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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10

Radiation breakage of DNA: a model based on random-walk chromatin structure

Monte Carlo computer software, called DNAbreak, has recently been developed to analyze observed non-random clustering of DNA double strand breaks in chromatin after exposure to densely ionizing radiation. The software models coarse-grained configurations of chromatin and radiation tracks, small-scale details being suppressed in order to obtain statistical results for larger scales, up to the size of a whole chromosome. We here give an analytic counterpart of the numerical model, useful for benchmarks, for elucidating the numerical results, for analyzing the assumptions of a more general but less mechanistic "randomly-located-clusters" formalism, and, potentially, for speeding up the calculations. The equations characterize multi-track DNA fragment-size distributions in terms of one-track action; an important step in extrapolating high-dose laboratory results to the much lower doses of main interest in environmental or occupational risk estimation. The approach can utilize the experimental information on DNA fragment-size distributions to draw inferences about large-scale chromatin geometry during cell-cycle interphase.

Chromatin/radiation effects↗

Launch Vehicle Propulsion Parameter Design Multiple Selection Criteria

The optimization tool described herein addresses and emphasizes the use of computer tools to model a system and focuses on a concept development approach for a liquid hydrogen/liquid oxygen single-stage-to-orbit system, but more particularly the development of the optimized system using new techniques. This methodology uses new and innovative tools to run Monte Carlo simulations, genetic algorithm solvers, and statistical models in order to optimize a design concept. The concept launch vehicle and propulsion system were modeled and optimized to determine the best design for weight and cost by varying design and technology parameters. Uncertainty levels were applied using Monte Carlo Simulations and the model output was compared to the National Aeronautics and Space Administration Space Shuttle Main Engine. Several key conclusions are summarized here for the model results. First, the Gross Liftoff Weight and Dry Weight were 67% higher for the design case for minimization of Design, Development, Test and Evaluation cost when compared to the weights determined by the minimization of Gross Liftoff Weight case. In turn, the Design, Development, Test and Evaluation cost was 53% higher for optimized Gross Liftoff Weight case when compared to the cost determined by case for minimization of Design, Development, Test and Evaluation cost. Therefore, a 53% increase in Design, Development, Test and Evaluation cost results in a 67% reduction in Gross Liftoff Weight. Secondly, the tool outputs define the sensitivity of propulsion parameters, technology and cost factors and how these parameters differ when cost and weight are optimized separately. A key finding was that for a Space Shuttle Main Engine thrust level the oxidizer/fuel ratio of 6.6 resulted in the lowest Gross Liftoff Weight rather than at 5.2 for the maximum specific impulse, demonstrating the relationships between specific impulse, engine weight, tank volume and tank weight. Lastly, the optimum chamber pressure for Gross Liftoff Weight minimization was 2713 pounds per square inch as compared to 3162 for the Design, Development, Test and Evaluation cost optimization case. This chamber pressure range is close to 3000 pounds per square inch for the Space Shuttle Main Engine.

Shelton, Joey Dewayne↗

Launch Vehicle Propulsion Design with Multiple Selection Criteria

The approach and techniques described herein define an optimization and evaluation approach for a liquid hydrogen/liquid oxygen single-stage-to-orbit system. The method uses Monte Carlo simulations, genetic algorithm solvers, a propulsion thermo-chemical code, power series regression curves for historical data, and statistical models in order to optimize a vehicle system. The system, including parameters for engine chamber pressure, area ratio, and oxidizer/fuel ratio, was modeled and optimized to determine the best design for seven separate design weight and cost cases by varying design and technology parameters. Significant model results show that a 53% increase in Design, Development, Test and Evaluation cost results in a 67% reduction in Gross Liftoff Weight. Other key findings show the sensitivity of propulsion parameters, technology factors, and cost factors and how these parameters differ when cost and weight are optimized separately. Each of the three key propulsion parameters; chamber pressure, area ratio, and oxidizer/fuel ratio, are optimized in the seven design cases and results are plotted to show impacts to engine mass and overall vehicle mass.

Shelton, Joey D.↗

Data Mining and Complex Problems: Case Study in Composite Materials

Data mining is defined as the discovery of useful, possibly unexpected, patterns and relationships in data using statistical and non-statistical techniques in order to develop schemes for decision and policy making. Data mining can be used to discover the sources and causes of problems in complex systems. In addition, data mining can support simulation strategies by finding the different constants and parameters to be used in the development of simulation models. This paper introduces a framework for data mining and its application to complex problems. To further explain some of the concepts outlined in this paper, the potential application to the NASA Shuttle Reinforced Carbon-Carbon structures and genetic programming is used as an illustration.

Rabelo, Luis↗

Supersonic Testing of 0.8 m Disk Gap Band Parachutes in the Wake of a 70 Deg Sphere Cone Entry Vehicle

Supersonic wind tunnel testing of Viking-type 0.8 m Disk-Gap-Band (DGB) parachutes was conducted in the NASA Glenn Research Center 10'x10' wind-tunnel. The tests were conducted in support of the Mars Science Laboratory Parachute Decelerator System development and qualification program. The aerodynamic coupling of the entry-vehicle wake to parachute flow-field is under investigation to determine the cause and functional dependence of a supersonic canopy breathing phenomenon referred to as area oscillations, characteristic of DGB's above Mach 1.5 operation. Four percent of full-scale parachutes (0.8 m) were constructed similar to the flight-article in material and construction techniques. The parachutes were attached to a 70-deg sphere-cone entry-vehicle to simulate the Mars flight configuration. The parachutes were tested in the wind-tunnel from Mach 2 to 2.5 in a Reynolds number range of 2x105 to 1x106, representative of a Mars deployment. Three different test configurations were investigated. In the first two configurations, the parachutes were constrained horizontally through the vent region to measure canopy breathing and wake interaction for fixed trim angles of 0 and 10 degrees from the free-stream. In the third configuration the parachute was unconstrained, permitted to trim and cone, similar to free-flight (but capsule motion is constrained), varying its alignment relative to the entry-vehicle wake. Non-intrusive test diagnostics were chosen to quantify parachute performance and provide insight into the flow field structure. An in-line loadcell provided measurement of unsteady and mean drag. Shadowgraph of the upstream parachute flow field was used to capture bow-shock motion and wake coupling. Particle image velocimetry provided first and second order flow field statistics over a planar region of the flow field, just upstream of the parachute. A photogrammetric technique was used to quantify fabric motion using multiple high speed video cameras to record the location in time and space of reflective targets placed on the canopy interior. The experimental findings including an updated drag model and the physical basis of the area oscillation phenomenon will be discussed.

EDL↗

Tropopause Laminar Cirrus and Its Role in the Lower Stratosphere Total Water Budget

Laminar cirrus are thin, extensive, isolated layers of ice clouds frequently observed in the tropical tropopause layer. Widespread laminar cirrus significantly affects tropical tropopause layer total water and thermal budget. In this study, we extract laminar cirrus from the Cloud‐Aerosol Lidar with Orthogonal Polarization Level 1 attenuated total backscatter images for January 2009, in order to characterize statistical properties of laminar cirrus cloud length, base, thickness, optical depth, and layer partial ice water path. These characteristics are used to develop an algorithm identifying laminar cirrus automatically from the Cloud‐Aerosol Lidar with Orthogonal Polarization Level 2 layer product for 2008–2017. The nearly 10‐year records reveal that tropopause laminar cirrus occurrence (30–40% of total cirrus) is strongly anticorrelated with the tropopause temperatures in that colder tropopause in frequent (super)saturation during boreal winter favors in situ formation of clouds. Interannually, anomalously warmer troposphere temperature (ΔT), easterly shear of the quasi‐biennial oscillation, and stronger upwelling branch of the Brewer‐Dobson circulation enhance laminar cirrus formation via cooling of the tropopause. The tropopause laminar cirrus carries ~0.05 mg/m(exp 3) (~0.5 ppmv) of ice water content during boreal winter and <0.01 mg/m(exp 3) during summer, which is anticorrelated with the seasonal variations of water vapor (H2O) observed by the Microwave Lime Sounder, indicating a temperature‐regulated partition between vapor and ice. Interannually, in cirrus‐rich region 1 ppmv decrease in H2O corresponds to 0.2–0.3 ppmv increase in ice water content. Frequently situated in (super)saturated air, tropopause laminar cirrus are likely to survive multiple lifecycles of the sublimation‐deposition processes, and may contribute up to 10% to the total water budget in the lower stratosphere. Satellites constantly observe thin, isolated, extensive layer of cirrus around the tropopause. The so‐called “laminar” cirrus occurrence and their ice amount are strongly regulated by temperature, such that colder temperatures favor more frequent (super)saturation, which results in more frequent laminar cirrus with more ice amount and therefore less water vapor. In this study we analyze laminar cirrus and water vapor from the Cloud‐Aerosol Lidar with Orthogonal Polarization and Microwave Lime Sounder observations, and hypothesize that laminar cirrus could act as an important transient water storage and contribute to the total water budget in the lower stratosphere.

Tao Wang↗

Scale resolving simulations of the NASA Juncture Flow Model using the LAVA solver

Two distinct simulation methodologies: Delayed Detached Eddy Simulation (DDES) and stress based Wall-modelled Large Eddy Simulation (WMLES) are evaluated using structured overset curvilinear grids for the NASA juncture flow model. While both methodologies are shown to mitigate the primary shortcomings of steady state Reynolds Averaged Navier Stokes(RANS) simulations, several unresolved aspects are identified. Strong sensitivity to RANS-typegrid refinement is observed in the DDES with a substantial deterioration of the solution quality with increasing spatial resolution associated with deficiencies in the shielding function. Mean profiles for attached boundary layers on the fuselage show spurious inflections suggesting modelled stress depletion on finer grids. Lower numerical dissipation in terms of spatial discretization and time step size is seen to improve the solution quality, and the advantage of using RC and QCR2000 corrections in the underlying RANS closure is demonstrated for DDES on RANS-type meshes. Equilibrium Wall-Modelled LES used grids that resolved the tripping dots over the fuselage nose and the wing leading edge, consistent with the experiment setup. These simulations resulted in a cost-competitive approach compared to DDES on RANS-type grids. Although the agreement between WMLES predictions of first and second order single point statistics with experimental measurements is promising, a fundamental shortcoming is noted in terms of an overshoot in streamwise momentum in corner regions of the wing-fuselage juncture. This excess momentum subsequently delays the onset of separation,thereby resulting in an underprediction in length of the separation bubble. Some quantitative sensitivity to numerical discretization is observed; lowering of numerical dissipation shows better agreement with the experiment.

T^3↗

Conditions of Loss Cone Filling by Scattering on the Curved Field Lines for 30 keV Protons During Geomagnetic Storm as Inferred From Numerical Trajectory Tracing

The rate of pitch angle scattering on the curved magnetic field lines is well parameterized by the ratio of the minimum field line curvature radius to the maximum effective particle gyroradius (K = RC/rg). The critical value of this ratio (Kcr) corresponding to the loss cone filling is of special interest since it corresponds to the low altitude isotropic boundaries (IBs). The early theoretical estimates gave Kcr = 8, whereas recent estimations of the K parameter on the field lines corresponding to the observed IBs during the geomagnetic storms revealed KIB values in the range of 3–30. We numerically trace the trajectories of the 30 keV protons in the magnetic field of the global magnetohydrodynamic simulation of the intense storm in order to infer statistical distribution of Kcr. The electric field and effects of nonstationarity are neglected in this study. It is found that although the Kcr values do show some variations during the course of the storm, its range is rather narrow 4 < Kcr < 8. The result suggests that higher KIB values found in the observational studies, if not caused by the magnetosphere-ionosphere mapping error, should be attributed to some other mechanism of pitch angle scattering. The Kcr values tend to be lower (4–6) during the main phase because the region of low K values approaches the Earth and the equatorial loss cone size becomes larger due to a larger equatorial magnetic field in the near earth region. The remaining variation of Kcr is explained by the presence of the guide component of the magnetic field.

S Dubyagin↗

Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

The Kalman filter is the optimal filter in the presence of known gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions. Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz model as well as more realistic models of the means and atmosphere. A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter situations to allow for correct update of the ensemble members. The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to be quite puzzling in that results state estimates are worse than for their filter analogue. In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use the Lorenz model to test and compare the behavior of a variety of implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Zhu, Yanqui↗

The Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

The Kalman filter is the optimal filter in the presence of known Gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions (e.g., Miller 1994). Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz (1963) model as well as more realistic models of the oceans (Evensen and van Leeuwen 1996) and atmosphere (Houtekamer and Mitchell 1998). A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter equations to allow for correct update of the ensemble members (Burgers 1998). The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to quite puzzling in that results of state estimate are worse than for their filter analogue (Evensen 1997). In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use Lorenz (1963) model to test and compare the behavior of a variety implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Zhu, Yanqiu↗

Fermi and Swift Gamma-Ray Burst Afterglow Population Studies

The new and extreme population of GRBs detected by Fermi-LAT shows several new features in high energy gamma-rays that are providing interesting and unexpected clues into GRB prompt and afterglow emission mechanisms. Over the last 6 years, it has been Swift that has provided the robust data set of UV/optical and X-ray afterglow observations that opened many windows into components of GRB emission structure. The relationship between the LAT GRBs and the well studied, fainter, less energetic GRBs detected by Swift-BAT is only beginning to be explored by multiwavelength studies. We explore the large sample of GRBs detected by BAT only, BAT and Fermi-GBM, and GBM and LAT, focusing on these samples separately in order to search for statistically significant differences between the populations, using only those GRBs with measured redshifts in order to physically characterize these objects. We disentangle which differences are instrumental selection effects versus intrinsic properties, in order to better understand the nature of the special characteristics of the LAT bursts.

Racusin, J. L.↗

Fermi and Swift Gamma-Ray Burst Afterglow Population Studies

The new and extreme population of GRBs detected by Fermi-LAT shows several new features in high energy gamma-rays that are providing interesting and unexpected clues into GRB prompt and afterglow emission mechanisms. Over the last 6 years, it has been Swift that has provided the robust data set of UV/optical and X-ray afterglow observations that opened many windows into components of GRB emission structure. The relationship between the LAT GRBs and the well studied, fainter, less energetic GRBs detected by Swift-BAT is only beginning to be explored by multi-wavelength studies. We explore the large sample of GRBs detected by BAT only, BAT and Fermi-GBM, and GBM and LAT, focusing on these samples separately in order to search for statistically significant differences between the populations, using only those GRBs with measured redshifts in order to physically characterize these objects. We disentangle which differences are instrumental selection effects versus intrinsic properties, in order to better understand the nature of the special characteristics of the LAT bursts.

Racusin, Judith I.↗

Fermi and Swift Gamma-Ray Burst Afterglow Population Studies

The new and extreme population of GRBs detected by Fermi -LAT shows several new features in high energy gamma-rays that are providing interesting and unexpected clues into GRB prompt and afterglow emission mechanisms. Over the last 6 years, it has been Swift that has provided the robust dataset of UV/optical and X-ray afterglow observations that opened many windows into components of GRB emission structure. The relationship between the LAT detected GRBs and the well studied, fainter, less energetic GRBs detected by Swift -BAT is only beginning to be explored by multi-wavelength studies. We explore the large sample of GRBs detected by BAT only, BAT and Fermi -GBM, and GBM and LAT, focusing on these samples separately in order to search for statistically significant differences between the populations, using only those GRBs with measured redshifts in order to physically characterize these objects. We disentangle which differences are instrumental selection effects versus intrinsic properties, in order to better understand the nature of the special characteristics of the LAT bursts.

Racusin, Judith L.↗

Small-Scale Variability of Large Cloud Drops

Cloud droplet size distribution is one of the most fundamental subjects in cloud physics. Understanding of spatial distribution and small-scale fluctuations of cloud droplets is essential for both cloud physics and atmospheric radiation. For cloud physics, it relates to the coalescence growth of raindrops while for radiation, it has a strong impact on a cloud's radiative properties. Most of the existing cloud radiation and precipitation formation models assume that the mean number of drops with a given radius varies proportionally to volume. The analysis of microphysical data on liquid water drop sizes shows that, for sufficiently small volumes, the number is proportional to the drop size dependent power of the volume. For abundant small drops present, the exponent is 1 as assumed in the conventional approach. However, for rarer large drops, the exponents fall below unity. At small scales, therefore, the mean number of large drops decreases with volume at a slower rate than the conventional approach assumes, suggesting more large drops at these scales than conventional models account for; their impact is consequently underestimated. Size dependent models of spatial distribution of cloud drops that simulate the observed power laws show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents. The strong clustering of large drops arises naturally from the observed power-law statistics. Current theories of photon-cloud interaction and warm rain formation will need radical revision in order to produce these statistics; their underlying equations are unable to yield the observed power law.

Marshak, Alexander↗

Effect of Random Geometric Uncertainty on the Computational Design of a 3-D Flexible Wing

The effect of geometric uncertainty due to statistically independent, random, normally distributed shape parameters is demonstrated in the computational design of a 3-D flexible wing. A first-order second-moment statistical approximation method is used to propagate the assumed input uncertainty through coupled Euler CFD aerodynamic / finite element structural codes for both analysis and sensitivity analysis. First-order sensitivity derivatives obtained by automatic differentiation are used in the input uncertainty propagation. These propagated uncertainties are then used to perform a robust design of a simple 3-D flexible wing at supercritical flow conditions. The effect of the random input uncertainties is shown by comparison with conventional deterministic design results. Sample results are shown for wing planform, airfoil section, and structural sizing variables.

Gumbert, C. R.↗

Statistical fatigue of graphite/epoxy angle-ply laminates in shear

A three-parameter fatigue and residual strength degradation model has been proposed to predict statistically the fatigue behavior of composite laminae under axial shear loadings. The fatigue behavior includes the fatigue life and the fatigue damage expressed in terms of the residual strength degradation. An experimental test program using graphite/epoxy /+ or - 45 deg/2s laminates has been conducted to generate statistically meaningful data in order to examine the validity of the theoretical model. It is shown that the correlation between the theoretical predictions and the test results on the statistical distributions of the fatigue life and the residual strength is excellent. Test results on the shear modulus degradation are also presented and discussed in detail in order to provide insight for the establishment of a shear modulus degradation model.

Yang, J. N.↗

A model for the simulation of atmospheric turbulence

A method that produces realistic simulations of atmospheric turbulence is developed and analyzed. The procedure makes use of a generalized spectral analysis, often called a proper orthogonal decomposition or the Karhunen-Loeve expansion. A set of criteria, emphasizing a realistic appearance, a correct spectral shape, and non-Gaussian statistics, is selected in order to evaluate the model turbulence. An actual turbulence record is analyzed in detail, providing both a standard for comparison and input statistics for the generalized spectral analysis. The simulation utilizes the eigenfunction-expansion procedure to produce preliminary time histories of the three velocity components simultaneously. It is found that important cross-statistical features are reasonably well-behaved.

Petersen, E. L.↗

The role of phenology in statistical crop acreage measurement

In order to achieve market acceptance, the accuracy of remote sensing systems needs to be increased from the historically achieved average level of approximately 80-85% to 96-98%, i.e., by a factor of at least three, preferably five. A theory of discrimination is developed based on the fine-grained spectral data from LACIE supersites. It is shown that significant improvements in discrimination accuracy are possible by exploiting the differentials of crop spectra occurring between different phenologic stages. The major effects of such techniques on data system design are examined with respect to recurrence frequency, data volume, and information extraction.

Castruccio, P. A.↗