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At least 1,207 records · Page 67

Accurate Magnetometer/Gyroscope Attitudes Using a Filter with Correlated Sensor Noise

Magnetometers and gyroscopes have been shown to provide very accurate attitudes for a variety of spacecraft. These results have been obtained, however, using a batch-least-squares algorithm and long periods of data. For use in onboard applications, attitudes are best determined using sequential estimators such as the Kalman filter. When a filter is used to determine attitudes using magnetometer and gyroscope data for input, the resulting accuracy is limited by both the sensor accuracies and errors inherent in the Earth magnetic field model. The Kalman filter accounts for the random component by modeling the magnetometer and gyroscope errors as white noise processes. However, even when these tuning parameters are physically realistic, the rate biases (included in the state vector) have been found to show systematic oscillations. These are attributed to the field model errors. If the gyroscope noise is sufficiently small, the tuned filter 'memory' will be long compared to the orbital period. In this case, the variations in the rate bias induced by field model errors are substantially reduced. Mistuning the filter to have a short memory time leads to strongly oscillating rate biases and increased attitude errors. To reduce the effect of the magnetic field model errors, these errors are estimated within the filter and used to correct the reference model. An exponentially-correlated noise model is used to represent the filter estimate of the systematic error. Results from several test cases using in-flight data from the Compton Gamma Ray Observatory are presented. These tests emphasize magnetometer errors, but the method is generally applicable to any sensor subject to a combination of random and systematic noise.

Sedlak, J.↗

Complex software dedicated for design and simulation of LPCE process for heavy water detritiation

The main purpose of this paper is to present a comprehensive software, SICA, designed to be used in water-hydrogen liquid phase catalytic exchange process (LPCE). The software calculates the water-gas catalytic isotopic exchange process, following the transfer of any H, D or T isotope from water to gas and vice versa. This software is useful for both design and laboratory-based research; the type of the catalytic filling (ordered or random) can be defined for any of these 2 cases, the isotopic calculation being specific to the package type. For the laboratory-based research, the performance of a catalytic packing can be determined by knowing the type and by using experimental results. Performance of the mixed catalytic packing is defined by mass transfer constants for each catalytic and hydrophilic package in that specific arrangement, and also for the isotope whose transfer is studied from one phase to another. Also, it has been established a link between these constants and commonly used parameters for the fillings performance defined by HETP (Height Equivalent of Theoretical Plate). To demonstrate the performance of the software, we present a comparative analysis of water-gas catalytic isotopic exchange on a column equipped with 3 types of filling: successive layers, random and structured (ordered package filled with catalyst). The program can be used for the LPCE process calculation, process used at detritiation facilities for CANDU reactors or fusion reactors. (authors)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Real-time onboard geometric image correction

A system to perform real time onboard geometric connection of LANDSAT D resolution satellite imagery is described. System requirements, algorithms, sensors, and other hardware components are defined. Feasibility of implementing the correction process is demonstrated using Kalman filter techniques to incorporate information from onboard ephemeris, attitude control, and ground control points. Random access sensor systems, such as charge injected devices and charge coupled devices are used to obtain pixel values at desired ground location, thus greatly reducing the data processing requirements.

Discenza, W.↗

Discrete One-Dimensional Coverage Process on a Renewal Process

Consider the following coverage model on ℕ, for each site i∈ℕ associate a pair (ξ{sub i},R{sub i}) where (ξ{sub i}){sub i≥0} is a 1-dimensional undelayed discrete renewal point process and (R{sub i}){sub i≥0} is an i.i.d. sequence of ℕ-valued random variables. At each site where ξ{sub i}=1 start an interval of length R{sub i}. Coverage occurs if every site of ℕ is covered by some interval. We obtain sharp conditions for both, positive and null probability of coverage. As corollaries, we extend results of the literature of rumor processes and discrete one-dimensional Boolean percolation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Delay-induced stochastic bifurcations in a bistable system under white noise

In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Seed classification with random forest models

Premise: To improve forest conservation monitoring, we developed a protocol to automatically count and identify the seeds of plant species with minimal resource requirements, making the process more efficient and less dependent on human operators. Methods and Results: Seeds from six North American conifer tree species were separated from leaf litter and imaged on a flatbed scanner. In the most successful species-classification approach, an ImageJ macro automatically extracted measurements for random forest classification in the software R. The method allows for good classification accuracy, and the same process can be used to train the model on other species. Conclusions: This protocol is an adaptable tool for efficient and consistent identification of seed species or potentially other objects. Automated seed classification is efficient and inexpensive, making it a practical solution that enhances the feasibility of large-scale monitoring projects in conservation biology.

59 BASIC BIOLOGICAL SCIENCES↗

Flow Intermittency, Dispersion, and Correlated Continuous Time Random Walks in Porous Media

We study the intermittency of fluid velocities in porous media and its relation to anomalous dispersion. Lagrangian velocities measured at equidistant points along streamlines are shown to form a spatial Markov process. As a consequence of this remarkable property, the dispersion of fluid particles can be described by a continuous time random walk with correlated temporal increments. This new dynamical picture of intermittency provides a direct link between the microscale flow, its intermittent properties, and non-Fickian dispersion.

Environmental Molecular Sciences Laboratory↗

Statistical modeling of software reliability

This working paper discusses the statistical simulation part of a controlled software development experiment being conducted under the direction of the System Validation Methods Branch, Information Systems Division, NASA Langley Research Center. The experiment uses guidance and control software (GCS) aboard a fictitious planetary landing spacecraft: real-time control software operating on a transient mission. Software execution is simulated to study the statistical aspects of reliability and other failure characteristics of the software during development, testing, and random usage. Quantification of software reliability is a major goal. Various reliability concepts are discussed. Experiments are described for performing simulations and collecting appropriate simulated software performance and failure data. This data is then used to make statistical inferences about the quality of the software development and verification processes as well as inferences about the reliability of software versions and reliability growth under random testing and debugging.

Miller, Douglas R.↗

Effect of a magnetic field on polarisation of light in an optical fibre with a random distribution of linear birefringence

A numerical model is proposed to describe the evolution of polarisation of a light wave propagating through a telecommunication fibre with random linear birefringence in a magnetic field. As a result of statistical processing of a set of numerical simulation results, a convenient phenomenological formula is obtained for the first time for the dependence of the average value of the polarisation rotation angle on the magnetic field, the fibre parameters and its length. It is found that the average value of the polarisation rotation angle in a long telecommunication fibre in the representation of the Stokes vectors linearly depends on the applied longitudinal magnetic field (as in the classical Faraday effect for an isotropic medium) but is proportional to the root of the fibre length. It is theoretically shown and experimentally confirmed that the polarisation rotation angle for an extended segment of a telecommunication fibre (50 km) is two orders of magnitude less than that for an isotropic fibre of the same length and material. (optical fibres)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Process Produces Low-Secondary-Electron-Emission Surfaces

Textured carbon layer applied to copper by sputtering. Carbon surface characterized by dense, random array of needle-like spires or peaks that extend perpendicularly from local copper surface. Spires approximately 7 micrometers in height and spaced approximately 3 micrometers apart, on average. Copper substrate essentially completely covered by carbon layer, is tenacious and not damaged by vibration loadings representative of multistage depressed collector (MDC) applications. Process developed primarily to provide extremely low-secondary-electron-emission surface for copper for use as highefficiency electrodes in MDC's for microwave amplifier traveling-wave tubes (TWT's). Tubes widely used in space communications, aircraft, and terrestrial applications.

Curren, A. N.↗

Non-Genomic Origins of Proteins and Metabolism

It is proposed that evolution of inanimate matter to cells endowed with a nucleic acid- based coding of genetic information was preceded by an evolutionary phase, in which peptides not coded by nucleic acids were able to self-organize into networks capable of evolution towards increasing metabolic complexity. Recent findings that truly different, simple peptides (Keefe and Szostak, 2001) can perform the same function (such as ATP binding) provide experimental support for this mechanism of early protobiological evolution. The central concept underlying this mechanism is that the reproduction of cellular functions alone was sufficient for self-maintenance of protocells, and that self- replication of macromolecules was not required at this stage of evolution. The precise transfer of information between successive generations of the earliest protocells was unnecessary and, possibly, undesirable. The key requirement in the initial stage of protocellular evolution was an ability to rapidly explore a large number of protein sequences in order to discover a set of molecules capable of supporting self- maintenance and growth of protocells. Undoubtedly, the essential protocellular functions were carried out by molecules not nearly as efficient or as specific as contemporary proteins. Many, potentially unrelated sequences could have performed each of these functions at an evolutionarily acceptable level. As evolution progressed, however proteins must have performed their functions with increasing efficiency and specificity. This, in turn, put additional constraints on protein sequences and the fraction of proteins capable of performing their functions at the required level decreased. At some point, the likelihood of generating a sufficiently efficient set of proteins through a non-coded synthesis was so small that further evolution was not possible without storing information about the sequences of these proteins. Beyond this point, further evolution required coupling between proteins and informational polymers that is characteristic to all known forms of life. The emergence of such coupling must be postulated in any scenario of the origin of life, no matter whether it starts with RNA or proteins. To examine the evolutionary potential of non-genomic systems, a simple, computationally tractable model, which is still capable of capturing the essential features of the real system, has been studied computationally. Both constructive and destructive processes have been introduced into the model in a stochastic manner. Instead of assuming random reaction sets, only a suite of protobiologically plausible reactions has been considered. Peptides have been explicitly considered as protoenzymes and their catalytic efficiencies have been assigned on the basis of biochemical principles and experimental estimates. Simulations have been carried out using a novel approach (The Next Reaction Method) that is appropriate even for very low concentrations of reactants. Studies have focused on global autocatalytic processes and their diversity.

Pohorille, Andrew↗

SU-F-I-43: A Software-Based Statistical Method to Compute Low Contrast Detectability in Computed Tomography Images

Purpose: The low contrast detectability (LCD) of a CT scanner is its ability to detect and display faint lesions. The current approach to quantify LCD is achieved using vendor-specific methods and phantoms, typically by subjectively observing the smallest size object at a contrast level above phantom background. However, this approach does not yield clinically applicable values for LCD. The current study proposes a statistical LCD metric using software tools to not only to assess scanner performance, but also to quantify the key factors affecting LCD. This approach was developed using uniform QC phantoms, and its applicability was then extended under simulated clinical conditions. Methods: MATLAB software was developed to compute LCD using a uniform image of a QC phantom. For a given virtual object size, the software randomly samples the image within a selected area, and uses statistical analysis based on Student’s t-distribution to compute the LCD as the minimal Hounsfield Unit’s that can be distinguished from the background at the 95% confidence level. Its validity was assessed by comparison with the behavior of a known QC phantom under various scan protocols and a tissue-mimicking phantom. The contributions of beam quality and scattered radiation upon the computed LCD were quantified by using various external beam-hardening filters and phantom lengths. Results: As expected, the LCD was inversely related to object size under all scan conditions. The type of image reconstruction kernel filter and tissue/organ type strongly influenced the background noise characteristics and therefore, the computed LCD for the associated image. Conclusion: The proposed metric and its associated software tools are vendor-independent and can be used to analyze any LCD scanner performance. Furthermore, the method employed can be used in conjunction with the relationships established in this study between LCD and tissue type to extend these concepts to patients’ clinical CT images.

60 APPLIED LIFE SCIENCES↗

Cascade random-quasi-phase-matched harmonic generation in polycrystalline ZnSe

Here, we experimentally and numerically investigated the cascade random-quasi-phase-matched harmonic generation in polycrystalline zinc selenide with tightly focused mid-infrared nanosecond laser pulses. We observed a sharp transition between two distinct intensity scaling regimes as a function of pump energy from sub I N to super I N , where I is the pump intensity and N is the harmonic order. To gain an understanding of the observations of this complex nonlinear process, we carried out simulations of the coupled three-wave mixing equations with random grain sizes and orientations. We found a grain size dependence of the effective phase-matching condition, suggesting that manipulation of grain size can be an effective pathway to phase-matching optimization. This approach may provide a framework for effectively enhancing high harmonic generation and other wave mixing effects in polycrystalline materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Random field estimation approach to robot dynamics

The difference equations of Kalman filtering and smoothing recursively factor and invert the covariance of the output of a linear state-space system driven by a white-noise process. Here it is shown that similar recursive techniques factor and invert the inertia matrix of a multibody robot system. The random field models are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. They are easier to describe than the models based on classical mechanics, which typically require extensive derivation and manipulation of equations of motion for complex mechanical systems. With the spatially random models, more primitive locally specified computations result in a global collective system behavior equivalent to that obtained with deterministic models. The primary goal of applying random field estimation is to provide a concise analytical foundation for solving robot control and motion planning problems.

Rodriguez, Guillermo↗

GANISP (GAN-assisted Importance SPlitting)

Genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be adjusted. Typically, a random perturbation is applied to the offspring. For some cases, this cloning technique may not be adequate and prevent variance reduction in the probability estimate. A GAN-based replication process is proposed to address this limitation. The perturbations applied to the clones are physically consistent instead of being randomly chosen. The proposed method allows reducing the variance in the probability estimation.

Hassanaly, Malik↗

OBSERVATIONAL SIGNATURES OF CORONAL LOOP HEATING AND COOLING DRIVEN BY FOOTPOINT SHUFFLING

The evolution of a coronal loop is studied by means of numerical simulations of the fully compressible three-dimensional magnetohydrodynamic equations using the HYPERION code. The footpoints of the loop magnetic field are advected by random motions. As a consequence, the magnetic field in the loop is energized and develops turbulent nonlinear dynamics characterized by the continuous formation and dissipation of field-aligned current sheets: energy is deposited at small scales where heating occurs. Dissipation is nonuniformly distributed so that only a fraction of the coronal mass and volume gets heated at any time. Temperature and density are highly structured at scales that, in the solar corona, remain observationally unresolved: the plasma of our simulated loop is multithermal, where highly dynamical hotter and cooler plasma strands are scattered throughout the loop at sub-observational scales. Numerical simulations of coronal loops of 50,000 km length and axial magnetic field intensities ranging from 0.01 to 0.04 T are presented. To connect these simulations to observations, we use the computed number densities and temperatures to synthesize the intensities expected in emission lines typically observed with the Extreme Ultraviolet Imaging Spectrometer on Hinode. These intensities are used to compute differential emission measure distributions using the Monte Carlo Markov Chain code, which are very similar to those derived from observations of solar active regions. We conclude that coronal heating is found to be strongly intermittent in space and time, with only small portions of the coronal loop being heated: in fact, at any given time, most of the corona is cooling down.

79 ASTRONOMY AND ASTROPHYSICS↗

Tough, processable semi-interpenetrating polymer networks from monomer reactants

A high temperature semi-interpenetrating polymer network (semi-IPN) was developed which had significantly improved processability, damage tolerance, and mechanical performance, when compared to the commercial Thermid materials. This simultaneous semi-IPN was prepared by mixing the monomer precursors of Thermid AL-600 (a thermoset) and NR-150B2 (a thermoplastic) and allowing the monomers to react randomly upon heating. This reaction occurs at a rate which decreases the flow and broadens the processing window. Upon heating at a higher temperature, there is an increase in flow. Because of the improved flow properties, broadened processing window and enhanced toughness, high strength polymer matrix composites, adhesives and molded articles can now be prepared from the acetylene end-capped polyimides which were previously inherently brittle and difficult to process.

Pater, Ruth H.↗

DESPERATE: A Python Library for Processing and Denoising NMR Spectra

NMR spectroscopy is an inherently insensitive technique with respect to the amount of observable signal. A common element in all NMR spectra is random thermal noise that is often characterized by a signal-to-noise ratio (SNR). SNR can be generically improved experimentally with repetitive signal averaging or during post-processing with apodization; the former of which often results in long experimental times and the latter results in the loss of spectral resolution. Denoising techniques can instead be used during post-processing to enhance SNR without compromising resolution. The most common approach relies on the singular-value decomposition (SVD) to discard noisy components of NMR data. SVD-based approaches work well, such as Cadzow and PCA, but are computationally expensive when used for large datasets that are often encountered in NMR (e.g., Carr-Purcell/Meiboom-Gill and nD datasets). Herein, we describe the implementation of a new wavelet transform (WT) routine for the fast and robust denoising of 1D and 2D NMR spectra. Several simulated and experimental datasets are denoised with both SVD-based Cadzow or PCA and WT’s, and the resulting SNR enhancements and spectral uniformity are compared. WT denoising offers similar and improved denoising compared with SVD and operates faster by several orders-of-magnitude in some cases. Further, all denoising and processing routines used in this work are included in a free and open-source Python library called DESPERATE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗