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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Cranial diameter pulsations measured by non-invasive ultrasound decrease with tilt

INTRODUCTION: Intracranial pressure (ICP) may play a significant role in physiological responses to microgravity by contributing to the nausea associated with microgravity exposure. However, effects of altered gravity on ICP in astronauts have not been investigated, primarily due to the invasiveness of currently available techniques. We have developed an ultrasonic device that monitors changes in cranial diameter pulsation non-invasively so that we can evaluate ICP dynamics in astronauts during spaceflight. This study was designed to demonstrate the feasibility of our ultrasound technique under the physiological condition in which ICP dynamics are changed due to altered gravitational force. METHODS: Six healthy volunteers were placed at 60 degrees head-up, 30 degrees headup, supine, and 15 degrees head-down positions for 3 min at each angle. We measured arterial blood pressure (ABP) with a finger pressure cuff, and cranial diameter pulsation with a pulsed phase lock loop device (PPLL). RESULTS: Analysis of covariance demonstrated that amplitudes of cranial diameter pulsations were significantly altered with the angle of tilt (p < 0.001). The 95% confidence interval for linear regression coefficients of the cranial diameter pulsation amplitudes with tilt angle was 0.862 to 0.968. However, ABP amplitudes did not show this relationship. DISCUSSION: Our noninvasive ultrasonic technique reveals that the amplitude of cranial diameter pulsation decreases as a function of tilt angle, suggesting that ICP pulsation follows the same relationship. It is demonstrated that the PPLL device has a sufficient sensitivity to detect changes non-invasively in ICP pulsation caused by altered gravity.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS2012

Particle Filtering for Model-Based Anomaly Detection in Sensor Networks

A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that postprocesses a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly. In order to reduce the involvement of domain experts significantly, several data-driven approaches have been proposed where models are automatically acquired from the data, thus bypassing the cost and effort of building system models. Many supervised learning methods can efficiently learn operational and fault models, given large amounts of both nominal and fault data. However, for domains such as RETS data, the amount of anomalous data that is actually available is relatively small, making most supervised learning methods rather ineffective, and in general met with limited success in anomaly detection. The fundamental problem with existing approaches is that they assume that the data are iid, i.e., independent and identically distributed, which is violated in typical RETS data. None of these techniques naturally exploit the temporal information inherent in time series data from the sensor networks. There are correlations among the sensor readings, not only at the same time, but also across time. However, these approaches have not explicitly identified and exploited such correlations. Given these limitations of model-free methods, there has been renewed interest in model-based methods, specifically graphical methods that explicitly reason temporally. The Gaussian Mixture Model (GMM) in a Linear Dynamic System approach assumes that the multi-dimensional test data is a mixture of multi-variate Gaussians, and fits a given number of Gaussian clusters with the help of the wellknown Expectation Maximization (EM) algorithm. The parameters thus learned are used for calculating the joint distribution of the observations. However, this GMM assumption is essentially an approximation and signals the potential viability of non-parametric density estimators. This is the key idea underlying the new approach.

Solano, Wanda↗
NASA NTRS2018

Operator Trust Function for Predicted Drone Arrival

To realize the full benefit from autonomy, systems will have to react to unknown events and uncertain dynamic environments. The resulting number of behaviors is essentially infinite; thus, the system is effectively non-deterministic but an operator needs to understand and trust the actions of the autonomous vehicles. This research began to tackle non-deterministic systems and trust by beginning to develop a user trust function based on intent information displayed and the prescribed bounds on allowable behaviors/actions of the non-deterministic system. Linear regression shows promise on being able to predict a person’s confidence of the machine’s prediction. Linear regression techniques indicated that subject characteristics, scenario difficulty, the experience with the system, and confidence earlier in the scenario account for approximately 60% of the variation in confidence ratings. This paper details the specifics of the liner regression model – essentially a trust function – for predicting a person’s confidence.

Trujillo, Anna C.↗
DOE OSTI2021

Dynamics of disordered mechanical systems with large connectivity, free probability theory, and quasi-Hermitian random matrices

Disordered mechanical systems with high connectivity represent a limit opposite to the more familiar case of disordered crystals. Individual ions in a crystal are subjected essentially to nearest-neighbor interactions. In contrast, the systems studied in this paper have all their degrees of freedom coupled to each other. Thus, the problem of linearized small oscillations of such systems involves two full positive-definite and non-commuting matrices, as opposed to the sparse matrices associated with disordered crystals. Consequently, the familiar methods for determining the averaged vibrational spectra of disordered crystals, introduced many years ago by Dyson and Schmidt, are inapplicable for highly connected disordered systems. In this paper we apply random matrix theory (RMT) to calculate the averaged vibrational spectra of such systems, in the limit of infinitely large system size. At the heart of our analysis lies a calculation of the average spectrum of the product of two positive definite random matrices by means of free probability theory techniques. We also show that this problem is intimately related with quasi-hermitian random matrix theory (QHRMT), which means that the ‘hamiltonian’ matrix is hermitian with respect to a non-trivial metric. This extends ordinary hermitian matrices, for which the metric is simply the unit matrix. The analytical results we obtain for the spectrum agree well with our numerical results. The latter also exhibit oscillations at the high-frequency band edge, which fit well the Airy kernel pattern. We also compute inverse participation ratios of the corresponding amplitude eigenvectors and demonstrate that they are all extended, in contrast with conventional disordered crystals. Finally, we compute the thermodynamic properties of the system from its spectrum of vibrations. In addition to matrix model analysis, we also study the vibrational spectra of various multi-segmented disordered pendula, as concrete realizations of highly connected mechanical systems. A universal feature of the density of vibration modes, common to both pendula and the matrix model, is that it tends to a non-zero constant at vanishing frequency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Higher-order tails and RG flows due to scattering of gravitational radiation from binary inspirals

Abstract We establish and develop a novel methodology to treat higher-order non-linear effects of gravitational radiation that is scattered from binary inspirals, which employs modern scattering-amplitudes methods on the effective picture of the binary as a composite particle. We spell out our procedure to study such effects: assembling tree amplitudes via generalized-unitarity methods and employing the closed-time-path formalism to derive the causal effective actions, which encompass the full conservative and dissipative dynamics. We push through to a new state of the art for these higher-order effects, up to the third subleading tail effect, at order$$ {G}_N^5 $$ G N 5 and the 5-loop level, which corresponds to the 8.5PN order. We formulate the consequent dissipated energy for these higher-order corrections, and carry out a renormalization analysis, where we uncover new subleading RG flow of the quadrupole coupling. For all higher-order tail effects we find perfect agreement with partial observable results in PN and self-force theories, where available.

Physics↗
DOE OSTI2021

A new coupled multiphase flow–finite strain deformation–fault slip framework for induced seismicity

Production of hydrocarbons and water from subsurface reservoirs are known to cause permanent deformation of the reservoir and seismicity along faults both of which are detrimental to sustainable development of natural resources. Most of the prior studies on understanding fluid flow-induced plasticity and seismicity have focused on one or the other phenomenon due to the numerical difficulty associated with simultaneous modeling of the two failure phenomena because stress and deformation evolve non-linearly in both plasticity and seismicity. However, in reservoirs undergoing long-term production, plastic failure can alter the stress paths of points on a fault such that the onset, location, and magnitude of actual seismic events can no longer be predicted by a poroelastic simulation due to inaccurate stress and deformation history. We present a computational framework for coupled multiphase flow, finite strain poroplastic deformation, and dynamic fault slip and use it to understand the impact of plastic deformation on the onset, location, and magnitude of induced fault slip events. We evaluate the impact of plasticity on reservoir pressure, deformation, induced stress, and fault slip by comparing infinitesimal strain elastic and finite strain poro-elastoplastic models. For real-world applications, we consider different scenarios where the reservoir is either mechanically weaker or stronger than the caprock. We analyze the stress evolution as a function of the change in reservoir pressure to understand the role of contrast in reservoir and caprock elastic moduli on geomechanical stability. The results show that the poroplastic reservoir exhibits larger vertical deformation and delayed slip than the poroelastic reservoir after the same amount of oil production. For the same amount of pressure drop, a reservoir with a smaller modulus than the caprock displays a larger vertical displacement and an earlier onset of both plastic failure and fault slip. For a reservoir with a larger modulus than the caprock, vertical displacement is larger on the reservoir top boundary and smaller on the ground surface, and a higher pressure drop is needed to induce plastic failure and fault slip.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Power matching to pulsed inductively coupled plasmas

Matching of power delivery to nonlinear loads in plasma processing is a continuing challenge. Plasma reactors used in microelectronics fabrication are increasingly multi-frequency and/or pulsed, producing a non-linear and, in many cases, non-steady state electrical termination that can complicate efficient power coupling to the plasma. This is particularly the case for pulsed inductively coupled plasmas where the impedance of the plasma can significantly change during the start-up-transient and undergo an E–H (capacitive-to-inductive) transition. In this paper, we discuss the results from a computational investigation of the dynamics of power matching to pulsed inductively coupled plasmas (Ar/Cl 2 mixtures of tens of mTorr pressure) using fixed component impedance matching networks and their consequences on plasma properties. In this investigation, we used set-point matching where the components of the matching network provide a best-case impedance match (relative to the characteristic impedance of the power supply) at a chosen time during the pulsed cycle. Matching impedance early during the pulse enables power to feed the E-mode, thereby emphasizing capacitive coupling and large excursions in the plasma potential. This early power coupling enables a more rapid ramp-up in plasma density while being mismatched during the H-mode later in the pulse. The early match also produces more energetic ion bombardment of surfaces. Matching late in the pulse diminishes power dissipated in the E-mode at the cost of also reducing the rate of increase in plasma density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Estimating and Calibrating DER Model Parameters Using Levenberg–Marquardt Algorithm in Renewable Rich Power Grid

The proliferation of inverter-based distributed energy resources (IBDERs) has increased the number of control variables and dynamic interactions, leading to new grid control challenges. For stability analysis and designing appropriate protection controls, it is important that IBDER models are accurate. This paper focuses on the accurate estimation and parameter calibration of DER_A, a recently proposed aggregated IBDER model. In particular, we focus on the parameters of the reactive power–voltage regulation module. We formulate the problem of parameter tuning as a non-linear least square minimization problem and solve it using the Levenberg–Marquardt (LM) method. The LM method is primarily chosen due to its flexibility in adaptively selecting between the steepest descent and Gauss–Newton methods through a damping parameter. The LM approach is used to minimize the error between the actual measurements and the estimated response of the model. Further, the computational challenges posed by the numerical calculation of the Jacobian are tackled using a quasi-Newton root-finding approach. The proposed method is validated on a real feeder model in the northeastern part of the United States. The feeder is modeled in OpenDSS and the measurements thus obtained are fed to the DER_A model for calibration. The simulation results indicate that our approach is able to successfully calibrate the relevant model parameters quickly and with high accuracy, with a total sum of square error of 3.57 × 10 –7 .

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1998

On Convergence Acceleration Techniques for Unstructured Meshes

A discussion of convergence acceleration techniques as they relate to computational fluid dynamics problems on unstructured meshes is given. Rather than providing a detailed description of particular methods, the various different building blocks of current solution techniques are discussed and examples of solution strategies using one or several of these ideas are given. Issues relating to unstructured grid CFD problems are given additional consideration, including suitability of algorithms to current hardware trends, memory and cpu tradeoffs, treatment of non-linearities, and the development of efficient strategies for handling anisotropy-induced stiffness. The outlook for future potential improvements is also discussed.

Mavriplis, Dimitri J.↗
NASA NTRS1993

Testing approximations for non-linear gravitational clustering

The accuracy of various analytic approximations for following the evolution of cosmological density fluctuations into the nonlinear regime is investigated. The Zel'dovich approximation is found to be consistently the best approximation scheme. It is extremely accurate for power spectra characterized by n = -1 or less; when the approximation is 'enhanced' by truncating highly nonlinear Fourier modes the approximation is excellent even for n = +1. The performance of linear theory is less spectrum-dependent, but this approximation is less accurate than the Zel'dovich one for all cases because of the failure to treat dynamics. The lognormal approximation generally provides a very poor fit to the spatial pattern.

Coles, Peter↗
DOE OSTI2022

Can electric fields drive chemistry for an aqueous microdroplet?

Abstract Reaction rates of common organic reactions have been reported to increase by one to six orders of magnitude in aqueous microdroplets compared to bulk solution, but the reasons for the rate acceleration are poorly understood. Using a coarse-grained electron model that describes structural organization and electron densities for water droplets without the expense of ab initio methods, we investigate the electric field distributions at the air-water interface to understand the origin of surface reactivity. We find that electric field alignments along free O–H bonds at the surface are ~16 MV/cm larger on average than that found for O–H bonds in the interior of the water droplet. Furthermore, electric field distributions can be an order of magnitude larger than the average due to non-linear coupling of intramolecular solvent polarization with intermolecular solvent modes which may contribute to even greater surface reactivity for weakening or breaking chemical bonds at the droplet surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1983

Transonic pressure distributions on a rectangular supercritical wing oscillating in pitch

Steady and unsteady aerodynamic data were measured on a rectangular wing with a 12 percent thick supercritical airfoil mounted in the NASA Langley Transonic Dynamics Tunnel. The wing was oscillated in pitch to generate the unsteady aerodynamic data. The purpose of the wind-tunnel test was to measure data for use in the development and assessment of transonic analytical codes. The effects on the wing pressure distributions of Mach number, mean angle of attack, and oscillation frequency and amplitude were measured. Results from the newly-developed XTRAN3S program (a non-linear transonic small disturbance code) and from the RHOIV program (a linear lifting surface kernel function code) were compared to measured data for a Mach number of 0.7 and for oscillation frequencies ranging from 0 to 20 Hz. The XTRAN3S steady and unsteady results agreed fairly well with the measured data. The RHOIV unsteady-result agreement was fair but, of course, did not predict shock effects.

Ricketts, R. H.↗
NASA NTRS1996

Dust Coagulation in Protoplanetary Accretion Disks

The time evolution of dust particles in circumstellar disk-like structures around protostars and young stellar objects is discussed. In particular, we consider the coagulation of grains due to collisional aggregation. The coagulation of the particles is calculated by solving numerically the non-linear Smoluchowski equation. The different physical processes leading to relative velocities between the grains are investigated. The relative velocities may be induced by Brownian motion, turbulence and drift motion. Starting from different regimes which can be identified during the grain growth we also discuss the evolution of dust opacities. These opacities are important for both the derivation of the circumstellar dust mass from submillimeter/millimeter continuum observations and the dynamical behavior of the disks. We present results of our numerical studies of the coagulation of dust grains in a turbulent protoplanetary accretion disk described by a time-dependent one-dimensional (radial) alpha-model. For several periods and disk radii, mass distributions of coagulated grains have been calculated. From these mass spectra, we determined the corresponding Rosseland mean dust opacities. The influence of grain opacity changes due to dust coagulation on the dynamical evolution of a protostellar disk is considered. Significant changes in the thermal structure of the protoplanetary nebula are observed. A 'gap' in the accretion disk forms at the very frontier of the coagulation, i.e., behind the sublimation boundary in the region between 1 and 5 AU.

Schmitt, W.↗
NASA NTRS1997

Detection of chaotic determinism in time series from randomly forced maps

Time series from biological system often display fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". Despite this effort, it has been difficult to establish the presence of chaos in time series from biological sytems. The output from a biological system is probably the result of both its internal dynamics, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes, i.e., a positive characteristic exponent that leads to sensitivity to initial conditions. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Non-NASA Center↗
NASA NTRS2011

Non-Contact Thrust Stand Calibration Method for Repetitively-Pulsed Electric Thrusters

A thrust stand calibration technique for use in testing repetitively-pulsed electric thrusters for in-space propulsion has been developed and tested using a modified hanging pendulum thrust stand. In the implementation of this technique, current pulses are applied to a solenoidal coil to produce a pulsed magnetic field that acts against the magnetic field produced by a permanent magnet mounted to the thrust stand pendulum arm. The force on the magnet is applied in this non-contact manner, with the entire pulsed force transferred to the pendulum arm through a piezoelectric force transducer to provide a time-accurate force measurement. Modeling of the pendulum arm dynamics reveals that after an initial transient in thrust stand motion the quasisteady average deflection of the thrust stand arm away from the unforced or zero position can be related to the average applied force through a simple linear Hooke s law relationship. Modeling demonstrates that this technique is universally applicable except when the pulsing period is increased to the point where it approaches the period of natural thrust stand motion. Calibration data were obtained using a modified hanging pendulum thrust stand previously used for steady-state thrust measurements. Data were obtained for varying impulse bit at constant pulse frequency and for varying pulse frequency. The two data sets exhibit excellent quantitative agreement with each other as the constant relating average deflection and average thrust match within the errors on the linear regression curve fit of the data. Quantitatively, the error on the calibration coefficient is roughly 1% of the coefficient value.

Wong, Andrea R.↗
DOE OSTI2023

Rapid activation of non-oriented mechanophores via shock loading and spallation

Mechanophores (MPs), stimuli-responsive molecules that respond chromatically to mechanochemical reactions, are important for understanding the coupling between mechanics and chemistry as well as in engineering applications. However, the atomic-level understanding of their activation originates from gas phase studies or under simple linear elongation forces directly on molecules or polymer chains containing MPs. The effect of many-body distortions, pervasive in condensed-phase applications, is not understood. Therefore, we performed large-scale molecular dynamics (MD) simulations of a poly(methyl methacrylate)-spiropyran copolymer under dynamic mechanical loading and studied the activation of the MP under various conditions from dynamical compression to tension during unloading. Detailed analysis of the all-atom MD trajectories shows that the MP blocks experience significant many-body intramolecular distortion that can significantly decrease the activation barrier as compared with when deformation rates are slow relative to molecular relaxation time scales. Here we find that the reactivity of MPs under material compression states is governed by many-body effects of intramolecular torsions, whereas under tension, the reactions are governed by tensile stresses.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Delta modulation

The results are presented of a study dealing with the problems of source encoding using delta modulation. An algorithm is described which was employed in the design of an adaptive delta modulation. The algorithm is extremely inexpensive to implement and features extremely desirable characteristics such as a 40 db dynamic range and a 90 percent non-redundant word intelligibility at a bit rate of 9.6 kb/s. A new concept is presented in delta modulation design, the nth-order delta modulator. The nth order delta modulator increases the maximum SNR of a delta modulator but not its dynamic range. It is shown that a 2nd order delta modulator, which employs two delta modulators in cascade, results in a 15 db output SNR improvement over a linear delta modulator operating at 27 db. Two additional areas of research are discussed. The first area involves decomposition of voice and the second is concerned with the source encoding of video signals.

Schilling, D. L.↗
NASA NTRS1995

Linear and nonlinear trending and prediction for AVHRR time series data

The variability of AVHRR calibration coefficient in time was analyzed using algorithms of linear and non-linear time series analysis. Specifically we have used the spline trend modeling, autoregressive process analysis, incremental neural network learning algorithm and redundancy functional testing. The analysis performed on available AVHRR data sets revealed that (1) the calibration data have nonlinear dependencies, (2) the calibration data depend strongly on the target temperature, (3) both calibration coefficients and the temperature time series can be modeled, in the first approximation, as autonomous dynamical systems, (4) the high frequency residuals of the analyzed data sets can be best modeled as an autoregressive process of the 10th degree. We have dealt with a nonlinear identification problem and the problem of noise filtering (data smoothing). The system identification and filtering are significant problems for AVHRR data sets. The algorithms outlined in this study can be used for the future EOS missions. Prediction and smoothing algorithms for time series of calibration data provide a functional characterization of the data. Those algorithms can be particularly useful when calibration data are incomplete or sparse.

Smid, J.↗