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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 1,477 records · Page 82

Moire interferometry for thermal expansion of composites

Moire interferometry by reflection is described and demonstrated for the case of a real reference grating of 1200 lines/mm. Extraneous beams can be displaced and stopped by using a wedge-shaped air gap between reference and specimen gratings. Double-order dominance, the use of diffraction sequences for reflection, the isolation of preferred sequences, and the use of two-beam interference are discussed. Experimental accuracy is enhanced significantly by using several data points to establish displacements along a line, and random errors characterized by one standard deviation can be as small as one microstrain. The method is well adapted to thermal environments, coefficients of thermal expansion of selected graphite-epoxy laminates being determined in the temperature range of 297-422 K. Very good precision was achieved for a wide range of thermal expansion coefficients, from approximately zero to 27 microstrains/K.

Bowles, D. E.↗

Dynamic stress intensity analysis of cracked panels

A spectral analysis method is presented for the extraction of frequency dependent strain energy release rates and stress intensity factors. The approach is based on the crack closure technique and is formulated directly in the frequency domain. Because of this, it is computationally more efficient than an alternative time domain approach for systems exhibiting peak behavior. The method is demonstrated for a center cracked panel subject to static in-plane and random acoustic loading.

Rizzi, Stephen A.↗

Science with High Spatial Resolution Far-Infrared Data

The goal of this workshop was to discuss new science and techniques relevant to high spatial resolution processing of far-infrared data, with particular focus on high resolution processing of IRAS data. Users of the maximum correlation method, maximum entropy, and other resolution enhancement algorithms applicable to far-infrared data gathered at the Infrared Processing and Analysis Center (IPAC) for two days in June 1993 to compare techniques and discuss new results. During a special session on the third day, interested astronomers were introduced to IRAS HIRES processing, which is IPAC's implementation of the maximum correlation method to the IRAS data. Topics discussed during the workshop included: (1) image reconstruction; (2) random noise; (3) imagery; (4) interacting galaxies; (5) spiral galaxies; (6) galactic dust and elliptical galaxies; (7) star formation in Seyfert galaxies; (8) wavelet analysis; and (9) supernova remnants.

Terebey, Susan↗

Temperature dependence of Lorentz air-broadening and pressure-shift coefficients of (12)CH4 lines in the 2.3-micron spectral region

High-resolution (0.01/cm) absorption spectra of lean mixtures of CH4 in dry air were recorded with the McMath-Pierce Fourier transform spectrometer (FTS) of the National Solar Observatory on Kitt Peak at various temperatures between 24 and -61 C. The spectra have been analyzed to determine the values at room temperature of pressure-broadened widths and pressure-induced shifts of more than 740 transitions. The temperature dependence of air-broadened widths and pressure-induced shifts was deduced for approx. 370 transitions in the nu(sub 1) + nu(sub 4), nu(sub 3) + nu(sub 4), and nu(sub 2) + nu(sub 3) bands of (12)CH4 located between 4118 and 4615/cm. These results were obtained by analyzing a total of 29 spectra simultaneously using a multi-spectral non-linear least-squares fitting technique. This new technique allowed the determination of correlated spectral line parameters (e.g. intensity and broadening coefficient) better than the procedure of averaging values obtained by fitting the spectra individually. This method also provided a direct determination of the uncertainties in the retrieved parameters due to random errors. For each band analysed in this study the dependence of the various spectral line parameters upon the tetrahedral symmetry species and the rotational quantum numbers of the transitions is also presented.

Devi, V. Malathy↗

Analysis of Ceramic Color by Special Reflectance

Radiometric and visual techniques are compared as quantitative methods for determining pottery color. An analysis of fifty-two prehistoric sherds selected at random from a multicomponent site indicates that there is an increase in the accuracy and efficiency in determining color using a spectroradiometer over subjective visual observations. Further, radiometric data can be transformed to CIE chromacity coordinates and Munsell color from spectral reflectance curves and analysed directly to access quantitative accuracy.

Giardino, Marco↗

Postural control model interpretation of stabilogram diffusion analysis

Collins and De Luca [Collins JJ. De Luca CJ (1993) Exp Brain Res 95: 308-318] introduced a new method known as stabilogram diffusion analysis that provides a quantitative statistical measure of the apparently random variations of center-of-pressure (COP) trajectories recorded during quiet upright stance in humans. This analysis generates a stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons. SDFs have a characteristic two-part form that suggests the presence of two different control regimes: a short-term open-loop control behavior and a longer-term closed-loop behavior. This paper demonstrates that a very simple closed-loop control model of upright stance can generate realistic SDFs. The model consists of an inverted pendulum body with torque applied at the ankle joint. This torque includes a random disturbance torque and a control torque. The control torque is a function of the deviation (error signal) between the desired upright body position and the actual body position, and is generated in proportion to the error signal, the derivative of the error signal, and the integral of the error signal [i.e. a proportional, integral and derivative (PID) neural controller]. The control torque is applied with a time delay representing conduction, processing, and muscle activation delays. Variations in the PID parameters and the time delay generate variations in SDFs that mimic real experimental SDFs. This model analysis allows one to interpret experimentally observed changes in SDFs in terms of variations in neural controller and time delay parameters rather than in terms of open-loop versus closed-loop behavior.

NASA Program Biomedical Research and Countermeasur↗

Circular Data Images for Directional Data

Directional data includes vectors, points on a unit sphere, axis orientation, angular direction, and circular or periodic data. The theoretical statistics for circular data (random points on a unit circle) or spherical data (random points on a unit sphere) are a recent development. An overview of existing graphical methods for the display of directional data is given. Cross-over occurs when periodic data are measured on a scale for the measurement of linear variables. For example, if angle is represented by a linear color gradient changing uniformly from dark blue at -180 degrees to bright red at +180 degrees, the color image will be discontinuous at +180 degrees and -180 degrees, which are the same location. The resultant color would depend on the direction of approach to the cross-over point. A new graphical method for imaging directional data is described, which affords high resolution without color discontinuity from "cross-over". It is called the circular data image. The circular data image uses a circular color scale in which colors repeat periodically. Some examples of the circular data image include direction of earth winds on a global scale, rocket motor internal flow, earth global magnetic field direction, and rocket motor nozzle vector direction vs. time.

Morpet, William J.↗

Active learning in the presence of unlabelable examples

We propose a new active learning framework where the expert labeler is allowed to decline to label any example. This may be necessary because the true label is unknown or because the example belongs to a class that is not part of the real training problem. We show that within this framework, popular active learning algorithms (such as Simple) may perform worse than random selection because they make so many queries to the unlabelable class. We present a method by which any active learning algorithm can be modified to avoid unlabelable examples by training a second classifier to distinguish between the labelable and unlabelable classes. We also demonstrate the effectiveness of the method on two benchmark data sets and a real-world problem.

active learning↗

Sensitivity of Polar Stratospheric Ozone Loss to Uncertainties in Chemical Reaction Kinetics

Several recent observational and laboratory studies of processes involved in polar stratospheric ozone loss have prompted a reexamination of aspect of out understanding for this key indicator of global change. To a large extent, our confidence in understanding and projecting changes in polar and global ozone is based on our ability to to simulate these process in numerical models of chemistry and transport. These models depend on laboratory-measured kinetic reaction rates and photlysis cross section to simulate molecular interactions. In this study we use a simple box-model scenario for Antarctic ozone to estimate the uncertainty in loss attributable to known reaction kinetic uncertainties. Following the method of earlier work, rates and uncertainties from the latest laboratory evaluation are applied in random combinations. We determine the key reaction and rates contributing the largest potential errors and compare the results to observations to evaluate which combinations are consistent with atmospheric data. Implications for our theoretical and practical understanding of polar ozone loss will be assessed.

Kawa, S. Randolph↗

Sensitivity of Polar Stratospheric Ozone Loss to Uncertainties in Chemical Reaction Kinetics

Several recent observational and laboratory studies of processes involved in polar stratospheric ozone loss have prompted a reexamination of aspects of our understanding for this key indicator of global change. To a large extent, our confidence in understanding and projecting changes in polar and global ozone is based on our ability to simulate these processes in numerical models of chemistry and transport. The fidelity of the models is assessed in comparison with a wide range of observations. These models depend on laboratory-measured kinetic reaction rates and photolysis cross sections to simulate molecular interactions. A typical stratospheric chemistry mechanism has on the order of 50- 100 species undergoing over a hundred intermolecular reactions and several tens of photolysis reactions. The rates of all of these reactions are subject to uncertainty, some substantial. Given the complexity of the models, however, it is difficult to quantify uncertainties in many aspects of system. In this study we use a simple box-model scenario for Antarctic ozone to estimate the uncertainty in loss attributable to known reaction kinetic uncertainties. Following the method of earlier work, rates and uncertainties from the latest laboratory evaluations are applied in random combinations. We determine the key reactions and rates contributing the largest potential errors and compare the results to observations to evaluate which combinations are consistent with atmospheric data. Implications for our theoretical and practical understanding of polar ozone loss will be assessed.

Kawa, S. Randolph↗

Analysis of Variance in the Modern Design of Experiments

This paper is a tutorial introduction to the analysis of variance (ANOVA), intended as a reference for aerospace researchers who are being introduced to the analytical methods of the Modern Design of Experiments (MDOE), or who may have other opportunities to apply this method. One-way and two-way fixed-effects ANOVA, as well as random effects ANOVA, are illustrated in practical terms that will be familiar to most practicing aerospace researchers.

Deloach, Richard↗

Design Considerations for Human Rating of Liquid Rocket Engines

I.Human-rating is specific to each engine; a. Context of program/project must be understood. b. Engine cannot be discussed independently from vehicle and mission. II. Utilize a logical combination of design, manufacturing, and test approaches a. Design 1) It is crucial to know the potential ways a system can fail, and how a failure can propagate; 2) Fault avoidance, fault tolerance, DFMR, caution and warning all have roles to play. b. Manufacturing and Assembly; 1) As-built vs. as-designed; 2) Review procedures for assembly and maintenance periodically; and 3) Keep personnel trained and certified. c. There is no substitute for test: 1) Analytical tools are constantly advancing, but still need test data for anchoring assumptions; 2) Demonstrate robustness and explore sensitivities; 3) Ideally, flight will be encompassed by ground test experience. III. Consistency and repeatability is key in production a. Maintain robust processes and procedures for inspection and quality control based upon development and qualification experience; b. Establish methods to "spot check" quality and consistency in parts: 1) Dedicated ground test engines; 2) Random components pulled from the line/lot to go through "enhanced" testing.

Parkinson, Douglas↗

Methods of designing programmable inducible promoters

Described herein is a method for identifying synthetic inducible promoters that have specified induction and/or repression for DNA binding proteins such as an allosteric transcription factor and an inducer molecule. The method includes an in vitro selection from an unselected polynucleotide library comprising a plurality of random degeneracies, and an in vivo selection to produce an induced promoter library. Produced is an induction table, which allows the selection of a promoter with specific induction and/or repression properties. Also included are biosensors containing the synthetic inducible promoters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Micromagnet PUF readout using a quantum diamond microscope

A physically unclonable function (PUF) and a method of reading it are provided. The PUF is constituted by a microfabricated array of randomly polarized micromagnets disposed on a substrate. The PUF can be read by creating a magnetization map of the PUF from the signal output of a quantum diamond microscope (QDM) and converting the magnetization map to a numerical sequence.

Kehayias, Pauli Mark↗

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

This paper is the basis for a presentation help at the 2026 Georgia Tech Fault & Disturbance Analysis Conference, which can be found at OSTI # 3168287 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danovo Energy Solutions]↗

Markovian transport processes in a heterogeneous, variably saturated watershed: A multi-domain spatial Markov model

Transport processes in watersheds remain challenging to describe accurately with upscaled models because of their intricate complexities at multiple scales that can lead to multi-modal, non-Fickian breakthrough curves. One of the recent advances in solute transport modeling has been the Lagrangian spatial Markov model (SMM), which describes transport using velocity increments and models the correlated transitions between them. The method has been applied previously to saturated porous media and fractured media, but these successful applications suggest it may be useful for describing watershed scale processes as well. An existing, 3-D, heterogeneous variably saturated model of a headwaters catchment and classical random walk particle tracking were used to generate a forward simulation and the resulting transport was analyzed with a spatial Markov framework. Existing SMM methods were used to analyze the transport paths through the complex, unconfined domain and we found that the vadose zone plays an important role in the correlation structure. As such, a new kind of SMM is proposed, termed a multi-domain SMM (MD-SMM), that uses separate correlation models for auto-transitions in the vadose zone and the saturated zone, and for the cross-transitions between them. The MD-SMM improves representation of transport relative to the single domain model and can naturally delineate times when a particle is in the vadose zone or the saturated zone, adding an additional degree of realism to the upscaled model. Lastly, we show that the transition probability matrix for transport in the saturated portion of this unconfined system is approximately Markovian, which is an important validation of the proposed framework.

54 ENVIRONMENTAL SCIENCES↗

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerated basis adaptation in homogeneous chaos spaces

Polynomial chaos expansions (PCE) provide an efficient approach to uncertainty quantification (UQ) and have been adapted to diverse applications across the spectrum of science and engineering. For situations involving large stochastic parameterizations, the curse of dimensionality renders PCE-based methods computationally prohibitive. A basis adaptation approach for PCE was proposed by Tipireddy and Ghanem (2014) which transforms the input random variables through an isometry such that sufficient probabilistic characterization of specific quantities of interest (QoI) is concentrated in an algebraic manifold embedded in the linear span of the dominant transformed variables. While quite versatile, that original version of the PCE basis adaptation exhibited slow convergence for a number of problems of practical significance. In the present paper, we propose two novel methods to accelerate the convergence of the original basis adaptation approach, thus expanding its reach while also providing insight into its performance. In the first method, information gained from a pilot PCE representation is used to correct the mean and Gaussian coefficients in the adapted space. By taking advantages of probabilistic information in higher dimensional adaptation gleaned from an initial adaptation, the second method updates the rotation matrix used to identify the dominant transformed variables. In this manner, the new rotation matrix concentrates even more probabilistic information in its first few dimensions. These two method can be combined to achieve even better performance, the combined method is referred to as sequentially optimized adaptation method. Here, the methods are demonstrated on an analytical test function and a model of a space structure with several sub-components and a non-smooth quantity of interest representing the maximum acceleration over time. Both methods achieve accelerated convergence of the basis adaptation approach with negligible additional costs.

Accelerated convergence↗