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At least 577 records · Page 32

Towards the spatial resolution of metalloprotein charge states by detailed modeling of XFEL crystallographic diffraction

Oxidation states of individual metal atoms within a metalloprotein can be assigned by examining X-ray absorption edges, which shift to higher energy for progressively more positive valence numbers. Indeed, X-ray crystallography is well suited for such a measurement, owing to its ability to spatially resolve the scattering contributions of individual metal atoms that have distinct electronic environments contributing to protein function. However, as the magnitude of the shift is quite small, about +2 eV per valence state for iron, it has only been possible to measure the effect when performed with monochromated X-ray sources at synchrotron facilities with energy resolutions in the range 2–3 × 10 −4 (Δ E / E ). This paper tests whether X-ray free-electron laser (XFEL) pulses, which have a broader bandpass (Δ E / E = 3 × 10 −3 ) when used without a monochromator, might also be useful for such studies. The program nanoBragg is used to simulate serial femtosecond crystallography (SFX) diffraction images with sufficient granularity to model the XFEL spectrum, the crystal mosaicity and the wavelength-dependent anomalous scattering factors contributed by two differently charged iron centers in the 110-amino-acid protein, ferredoxin. Bayesian methods are then used to deduce, from the simulated data, the most likely X-ray absorption curves for each metal atom in the protein, which agree well with the curves chosen for the simulation. The data analysis relies critically on the ability to measure the incident spectrum for each pulse, and also on the nanoBragg simulator to predict the size, shape and intensity profile of Bragg spots based on an underlying physical model that includes the absorption curves, which are then modified to produce the best agreement with the simulated data. This inference methodology potentially enables the use of SFX diffraction for the study of metalloenzyme mechanisms and, in general, offers a more detailed approach to Bragg spot data reduction.

59 BASIC BIOLOGICAL SCIENCES↗

Wing Shape Sensing from Measured Strain

A new two-step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least-squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to interpolate and extrapolate the deflection and slope of the entire structure through the use of the System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular plate wing. The theory is then applied to test data from a cantilevered swept-plate wing model. Computed results are compared with finite element results, results using another strain-based method, and photogrammetry data. For the computational model under an aeroelastic load, maximum deflection errors in the fore and aft, lateral, and vertical directions are -3.2 percent, 0.28 percent, and 0.09 percent, respectively; and maximum slope errors in roll and pitch directions are 0.28 percent and -3.2 percent, respectively. For the experimental model, deflection results at the tip are shown to be accurate to within 3.8 percent of the photogrammetry data and are accurate to within 2.2 percent in most cases. In general, excellent matching between target and computed values are accomplished in this study. Future refinement of this theory will allow it to monitor the deflection and health of an entire aircraft in real time, allowing for aerodynamic load computation, active flexible motion control, and active induced drag reduction..

system equivalent reduction and expansion process↗

Gray-Box Modeling for Distribution Systems With Inverter-Based Resources: Integrating Physics-Based and Data-Driven Approaches

Here, in this paper, we develop a novel gray-box modeling approach for distribution systems with inverter-based resources (IBRs). The proposed gray-box modeling method aims to improve estimation accuracy by taking advantages of both physics-based (white-box) and data-driven (black-box) modeling approaches. To this end, we utilize partial physical knowledge of the system, including the inverters’ structures and control diagrams, as well as the equivalent network model simplified through Kron reduction. The white-box model containing unknown parameters is then constructed with mathematical equations and an optimization-based method is subsequently employed to identify these unknown parameters within the white-box model. Next, the graybox modeling framework is then constructed by embedding the output variables of the white-box model into the input vector of a black-box model (represented using a neural network). Finally, the black-box section is trained using the collected input-output datasets and the gray-box model is then obtained. Furthermore, case studies demonstrate that our gray-box modeling approach effectively improves estimation accuracy compared to purely physics-based or data-driven methods.

42 ENGINEERING↗

Compressing subbanded image data with Lempel-Ziv-based coders

A method of improving the compression of image data using Lempel-Ziv-based coding is presented. Image data is first processed with a simple transform, such as the Walsh Hadamard Transform, to produce subbands. The subbanded data can be rounded to eight bits or it can be quantized for higher compression at the cost of some reduction in the quality of the reconstructed image. The data is then run-length coded to take advantage of the large runs of zeros produced by quantization. Compression results are presented and contrasted with a subband compression method using quantization followed by run-length coding and Huffman coding. The Lempel-Ziv-based coding in conjunction with run-length coding produces the best compression results at the same reconstruction quality (compared with the Huffman-based coding) on the image data used.

Glover, Daniel↗

A reforecasting-based dynamic reserve estimation for variable renewable generation and demand uncertainty

The installed capacity of renewables-based energy sources has been increasing in traditional power systems. In order to accommodate the increased variability and uncertainty associated with the deeper penetration of renewable sources like solar and wind, adjusted amounts of dynamic reserve are needed. Although probabilistic dynamic reserve estimation methods have been previously developed, most of them consider the uncertainty to be represented by parametric density functions that tend to perform poorly under extreme events and, moreover, neglect uncertainty introduced by the forecasting model itself. Toward addressing these limitations, this work presents, for the first time, a dynamic reserve estimation method for flexibility that incorporates nonparametric density estimation and a machine learning based reforecasting to provide a day-ahead prediction of the mean and spread of uncertainty around the base forecast. The prediction is, in turn, used to estimate the up and down reserve relative to the base forecast. Here, the present method takes various endogenous and exogenous features, including the calendar variables, as input to estimate the day-ahead reserve. Using a combination of reforecasting and dynamic reserve estimation techniques, the method is shown to adjust better to the dynamic nature of reserve requirements providing only what is needed to accommodate the expected deviations. Considering California Independent System Operator (CAISO) solar, wind and load data over an 18 month period, up to 67% reduction in the amount of reserve capacity needed for a one day reserve and reserve penalty for solar uncertainty is demonstrated. Additionally, the risk of reserve insufficiency in meeting the net demand is reduced by 20% with the proposed method.

14 SOLAR ENERGY↗

Planetary Protection at Marshall Space Flight Center

Introduction: NASA Marshall Space Flight Center (MSFC) is historically known for its role in propulsion. While this is still the mainstay of MSFC’s expertise, many unique capabilities exist at MSFC which pertain to Planetary Protection (PP), including 1) identifying PP threats, and 2) developing novel methods to neutralize those threats. Furthermore, because these capabilities exist among diverse groups at MSFC, this work promotes collaboration both within and outside MSFC to expand and develop PP studies related to a full spectrum of NASA research, design, manufacture, and test interests. This abstract describes the PP research ongoing at MSFC and describes how it contributes to NASA’s overall PP objectives. Microbial Identification in Cleanrooms: One of the greatest threats to successful implementation of PP requirements is recontamination post bioburden reduction. One method to prevent recontamination is to keep the spacecraft in clean environments (i.e. cleanrooms) as much as possible during assembly and integration. However, cleanrooms are not without their own sources of contamination, which is why NASA is interested in monitoring the cleanliness of cleanrooms and characterizing the microbial species present. Such information allows a greater understanding of the resistance of these microbes to cleaning methods, as well as the risk of their contaminating the targeted planetary body of a given mission. MSFC has multiple cleanrooms of various ISO cleanliness levels onsite. We sampled the air and surfaces of three of these rooms, isolated microbes, and then sequenced the 16S rRNA gene or ITS region of the 18S rRNA gene for bacterial and fungal isolates, respectively. This has resulted in a microbial library which currently includes nearly 100 isolates. Microbial Enumeration of Spacecraft Materials: Currently, there are only a couple bioburden reduction methods approved by NASA, and often the harshness of these methods presents additional concerns or risks related to material properties. The goal of this research is to assess the microbial content of solid rocket motor (SRM) materials potentially used for lander missions. This work aims to more accurately define the risk of planetary contamination by providing empirical data associated with commonly used SRM raw materials. In this study, we pulverized nonmetallic SRM materials using a cryogenic grinder, then analyzed the resulting substrate for microbial colony forming units (CFU). We found that many SRM nonmetallic materials do not harbor detectable bioburden, though a range existed depending on the material. The results from this work provide quantitative data to potentially reduce concerns of contamination, while also providing a foundation for follow up studies into additional sterilization methods and molecular identification of contaminating microbes. Space Environmental Effects on Microbial Survival: One potential area of microbial reduction is the space environment. Understanding the survivability of hardy microbes in space-like conditions is a crucial first step in answering how space may reduce bioburden and if it can be relied upon for adherence to PP requirements. This work studied the effects of ultraviolet (UV) and ionizing radiation on survival of Bacillus atrophaeus spores. Microbes were dried on relevant polymeric materials then exposed to space environmental stressors. Coupons were submerged in water, diluted, and plated to determine survival compared with controls. We found that both UV and ionizing radiation were capable of reducing viability by nearly 99%, but there were still survivors, some with changed morphology indicating resistance mechanisms within certain cells. Manufacturing credit: Finally, given the above-mentioned limitations of the NASA-approved bioburden reduction methods, there is interest in understanding if manufacturing processes may provide enough bioburden reduction without additional PP-specific bakeouts. For instance, some material additives may be antimicrobial. Given this, we investigated the effects of several commonly used rubber additives on the growth of B. atrophaeus spores. We found that some of the materials inhibited growth of the spores, possibly supporting the use of these additives on missions with PP constraints. Future work into manufacturing credit for bioburden reduction includes inoculation of green insulation with B. atrophaeus spores, followed by a typical cure. Thermal profiles will be verified for appropriate temperature and durations to meet PP requirements, and cured samples will be analyzed using a cryogenic grinder to determine survivability of spores.

Chelsi D. Cassilly↗

A Step-Down Test Procedure for Wavelet Shrinkage Using Bootstrapping

Wavelet thresholding (or shrinkage) attempts to remove the noises existing in the signals while preserving inherent pattern characteristics in the reconstruction of true signals. For data-denoising purpose, we present a new wavelet thresholding procedure which employs the step-down testing idea of identifying active contrasts in unreplicated fractional factorial experiments. The proposed method employs bootstrapping methods to a step-down test for thresholding wavelet coefficients. By introducing the concept of a false discovery error rate in testing wavelet coefficients, we shrink the wavelet coefficients with p -values higher than the error rate. The error rate controls the expected proportion of wrongly accepted coefficients among chosen wavelet coefficients. Bootstrap samples are used to approximate the p -value for computational efficiency. We also present some guidelines for selecting the values of hyper-parameters which affect the performance in the step-down thresholding procedure. Based on some common testing signals and an air-conditioner sounds example, the comparison of our proposed procedure with other thresholding methods in the literature is performed. The analytical results show that the proposed procedure has a potential in data-denoising and data-reduction in a variety of signal reconstruction applications.

42 ENGINEERING↗

A Method for Estimating Time-Series PV Production Loss From Solar Tracking Failures

Solar tracking system failures can dramatically reduce photovoltaic (PV) system energy output through suboptimal irradiance capture and self-shading loss. Detecting tracker failures is not always straightforward; unlike other common PV system failures like inverter outages and blown fuses which take portions of a system completely offline, tracker failures only partially reduce output power and can go unnoticed as a result. Additionally, tracker failures can take one of several forms, each with their own loss characteristics. Here we present two methods of detecting tracker failure events from time-series production data and a method for estimating the associated production loss. Compared with existing detection methods, the proposed power-based detection method showed 0-17% reductions in Type I error rate depending on weather conditions. Here, the loss model estimated production loss with low error (mean bias error = -2.3 %, root-mean-squared error = 6%) in a rudimentary validation.

14 SOLAR ENERGY↗

Performance of optical sensors for cloud measurements deployed by the ARM Aerial Facility during ACE-ENA

During the Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA), a variety of in situ optical sensors using shadow imaging, scattering and holography were deployed by the Atmospheric Radiation Measurement (ARM) Aerial Facility to determine cloud properties. Taking advantage of the wide, overlapping range of instrumentation, we compare in situ cloud data from several different measurement methods for droplets up to 100 µm. Further, data processing was tailored to the encountered conditions, leading to good agreement. Improvements include noise reduction for holography and better out-of-focus correction for shadow imaging. Comparison between direct liquid water content measurements and optical sensors showed better agreement at higher droplet number concentrations (>120/cm 3 ).

47 OTHER INSTRUMENTATION↗

Spectra-spectroheliograph observations.

This paper describes a photographic technique for recording solar spectra. The technique, which we call spectra-spectroheliography, requires the same amount of observing time as conventional spectroheliography but yields much more information. Data reduction techniques have been developed to use this information for the construction of spectroheliograms and other contour maps. Parameters investigated by this method include the vector magnetic field, line-of-sight velocity, continuum intensity, and line strength. Results indicate (1) good correlation between bright regions in spectroheliograms and small vertical magnetic fields; (2) poorer correlation between larger magnetic fields and bright regions; (3) a feature in the continuum resembling a pore but having no vertical magnetic field; and (4) a gradient in the vertical magnetic field of 12kG/arc sec.

Title, A. M.↗

Astrometric observations of the satellites of the outer planets. I - The Galilean satellites in 1977

Astrometric observations of the Galilean satellites of Jupiter performed around the opposition of 1977 with a 67-cm photovisual refractor are reported. The measurements are reduced to absolute and intersatellite positions by two different methods: a linear least-squares plate-constant solution to the AGK3 reference-star frame and the trail-scale method of Pascu (1977). Results of a plate-constant reduction are also presented for two observations of JV (Amalthea). Comparison of the data with Liske's (1978) theoretical predictions for the intersatellite positions indicates no systematic bias in the data; a probable scatter of about 15 arcsec in both right ascension and declination is estimated.

Ianna, P. A.↗

An industrial perspective of the LANDSAT opportunity

The feasibility of enhancing LANDSAT products to provide the greatest usability low cost data possible can be determined through government sponsorship and finance of one or more task forces composed of a critical number of experts in multiple disciplines from many industries and academia. The synergism of multiple minds addressing singular problems without the creation of permanent or perpetual structures must yield output in the form of implementable specifications, even if presented as alternatives. Changes are needed within the spacecraft in order to account for Sun angle changes. The use of pointing accuracy to make geometric corrections (and possible radiometric corrections, is needed more than onboard data reduction and information extraction, which assume a proper knowledge of application and reduce potential utilization. Multilinear arrays need to be investigated and methods for sensor calibration and for determining the effects of atmospheric inversion, as well as the best way to back out the modulation transfer function must be determined.

Williams, B. F.↗

The NASA Langley laminar-flow-control experiment on a swept, supercritical airfoil - Drag equations

The Langley Research Center has designed a swept, supercritical airfoil incorporating Laminar Flow Control for testing at transonic speeds. Analytical expressions have been developed and an evaluation made of the experimental section drag, composed of suction drag and wake drag, using theoretical design information and experimental data. The analysis shows that, although the sweep-induced boundary-layer crossflow influence on the wake drag is too large to be ignored and there is not a practical method for evaluating these crossflow effects on the experimental wake data, the conventional unswept 2-D wake-drag computation used in the reduction of the experimental data is at worst 10 percent too high.

Brooks, Cuyler W., Jr.↗

Jet Noise Reduction

The Acoustics Branch is responsible for reducing noise levels for jet and fan components on aircraft engines. To do this, data must be measured and calibrated accurately to ensure validity of test results. This noise reduction is accomplished by modifications to hardware such as jet nozzles, and by the use of other experimental hardware such as fluidic chevrons, elliptic cores, and fluidic shields. To insure validity of data calibration, a variety of software is used. This software adjusts the sound amplitude and frequency to be consistent with data taken on another day. Both the software and the hardware help make noise reduction possible. work properly. These software programs were designed to make corrections for atmosphere, shear, attenuation, electronic, and background noise. All data can be converted to a one-foot lossless condition, using the proper software corrections, making a reading independent of weather and distance. Also, data can be transformed from model scale to full scale for noise predictions of a real flight. Other programs included calculations of Over All Sound Pressure Level (OASPL), Effective Perceived Noise Level (EPNL). OASPL is the integration of sound with respect to frequency, and EPNL is weighted for a human s response to different sound frequencies and integrated with respect to time. With the proper software correction, data taken in the NATR are useful in determining ways to reduce noise. display any difference between two or more data files. Using this program and graphs of the data, the actual and predicted data can be compared. This software was tested on data collected at the Aero Acoustic Propulsion Laboratory (AAPL) using a variety of window types and overlaps. Similarly, short scripts were written to test each individual program in the software suite for verification. Each graph displays both the original points and the adjusted points connected with lines. During this summer, data points were taken during a live experiment at the AAPL to measure Nozzle Acoustic Test Rig (NATR) background noise levels. Six condenser microphones were placed in strategic locations around the dome and the inlet tunnel to measure different noise sources. From the control room the jet was monitored with the help of video cameras and other sensors. The data points were recorded, reduced, and plotted, and will be used to plan future modifications to the NATR. The primary goal to create data reduction test programs and provide verification was completed. As a result of the internship, I learned C/C++, UNIX/LINUX, Excel, and acoustic data processing methods. I also recorded data at the AAPL, then processed and plotted it. These data would be useful to compare against existing data. In addition, I adjusted software to work on the Mac OSX platform. And I used the available training resources.

Kenny, Patrick↗

Design and Analysis of Subscale and Full-Scale Buckling-Critical Cylinders for Launch Vehicle Technology Development

NASA s Shell Buckling Knockdown Factor (SBKF) project has the goal of developing new analysis-based shell buckling design factors (knockdown factors) and design and analysis technologies for launch vehicle structures. Preliminary design studies indicate that implementation of these new knockdown factors can enable significant reductions in mass and mass-growth in these vehicles. However, in order to validate any new analysis-based design data or methods, a series of carefully designed and executed structural tests are required at both the subscale and full-scale levels. This paper describes the design and analysis of three different orthogrid-stiffeNed metallic cylindrical-shell test articles. Two of the test articles are 8-ft-diameter, 6-ft-long test articles, and one test article is a 27.5-ft-diameter, 20-ft-long Space Shuttle External Tank-derived test article.

Hilburger, Mark W.↗

Multidimensional Processing and Visual Rendering of Complex 3D Biomedical Images

The proposed technology uses advanced image analysis techniques to maximize the resolution and utility of medical imaging methods being used during spaceflight. We utilize COTS technology for medical imaging, but our applications require higher resolution assessment of the medical images than is routinely applied with nominal system software. By leveraging advanced data reduction and multidimensional imaging techniques utilized in analysis of Planetary Sciences and Cell Biology imaging, it is possible to significantly increase the information extracted from the onboard biomedical imaging systems. Year 1 focused on application of these techniques to the ocular images collected on ground test subjects and ISS crewmembers. Focus was on the choroidal vasculature and the structure of the optic disc. Methods allowed for increased resolution and quantitation of structural changes enabling detailed assessment of progression over time. These techniques enhance the monitoring and evaluation of crew vision issues during space flight.

Sams, Clarence F.↗

Emergent Adaptive Noise Reduction from Communal Cooperation of Sensor Grid

In the last decade, the realization of small, inexpensive, and powerful devices with sensors, computers, and wireless communication has promised the development of massive sized sensor networks with dense deployments over large areas capable of high fidelity situational assessments. However, most management models have been based on centralized control and research has concentrated on methods for passing data from sensor devices to the central controller. Most implementations have been small but, as it is not scalable, this methodology is insufficient for massive deployments. Here, a specific application of a large sensor network for adaptive noise reduction demonstrates a new paradigm where communities of sensor/computer devices assess local conditions and make local decisions from which emerges a global behaviour. This approach obviates many of the problems of centralized control as it is not prone to single point of failure and is more scalable, efficient, robust, and fault tolerant

Jones, Kennie H.↗

Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction

In this paper, we propose a variational approach to estimate eddy viscosity using forward sensitivity method (FSM) for closure modeling in nonlinear reduced order models. FSM is a data assimilation technique that blends model's predictions with noisy observations to correct initial state and/or model parameters. We apply this approach on a projection based reduced order model (ROM) of the one-dimensional viscous Burgers equation with a square wave defining a moving shock, and the two-dimensional vorticity transport equation formulating a decay of Kraichnan turbulence. We investigate the capability of the approach to approximate an optimal value for eddy viscosity with different measurement configurations. Specifically, we show that our approach can sufficiently assimilate information either through full field or sparse noisy measurements to estimate eddy viscosity closure to cure standard Galerkin reduced order model (GROM) predictions. Therefore, our approach provides a modular framework to correct forecasting error from a sparse observational network on a latent space. We highlight that the proposed GROM-FSM framework is promising for emerging digital twin applications, where real-time sensor measurements can be used to update and optimize surrogate model's parameters.

42 ENGINEERING↗