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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 811 records · Page 45

All sources NASA NTRS DOE OSTI

NASA NTRS1972

Sequence data - Magnitude and implications of some ambiguities.

A stochastic model is applied to the divergence of the horse-pig lineage from a common ansestor in terms of the alpha and beta chains of hemoglobin and fibrinopeptides. The results are compared with those based on the minimum mutation distance model of Fitch (1972). Buckwheat and cauliflower cytochrome c sequences are analyzed to demonstrate their ambiguities. A comparative analysis of evolutionary rates for various proteins of horses and pigs shows that errors of considerable magnitude are introduced by Glx and Asx ambiguities into evolutionary conclusions drawn from sequences of incompletely analyzed proteins.

Holmquist, R.↗

NASA NTRS1976

Linear and nonlinear analysis of orbital telescope/space shuttle dynamics and control

Work completed on the design and study of an annular suspension and pointing (ASP) system for the space shuttle was presented. This system makes use of a magnetically suspended vernier pointing assembly. The following objectives were pursued in this study: (1) development of a detailed mathematical model of the Space Shuttle/ASP system, (2) design of control laws in order to obtain the desired pointing performance, and (3) prediction of the statistical pointing accuracies in the presence of stochastic disturbances such as crew-motion, and sensor and actuator noise. The first two of these objectives are documented in this report.

Roberts, A. S., Jr.↗

DOE OSTI2022

Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments

Here, we present a novel stochastic approach to binary optimization suited for optimal experimental design (OED) for Bayesian inverse problems governed by mathematical models such as partial differential equations. The OED utility function, namely, the regularized optimality criterion, is cast into a stochastic objective function in the form of an expectation over a multivariate Bernoulli distribution. The probabilistic objective is then solved by using a stochastic optimization routine to find an optimal observational policy. This formulation (a) is generally applicable to binary optimization problems with soft constraints and is ideal for OED and sensor placement problems; (b) does not require differentiability of the original objective function (e.g., a utility function in OED applications) with respect to the design variable, and thus it enables direct employment of sparsity-enforcing penalty functions such as $\ell_0$, without needing to utilize a continuation procedure or apply a rounding technique; (c) exhibits much lower computational cost than traditional gradient-based relaxation approaches; and (d) can be applied to both linear and nonlinear OED problems with proper choice of the utility function. The proposed approach is analyzed from an optimization perspective with detailed convergence analysis of the optimization approach and is also analyzed from a machine learning perspective with correspondence to policy gradient reinforcement learning. The approach is demonstrated numerically by using an idealized two-dimensional Bayesian linear inverse problem and validated by extensive numerical experiments carried out for sensor placement in a parameter identification setup.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Towards Fully Secure 5G Ultra-Low Latency Communications: A Cost-Security Functions Analysis

Future components to enhance the basic, native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered, or lightweight solutions adapted to ultra-reliable low-latency communications (URLLC) but whose security properties remain under discussion. Although different 5G network slices may have different requirements, in general, both visions seem to fall short at provisioning secure URLLC in the future. In this work we address this challenge, by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks. We categorize those new security components into different groups according to their purpose and deployment scope. We propose to analyze them in the context of existing 5G architectures using two different approaches. First, using model checking techniques, we will evaluate the probability of an attacker to be successful against each security solution. Second, using analytical models, we will analyze the impact of these security mechanisms in terms of delay, throughput consumption, and reliability. Finally, we will combine both approaches using stochastic cost-security functions and the PRISM model checker to create a global picture. Our results are first evidence of how a 5G network that covers and strengthened all security areas through enhanced, dedicated non-native mechanisms could only guarantee secure URLLC with a probability of ~55%.

5G networks↗

DOE OSTI2025

Layered patterns of active scalar fields in a two-dimensional magnetohydrodynamic system

Here, we observe the formation of staircase patterns in the magnetic potential (𝐴) in a weakly magnetized two-dimensional magnetohydrodynamic system driven by a forced, fluctuating vortex array. Layering occurs due to inhomogeneous mixing of 𝐴 by vortex cells. Magnetic Reynolds number (𝑅 𝑚 )–dependent quenching of the turbulent diffusion of 𝐴 by weak magnetic fields increases the disparity between the (short) cell circulation time and the (long) time for intercell transport of magnetic potential. Thus, magnetic fields strengthen transport barriers between cells and reinforce the staircase, relative to its passive scalar counterpart. The analysis reveals a feedback mechanism, which promotes staircase formation. Magnetic staircases persist in both the flux expulsion (𝑅 𝑚 ⁢𝑣$^2_𝐴$/𝑈$^2_0$<1) and vortex disruption (𝑅 𝑚 ⁢𝑣$^2_𝐴$/𝑈$^2_0$≥1) limits. In the latter case, residual vortex cells homogenize 𝐴. Global layering morphology is shown to be well characterized by staircase curvature. Stochastic forcing of magnetic potential can support magnetic staircases against resistive decay.

magnetohydrodynamics↗

NASA NTRS1974

Monitoring the sea surface with a short pulse radar

A solution is presented for the scattering of short pulses from a stochastic, corrugated surface relative to the sea for the case of a narrow-beam transmitting antenna pointing near nadir. The spectrum of the received power and its time history are calculated and this solution is used to show that a measure of the variance of the surface ordinant can be obtained from the backscattered power. Included explicitly in the analysis is the finite nature of the source and the role of the small-scale wave structure (capillary wave range). It is shown that when sufficiently short pulses are transmitted, one can obtain a measure of the variance of the large scale surface ordinant from either the temporal spacing of the peaks in the returned power or from the envelope of the spectrum of the received power. Assuming an appropriate model for the statistics and spectrum of the surface ordinate, the variance can be used to compute the wind speed and the significant wave height of the surface.

Le Vine, D. M.↗

DOE OSTI2022

Eagle Behavior and Risk Modeling for Wind Energy Webinar

NREL presents recent progress in the development and validation of new eagle behavioral models, highlighting applications for wind-plant siting and operations. This webinar features talks focused on three areas: atmospheric modeling across the spatiotemporal scales of interest, facility-scale behavioral modeling, and turbine-scale data-driven behavioral modeling. A final presentation demonstrates micrositing as an application of our completely open-source analysis framework.

agent-based movement model↗

DOE OSTI2022

Stress-controlled fatigue of HfNbTaTiZr high-entropy alloy and associated deformation and fracture mechanisms

The stress-controlled fatigue tests are carried out at a stress ratio of 0.1 and a frequency of 10 Hz, and span both low-cycle and high-cycle regimes by varying the applied stress amplitudes. The high-cycle fatigue regime gives a fatigue strength of 497 MPa and a fatigue ratio of 0.44. At equivalent conditions, the alloy's fatigue strength is greater than all other high-entropy alloys (HEAs) with reported high-cycle fatigue data, dilute body-centered cubic alloys, and many structural alloys such as steels, titanium alloys, and aluminum alloys. Through in-depth analyses of crack-propagation trajectories, fracture-surface morphologies and deformation plasticity by means of various microstructural analysis techniques and theoretical frameworks, the alloy's remarkable fatigue resistance is attributed to delayed crack initiation in the high-cycle regime, which is achieved by retarding the formation of localized persistent slip bands, and its good resistance to crack propagation in the low-cycle regime, which is accomplished by intrinsic toughening backed up by extrinsic toughening. Additionally, the stochastic nature of the fatigue data is neatly captured with a 2-parameter Weibull model.

36 MATERIALS SCIENCE↗

NASA NTRS1972

An adaptive technique for a redundant-sensor navigation system.

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. This adaptive system is structured as a multistage stochastic process of detection, identification, and compensation. It is shown that the detection system can be effectively constructed on the basis of a design value, specified by mission requirements, of the unknown parameter in the actual system, and of a degradation mode in the form of a constant bias jump. A suboptimal detection system on the basis of Wald's sequential analysis is developed using the concept of information value and information feedback. The developed system is easily implemented, and demonstrates a performance remarkably close to that of the optimal nonlinear detection system. An invariant transformation is derived to eliminate the effect of nuisance parameters such that the ambiguous identification system can be reduced to a set of disjoint simple hypotheses tests. By application of a technique of decoupled bias estimation in the compensation system the adaptive system can be operated without any complicated reorganization.

Chien, T.-T.↗

NASA NTRS1984

Algorithms for output feedback, multiple-model, and decentralized control problems

The optimal stochastic output feedback, multiple-model, and decentralized control problems with dynamic compensation are formulated and discussed. Algorithms for each problem are presented, and their relationship to a basic output feedback algorithm is discussed. An aircraft control design problem is posed as a combined decentralized, multiple-model, output feedback problem. A control design is obtained using the combined algorithm. An analysis of the design is presented.

Halyo, N.↗

NASA NTRS1990

An approach to rescheduling activities based on determination of priority and disruptivity

A constraint-based scheduling system called SPIKE is being used to create long term schedules for the Hubble Space Telescope. Feedback for the spacecraft or from other ground support systems may invalidate some scheduling decisions and those activities concerned must be reconsidered. A function rescheduling priority is defined which for a given activity performs a heuristic analysis and produces a relative numerical value which is used to rank all such entities in the order that they should be rescheduled. A function disruptivity is also defined that is used to place a relative numeric value on how much a pre-existing schedule would be changed in order to reschedule an activity. Using these functions, two algorithms (a stochastic neural network approach and an exhaustive search approach) are proposed to find the best place to reschedule an activity. Prototypes were implemented and preliminary testing reveals that the exhaustive technique produces only marginally better results at much greater computational cost.

Sponsler, Jeffrey L.↗

NASA NTRS2002

A statistical model for interpreting computerized dynamic posturography data

Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.

NASA Discipline Neuroscience↗

DOE OSTI2020

GoldSim E-Area Low-Level Waste Facility Aquifer Zone Model Calibration Methodology

This report documents the development and calibration of the E-Area Low-Level Waste Facility (ELLWF) Gold Sim aquifer model. It provides a methodology on how a Gold Sim aquifer model can be calibrated to specific PORFLOW-based aquifer predictions. The calibration activity presented within this report focuses on the Slit Trench #06 (ST06) location that resides within the center set of Slit Trenches. This Gold Sim-based aquifer model is a generic model capable of being calibrated to any of the other trench locations within E-Area. In addition, subsequent activities (beyond the scope of this effort) will couple this GoldSim-based aquifer model to various GoldSim-based trench models, with the intent of performing stochastic analyses that couple all pertinent fate and transport processes from the ground surface up to the 100-m point of assessment (POA).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1990

Performability analysis using semi-Markov reward processes

Beaudry (1978) proposed a simple method of computing the distribution of performability in a Markov reward process. Two extensions of Beaudry's approach are presented. The method is generalized to a semi-Markov reward process by removing the restriction requiring the association of zero reward to absorbing states only. The algorithm proceeds by replacing zero-reward nonabsorbing states by a probabilistic switch; it is therefore related to the elimination of vanishing states from the reachability graph of a generalized stochastic Petri net and to the elimination of fast transient states in a decomposition approach to stiff Markov chains. The use of the approach is illustrated with three applications.

Ciardo, Gianfranco↗

NASA NTRS2005

Life Modeling and Design Analysis for Ceramic Matrix Composite Materials

The primary research efforts focused on characterizing and modeling static failure, environmental durability, and creep-rupture behavior of two classes of ceramic matrix composites (CMC), silicon carbide fibers in a silicon carbide matrix (SiC/SiC) and carbon fibers in a silicon carbide matrix (C/SiC). An engineering life prediction model (Probabilistic Residual Strength model) has been developed specifically for CMCs. The model uses residual strength as the damage metric for evaluating remaining life and is posed probabilistically in order to account for the stochastic nature of the material s response. In support of the modeling effort, extensive testing of C/SiC in partial pressures of oxygen has been performed. This includes creep testing, tensile testing, half life and residual tensile strength testing. C/SiC is proposed for airframe and propulsion applications in advanced reusable launch vehicles. Figures 1 and 2 illustrate the models predictive capabilities as well as the manner in which experimental tests are being selected in such a manner as to ensure sufficient data is available to aid in model validation.

Source record↗

DOE OSTI2020

Measurement Uncertainty in One-Of-A-Kind Event Data Analysis

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable, have unavoidable built-in differences resulting in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates over the measurement uncertainty. Range of true values depends on built-in differences in physics of the experiment. Stochastic physical processes result typically in a broader range of true values than non-stochastic processes do. Measurement uncertainty depends on a measurement method (properties of the detector not of the experiment). Modern measurement methods, including digital ones, frequently make the measurement uncertainty very small. When data from one–of –a kind experiment are analyzed, only the measurement uncertainty is reported. It provides no information about the range of true experimental values, neither about reliability of a reported data point. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable. Methods for data analysis from an experiment repeated statistically significant number of times are very well developed. They do not require a detailed expertise in physics of an experiment, nor in the properties of the measurement system used, and meaning of the reported uncertainty is well understood in any scientific community. It all changes when data from one-of-a-kind experiment is analyzed. Analyst’s expertise is required both in the physics of the experiment and in all aspects of the measurement system, all possible malfunctions. Data users must remember that only measurement uncertainty is reported from any one-of-a-kind experiment. Theory with simulations may provide estimation of expected built-in differences in the experiment, and by this of expected range of true values for a given experiment; yet measurement uncertainty can never be used in place of the range of true experimental values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Perturbative analysis of low-frequency instabilities in high-field ST40 experiments

Abstract Linear and nonlinear perturbative analyses of low-frequency instabilities are presented for ST40 spherical torus high field plasmas, with simultaneous neutral beam heating due to two tangential sources at 25 keV and 55 keV. Initial plasma profiles on which the TRANSP and NUBEAM codes were based were obtained using an integrated analysis of several diagnostics including line-of-sight integrated and volume average measurements, as well as limited profile information from a charge-exchange-recombination spectrometer. Magnetohydrodynamics (MHD) analysis using the NOVA/NOVA-K codes suggests that the modes in the experiments are core-localized n = 1 eigenmodes with mixed acoustic and electromagnetic Alfvénic polarization. The global transport combined with the perturbative mode analysis indicates that there is greater tendency for bursty chirping response as the level of background micro-turbulence decreases in time and those predictions are shown to be consistent with the experimental data. This finding is interpreted in terms of the suppression of coherent phase-space structures that support chirping when the resonant fast ion dynamics is dominated by frequent stochastic, orbit-decorrelating events.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Interpretable Data-Driven Probabilistic Power System Load Margin Assessment with Uncertain Renewable Energy and Loads

The increasing uncertainties caused by the high-penetration of stochastic renewable generation resources poses a significant threat to the power system voltage stability. To address this issue, this paper proposes a probabilistic deep kernel learning enabled surrogate model to extract the hidden relationship between uncertain sources, i.e., wind power and loads, and load margin for probabilistic load margin assessment (PLMA). Unlike other deep learning approaches, a kernel SHAP provides the sensitivity analysis as well as interpretability of the inputs to outputs influences. This allows identifying the critical factors that affect load margin so that corrective control can be initiated for stability enhancement. Numerical results carried out on the IEEE 118-bus power system demonstrate the accuracy and efficiency of the proposed data-driven PLMA scheme.

deep kernel learning↗