (ART), is currently being investigated both theoretically and experimentally. This new concept has potential application to reducing interior noise due to the propellers in advanced turboprop aircraft as well as for existing aircraft configurations.

Bliss, Donald B.↗
NASA NTRS2019

Machine Learning, Markov Chain Monte Carlo, and Optimal Algorithms to Characterize the AdvACT Kilopixel Transition-Edge Sensor Arrays

Next-generation focal planes comprising dozens of kilopixel transition-edge sensor (TES) arrays require new methods to rapidly screen candidate arrays, evaluate array non-idealities in the field, identify outlier devices for removal, and optimize the array performance in the field. We demonstrate robust methods to estimate TES parameters (critical temperatures and thermal conductivity parameters) and their uncertainties using a custom Markov Chain Monte Carlo (MCMC) algorithm. We also constrain systematic effects in estimating the TES parameters from non-isothermal current-voltage curves (IVs) at approximately a ~3% level. Additionally, for the first time, we have applied Machine Learning (ML) algorithms to tune detector arrays and optimize their performance.

Maria Salatino↗