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At least 91 records · Page 5

Error analysis of optical correlators

With the growing interest in using binary phase only filters (BPOF) in optical correlators that are implemented on magnetooptic spatial light modulators, an understanding of the effect of errors in system alignment and optical components is critical in obtaining optimal system performance. We present simulations of optical correlator performance degradation in the presence of eight errors. We break these eight errors into three groups: 1) alignment errors, 2) errors due to a combination of component imperfections and alignment errors, and 3) errors which result solely from non-ideal components. Under the first group, we simulate errors in the distance from the object to the first principle plane of the transform lens, the distance from the second principle plane of the transform lens to the filter plane, and rotational misalignment of the input mask with the filter mask. Next we consider errors which result from a combination of alignment and component imperfections. These include errors in the transform lens, the phase compensation lens, and the inverse Fourier transform lens. Lastly we have the component errors resulting from the choice of spatial light modulator. These include contrast error and phase errors caused by the non-uniform flatness of the masks. The effects of each individual error are discussed, and the result of combining all eight errors under assumptions of reasonable tolerances and system parameters is also presented. Conclusions are drawn as to which tolerances are most critical for optimal system performance.

Ma, Paul W.↗

Spatial thermal radiometry contribution to the Massif Armoricain and the Massif Central France litho-structural study

Thermal zones delimited on HCMM images, by visual interpretation only, were correlated with geological units and carbonated rocks, granitic, and volcanic rocks were individualized rock signature is evolutive parameter and some distinctions were made by addition of day, night and seasonal thermal image interpretation. This analysis also demonstrated that forest cover does not mask the underlying rocks thermal signature. Thermal linears are associated with known tectonics but the observed thermal variations from day to night and from one to another represent a promising concept to be studied in function of neotectonics and hydrogeology. The thermal anomalies discovered represent a potential interest which is to be evaluated. Significant results were obtained in the Mont Dore area and additional geological targets were defined in the Paris Basin and the Montmarault granite.

Scanvic, J. Y.↗

Spatial thermal radiometry contribution to the Massif Armoricain and the Massif Central (France) litho-structural study

Thermal zones delimited on HCMM images, by visual interpretation only, were correlated with geological units and carbonated rocks, granitic, and volcanic rocks were individualized. Rock signature is an evolutive parameter and some distinctions were made by addition of day, night and seasonal thermal image interpretation. This analysis also demonstrated that forest cover does not mask the underlying rocks thermal signature. Thermal anomalies were discovered. Geological targets were defined in the Paris Basin and the Montmarault granite.

Scanvic, J. Y.↗

Shadow masks predictions in SPARC tokamak plasma-facing components using HEAT code and machine learning methods

Here, this work uses machine learning (ML) to complement HEAT (Heat flux Engineering Analysis Toolkit) by developing 3-D footprint surrogate models for fast and accurate heat load calculations in the divertor of the SPARC tokamak. The focus is on shadowed regions, or magnetic shadows, caused by the 3-D geometry of plasma-facing components (PFCs). ML classifiers are employed to create a surrogate model for HEAT generated shadow masks, predicting these shadow masks and divertor heat flux profiles based on a diverse range of equilibria and only the plasma current, safety factor(q95) at the edge, and magnetic flux angles as input parameters. The ultimate goal is to integrate the model for real-time control and future operational decisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehicles

The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.

33 ADVANCED PROPULSION SYSTEMS↗

Uncertainty analysis of Resource Demand Model for Covid-19

As part of the Department of Energy response to the novel coronavirus pandemic of 2020, a modeling effort was sponsored by the DOE Office of Science. One task of this modeling effort at Sandia was to develop a model to predict medical resource needs given various patient arrival scenarios. Resources needed include personnel resources (nurses, ICU nurses, physicians, respiratory therapists), fixed resources (regular or ICU beds and ventilators), and consumable resources (masks, gowns, gloves, face shields, sedatives). This report documents the uncertainty analysis that was performed on the resource model. The uncertainty analysis involved sampling 26 input parameters to the model. The sampling was performed conditional on the patient arrival streams that also were inputs to the model. These patient arrival streams were derived from various epidemiology models and had a significant effect on the projected resource needs. In this report, we document the sampling approach, the parameter ranges used, and the computational workflow necessary to perform large-scale uncertainty studies for every county and state in the United States.

59 BASIC BIOLOGICAL SCIENCES↗

Translation and rotation equivariant normalizing flow (TRENF) for optimal cosmological analysis

ABSTRACT Our Universe is homogeneous and isotropic, and its perturbations obey translation and rotation symmetry. In this work, we develop translation and rotation equivariant normalizing flow (TRENF), a generative normalizing flow (NF) model which explicitly incorporates these symmetries, defining the data likelihood via a sequence of Fourier space-based convolutions and pixel-wise non-linear transforms. TRENF gives direct access to the high dimensional data likelihood p(x|y) as a function of the labels y, such as cosmological parameters. In contrast to traditional analyses based on summary statistics, the NF approach has no loss of information since it preserves the full dimensionality of the data. On Gaussian random fields, the TRENF likelihood agrees well with the analytical expression and saturates the Fisher information content in the labels y. On non-linear cosmological overdensity fields from N-body simulations, TRENF leads to significant improvements in constraining power over the standard power spectrum summary statistic. TRENF is also a generative model of the data, and we show that TRENF samples agree well with the N-body simulations it trained on, and that the inverse mapping of the data agrees well with a Gaussian white noise both visually and on various summary statistics: when this is perfectly achieved the resulting p(x|y) likelihood analysis becomes optimal. Finally, we develop a generalization of this model that can handle effects that break the symmetry of the data, such as the survey mask, which enables likelihood analysis on data without periodic boundaries.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of Retinal Vascular Branching in Human Subjects Undergoing 70-Day Head-Down Tilt by NASAs VESGEN Software

Significant risks for visual impairment were discovered recently in astronauts following spaceflight, especially after long-duration missions. We hypothesize that microgravity-induced fluid shifts result in pathological changes within the retinal vasculature that precede visual and other ocular impairments. We therefore are analyzing retinal vessels in healthy subjects before and after head-down tilt (HDT), a ground-based microgravity analog with NASA's VESsel GENeration Analysis (VESGEN) software. Methods. Spectralis® infrared (IR) fundus images were collected from both eyes of 6 subjects before and after 70 days of bed rest at 6 degree HDT (NASA Campaign 11). For our retrospective study, branching patterns in arterial and venous trees are mapped by VESGEN into vessel branching generations (Gx) that are quantified by parameters such as densities of vessel length (Lv), area (Av), number (Nv) and fractal dimension (Df) as described previously for diabetic retinopathy (IOVS 51(1):498). Results are further assigned by VESGEN into groups of large (G1-3), medium (G4-6) and small (G≥7) vessels. Results. All subjects remained asymptomatic throughout duration of HDT. To date, we have analyzed one IR image from each of the 12 eyes. Interestingly, two groups of the masked study population identified by VESGEN are distinguished by the presence or absence of small veins (G≥7). For example, L≥7 and Av≥7 are 2.7+/-1.3 E-4 px/px2 and 7.2+/-3.6 E-4 px2/px2 in 6 retinas, but 0 in the other 6 retinas. Nonetheless, the space-filling properties of the entire venous trees were remarkably uniform by all parameters, such as Df = 1.56+/-0.02 for 6 retinas with G≥7 and 1.55+/-0.02 for retinas without G≥7. No small arteries (G≥7) were detected. Conclusions. For our preliminary masked analysis, two groups of venous trees with and without small veins (G≥7) were clearly revealed by VESGEN. Upon completing all images and unmasking the subject status of before and after HDT, we will determine whether differences in the presence or absence of small veins are important correlates, and perhaps reliable predictors, of other ocular and physiological adaptations to prolonged head-down tilt and microgravity. Clinical methods for examining adaptive microvascular remodeling in the retina to microgravity space flight are not currently established.

Fractal↗

Optical Characterization of the Keck Array and BICEP3 CMB Polarimeters from 2016 to 2019

The BICEP/Keck experiment (BK) is a series of small-aperture refracting telescopes observing degree-scale cosmic microwave background (CMB) polarization from the South Pole in search of a primordial B-mode signature. This B-mode signal arises from primordial gravitational waves interacting with the CMB and has amplitude parametrized by the tensor-to-scalar ratio r. Since 2016, BICEP3 and the Keck Array have been observing with 4800 total antenna-coupled transition-edge sensor detectors, with frequency bands spanning 95, 150, 220, and 270 GHz. Here we present the optical performance of these receivers from 2016 to 2019, including far-field beams measured in situ with an improved chopped thermal source and instrument spectral response measured with a field-deployable Fourier transform spectrometer. As a pair differencing experiment, an important systematic that must be controlled is the differential beam response between the co-located, orthogonally polarized detectors. We generate per-detector far-field beam maps and the corresponding differential beam mismatch that is used to estimate the temperature-to-polarization leakage in our CMB maps and to give feedback on detector and optics fabrication. The differential beam parameters presented here were estimated using improved low-level beam map analysis techniques, including efficient removal of non-Gaussian noise as well as improved spatial masking. These techniques help minimize systematic uncertainty in the beam analysis, with the goal of constraining the bias on r induced by temperature-to-polarization leakage to be subdominant to the statistical uncertainty. This is essential as we progress to higher detector counts in the next generation of CMB experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Make the Fastest Faster: Importance Mask Synthesis for Interactive Volume Visualization using Reconstruction Neural Networks

Visualizing a large-scale volumetric dataset with high resolution is challenging due to the substantial computational time and space complexity. Recent deep learning-based image inpainting methods significantly improve rendering latency by reconstructing a high-resolution image for visualization in constant time on GPU from a partially rendered image where only a portion of pixels go through the expensive rendering pipeline. However, existing solutions need to render every pixel of either a predefined regular sampling pattern or an irregular sample pattern predicted from a low-resolution image rendering. Both methods require a significant amount of expensive pixel-level rendering. In this work, we provide Importance Mask Learning (IML) and Synthesis (IMS) networks, which are the first attempts to directly synthesize important regions of the regular sampling pattern from the user’s view parameters, to further minimize the number of pixels to render by jointly considering the dataset, user behavior, and the downstream reconstruction neural network. Our solution is a unified framework to handle various types of inpainting methods through the proposed differentiable compaction/decompaction layers. Experiments show our method can further improve the overall rendering latency of state-of-the-art volume visualization methods using reconstruction neural network for free when rendering scientific volumetric datasets. Our method can also directly optimize the off-the-shelf pre-trained reconstruction neural networks without elongated retraining.

Large-scale data↗

An experimental study of dynamic stall on advanced airfoil sections. Volume 1: Summary of the experiment

The static and dynamic characteristics of seven helicopter sections and a fixed-wing supercritical airfoil were investigated over a wide range of nominally two dimensional flow conditions, at Mach numbers up to 0.30 and Reynolds numbers up to 4 x 10 to the 6th power. Details of the experiment, estimates of measurement accuracy, and test conditions are described in this volume (the first of three volumes). Representative results are also presented and comparisons are made with data from other sources. The complete results for pressure distributions, forces, pitching moments, and boundary-layer separation and reattachment characteristics are available in graphical form in volumes 2 and 3. The results of the experiment show important differences between airfoils, which would otherwise tend to be masked by differences in wind tunnels, particularly in steady cases. All of the airfoils tested provide significant advantages over the conventional NACA 0012 profile. In general, however, the parameters of the unsteady motion appear to be more important than airfoil shape in determining the dynamic-stall airloads.

Mccroskey, W. J.↗

Algorithms and Libraries

This exploratory study initiated our inquiry into algorithms and applications that would benefit by latency tolerant approach to algorithm building, including the construction of new algorithms where appropriate. In a multithreaded execution, when a processor reaches a point where remote memory access is necessary, the request is sent out on the network and a context--switch occurs to a new thread of computation. This effectively masks a long and unpredictable latency due to remote loads, thereby providing tolerance to remote access latency. We began to develop standards to profile various algorithm and application parameters, such as the degree of parallelism, granularity, precision, instruction set mix, interprocessor communication, latency etc. These tools will continue to develop and evolve as the Information Power Grid environment matures. To provide a richer context for this research, the project also focused on issues of fault-tolerance and computation migration of numerical algorithms and software. During the initial phase we tried to increase our understanding of the bottlenecks in single processor performance. Our work began by developing an approach for the automatic generation and optimization of numerical software for processors with deep memory hierarchies and pipelined functional units. Based on the results we achieved in this study we are planning to study other architectures of interest, including development of cost models, and developing code generators appropriate to these architectures.

Dongarra, Jack↗

Optimization of Lyot Coronagrah focal plane masks for improved low-order wavefront sensing

The WFIRST Coronagraph uses a Low-Order Wavefront Sensing and Control (LOWFS/C) subsystem to stabilize the stellar wavefront. This is true for the Hybrid Lyot Coronagraph (HLC), the Shaped Pupil Coronagraph (SPC) spectrograph, and the SPC wide field of view modes. For the SPC spectrograph, we have found via modeling and simulations that a focal plane mask (FPM) with an elliptical phase dimple can reduce the LOWFS errors significantly compared to the conventional, circular phase dimple. For HLC designs, we concurrently optimized the FPM parameters and deformable mirror shapes using our open-source software toolbox, the Fast Linearized Coronagraph Optimizer (FALCO). This process resulted in new FPMs with non-uniform central-area phase modulation. We have found in numerical simulations that such FPMs still provide sufficient LOWFS performance. In this paper, we will present the LOWFS performance for several new HLC and SPC FPM designs.

Riggs, A.J. Eldorado↗

Length Scale and Gravity Effects on Microgravity Boiling Heat Transfer

Boiling is a complex phenomenon where hydrodynamics, heat transfer, mass transfer, and interfacial phenomena are tightly interwoven. An understanding of boiling and critical heat flux in microgravity environments is of importance to space based hardware and processes such as heat exchange, cryogenic fuel storage and transportation, electronic cooling, and material processing due to the large amounts of heat that can be removed with relatively little increase in temperature. Although research in this area has been performed in the past four decades, the mechanisms by which heat is removed from surfaces in microgravity are still unclear. In earth gravity, buoyancy is an important parameter that affects boiling heat transfer through the rate at which bubbles are removed from the surface. A simple model describing the bubble departure size based on a quasistatic force balance between buoyancy and surface tension is given by the Fritz [I] relation: Bo(exp 1/2) = 0.0208 theta where Bo is the ratio between buoyancy and surface tension forces. For small, rapidly growing bubbles, inertia associated with the induced liquid motion can also cause bubble departure. In microgravity, the magnitude of effects related to natural convection and buoyancy are small and physical mechanisms normally masked by natural convection in earth gravity such as Marangoni convection can substantially influence the boiling and vapor bubble dynamics. CHF (critical heat transfer) is also substantially affected by microgravity. In 1 g environments, Bo has been used as a correlating parameter for CHF. Zuber's CHF model for an infinite horizontal surface assumes that vapor columns formed by the merger of bubbles become unstable due to a Helmholtz instability blocking the supply of liquid to the surface. The jets are spaced lambda(sub D) apart, where lambda(sub D) = 2pi square root of 3[(sigma)/(g(rho(sub l) - rho(sub v)](exp 1/2) = 2pi square root of 3 L Bo(exp -1/2) = square root of 3 lambda(sub c) and is the wavelength that amplifies most rapidly. The critical wavelength, lambda(sub c), is the wavelength below which a vapor layer underneath a liquid layer is stable. For heaters with Bo smaller than about 3 (heaters smaller than lambda(sub D)), the above model is not applicable, and surface tension effects dominate. Bubble coalescence is thought to be the mechanism for CHF under these conditions. Small Bo can result by decreasing the size of a heater in earth gravity, or by operating a large heater in a lower gravity environment. In the microgravity of space, even large heaters can have low Bo, and models based on Helmholtz instability should not be applicable. The macrolayer model of Haramura and Katto is dimensionally equivalent to Zuber's model and has the same dependence on gravity, so it should not be applicable as well. The goal of this work is to determine how boiling heat transfer mechanisms in a low-g environment are altered from those at higher gravity levels. Boiling data using a microheater array was obtained under gravity environments ranging from 1.8 g to 0.02 g with heater sizes ranging from 2.7 mm to 1 mm. The boiling behavior for 2.7 mm at 0.02 g looked quite similar to boiling on the 1 mm heater at 1 g-the formation of a large primary bubble surrounded by smaller satellite bubbles was observed under both conditions. The similarity suggests that for heaters smaller than some fraction of I(sub c), coalescence and surface tension dominate boiling heat transfer. It also suggests that microgravity boiling can be studied by studying boiling on very small heaters.

Kim, Jungho↗

Increase in whole-body peripheral vascular resistance during three hours of air or oxygen prebreathing

Male and female subjects prebreathed air or 100% oxygen through a mask for 3.0 hours while comfortably reclined. Blood pressures, heart rate, and cardiac output were collected before and after the prebreathe. Peripheral vascular resistance (PVR) was calculated from these parameters and increased by 29% during oxygen prebreathing and 15% during air prebreathing. The oxygen contributed substantially to the increase in PVR. Diastolic blood pressure increased by 18% during the oxygen prebreathe while stystolic blood pressure showed no change under either procedure. The increase in PVR during air prebreathing was attributed to procedural stress common to air and oxygen prebreathing.

Waligora, J. M.↗

Cellular Statistical Models of Broken Cloud Fields. Part IV: Effects of Pixel Size on Idealized Satellite Observations

In the fourth part of our “Cellular Statistical Models of Broken Cloud Fields” series we use the binary Markov processes framework for quantitative investigation of the effects of low resolution of idealized satellite observations on the statistics of the retrieved cloud masks. We assume that the cloud fields are Markovian and are characterized by the “actual” cloud fraction (CF) and scale length. We use two different models of observations: a simple discrete-point sampling and a more realistic “pixel” protocol. The latter is characterized by a state attribution function (SAF) which has the meaning of the probability that the pixel with a certain CF is declared cloudy in the observed cloud mask. The stochasticity of the SAF means that the cloud/clear attribution is not ideal and can be affected by external or unknown factors. We show that the observed cloud masks can be accurately described as Markov chains of pixels and use the master-matrix formalism (introduced in Part III of the series) for analytical computation of their parameters: the “observed” CF and scale length. This procedure allows us to establish a quantitative relationship (which is pixel-size dependent) between the actual and the observed cloud-field statistics. The feasibility of restoring the former from the latter is considered. The adequacy of our analytical approach to idealized observations is evaluated using numerical simulations. Comparison of the observed parameters of the simulated datasets with their theoretical expectations showed an agreement within 0.005 for the CF, while for the scale length it is within 1% in the sampling case and within 4% in the pixel case.

Mikhail D. Alexandrov↗

Coronal Plumes in the Fast Solar Wind

The expansion of a coronal hole filled with a discrete number of higher density coronal plumes is simulated using a time-dependent two-dimensional code. A solar wind model including an exponential coronal heating function and a flux of Alfven waves propagating both inside and outside the structures is taken as a basic state. Different plasma plume profiles are obtained by using different scale heights for the heating rates. Remote sensing and solar wind in situ observations are used to constrain the parameter range of the study. Time dependence due to plume ignition and disappearance is also discussed. Velocity differences of the order of approximately 50 km/s, such as those found in microstreams in the high-speed solar wind, may be easily explained by slightly different heat deposition profiles in different plumes. Statistical pressure balance in the fast wind data may be masked by the large variety of body and surface waves which the higher density filaments may carry, so the absence of pressure balance in the microstreams should not rule out their interpretation as the extension of coronal plumes into interplanetary space. Mixing of plume-interplume material via the Kelvin-Helmholtz instability seems to be possible within the parameter ranges of the models defined here, only at large di stances from the Sun, beyond 0.2-0.3 AU. Plasma and composition measurements in the inner heliosphere, such as those which will become available with Solar Orbiter and Solar Probe Plus, should therefore definitely be able to identify plume remnants in the solar wind.

Velli, Marco↗

A non-local thermodynamic equilibrium, line-blanketed synthetic spectrum of Iota Herculis - C, Al, and Si lines

A non-LTE line-blanketed model stellar atmosphere is used to compute a model of I Herculis (B3 IV) with a Teff of 17,500 K and a log g of 3.75, following the conclusions of Peters and Polidan (1985). Detailed profiles of a number of lines of C, Al, and Si in the 1200-2000-A region are computed, including the resonance lines of C II, Al II, and Al III. These profiles are compared to observations obtained from the coaddition of eight IUE SWP images, using a technique developed by Leckrone and Adelman (1989). Comparison of carbon lines with a model that is underabundant in carbon by a factor of 2 relative to the sun indicates that the C abundance of Iota Her is at most one-half solar. Non-LTE effects are examined by comparing an LTE model possessing identical atmospheric parameters with the non-LTE model. Substantial differences in the populations of the model atomic states are found, but differences in the temperature structure of the two models often mask the non-LTE effects in the synthetic spectra.

Grigsby, James A.↗