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At least 469 records · Page 26

New constraints on sodium production in globular clusters from the Na 23 ( He 3 , d ) Mg 24 reaction

The star-to-star anticorrelation of sodium and oxygen is a defining feature of globular clusters, but, to date, the astrophysical site responsible for this unique chemical signature remains unknown. Sodium enrichment within these clusters depends sensitively on reaction rate of the sodium destroying reactions 23 Na(p, γ) and 23 Na(p,α). In this paper, we report the results of a 23 Na( 3 He,d) 24 Mg transfer reaction carried out at Triangle Universities Nuclear Laboratory using a 21 MeV 3 He beam. Astrophysically relevant states in 24 Mg between 11 < E x < 12 MeV were studied using high-resolution magnetic spectroscopy, thereby allowing the extraction of excitation energies and spectroscopic factors. Bayesian methods are combined with the distorted wave Born approximation to assign statistically meaningful uncertainties to the extracted spectroscopic factors. For the first time, these uncertainties are propagated through to the estimation of proton partial widths. Our experimental data are used to calculate the reaction rate. The impact of the new rates are investigated using asymptotic giant branch star models. Furthermore, it is found that while the astrophysical conditions still dominate the total uncertainty, intramodel variations on sodium production from the 23 Na(p, γ) and 23 Na(p,α) reaction channels are a lingering source of uncertainty.

20 ≤ A ≤ 38↗

Recursive Branching Simulated Annealing Algorithm

This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal solution, and the region from which new configurations can be selected shrinks as the search continues. The key difference between these algorithms is that in the SA algorithm, a single path, or trajectory, is taken in parameter space, from the starting point to the globally optimal solution, while in the RBSA algorithm, many trajectories are taken; by exploring multiple regions of the parameter space simultaneously, the algorithm has been shown to converge on the globally optimal solution about an order of magnitude faster than when using conventional algorithms. Novel features of the RBSA algorithm include: 1. More efficient searching of the parameter space due to the branching structure, in which multiple random configurations are generated and multiple promising regions of the parameter space are explored; 2. The implementation of a trust region for each parameter in the parameter space, which provides a natural way of enforcing upper- and lower-bound constraints on the parameters; and 3. The optional use of a constrained gradient- search optimization, performed on the continuous variables around each branch s configuration in parameter space to improve search efficiency by allowing for fast fine-tuning of the continuous variables within the trust region at that configuration point.

Bolcar, Matthew↗

Mercury's Seasonal Sodium Exosphere: MESSENGER Orbital Observations

The Mercury Atmospheric and Surface Composition Spectrometer (MASCS) Ultraviolet and Visible Spectrometer (UVVS) on the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft now orbiting Mercury provides the first close-up look at the planet's sodium exosphere. UVVS has observed the exosphere from orbit almost daily for over 10 Mercury years. In this paper we describe and analyze a subset of these data: altitude profiles taken above the low-latitude dayside and south pole. The observations show spatial and temporal variation but there is little or no year-to-year variation; we do not see the episodic variability reported by ground-based observers. We used these altitude profiles to make estimates of sodium density and temperature. The bulk of the exosphere is about 1200 K, much warmer than Mercury's surface. This value is consistent with some ground-based measurements and suggests that photon-stimulated desorption is the primary ejection process. We also observe a tenuous energetic component but do not see evidence of the predicted thermalized (or partially thermalized) sodium near Mercury's surface temperature. Overall we do not see the variable mixture of temperatures predicted by most Monte Carlo models of the exosphere.

Exosphere↗

Phycobilisome core architecture influences photoprotective quenching by the Orange Carotenoid Protein

Photosynthetic organisms rely on sophisticated photoprotective mechanisms to prevent oxidative damage under high or fluctuating solar illumination. Cyanobacteria, which have evolved a unique, water-soluble light-harvesting complex—the phycobilisome—achieve photoprotection through a photoactivatable quencher called the Orange Carotenoid Protein (OCP). Phycobilisomes are highly symmetric and modular, formed by hierarchical assembly of conserved subunits into diverse geometries ranging from simple bundles to elaborate fan- or bouquet-like macromolecular architectures. Although OCP is known to provide photoprotection across species of cyanobacteria with different phycobilisome structures, it is not known whether or how these structural variations relate to changes in the photoprotective function of OCP. For example, OCP was recently discovered to bind as a dimer at two specific instances of an abundant structural motif on the tricylindrical phycobilisome of Synechocystis sp. PCC 6803, yet these sites are sterically inaccessible on a more common pentacylindrical phycobilisome ( Anabaena sp. PCC 7120). To understand how structural modularity and binding specificity contribute to conservation of OCP binding sites and function across different phycobilisome architectures, here we compare experimentally measured photophysical states accessible to these prototypical tricylindrical and pentacylindrical phycobilisomes, with and without OCP, at the single-molecule level. Together with Monte Carlo simulations of exciton transfer in OCP-quenched phycobilisomes, our results suggest that OCP binds at distinct and specific sites in each type of phycobilisome, yet provides nearly identical quenching strength to both phycobilisomes. Our findings highlight the utility of modular phycobilisome structures in balancing robust conservation of photoprotective function with adaptability of site-specific binding across species.

59 BASIC BIOLOGICAL SCIENCES↗

Polarimetric thermal emission from rough surfaces

Recent theoretical works have suggested the potential of passive polarimetry in the remote sensing of geophysical media. It was shown that the third Stokes parameter U of the thermal emission may become larger for azimuthally asymmetric fields of observation. In order to investigate the potential applicability of passive polarimetry to the remote sensing of ocean surface, measurements of the polarimetric thermal emission from a sinusoidal water surface and a numerical study of the polarimetric thermal emission from randomly rough ocean surfaces were performed. Measurements of sinusoidal water surface thermal emission were performed using a sinusoidal water surface which was created by placing a thin sheet of fiberglass with a sinusoidal profile in two dimensions extended infinitely in the third dimension onto a water surface. The theory of thermal emission from a 'two-layer' periodic surface is derived and the exact solution is performed using both the extended boundary condition method (EBC) and the method of moments (MOM). The theoretical predictions are found to be in good agreement with the experimental results once the effects of the radiometer antenna pattern are included and the contribution of background noise to the measurements is modeled. The experimental results show that the U parameter indicates the direction of periodicity of the water surface and can approach values of up to 30 K for the surface observed. Next, a numerical study of polarimetric thermal emission from randomly rough surfaces was performed. A Monte Carlo technique utilizing an exact method for calculating thermal emission was chosen for the study to avoid any of the limitations of the commonly used approximate methods in rough surface scattering. In this Monte Carlo technique, a set of finite rough surface profiles in two dimensions with desired statistics was generated and extended periodically. The polarimetric thermal emission from each surface of the set was then calculated using both the EBC and the MOM and the results were averaged. The surface statistics chosen were intended to model a wind perturbed ocean surface in the X to Ku band microwave region. The results indicate that the U parameter is sensitive to the azimuthal angle between the surface periodicity and the looking angle and to the rms height of the surface, and that the U parameter is fairly insensitive to variations in polar angle, permittivity, surface power law spectrum, and surface spectrum high frequency cutoff. These properties give further strength to the idea of using the U parameter to detect wind direction over the ocean.

Johnson, J. T.↗

Analysis of the Challenges in Developing Sample-Based Multi-fidelity Estimators for Non-deterministic Models

Multifidelity (MF) uncertainty quantification (UQ) seeks to leverage and fuse information from a collection of models to achieve greater statistical accuracy with respect to a single-fidelity counterpart, while maintaining an efficient use of computational resources. Despite many recent advancements in MF UQ, several challenges remain and these often limit its practical impact in certain application areas. In this manuscript, we focus on the challenges introduced by nondeterministic models to sampling MF UQ estimators. Nondeterministic models produce different responses for the same inputs, which means their outputs are effectively noisy. MF UQ is complicated by this noise since many state-of-the-art approaches rely on statistics, e.g., the correlation among models, to optimally fuse information and allocate computational resources. Here, we demonstrate how the statistics of the quantities of interest, which impact the design, effectiveness, and use of existing MF UQ techniques, change as functions of the noise. With this in hand, we extend the unifying approximate control variate framework to account for nondeterminism, providing for the first time a rigorous means of comparing the effect of nondeterminism on different multifidelity estimators and analyzing their performance with respect to one another. Numerical examples are presented throughout the manuscript to illustrate and discuss the consequences of the presented theoretical results.

97 MATHEMATICS AND COMPUTING↗

Density, Velocity and Ionization Structure in Accretion-Disc Winds

This was a project to exploit the unique capabilities of FUSE to monitor variations in the wind- formed spectral lines of the luminous, low-inclination, cataclysmic variables(CV) -- RW Sex. (The original proposal contained two additional objects but these were not approved.) These observations were intended to allow us to determine the relative roles of density and ionization state changes in the outflow and to search for spectroscopic signatures of stochastic small-scale structure and shocked gas. By monitoring the temporal behavior of blue-ward extended absorption lines with a wide range of ionization potentials and excitation energies, we proposed to track the changing physical conditions in the outflow. We planned to use a new Monte Carlo code to calculate the ionization structure of and radiative transfer through the CV wind. The analysis therefore was intended to establish the wind geometry, kinematics and ionization state, both in a time-averaged sense and as a function of time.

Sonneborn, George↗

CTRANS: A Monte Carlo program for radiative transfer in plane parallel atmospheres with imbedded finite clouds: Development, testing and user's guide

The program called CTRANS is described which was designed to perform radiative transfer computations in an atmosphere with horizontal inhomogeneities (clouds). Since the atmosphere-ground system was to be richly detailed, the Monte Carlo method was employed. This means that results are obtained through direct modeling of the physical process of radiative transport. The effects of atmopheric or ground albedo pattern detail are essentially built up from their impact upon the transport of individual photons. The CTRANS program actually tracks the photons backwards through the atmosphere, initiating them at a receiver and following them backwards along their path to the Sun. The pattern of incident photons generated through backwards tracking automatically reflects the importance to the receiver of each region of the sky. Further, through backwards tracking, the impact of the finite field of view of the receiver and variations in its response over the field of view can be directly simulated.

Source record↗

A Statistical Simulation Approach to Safe Life Fatigue Analysis of Redundant Metallic Components

This paper introduces a dual active load path fail-safe fatigue design concept analyzed by Monte Carlo simulation. The concept utilizes the inherent fatigue life differences between selected pairs of components for an active dual path system, enhanced by a stress level bias in one component. The design is applied to a baseline design; a safe life fatigue problem studied in an American Helicopter Society (AHS) round robin. The dual active path design is compared with a two-element standby fail-safe system and the baseline design for life at specified reliability levels and weight. The sensitivity of life estimates for both the baseline and fail-safe designs was examined by considering normal and Weibull distribution laws and coefficient of variation levels. Results showed that the biased dual path system lifetimes, for both the first element failure and residual life, were much greater than for standby systems. The sensitivity of the residual life-weight relationship was not excessive at reliability levels up to R = 0.9999 and the weight penalty was small. The sensitivity of life estimates increases dramatically at higher reliability levels.

Matthews, William T.↗

The Effect of Stochastically Varying Creep Parameters on Residual Stresses in Ceramic Matrix Composites

Constituent properties, along with volume fraction, have a first order effect on the microscale fields within a composite material and influence the macroscopic response. Therefore, there is a need to assess the significance of stochastic variation in the constituent properties of composites at the higher scales. The effect of variability in the parameters controlling the time-dependent behavior, in a unidirectional SCS-6 SiC fiber-reinforced RBSN matrix composite lamina, on the residual stresses induced during processing is investigated numerically. The generalized method of cells micromechanics theory is utilized to model the ceramic matrix composite lamina using a repeating unit cell. The primary creep phases of the constituents are approximated using a Norton-Bailey, steady state, power law creep model. The effect of residual stresses on the proportional limit stress and strain to failure of the composite is demonstrated. Monte Carlo simulations were conducted using a normal distribution for the power law parameters and the resulting residual stress distributions were predicted.

residual stress↗

The Effect of Stochastically Varying Creep Parameters on Residual Stresses in Ceramic Matrix Composites

Constituent properties, along with volume fraction, have a first order effect on the microscale fields within a composite material and influence the macroscopic response. Therefore, there is a need to assess the significance of stochastic variation in the constituent properties of composites at the higher scales. The effect of variability in the parameters controlling the time-dependent behavior, in a unidirectional SCS-6 SiC fiber-reinforced RBSN matrix composite lamina, on the residual stresses induced during processing is investigated numerically. The generalized method of cells micromechanics theory is utilized to model the ceramic matrix composite lamina using a repeating unit cell. The primary creep phases of the constituents are approximated using a Norton-Bailey, steady state, power law creep model. The effect of residual stresses on the proportional limit stress and strain to failure of the composite is demonstrated. Monte Carlo simulations were conducted using a normal distribution for the power law parameters and the resulting residual stress distributions were predicted.

processing↗

Influence of Thermophysical Property Variability on Thermal Predictions of Ti-6Al-4V

The additive manufacturing (AM) industry has experienced rapid growth in recent decades as industrial interest in the process has grown. Because of this, there are many groups interested in simulations of the AM process. However, the influence of thermophysical property variability on the melt pool geometry during processing of various AM alloys is unclear. The goal of my work at NASA Langley Research Center (LaRC) was to characterize this influence on Ti-6Al-4V during AM processing alongside developing a tool to enable equivalent studies on other AM materials. To facilitate this process, a database tool was developed to contain and organize thermophysical data previously reported by primary sources. The specific thermophysical properties of interest for this study were density, specific heat capacity, and conductivity. Thermal diffusivity was calculated using the other three properties. This data was then fit with a Gaussian distribution and then randomly sampled from using Monte Carlo random value sampling. Using the Rosenthal equation, this sample data was used to simulate the temperature field during additive manufacturing and extract the melt pool geometry. Specifically, the melt pool’s length, width, and depth. This process was repeated an arbitrary number of times, with the default being 1000. Once this information was obtained, histograms were made showing the distributions of the sizes of the melt pool’s length, width, and depth. Representative statistical metrics of the distributions were calculated (mean, standard deviation, and coefficient of variance). This work found that at the simulated processing values, the melt pool’s width and depth had a 5.7% variation while the length had a 3.2% variation. Additionally, a tool was constructed to graph a thermal color map representation of the melt pool for specific, arbitrary values of density, specific heat, and conductivity. This tool allowed for more efficient plotting of individual queries of the thermophysical properties. The results that were observed in the research were that values reported in literature vary and this variance can have a significant impact on the simulation. Predictions of the melt pool’s dimensions show that length has a standard deviation of approximately 6 μm, width has a standard deviation of approximately 5 μm, and depth can vary by approximately 3 μm. Considering the mean sizes of length, width, and depth are 185 μm, 88 μm, and 44 μm respectively, such a deviation is significant. This shows that depth, for example, could be more than 10% larger or smaller than expected. This demonstrates that variability in the reported thermophysical properties are not negligible and should be expected to have an influence on the results of the laser powder bed fusion additive manufacturing process. When simulating this process in the future, measures should be taken to account for this discrepancy and the uncertainty involved

Justin Martin↗

An Iterative Response-Surface-Based Approach for Chance-Constrained AC Optimal Power Flow Considering Dependent Uncertainty

A modern power system is characterized by a stochastic variation of the loads and an increasing penetration of renewable energy generation, which results in large uncertainties in its states. These uncertainties bring formidable challenges to the power system planning and operation process. To address these challenges, we propose a cost-effective, iterative response-surface-based approach for the chance-constrained AC optimal power-flow problem that aims to ensure the secure operation of the power systems considering dependent uncertainties. Starting from a stochastic-sampling-based framework, we first utilize the copula theory to simulate the dependence among multivariate uncertain inputs. Then, to reduce the prohibitive computational time required in the traditional Monte-Carlo method, we propose, instead of using the original complicated power-system model, to rely on a polynomial-chaos-based response surface. This response surface allows us to efficiently evaluate the time-consuming power-system model at arbitrary distributed sampled values with a negligible computational cost. This further enables us to efficiently conduct an online stochastic testing for the system states that not only screens out the statistical active constraints, but also assists in a better design of the tightened bounds without using any Gaussian or symmetric assumption. Finally, an iterative procedure is executed to fine-tune the optimal solution that better satisfies a predefined probability. The simulations conducted in multiple test systems demonstrate the excellent performance of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Shock-Wave/Boundary-Layer Interactions in Hypersonic Low Density Flows

Results of numerical simulations of Mach 10 air flow over a hollow cylinder-flare and a double-cone are presented where viscous effects are significant. The flow phenomena include shock-shock and shock- boundary-layer interactions with accompanying flow separation, recirculation, and reattachment. The purpose of this study is to promote an understanding of the fundamental gas dynamics resulting from such complex interactions and to clarify the requirements for meaningful simulations of such flows when using the direct simulation Monte Carlo (DSMC) method. Particular emphasis is placed on the sensitivity of computed results to grid resolution. Comparisons of the DSMC results for the hollow cylinder-flare (30 deg.) configuration are made with the results of experimental measurements conducted in the ONERA RSCh wind tunnel for heating, pressure, and the extent of separation. Agreement between computations and measurements for various quantities is good except that for pressure. For the same flow conditions, the double- cone geometry (25 deg.- 65 deg.) produces much stronger interactions, and these interactions are investigated numerically using both DSMC and Navier-Stokes codes. For the double-cone computations, a two orders of magnitude variation in free-stream density (with Reynolds numbers from 247 to 24,7 19) is investigated using both computational methods. For this range of flow conditions, the computational results are in qualitative agreement for the extent of separation with the DSMC method always predicting a smaller separation region. Results from the Navier-Stokes calculations suggest that the flow for the highest density double-cone case may be unsteady; however, the DSMC solution does not show evidence of unsteadiness.

Moss, James N.↗

Mercury's Seasonal Sodium Exosphere: MESSENGER Orbital Observations

The Mercury Atmospheric and Surface Composition Spectrometer (MASCS) Ultraviolet and Visible Spectrometer (UVVS) on the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft now orbiting Mercury provides the first close-up look at the planet's sodium exosphere. UVVS has observed the exosphere from orbit almost daily for over 10 Mercury years. In this paper we describe and analyze a subset of these data: altitude profiles taken above the low-latitude dayside and south pole. The observations show spatial and temporal variations, but there are no obvious year-to-year variations in most of the observations. We do not see the episodic variability reported by some ground-based observers. We used these altitude profiles to make estimates of sodium density and temperature. The bulk of the exosphere, at about 1200 K, is much warmer than Mercury's surface. This value is consistent with some ground-based measurements and suggests that photon-stimulated desorption is the primary ejection process. We also observe a tenuous energetic component but do not see evidence of the predicted thermalized (or partially thermalized) sodium near Mercury's surface temperature. Overall we do not see the variable mixture of temperatures predicted by most Monte Carlo models of the exosphere.

Environment↗

Towards Integrated Computational Materials Engineering for Quantifying Performance Impacts of Microstructure and Defect Interactions in Powder Bed Fusion Parts

Powder bed fusion (PBF) additive manufacturing (AM) enables the creation of parts with complexity and functionality levels that were previously impossible with traditional manufacturing methods. By modifying the laser power, hatch spacing, or the numerous other processing parameters, the PBF process supports the production of a wide set of materials and geometries. However, that same process parameter design flexibility causes the process-design space of PBF to be massive and expensive to explore experimentally. Another challenge is quality variation across a build. As a part is being built, geometric variance between locations, such as at a thin-wall section vs. the bulk material, may cause the specified processing parameters to no longer be acceptable for producing defect-free printing. Furthermore, if the processing parameters deviate during the print process, it is difficult to assess if the part will still perform satisfactorily. Integrated Computational Materials Engineering (ICME) provides a way to understand and address these various challenges. This talk will present advancements in process-structure simulations of PBF at NASA Langley Research Center. The ability to simulate grain-scale PBF microstructures using the Physically Based Monte Carlo method will be demonstrated and compared to experimental measurements. Techniques for simulating three-dimensional lack-of-fusion and keyhole porosity defects based on the specific processing conditions and approaches for integrating the two porosity prediction techniques alongside the computational microstructure evolution models will be shown. Finally, the integration of simulated PBF microstructures, embedded process defects, and crystal plasticity finite element models to elucidate the interaction of porosity and microstructure on micromechanical fields will be demonstrated. These integrated techniques demonstrate an example of using ICME to relate processing to performance for PBF AM materials. With continued maturity, it is hoped that such ICME approaches will lead to next-generation computational-materials supported qualification and certification of AM parts.

Additive manufacturing↗

Solid propellant rocket motor internal ballistics performance variation analysis, phase 3

Results of research aimed at improving the predictability of off nominal internal ballistics performance of solid propellant rocket motors (SRMs) including thrust imbalance between two SRMs firing in parallel are reported. The potential effects of nozzle throat erosion on internal ballistic performance were studied and a propellant burning rate low postulated. The propellant burning rate model when coupled with the grain deformation model permits an excellent match between theoretical results and test data for the Titan IIIC, TU455.02, and the first Space Shuttle SRM (DM-1). Analysis of star grain deformation using an experimental model and a finite element model shows the star grain deformation effects for the Space Shuttle to be small in comparison to those of the circular perforated grain. An alternative technique was developed for predicting thrust imbalance without recourse to the Monte Carlo computer program. A scaling relationship used to relate theoretical results to test results may be applied to the alternative technique of predicting thrust imbalance or to the Monte Carlo evaluation. Extended investigation into the effect of strain rate on propellant burning rate leads to the conclusion that the thermoelastic effect is generally negligible for both steadily increasing pressure loads and oscillatory loads.

Sforzini, R. H.↗

Observations and Models of the Lunar Sodium Exosphere 1988 - 1999

Sodium in the lunar exosphere is easily observed from the Earth's surface due to its strong resonance emission lines in the visible region of the spectrum. Although sodium is a trace element, it is easily ejected from the surface by a number of processes. The variation of this exospheric constituent both spatially and temporally can help to constrain these sources and the loss processes and their timescales. Due to a revival of interest in the Moon and its volatiles, observations of the lunar exosphere obtained at the McMath-Pierce solar telescope in 1998 and 1999 have recently been reduced and analyzed. In addition, observations of the lunar sodium exosphere obtained with the Mt. Lemmon Lunar Coronagraph on Mt. Lemmon, Arizona, have also been published. We combine these new data with data previously published and reanalyzed by Sarantos et al. This comprehensive data set will be modeled using both a simple Chamberlain exosphere model and a comprehensive Monte Carlo model.

Killen, Rosemary↗