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At least 1,657 records · Page 92

Control of optical systems

Some of the current and planned activities at the Air Force Systems Command in structures and controls for optical-type systems are summarized. Many of the activities are contracted to industry; one task is an in-house program which includes a hardware test program. The objective of the in-house program, referred to as the Aluminum Beam Expander Structure (ABES), is to address issues involved in on-orbit system identification. The structure, which appears similar to the LDR backup structure, is about 35 feet tall. The activity to date has been limited to acquisition of about 250 hours of test data. About 30 hours of data per excitation force is gathered in order to obtain sufficient data for a good statistical estimate of the structural parameters. The development of an Integrated Structural Modeling (ISM) computer program is being done by Boeing Aerospace Company. The objective of the contracted effort is to develop a combined optics, structures, thermal, controls, and multibody dynamics simulation code.

Founds, D.↗

Discrimination of alkalinity in granitoid Rocks: A potential TIMS application

In mineral exploration, the ability to distinguish and map petrochemical variations of magmatic rocks can be a useful reconnaissance tool. Alkalinity is one such petrochemical parameter and is used in the characterization of granitoid rocks. In quartz normative plutonic rocks, alkalinity is related to the composition and abundance of feldspars. Together with quartz abundance, knowledge of feldspar modes allows the classification of these igneous rocks according to the Streckeisen diagram. Alternative classification schemes rely on whole rock geochemistry instead of mineral identifications. The relative ease of obtaining whole rock analyses means that geochemical classifications tend to be favored in exploration geology. But the technique of thermal infrared spectroscopy of rocks yields information on mineralogy and is one that can be applied remotely. The goal of the current work then is to establish whether data from TIMS can be used to distinguish the mineralogical variations that relate to alkalinity. An ideal opportunity to test this thesis arises from the work presented in a paper by Dewitt (1989). This paper contains the results of mapping and analysis of Proterozoic plutonic rocks in north-central Arizona. The map resulting from this work delineates plutons according to alkalinity in an effort to establish a trend or polarity in the regional magmatism. Also contained within this paper are brief descriptions of the mineralogy of half of the region's plutons. This combination of mineralogical and geochemical information was the rationale behind choosing this area as a site for TIMS over flights. A portion of the region centered on the northern Bradshaw Mountains was selected because it contains plutons of all three alkalinity classifications (alkali-calcic, calc-alkalic, and calic) present on DeWitt's map within a relatively small area. The site was flown in August of 1994 and the data received a few days before the writing of this manuscript. Most of this paper is devoted to the description of laboratory based spectroscopy and spectral simulations. These are required to gain insight into the correct procedures for enhancing the relatively small differences in the low spectral resolution TIMS data.

Ruff, Steven W.↗

Enhanced Dynamic Equivalent Identification Method of Large-Scale Power Systems Using Multiple Event

The increasing complexity of the interconnected power system makes high-fidelity dynamic simulation models computationally more intensive. To improve computation efficiency, model reduction techniques have been investigated to only preserve the dynamics in a limited area of interest (study area), while deriving equivalent representation for the external area. For this purpose, a measurement-based reduction approach using system identification techniques has been previously proposed. In that case, external areas are represented by dynamic equivalent loads using transfer function estimation. In this paper, in order to enhance the accuracy of the reduced model in preserving dynamics of the study area, multiple “grid” events of different types and at different locations are considered for identifying the parameters of the equivalent loads. Case studies are carried out in the NPCC 140-bus system. Comparison are made between multiple events training and single event training, highlighting the advantages of the proposed method in providing a better representation of the grid dynamics under different operating conditions.

Xue, Yaosuo↗

De novo Nanopore read quality improvement using deep learning

BACKGROUND: Long read sequencing technologies such as Oxford Nanopore can greatly decrease the complexity of de novo genome assembly and large structural variation identification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. The limited sensitivity of existing read-based error correction methods can cause large-scale mis-assemblies in the assembled genomes, motivating further innovation in this area. RESULTS: Here we developed a Convolutional Neural Network (CNN) based method, called MiniScrub, for identification and subsequent "scrubbing" (removal) of low-quality Nanopore read segments to minimize their interference in downstream assembly process. MiniScrub first generates read-to-read overlaps via MiniMap2, then encodes the overlaps into images, and finally builds CNN models to predict low-quality segments. Applying MiniScrub to real world control datasets under several different parameters, we show that it robustly improves read quality, and improves read error correction in the metagenome setting. Compared to raw reads, de novo genome assembly with scrubbed reads produces many fewer mis-assemblies and large indel errors. CONCLUSIONS: MiniScrub is able to robustly improve read quality of Oxford Nanopore reads, especially in the metagenome setting, making it useful for downstream applications such as de novo assembly. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub .

59 BASIC BIOLOGICAL SCIENCES↗

Identification of linear multivariable systems from a single set of data by identification of observers with assigned real eigenvalues

This paper presents a formulation for identification of linear multivariable systems from a single set of input-output data. The identification method is formulated with the mathematical framework of learning identification, by extension of the repetition domain concept to include shifting time intervals. This contrasts existing learning approaches that require data from multiple experiments. In this method, the system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded real eigenvalue assignment procedure. Through this relationship, the Markov parameters of the observer are identified. The Markov parameters of the actual system are recovered from those of the observer, and then used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples presented to illustrate the proposed method.

Phan, Minh↗

Tests of a simple data merging algorithm for the GONG project

The GONG (Global Oscillation Network Group) project proposes to reduce the impact of diurnal variations on helioseismic measurements by making long-term observations of solar images from six sites placed around the globe. The sun will be observed nearly constantly for three years, resulting in the acquisition of l+ terabyte of image data. To use the solar network to maximum advantage, the images from the sites must be combined into a single time series to determine mode frequencies, amplitudes, and line widths. Initial versions of combined, i.e., merged, time series were made using a simple weighted average of data from different sites taken simultaneously. In order to accurately assess the impact of the data merge on the helioseismic measurements, a set of artificial solar disk images was made using a standard solar model and containing a well known set of oscillation modes and frequencies. This undegraded data set and data products computed from it were used to judge the relative merits of various data merging schemes. The artificial solar disk images were subjected to various instrumental and atmospheric degradations, dependent on site and time, in order to create a set of images simulating those likely to be taken at the site. The degraded artificial solar disk images for the six observing sites were combined in various ways to form merged time series of images and mode coefficients. Various forms of a weighted average were used, including an equally-weighted average, an average with weights dependent upon air mass and averages with weights dependent on various quality assurance parameters. Both the undegraded solar disk image time series and several time series made up of various combinations of the degraded solar disk images from the six sites were subjected to standard helioseismic measurement processing. This processing consisted of coordinate remapping, detrending, spherical harmonic transformation, computation of power series for the oscillation mode coefficients, and mode frequency identification. Visual and statistical evaluation of the merged data sets themselves and differences between the merged and undegraded data set shows good agreement between the two data sets. Some slight differences in image scale and registration appear between the undegraded data set and the various merged data sets. In the set of power series made from the mode coefficients of the merged data sets, some power leakage is observed into the background and into slightly lower l-value modes, especially at higher l-value mode frequencies. The results of the comparison of time series and mode oscillation frequencies of the undegraded data with those of the data merged using weighted averages indicate that, at least for p-mode solar oscillations, a weighted average of either the detrended remapped images or the mode coefficients gives good determination of the mode frequencies and adequate-to-good determination of the amplitudes and widths of the mode frequency lines. This conclusion is most advantageous to the analysis of the massive amounts of data to be received by the GONG network.

Williams, W. E.↗

Identifying Geographic Areas at Risk of Soil-transmitted Helminthes Infection Using Remote Sensing and Geographical Information Systems: Boaco, Nicaragua as a Case Study

Several types of intestinal nematodes, that can infect humans and specially school-age children living in poverty, develop part of their life cycle in soil. Presence and survival of these parasites in the soil depend on given environmental characteristics like temperature and moisture that can be inferred with remote sensing (RS) technology. Prevalence of diseases caused by these parasitic worms can be controlled and even eradicated with anthelmintic drug treatments and sanitation improvement. Reliable and updated identification of geographic areas at risk is required to implement effective public health programs; to calculate amount of drug required and to distribute funding for sanitation projects. RS technology and geographical information systems (GIS) will be used to analyze for associations between in situ prevalence and remotely sensed data in order to establish RS proxies of environmental parameters that indicate the presence of these parasits. In situ data on helminthisasis will be overlaid over an ecological map derived from RS data using ARC Map 9.3 (ESRI). Temperature, vegetation, and distance to bodies of water will be inferred using data from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat TM and ETM+. Elevation will be estimated with data from The Shuttle Radar Topography Mission (SRTM). Prevalence and intensity of infections are determined by parasitological survey (Kato Katz) of children enrolled in rural schools in Boaco, Nicaragua, in the communities of El Roblar, Cumaica Norte, Malacatoya 1, and Malacatoya 2). This study will demonstrate the importance of an integrated GIS/RS approach to define clusters and areas at risk. Such information will help to the implementation of time and cost efficient control programs and sanitation efforts.

Moreno, Max J.↗

Application of Machine Learning to Rotorcraft Health Monitoring

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

machine learning↗

Identification and Validation of Virtual Battery Model for Heterogeneous Devices

The potential of distributed energy resources in providing grid services can be maximized with the recent advancements in demand side control. Effective utilization of this control strategy requires the knowledge of aggregate flexibility of the distributed energy resources (DERs). Recent works have shown that the aggregate flexibility of DERs can be modeled as a virtual battery (VB) whose state evolution is governed by a first order system including self dissipation. The VB parameters (self dissipation rate, energy capacity) are obtained by solving an optimization problem which minimizes the tracking performance of the ensemble and the proposed first order model. For the identified first order model, time varying power limits are calculated using binary search algorithms. Finally, this proposed framework is demonstrated for different homogeneous and heterogeneous ensembles consisting of air conditioners (ACs) and electric water heaters (EWHs).

Nandanoori, Sai Pushpak↗

Frequency domain system identification methods - Matrix fraction description approach

This paper presents the use of matrix fraction descriptions for least-squares curve fitting of the frequency spectra to compute two matrix polynomials. The matrix polynomials are intermediate step to obtain a linearized representation of the experimental transfer function. Two approaches are presented: first, the matrix polynomials are identified using an estimated transfer function; second, the matrix polynomials are identified directly from the cross/auto spectra of the input and output signals. A set of Markov parameters are computed from the polynomials and subsequently realization theory is used to recover a minimum order state space model. Unevenly spaced frequency response functions may be used. Results from a simple numerical example and an experiment are discussed to highlight some of the important aspect of the algorithm.

Horta, Luca G.↗

Data Analysis for DNA Stable Isotope Probing Experiments Using Multiple Window High-Resolution SIP

DNA stable isotope probing (DNA-SIP) allows for the identification of microbes that assimilate isotopically labeled substrates into DNA. Here we describe the analysis of sequencing data using the multiple window high-resolution DNA-SIP method (MW-HR-SIP). MW-HR-SIP has improved accuracy over other methods and is easily implemented on the statistical platform R. Here, we also discuss key experimental parameters to consider when designing DNA-SIP experiments and how these parameters affect accuracy of analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml

We present the implementation of binary and ternary neural networks in the hls4ml library, designed to automatically convert deep neural network models to digital circuits with FPGA firmware. Starting from benchmark models trained with floating point precision, we investigate different strategies to reduce the network's resource consumption by reducing the numerical precision of the network parameters to binary or ternary. We discuss the trade-off between model accuracy and resource consumption. In addition, we show how to balance between latency and accuracy by retaining full precision on a selected subset of network components. As an example, we consider two multiclass classification tasks: handwritten digit recognition with the MNIST data set and jet identification with simulated proton-proton collisions at the CERN Large Hadron Collider. The binary and ternary implementation has similar performance to the higher precision implementation while using drastically fewer FPGA resources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluation of a methodology for model identification in the time domain

A model identification methodology for structural dynamics has been applied to simulated vibrational data as a first step in evaluating its accuracy. The evaluation has taken into account a wide variety of factors which affect the accuracy of the procedure. The effects of each of these factors were observed in both the response time histories and the estimates of the parameters of the model by comparing them with the exact values of the system. Each factor was varied independently but combinations of these have also been considered in an effort to simulate real situations. The results of the tests have shown that for the chain model, the procedure yields robust estimates of the stiffness parameters under the conditions studied whenever uniqueness is ensured. When inaccuracies occur in the results, they are intimately related to non-uniqueness conditions inherent in the inverse problem and not to shortcomings in the methodology.

Beck, R. T.↗

Characterization of a Laminate Flat Plate Diffusion Flame in Microgravity using PIV, Visible and CH Emissions

Motivated by fire safety concerns and the advent of long-term micro-gravity facilities, a cooperative program has been developed to study the mechanisms and material properties that control flow assisted (co-current) flame spread. This program has used as a common fire scenario a reacting steady-state boundary layer. Preliminary studies explored the aerodynamics of a reacting boundary layer by simulating a condensed fuel by means of a gas burner. Stability curves for ethane air flames were obtained and different burning regimes were identified. An important feature of this study was the independent identification of the different mechanisms leading to the instability of the flow. It was observed that fuel injection velocity and thermal expansion independently contributed to the separation of the flow at the leading edge of the burner. The occurrence of separation resulted in complex three-dimensional flow patterns that have a dominant effect on critical fire safety parameters such as the stand-off distance and flame length. This work was extended to a solid fuel (PMMA) leading to a Sounding Rocket experiment (Mini-Texus-6). The solid phase showed similar flow patterns, mostly present at low flow velocities (<100 mm/s) but the results clearly demonstrated that the thermal balance at the pyrolyzing fuel surface is the dominant mechanism that controls both stand-off distance and flame length. This thermal balance could be described in a global manner by means of a total mass transfer or "B" number. This "B" number incorporates surface re-radiation, radiative feedback and in-depth heat conduction as first prescribed by Emmons. The mass transfer number becomes the single parameter that determines the evolution of these fire safety variables (flame length, stand-off distance) and therefore can be used as a ranking criterion to assess the flammability of materials. The particular configuration is representative of the NASA upward flame spread test (Test 1) therefore this approach can be used in the interpretation of the results obtained from this test. Nevertheless, complete validation of this approach has not been fully achieved due, mainly because all the measurements necessary to compare with the theoretical predictions have not been obtained. Following these studies two different directions have been taken. The first attempts to elucidate the details of the gas phase combustion reaction and the associated flow field by means of quantitative and qualitative measurements. The second approach, a more practical one, is to apply this methodology to the assessment of material flammability. The former is currently being conducted with a gas burner because it allows for easier control and longer experimentation time. The results obtained so far will be presented in more detail. The latter is a new program therefore only a brief summary of the objectives will be presented.

Joulain, P.↗

Hydrogen Abundance and Distribution on (101955) Bennu

Asteroids were likely a major source of volatiles and water to early Earth. Quantifying the hydration of asteroids is necessary to constrain models of the formation and evolution of the Solar System and the origin of Life on Earth. The OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) mission showed that near-Earth asteroid (101955) Bennu contains widespread, abundant hydrated phyllosilicates, indicated by a ubiquitous absorption at ~ 2.7 μm. The objective of this work is to quantify the hydration—that is, the hydrogen content—of phyllosilicates on Bennu's surface and investigate how this hydration varies spatially. We analyse spectral parameters (normalized optical path length, NOPL; effective single-scattering albedo, ESPAT; and Gaussian modeling) computed from the hydrated phyllosilicate absorption band of spatially resolved visible–near-infrared spectra acquired by OVIRS (the OSIRIS-REx Visible and InfraRed Spectrometer). We also computed the same spectral parameters using laboratory-measured spectra of meteorites including CMs, CIs, and the ungrouped C2 Tagish Lake. We estimate the mean hydrogen content of water and hydroxyl groups in hydrated phyllosilicates on Bennu's surface to be 0.71 ± 0.16 wt%. This value is consistent with the hydration range of some aqueously altered meteorites (CMs, C2 Tagish Lake), but not the most aqueously altered group (CIs). The sample collection site of the OSIRIS-REx mission has slightly higher hydrogen content than average. Spatial variations in hydrogen content on Bennu's surface are linked to geomorphology, and may have been partially inherited from its parent body.

A. Praet↗

Prospects of charmonium studies in the Belle-II experiment

TheBelle-II experiment at the SuperKEKB super-B factorywill begin data acquisition in 2016, the expected integrated luminosity being 50 ab{sup -1}. A statistical data sample of record volume 50 times as large as that of the statistical data sample accumulated earlier at the Belle detector will make it possible to measure precisely the parameters of new exotic states discovered recently at B factories and to clarify the origin of these states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Automatically generated model for light alkene combustion

Light alkenes are common combustion intermediates for a variety of fuels. Therefore, understanding their oxidation and pyrolysis chemistry is key to building detailed mechanisms for heavier fuels. This work was focused on the development and evaluation of a detailed kinetic mechanism suitable for the combustion of light alkenes up to C 4 without the use of tuned parameters, instead, the parameter values come from first principles or direct measurements. The generated mechanism accurately estimates the laminar burning velocity (S u ) and ignition delay time (IDT) of light alkenes available in the literature, which represent fundamental combustion properties at a wide range of conditions. Because each parameter is thought to have a physically realistic value, not tuned to these measurements, the new model could be used as a sub-mechanism in models for other applications. The reaction network was generated with the open-source Reaction Mechanism Generator (RMG) software. Sensitivity analyses were performed under wide ranges of temperatures and pressures, allowing for the identification of the most impactful species and reactions. Based on these, a comprehensive thermochemistry database, including calculations on 550 molecules performed in this work at the CBS-QB3 level of theory, and a kinetic library, including theoretically-derived reaction rates retrieved from the literature, were built and used in the mechanism generation. The developed mechanism was compared against several existing detailed kinetic mechanisms for ethene, propene, 1-butene, 2-butene, and isobutene. Here, the newly generated model is the most accurate among the ones analyzed, in terms of fractional bias and normalized mean square error. Hence, this new model was used to analyze the chemistry of alkene combustion. Key rate coefficients were compared, to identify the cause of deviations between the models and possible areas for further improvements.

09 BIOMASS FUELS↗

Clear as mud redefined: Tunable transparent mineral scaffolds for visualizing microbial processes below ground

Microbes inhabiting complex porous microenvironments in sediments and aquifers catalyze reactions that are critical to global biogeochemical cycles and ecosystem health. However, the opacity and complexity of porous sediment and rock matrices have considerably hindered the study of microbial processes occurring within these habitats. Here, we generated microbially compatible, optically transparent mineral scaffolds to visualize and investigate microbial colonization and activities occurring in these environments, in laboratory settings and in situ. Using inexpensive synthetic cryolite mineral, we produced optically transparent scaffolds mimicking the complex 3D structure of sediments and rocks by adapting a suspension-based, freeze-casting technique commonly used in materials science. Fine-tuning of parameters, such as freezing rate and choice of solvent, provided full control of pore size and architecture. The combined effects of scaffold porosity and structure on the movement of microbe-sized particles, tested using velocity tracking of fluorescent beads, showed diverse yet reproducible behaviors. The scaffolds we produced are compatible with epifluorescence microscopy, allowing the fluorescence-based identification of colonizing microbes by DNA-based staining and fluorescence in situ hybridization (FISH) to depths of 100 µm. Additionally, Raman spectroscopy analysis indicates minimal background signal in regions used for measuring deuterium and 13 C enrichment in microorganisms, highlighting the potential to directly couple D 2 O or 13 C stable isotope probing and Raman-FISH for quantifying microbial activity at the single-cell level. To demonstrate the relevance of cryolite scaffolds for environmental field studies, we visualized their colonization by diverse microorganisms within rhizosphere sediments of a coastal seagrass plant using epifluorescence microscopy. The tool presented here enables highly resolved, spatially explicit, and multimodal investigations into the distribution, activities, and interactions of underground microbes typically obscured within opaque geological materials until now.

36 MATERIALS SCIENCE↗