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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

A Miniaturized Laser Heterodyne Radiometer for Greenhouse Gas Measurements in the Atmospheric Column

Laser Heterodyne Radiometry is a technique adapted from radio receiver technology has been used to measure trace gases in the atmosphere since the 1960s.By leveraging advances in the telecommunications industry, it has been possible to miniaturize this technology.The mini-LHR (Miniaturized Laser Heterodyne Radiometer) has been under development at NASA Goddard Space flight Center since 2009. This sun-viewing instrument measures carbon dioxide and methane in the atmospheric column and operates in tandem with an AERONET sun photometer producing a simultaneous measure of aerosols. The mini-LHR has been extensively field tested in a range of locations ranging in the continental US as well as Alaska and Hawaii and now operates autonomously with sensitivities of approximately 0.2 ppmv and approximately10 ppbv, for carbon dioxide and methane respectively, for 10 averaged scans under clear sky conditions.

CO2↗
NASA NTRS1978

Bidirectional overadaptation achieved by executing leftward or rightward head movements during unidirectional rotation

Nine college age males, all prone to motion sickness, were subjects in an experiment designed to test adaptation to motion. Subjects were placed in a slow rotation room (SRR) for varying intervals and asked to perform headward movements. Degree of adaptation to the SRR was measured in the framework of 3 categories: reduction of ataxia, reduction of oculogyral illusion, and reduction of epiphenomena, which includes symptoms of motion sickness. 'Satisfactory' adaptation was acquired and retained in 7 of the 9 subjects. Tables are presented summarizing the results.

Graybiel, A.↗
NASA NTRS1984

Assessment of Techniques for Measuring Tropospheric H Sub x O Sub Y: Summary

The objectives were: (1) to provide an assessment of the capability of the existing sensors of HxOy species at levels characteristic of the nonurban troposphere; (2) to identify those techniques adaptable to real-time measurement (sampled or continuous) onboard an aircraft platform; (3) to address the concern for intercalibration and intercomparison of techniques for measuring specific species; and (4) to recommend promising technologies for research and development for measuring important species for which a capability does not now exist or is presently of inadequate sensitivity.

Source record↗
DOE OSTI2021

Suppression of ITG turbulence due to spectral shift during biasing induced H-mode on HBT-EP

Investigations of biasing induced H-mode discharges on HBT-EP show that the edge turbulence is consistent with the ion temperature gradient) mode and have allowed for the controlled observation of the effect of applied flow shear on the turbulence. Measurements of the radial wavenumber spectrum of floating potentials at the edge show that the turbulence intensity decreases with increasing shift in the spectrum average ⟨ k r ⟩ when increasing amounts of bias probe voltage (and increasing amounts of flow shear) is applied. This is in agreement with the spectral shift model [Staebler et al., Phys. Rev. Lett. 110, 055003 2013] for turbulence suppression via sheared flow. A shift in the wavenumber spectrum occurs at applied electrode voltages and currents below the threshold needed for an L–H transition, and a dithering transition is obtained when biasing near the threshold. Suppression of blob-filament turbulence in the scrape-off layer (SOL) precedes the L–H transition, with the SOL turbulence remaining low throughout the dithering phase, despite the modulation of turbulence levels in the nearby edge. This demonstrates that the SOL turbulence “decouples” from the edge turbulence. The spectral shift in the measured radial wavenumber is corroborated by the direct measurement of eddy tilt angle using a novel time delay analysis technique first developed for Doppler reflectometry [Pinzon et al., Plasma Phys. Controlled Fusion 61, 105009 (2019)] but adapted here for floating potential measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1994

Modeling scramjet combustor flowfields with a grid adaptation scheme

The accurate description of flow features associated with the normal injection of fuel into supersonic primary flows is essential in the design of efficient engines for hypervelocity aerospace vehicles. The flow features in such injections are complex with multiple interactions between shocks and between shocks boundary layers. Numerical studies of perpendicular sonic N2 injection and mixing in a Mach 3.8 scramjet combustor environment are discussed. A dynamic grid adaptation procedure based on the equilibration of spring-mass system is employed to enhanced the description of the complicated flow features. Numerical results are compared with experimental measurements and indicate that the adaptation procedure enhances the capability of the modeling procedure to describe the flow features associated with scramjet combustor components.

Ramakrishnan, R.↗
NASA NTRS1996

Stochastic Filtering of Rain Profiles Using Radar, Surface-Referenced Radar, or Combined Radar-Radiometer Measurements

This paper describes a computationally efficient nearly optimal Bayesian algorithm to estimate rain (and drop size distribution) profiles, given a radar reflectivity profile at a single attenuating wavelength. In addition to estimating the averages of all the mutually ambiguous combinations of rain parameters that can produce the data observed, the approach also calculates the n-ns uncertainty in its estimates (this uncertainty thus quantifies "the amount of ambiguity" in the "solution"). The paper also describes a more general approach that can make estimates based on a radar reflectivity profile together with an approximate measurement of the path-integrated attenuation, or a radar reflectivity profile and a set of passive microwave brightness temperatures. This more general "combined" algorithm is currently being adapted for the Tropical Rainfall Measuring Mission.

Haddad, Ziad S.↗
NASA NTRS2000

Biocybernetic Control of Vigilance Task Parameters

The major focus of the present proposal was to examine psychophysiological variables that are related to hazardous states of awareness induced by monitoring automated systems. With the increased use of automation in today's work environment, people's roles in the work place are being redefined from that of active participant to one of passive monitor. Although the introduction of automated systems has a number of benefits, there are also a number of disadvantages regarding the worker performance. Byrne and Parasuraman (1996) have argued for the use of psychophysiological measures in both the development and the implementation of adaptive automation. While both performance based and model based adaptive automation have been studied, the use of psychophysiological measures, especially EEG, offers the advantage of real time evaluation of the state of the subject. Previous investigations of the closed-loop adaptive automation system in our laboratory, supported by NASA, have employed a compensatory tracking task which involved the use of a joystick to maintain the position of a cursor in the middle of a video screen. This research demonstrated that, in an adaptive automation, closed-loop environment, subjects perform a tracking task better under a negative, compared to a positive, feedback condition. While tracking is comparable to some aspects of flying an airplane, it does not simulate the environment found in the cockpit of modern commercial airplanes. Since a large part of the flying responsibilities in commercial airplanes is automated, the primary responsibility of pilots is to monitor the automation and to respond when the automation fails. Because failures are relatively rare, pilots often suffer from hazardous states of awareness induced by long term vigilance of the automated system. Consequently, the aim of the current study was to investigate the ability of the closed-loop, adaptive automation system in a vigilance paradigm. It is also important to note that tracking involves a continuous, though low level, motor response. Since it is not clear how such activity might affect performance of the adaptive automation system, it was thought to be important to evaluate how the system functioned when there was minimal motor output by the subjects. The current study used the closed-loop system, developed at NASA-Langley Research Center, to control the state of awareness of subjects while they performed a vigilance task. Several experiments were conducted to examine the use of EEG feedback to control a target dimension used in the task. Changes in a subject's arousal, as defined by specific EEG indexes, produced stimulus changes known to affect task performance. In addition, different electrode sites, compared to previous research, were sampled to determine the optimum configuration with regard to the following criteria: (1) task performance and (2) EEG index.

Freeman, Frederick G.↗
DOE OSTI2022

Expanding the range of the resolvable strain from distributed fiber optic sensors using a local adaptive reference approach

Optical frequency domain reflectometry (OFDR) is a spectral measurement technique in which shifts in the local Rayleigh backscatter spectra can be used to perform distributed temperature or strain measurements relative to a reference measurement using ordinary single-mode optical fibers. Here, we demonstrate a data processing methodology for improving the resolvable range of temperature and strain by adaptively varying the reference measurement position by position, based on the time evolution of the local optical intensities and the correlation between the reference and active measurements. These methods nearly double the resolvable range of temperature and strain compared with that achieved using the traditional static reference approach.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Development of Head-Trunk Coordination Measures for Monitoring Postflight Sensorimotor Readaptation Strategies

During exploration missions, individual health assessments will be required to account for variability in neurosensory adaptation and task readiness for the initial extravehicular activities (EVAs). Previous research has identified postflight vestibular alterations and disruptions in head-trunk coordination after both short and long duration spaceflight missions. Astronauts were found to minimize head angular displacement and utilize a consistent forward head tilt theorized as a compensatory approach to stabilize the cephalic system and reduce motion sickness during readaptation to Earth’s gravity. Further, anecdotal self-reports from Shuttle crewmembers stated that pitch and side-to-side head movements immediately post-landing typically resulted in perceived angular self-motion. Notable disruptions also occur upon arrival in orbit, with astronauts choosing waist rotation rather than head movements during dynamic tasks. It is thought that the underlying sensorimotor disruptions may contribute to motion sickness in space and upon landing, postflight gait dysfunction, and inaccurate spatial orientation when performing daily tasks. To better characterize microgravity-induced sensorimotor adaptations, it is important to develop measures and monitoring tools that have high sensitivity in detecting changes in head-trunk coordination.

H M Weiss↗
NASA NTRS1991

Adaptive control with an expert system based supervisory level

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Sullivan, Gerald A.↗
DOE OSTI2023

High-throughput, dynamic, multi-dimensional: an expanding repertoire of plant respiration measurements

A recent burst of technological innovation and adaptation has greatly improved our ability to capture respiration rate data from plant sources. At the tissue level, several independent respiration measurement options are now available, each with distinct advantages and suitability, including high-throughput sampling capacity. These advancements facilitate the inclusion of respiration rate data into large-scale biological studies such as genetic screens, ecological surveys, crop breeding trials, and multi-omics molecular studies. As a result, our understanding of the correlations of respiration with other biological and biochemical measurements is rapidly increasing. Difficult questions persist concerning the interpretation and utilization of respiration data; concepts such as allocation of respiration to growth versus maintenance, the unnecessary or inefficient use of carbon and energy by respiration, and predictions of future respiration rates in response to environmental change are all insufficiently grounded in empirical data. However, we emphasize that new experimental designs involving novel combinations of respiration rate data with other measurements will flesh-out our current theories of respiration. Furthermore, dynamic recordings of respiration rate, which have long been used at the scale of mitochondria, are increasingly being used at larger scales of size and time to reflect processes of cellular signal transduction and physiological response to the environment. Herein, we also highlight how respiratory methods are being better adapted to different plant tissues including roots and seeds, which have been somewhat neglected historically.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II

We discuss the implementation of a suite of virtual diagnostics at the FACET-II facility currently under commissioning at SLAC National Accelerator Laboratory. The diagnostics will be used for the prediction of the longitudinal phase space along the linac, spectral reconstruction of the bunch profile, and non-destructive inference of transverse beam quality (emittance) while using edge radiation at the injector dogleg and bunch compressor locations. These measurements will be folded into adaptive feedbacks and Machine Learning (ML)-based reinforcement learning controls to improve the stability and optimize the performance of the machine for different experimental configurations. In this paper we describe each of these diagnostics with expected measurement results that are based on simulation data and discuss progress towards implementation in regular operations.

Emma, Claudio (ORCID:0000000247191831)↗
DOE OSTI2025

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

adaptation models↗
DOE OSTI2021

Phase noise limited frequency shift impulsive Raman spectroscopy

We introduce a method to enable optical amplification of a coherent Raman spectroscopy signal, which we call radio frequency (RF) Doppler Raman spectroscopy. In this article, we consider the perturbation of a probe pulse in a sample due to an excited Raman vibrational coherence as a generalized Doppler shift, which connects a time-varying optical path length (the product of the propagation length and refractive index, OPL = n ℓ) with an optical frequency shift. Amplification of a Raman signal outside of the focused interaction is enabled by converting the Doppler frequency shift experienced by a laser probe pulse into a periodic timing jitter. This transit time perturbation is detected through the phase of a RF electronic signal measured at a harmonic of the probe pulse train with a method adapted from precision metrology techniques used to measure laser pulse train timing jitter. Measurement of a timing jitter allows access to much lower noise floors than other coherent Raman techniques, and by exploiting the new capability to scale the signal of a coherent Raman spectroscopic signal, this method opens the potential to detect very weak Raman signals that are currently not observable due to limits of illumination intensity imposed by laser damage to the specimen and noise.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Adaptively coupled phase retrieval in multi-peak Bragg coherent diffraction imaging

Recent advances in Bragg coherent diffraction imaging (BCDI) experimental techniques permit routine measurement of multiple Bragg peaks from a single crystalline grain. The resulting images contain the full lattice distortion vector field which can be differentiated to provide lattice strain and rotation. With the advent of fourth-generation synchrotron light sources, such multi-peak datasets are produced at high rates, facilitating the need for rapid phase retrieval of the multiple peaks and subsequent image analysis. Here we describe and demonstrate a new implementation of a coupled phase retrieval technique for multi-peak BCDI which simultaneously treats each Bragg peak of the dataset and produces a three-dimensional image of the crystal's morphology and lattice distortion field. In addition, this method uses the redundant information contained in the various Bragg diffraction patterns to detect and suppress spurious signal appearing on the detector in a subset of the measurements. Compared with manual data editing, adaptive coupling produces a more consistent phase profile in reciprocal space and sharper surfaces in direct space, with no significant difference in computational cost. These improvements reduce the need for manual preprocessing and enable robust high-throughput analysis of multi-peak BCDI data, supporting near-real-time strain microscopy at modern synchrotron facilities.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Structured estimation - Sample size reduction for adaptive pattern classification

The Gaussian two-category classification problem with known category mean value vectors and identical but unknown category covariance matrices is considered. The weight vector depends on the unknown common covariance matrix, so the procedure is to estimate the covariance matrix in order to obtain an estimate of the optimum weight vector. The measure of performance for the adapted classifier is the output signal-to-interference noise ratio (SIR). A simple approximation for the expected SIR is gained by using the general sample covariance matrix estimator; this performance is both signal and true covariance matrix independent. An approximation is also found for the expected SIR obtained by using a Toeplitz form covariance matrix estimator; this performance is found to be dependent on both the signal and the true covariance matrix.

Morgera, S.↗