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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 559 records · Page 31

Binary pseudo-random patterned structures for modulation transfer function calibration and resolution characterization of a full-field transmission soft x-ray microscope

We present a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) one-dimensional sequences and two-dimensional arrays as an effective method for spectral characterization in the spatial frequency domain of a broad variety of metrology instrumentation, including interferometric microscopes, scatterometers, phase shifting Fizeau interferometers, scanning and transmission electron microscopes, and at this time, x-ray microscopes. The inherent power spectral density of BPR gratings and arrays, which has a deterministic white-noise-like character, allows a direct determination of the MTF with a uniform sensitivity over the entire spatial frequency range and field of view of an instrument. We demonstrate the MTF calibration and resolution characterization over the full field of a transmission soft x-ray microscope using a BPR multilayer (ML) test sample with 2.8 nm fundamental layer thickness. We show that beyond providing a direct measurement of the microscope’s MTF, tests with the BPRML sample can be used to fine tune the instrument’s focal distance. Our results confirm the universality of the method that makes it applicable to a large variety of metrology instrumentation with spatial wavelength bandwidths from a few nanometers to hundreds of millimeters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Generalized density matrix reexamined: Microscopic approach to collective dynamics in soft spherical nuclei

The generalized density matrix method is used to calculate microscopically the parameters of the collective Hamiltonian. Higher-order anharmonicities are obtained consistently with the lowest-order results, the mean field (Hartree-Fock-Bogoliubov equation), and the harmonic potential (quasiparticle random-phase approximation). The method is applied to soft spherical nuclei, where the anharmonicities are essential for restoring the stability of the system, as the harmonic potential becomes small or negative. The approach is tested in three models of increasing complexity: the Lipkin model, model with factorizable forces, and the quadrupole plus pairing model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Performance evaluation of fault-tolerant systems with application to the IUS

A new method for quantitatively evaluating the performance of fault-tolerant systems is developed and applied to an example. The method assumes that the random failure and diagnostic decision behavior of the system can be modeled by a finite state Markov process. A performance value must be assigned to each of the states of the model. The method then generates the moments of the probability mass function of the cumulative performance and uses these to generate a maximum entropy approximation to the performance PMF. Some computational considerations are discussed. The method is applied to a typical mission for the Inertial Upper Stage to examine the attitude accuracy performance of the inertial system.

Missana, J.-O.↗

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been proposed by the Society of Automotive Engineers (SAE). The test cases compare different probabilistic methods within NESSUS because it is important that a user can have confidence that estimates of stochastic parameters of a response will be within an acceptable error limit. For each response, the mean, standard deviation, and 0.99 percentile, are repeatedly estimated which allows confidence statements to be made for each parameter estimated, and for each method. Thus, the ability of several stochastic methods to efficiently and accurately estimate density parameters is compared using four valid test cases. While all of the reliability methods used performed quite well, for the new LHS module within NESSUS it was found that it had a lower estimation error than MC when they were used to estimate the mean, standard deviation, and 0.99 percentile of the four different stochastic responses. Also, LHS required a smaller amount of calculations to obtain low error answers with a high amount of confidence than MC. It can therefore be stated that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ and the newest LHS module is a valuable new enhancement of the program.

Chamis, Chrisos C.↗

Stochastic Inversion of Gaussian Random Media Using Transverse Coherence Functions for Reflected Waves: Theory and Method

The transverse coherence functions (TCFs) of phase and amplitude fluctuations of a seismic wave are powerful to estimate the spatial distribution, length scales, and strength of random heterogeneities. However, TCFs have been formulated for transmitted waves only, not for reflected waves. In this paper, we derive reflection TCFs for Gaussian random media. Furthermore, we propose to invert for Gaussian random media using the reflection TCFs based on the grid search. We validate the new reflection TCF formulas using 2D finite-difference numerical experiments. The numerical example also illustrates the feasibility and efficiency of the inversion. The stochastic inversion using reflected waves can be used in both exploration and global seismology.

58 GEOSCIENCES↗

Estimates of Random Error in Satellite Rainfall Averages

Satellite rain estimates are most accurate when obtained with microwave instruments on low earth-orbiting satellites. Estimation of daily or monthly total areal rainfall, typically of interest to hydrologists and climate researchers, is made difficult, however, by the relatively poor coverage generally available from such satellites. Intermittent coverage by the satellites leads to random "sampling error" in the satellite products. The inexact information about hydrometeors inferred from microwave data also leads to random "retrieval errors" in the rain estimates. In this talk we will review approaches to quantitative estimation of the sampling error in area/time averages of satellite rain retrievals using ground-based observations, and methods of estimating rms random error, both sampling and retrieval, in averages using satellite measurements themselves.

Bell, Thomas L.↗

On the room-temperature phase diagram of high pressure hydrogen: An ab initio molecular dynamics perspective and a diffusion Monte Carlo study

The finite-temperature phase diagram of hydrogen in the region of phase IV and its neighborhood was studied using the ab initio molecular dynamics (MD) and the ab initio path-integral molecular dynamics (PIMD). The electronic structures were analyzed using the density-functional theory (DFT), the random-phase approximation, and the diffusion Monte Carlo (DMC) methods. Taking the state-of-the-art DMC results as benchmark, comparisons of the energy differences between structures generated from the MD and PIMD simulations, with molecular and dissociated hydrogens, respectively, in the weak molecular layers of phase IV, indicate that standard functionals in DFT tend to underestimate the dissociation barrier of the weak molecular layers in this mixed phase. Because of this underestimation, inclusion of the quantum nuclear effects (QNEs) in PIMD using electronic structures generated with these functionals leads to artificially dissociated hydrogen layers in phase IV and an error compensation between the neglect of QNEs and the deficiencies of these functionals in standard ab initio MD simulations exists. This analysis partly rationalizes why earlier ab initio MD simulations complement so well the experimental observations. The temperature and pressure dependencies for the stability of phase IV were also studied in the end and compared with earlier results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Concepts for a theoretical and experimental study of lifting rotor random loads and vibrations. Phase 5C: Development of experimental methods

Test equipment which was built and the calibration tests are described. The test equipment consists of a two-bladed rotor of 16-in. diameter, the blades of which are elastically hinged in flapping. The feathering shaft of the blades can be harmonically rotated with the help of a cam mechanism located inside the hollow rotor shaft. The frequency range measured in the rotating system can be adjusted between 0 and 80 cps and the rotor speed between 0 and 40 cps. The test equipment is for measuring the flapping response of the blades to harmonic feathering excitation.

Hohenemser, K. H.↗

Methods and models for predicting fatigue crack growth under random loading

Papers are presented in the volume summarizing the baseline data, methodology, procedures, and results of a round-robin analysis which was conducted to predict the fatigue crack growth in 2219-T851 aluminum center-cracked specimens subjected to flight loading in random cycle-by-cycle format. The objective of the analysis was to assess whether data from constant-amplitude fatigue crack growth tests on center-cracked specimens can be used to predict fatigue crack growth lives under random loading. The following approaches are discussed in detail: a root-mean-square approach, a crack-closure model, a multi-parameter yield zone model, and a load-interaction model.

Chang, J. B.↗

Direct Randomized Benchmarking for Multiqubit Devices

Benchmarking methods that can be adapted to multiqubit systems are essential for assessing the overall or “holistic” performance of nascent quantum processors. The current industry standard is Clifford randomized benchmarking (RB), which measures a single error rate that quantifies overall performance. But, scaling Clifford RB to many qubits is surprisingly hard. It has only been performed on one, two, and three qubits as of this writing. This reflects a fundamental inefficiency in Clifford RB: the n-qubit Clifford gates at its core have to be compiled into large circuits over the one- and two-qubit gates native to a device. As n grows, the quality of these Clifford gates quickly degrades, making Clifford RB impractical at relatively low n. In this Letter, we propose a direct RB protocol that mostly avoids compiling. Instead, it uses random circuits over the native gates in a device, which are seeded by an initial layer of Clifford-like randomization. We demonstrate this protocol experimentally on two to five qubits using the publicly available ibmqx5. We believe this to be the greatest number of qubits holistically benchmarked, and this was achieved on a freely available device without any special tuning up. Our protocol retains the simplicity and convenient properties of Clifford RB: it estimates an error rate from an exponential decay. But, it can be extended to processors with more qubits—we present simulations on 10+ qubits—and it reports a more directly informative and flexible error rate than the one reported by Clifford RB. Here, we show how to use this flexibility to measure separate error rates for distinct sets of gates, and we use this method to estimate the average error rate of a set of cnot gates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Acquisition and processing of data for isotope-ratio-monitoring mass spectrometry

Methods are described for continuous monitoring of signals required for precise analyses of 13C, 18O, and 15N in gas streams containing varying quantities of CO2 and N2. The quantitative resolution (i.e. maximum performance in the absence of random errors) of these methods is adequate for determination of isotope ratios with an uncertainty of one part in 10(5); the precision actually obtained is often better than one part in 10(4). This report describes data-processing operations including definition of beginning and ending points of chromatographic peaks and quantitation of background levels, allowance for effects of chromatographic separation of isotopically substituted species, integration of signals related to specific masses, correction for effects of mass discrimination, recognition of drifts in mass spectrometer performance, and calculation of isotopic delta values. Characteristics of a system allowing off-line revision of parameters used in data reduction are described and an algorithm for identification of background levels in complex chromatograms is outlined. Effects of imperfect chromatographic resolution are demonstrated and discussed and an approach to deconvolution of signals from coeluting substances described.

NASA Discipline Exobiology↗

Development of a Probabilistic Component Mode Synthesis Method for the Analysis of Non-Deterministic Substructures

Standard methods of structural dynamic analysis assume that the structural characteristics are deterministic. Recognizing that these characteristics are actually statistical in nature, researchers have recently developed a variety of methods that use this information to determine probabilities of a desired response characteristic, such as natural frequency, without using expensive Monte Carlo simulations. One of the problems in these methods is correctly identifying the statistical properties of primitive variables such as geometry, stiffness, and mass. This paper presents a method where the measured dynamic properties of substructures are used instead as the random variables. The residual flexibility method of component mode synthesis is combined with the probabilistic methods to determine the cumulative distribution function of the system eigenvalues. A simple cantilever beam test problem is presented that illustrates the theory.

Brown, Andrew M.↗