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At least 1,639 records · Page 91

Uncertainty Estimation for SMAP Level-1 Brightness Temperature Assimilation at Different Timescales

Soil Moisture Active Passive (SMAP) mission brightness temperature (T(b) ) observations are assimilated into NASA’s Catchment Land Surface Model using an Ensemble Kalman filter to update simulations of surface and root-zone soil moisture. Different time series components of the T(b) observations are assimilated including anomalies, inter-annual variations, and high frequency variations. To optimize the weights that the data assimilation (DA) puts on the observations, the ratio between the uncertainties of modeled and observed T(b) is approximated using modeled and observed soil moisture uncertainties estimated using triple collocation analysis. In a benchmark experiment, T(b) observations are assimilated using a spatially constant 4 Kelvin (K) observation uncertainty, as in the operational SMAP Level-4 algorithm. All DA experiments exhibit notable skill improvements in most regions. Improvements are largest for the inter-annual variations in the simulations of both surface and root-zone soil moisture (mean improvements in terms of Pearson correlation (-) are 0.08 and 0.06, respectively). Anomaly simulations improve similarly (0.07), and improvements in the high-frequency variations are only observed for surface soil moisture simulations (0.06). No notable difference in skill - neither improvement nor deterioration - is observed between the experiments that use optimized observation uncertainty parameters and the 4 K benchmark experiment. This may be explained by the presence of large observation operator errors, which are analytically shown to have the potential to render post-update uncertainty insensitive to inaccuracies in estimates of the Kalman gain. These results have important implications for the design of soil moisture DA systems, in particular for parameterizing model and observation uncertainties.

Hydrology↗

INVESTIGATING THE POTENTIAL DILUTION OF THE METAL CONTENT OF HOT GAS IN EARLY-TYPE GALAXIES BY ACCRETED COLD GAS

The measured emission-weighted metal abundance of the hot gas in early-type galaxies has been known to be lower than theoretical expectations for 20 years. In addition, both X-ray luminosity and metal abundance vary significantly among galaxies of similar optical luminosities. This suggests some missing factors in the galaxy evolution process, especially the metal enrichment process. With Chandra and XMM-Newton, we studied 32 early-type galaxies (kT {approx}< 1 keV) covering a span of two orders of L{sub X,gas}/L{sub K} to investigate these missing factors. Contrary to previous studies that X-ray faint galaxies show extremely low Fe abundance ({approx}0.1 Z{sub Sun }), nearly all galaxies in our sample show an Fe abundance at least 0.3 Z{sub Sun }, although the measured Fe abundance difference between X-ray faint and X-ray bright galaxies remains remarkable. We investigated whether this dichotomy of hot gas Fe abundances can be related to the dilution of hot gas by mixing with cold gas. With a subset of 24 galaxies in this sample, we find that there is virtually no correlation between hot gas Fe abundances and their atomic gas content, which disproves the scenario that the low metal abundance of X-ray faint galaxies might be a result of the dilution of the remaining hot gas by pristine atomic gas. In contrast, we demonstrate a negative correlation between the measured hot gas Fe abundance and the ratio of molecular gas mass to hot gas mass, although it is unclear what is responsible for this apparent anti-correlation. We discuss several possibilities including that externally originated molecular gas might be able to dilute the hot gas metal content. Alternatively, the measured hot gas Fe abundance may be underestimated due to more complex temperature and abundance structures and even a two-temperature model might be insufficient to reflect the true value of the emission weighted mean Fe abundance.

79 ASTRONOMY AND ASTROPHYSICS↗

Unified understanding of the impact of semiflexibility, concentration, and molecular weight on macromolecular-scale ring diffusion

Conformationally fluctuating, globally compact macromolecules such as polymeric rings, single-chain nanoparticles, microgels, and many-arm stars display complex dynamic behaviors due to their rich topological structure and intermolecular organization. Synthetic rings are hybrid objects with conformations that display both ideal random walk and compact globular features, which can serve as models of genomic DNA. To date, emphasis has been placed on the effect of ring molecular weight on their unusual behaviors. Here, we combine simulations and a microscopic force-level theory to build a unified understanding for how key aspects of ring dynamics depend on different tunable molecular properties including backbone rigidity, monomer concentration, degree of traditional entanglement, and molecular weight. Our large-scale molecular dynamics simulations of ring melts with very different backbone stiffnesses reveal unanticipated behaviors which agree well with our generalized theory. This includes a universal master curve for center-of-mass diffusion constants as a function of molecular weight scaled by a chemistry and thermodynamic state-dependent critical molecular weight that generalizes the concept of an entanglement cross-over for linear chains. The key physics is how backbone rigidity and monomer concentration induced changes of the entanglement length, interring packing, degree of interpenetration, and liquid compressibility slow down space-time dynamic-force correlations on macromolecular scales. A power law decay of the center-of-mass diffusion constant with inverse molecular weight squared is the first consequence, followed by an ultraslow activated hopping transport regime. Our results set the stage to address slow dynamics and kinetic arrest in different families of compact synthetic and biological polymeric systems.

Science & Technology - Other Topics↗

Progressive Damage Modeling of Notched Composites

There is an increased interest in using non-crimp fabric reinforced composites for primary and secondary structural weight savings in high performance automobile applications. However, one of the main challenges in implementing these composites is the lack of understanding of damage progression under a wide variety of loading conditions for general configurations. Towards that end, researchers at GM and NASA are developing new damage models to predict accurately the progressive failure of these composites. In this investigation, the developed progressive failure analysis model was applied to study damage progression in center-notched and open-hole tension specimens for various laminate schemes. The results of a detailed study with respect to the effect of element size on the analysis outcome are presented.

Aitharaju, Venkat↗

Climate Change and Fetal Health: The Impacts of Exposure to Extreme Temperatures in New York City

Background: Climate change is projected to increase the frequency, intensity, and duration of heat waves while reducing cold extremes, yet few studies have examined the relationship between temperature and fetal health. Objectives: We estimate the impacts of extreme temperatures on birth weight and gestational age in Manhattan, a borough in New York City, and explore differences by socioeconomic status (SES). Methods: We combine average daily temperature from 1985 to 2010 with birth certificate data in Manhattan for the same time period. We then generate 33 downscaled climate model time series to project impacts on fetal health. Results: We find exposure to an extra day where average temperature 25 F and 85 F during pregnancy is associated with a 1.8 and 1.7 g (respectively) reduction in birth weight, but the impact varies by SES, particularly for extreme heat, where teen mothers seem most vulnerable. We find no meaningful, significant effect on gestational age. Using projections of temperature from these climate models, we project average net reductions in birth weight in the 2070- 2099 period of 4.6 g in the business-as-usual scenario. Conclusions: Results suggest that increasing heat events from climate change could adversely impact birth weight and vary by SES.

climate change↗

Axisymmetric inlet minimum weight design method

An analytical method for determining the minimum weight design of an axisymmetric supersonic inlet has been developed. The goal of this method development project was to improve the ability to predict the weight of high-speed inlets in conceptual and preliminary design. The initial model was developed using information that was available from inlet conceptual design tools (e.g., the inlet internal and external geometries and pressure distributions). Stiffened shell construction was assumed. Mass properties were computed by analyzing a parametric cubic curve representation of the inlet geometry. Design loads and stresses were developed at analysis stations along the length of the inlet. The equivalent minimum structural thicknesses for both shell and frame structures required to support the maximum loads produced by various load conditions were then determined. Preliminary results indicated that inlet hammershock pressures produced the critical design load condition for a significant portion of the inlet. By improving the accuracy of inlet weight predictions, the method will improve the fidelity of propulsion and vehicle design studies and increase the accuracy of weight versus cost studies.

Nadell, Shari-Beth↗

Finite Element Modeling and Analysis of Mars Entry Aeroshell Baseline Concept

The structure that is developed and analyzed in this project must be able to survive all the various load conditions that it will encounter along its course to Mars with the minimal amount of weight and material. At this stage, the goal is to study the capability of the structure using a finite element model (FEM). This FEM is created using a python script, and is numerically solved in Nastran. The purpose of the model is to achieve an optimization of mass given specific constraints on launch and entry. The generation and analysis of the baseline Rigid Mid-Range Lift to Drag Ratio Aeroshell model is a continuation and an improvement on previous work done for the FEM. The model is generated using Python programming with the axisymmetric placement of nodes for beam and shell elements. The shells are assigned a honeycomb sandwich material with an aluminum honeycomb core and composite face sheets, and the beams are assigned the same material as the shell face sheets. There are two load cases assigned to the model: Earth launch and Mars entry. The Earth launch case consists of pressure, gravity, and vibration loads, and the Mars entry case consists of just pressure and gravity loads. The Earth launch case was determined to be the driving case, though the analyses are performed for both cases to ensure the constraints are satisfied. The types of analysis performed with the model are design optimization, statics, buckling, normal modes, and frequency response, the last of which is only for the Earth launch load case. The final results indicated that all of the requirements are satisfied except the thermal limits, which could not yet be tested, and the normal modes for the Mars entry. However, the frequency limits during Mars entry are expected to be much higher than the lower frequency limits set for the analysis. In addition, there are still improvements that can be made in order to reduce the weight while still meeting all requirements.

Ahmed, Samee W.↗

Microscopic Simulation and Macroscopic Modeling for Thermal and Chemical Non-Equilibrium

This paper deals with the accurate microscopic simulation and macroscopic modeling of extreme non-equilibrium phenomena, such as encountered during hypersonic entry into a planetary atmosphere. The state-to-state microscopic equations involving internal excitation, de-excitation, dissociation, and recombination of nitrogen molecules due to collisions with nitrogen atoms are solved time-accurately. Strategies to increase the numerical efficiency are discussed. The problem is then modeled using a few macroscopic variables. The model is based on reconstructions of the state distribution function using the maximum entropy principle. The internal energy space is subdivided into multiple groups in order to better describe the non-equilibrium gases. The method of weighted residuals is applied to the microscopic equations to obtain macroscopic moment equations and rate coefficients. The modeling is completely physics-based, and its accuracy depends only on the assumed expression of the state distribution function and the number of groups used. The model makes no assumption at the microscopic level, and all possible collisional and radiative processes are allowed. The model is applicable to both atoms and molecules and their ions. Several limiting cases are presented to show that the model recovers the classical twotemperature models if all states are in one group and the model reduces to the microscopic equations if each group contains only one state. Numerical examples and model validations are carried out for both the uniform and linear distributions. Results show that the original over nine thousand microscopic equations can be reduced to 2 macroscopic equations using 1 to 5 groups with excellent agreement. The computer time is decreased from 18 hours to less than 1 second.

Modeling↗

Variability of building environmental assessment tools on evaluating carbon emissions

With an increasing importance of sustainability in construction, more and more clients and designers employ building environmental assessment (BEA) tools to evaluate the environmental friendliness of their building facilities, and one important aspect of evaluation in the BEA models is the assessment of carbon emissions. However, in the absence of any agreed framework for carbon auditing and benchmarking, the results generated by the BEA tools might vary significantly which could lead to confusion or misinterpretation on the carbon performance of a building. This study thus aims to unveil the properties of and the standard imposed by the current BEA models on evaluating the life cycle carbon emissions. The analyses cover the (i) weighting of energy efficiency and emission levels among various environmental performance indicators; (ii) building life cycle stages in which carbon is taken into consideration; (iii) objectiveness of assessment; (iv) baseline set for carbon assessment; (v) mechanism for benchmarking the emission level; and (v) limitations of the carbon assessment approaches. Results indicate that the current BEA schemes focus primarily on operational carbon instead of the emissions generated throughout the entire building life cycle. Besides, the baseline and benchmark for carbon evaluation vary significantly among the BEA tools based on the analytical results of a hypothetical building. The findings point to the needs for a more transparent framework for carbon auditing and benchmarking in BEA modeling. - Highlights: Black-Right-Pointing-Pointer Carbon emission evaluation in building environmental assessment schemes are studied. Black-Right-Pointing-Pointer Simulative carbon emission is modeled for building environmental assessment schemes. Black-Right-Pointing-Pointer Carbon assessments focus primarily on operational stage instead of entire lifecycle. Black-Right-Pointing-Pointer Baseline and benchmark of carbon assessment vary greatly among BEA schemes. Black-Right-Pointing-Pointer A more transparent and comprehensive framework for carbon assessment is required.

54 ENVIRONMENTAL SCIENCES↗

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Sparse distributed memory and related models

Described here is sparse distributed memory (SDM) as a neural-net associative memory. It is characterized by two weight matrices and by a large internal dimension - the number of hidden units is much larger than the number of input or output units. The first matrix, A, is fixed and possibly random, and the second matrix, C, is modifiable. The SDM is compared and contrasted to (1) computer memory, (2) correlation-matrix memory, (3) feet-forward artificial neural network, (4) cortex of the cerebellum, (5) Marr and Albus models of the cerebellum, and (6) Albus' cerebellar model arithmetic computer (CMAC). Several variations of the basic SDM design are discussed: the selected-coordinate and hyperplane designs of Jaeckel, the pseudorandom associative neural memory of Hassoun, and SDM with real-valued input variables by Prager and Fallside. SDM research conducted mainly at the Research Institute for Advanced Computer Science (RIACS) in 1986-1991 is highlighted.

Kanerva, Pentti↗

Network-Level Traffic Signal Cooperation: A Higher-Order Conflict Graph Approach

Traffic signal control and cooperation are extremely important to alleviate traffic congestion in a large traffic network. This study develops a higher-order conflict graph approach for network-wide traffic signal control and cooperation. A conflict graph is applied to model the traffic signal configurations, which identifies the conflict and unconflicted movements for each intersection. In conflict graph, the node represents each movement. The weight of each node can be defined as traffic volume, queue length, fuel consumption, or any weighted combinations of these measurements. The calculation of the optimal green light duration and green light sequence (for different movements) is equivalent to sequentially finding the maximum weight independent set (MWIS) in the conflict graph. The conflict graph also provides a uniform and efficient way to connect traffic signal operations among nearby intersections spatially. Then, we introduced the concept of the k -th order neighborhood to model the degree of connectivity between each movement to the movements at upstream or downstream intersections. The weight of each node in the higher-order conflict graph not only represents its own congestion level, but also relates to the traffic conditions of nearby intersections. Through this approach, the cooperation of multiple intersections can be realized by incorporating their spatial connectivity into conflict graph and solving the MWIS problem. A simulation network is built in SUMO to test the effectiveness of the proposed method. Results suggested that the proposed model outperformed other state-of-the-art signal control methods. Also, the scheme maintains good performance under varying traffic demands.

42 ENGINEERING↗

Quark model with chiral-symmetry breaking and confinement in the Covariant Spectator Theory

We propose a model for the quark-antiquark interaction in Minkowski space using the Covariant Spectator Theory. We show that with an equal-weighted scalar-pseudoscalar structure for the confining part of our interaction kernel the axial-vector Ward-Takahashi identity is preserved and our model complies with the Adler-zero constraint for pi-pi-scattering imposed by chiral symmetry.

Biernat, Elmer P.↗

Regulation of hematopoiesis in rats exposed to antiorthostatic, hypokinetic/hypodynamia. I - Model description

The effect of a 7-day suspension in a jacket and harness with 20-deg head-down tilt on body weight, food and water consumption, and hematological parameters is investigated experimentally in male Sprague-Dawley rats weighing 150-175 g. The results are presented in graphs and compared with those for unsuspended controls and with published data on rats and humans exposed to microgravity in space flight. Suspended rats are found to have reduced red-blood-cell mass, erythropoiesis, plasma volume (leading to temporarily increased hematocrit), body weight, and food and water consumption; rightward-shifted oxyhemoglobin-dissociation curves; and unchanged platelet count, leucocyte count or PHA reactivity, and red-blood-cell shape distribution. Since many of these effects are also seen in space flight, the present experimental model is considered a promising technique for simulating the hematopoietic effects of microgravity at 1 g.

Dunn, C. D. R.↗

Wind-Tunnel Tests of the 1/25-Scale Powered Model of the Martin JRM-1 Airplane. IV - Tests with Ground Board and with Modified Wing and Hull - TED No. NACA 232: Tests with Ground Board and with Modified Wing and Hull, TED No. NACA 232 - Part 4

Wind-tunnel tests were made of a 1/25 scale model of the Martin JRM-1 airplane to determine: (1) The longitudinal stability and control characteristics of the JRM-1 model near the water and lateral and directional stability characteristics with power while moving on the surface of the water, the latter being useful for the design of tip floats; (2) The stability and stalling characteristics of the wing with a modified airfoil contour; (3) Stability characteristics of a hull of larger design gross weight; The test results indicated that the elevator was powerful enough to trim the original model in a landing configuration at any lift coefficient within the specified range of centers of gravity. The ground-board tests for evaluating the aerodynamic forces and moments on an airplane in a simulated cross wind indicate a high dihedral effect in the presence of the ground board and, consequently, during low-speed taxying and take-off, large overturning moments would result which would have to be overcome by the tip floats.

Lockwood, Vernard E.↗

Orbital structure of the effective pairing interaction in the high-temperature superconducting cuprates

The nature of the effective interaction responsible for pairing in the high-temperature superconducting cuprates remains unsettled. This question has been studied extensively using the simplified single-band Hubbard model, which does not explicitly consider the orbital degrees of freedom of the relevant CuO 2 planes. Here, we use a dynamical cluster quantum Monte Carlo approximation to study the orbital structure of the pairing interaction in the three-band Hubbard model, which treats the orbital degrees of freedom explicitly. We find that the interaction predominately acts between neighboring copper orbitals, but with significant additional weight appearing on the surrounding bonding molecular oxygen orbitals. By explicitly comparing these results to those from the simpler single-band Hubbard model, our study provides strong support for the single-band framework for describing superconductivity in the cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

An input adaptive, pursuit tracking model of the human opertor

Developed and evaluated is a simple model of the input adaptive behavior of the human operator (HO) in a pursuit tracking task in which the plant controlled consists of a pure gain. If it is assumed that the HO is approximately an optimal predictor using only position and velocity information, then there is a simple method of computing the values of the model parameters in terms of the autocorrelation function of the input signal. Experimental evidence indicates that the ability of the HO to use velocity information decreases with increasing signal velocity indicating that a biased estimator of the velocity weighting should be used. A suitable approximation is derived which has rapid convergence and low variance. The model thus derived is compared to actual subject transfer functions and is found to be in close agreement. In addition to tracking random processes the model can adapt to and track deterministic signals, such as sine waves, up to approximately the frequency at which human operators begin to track precognitively.

Ware, J. R.↗

Analytical modeling of structure-soil systems for lunar bases

The study of the behavior of granular materials in a reduced gravity environment and under low effective stresses became a subject of great interest in the mid 1960's when NASA's Surveyor missions to the Moon began the first extraterrestrial investigation and it was found that Lunar soils exhibited properties quite unlike those on Earth. This subject gained interest during the years of the Apollo missions and more recently due to NASA's plans for future exploration and colonization of Moon and Mars. It has since been clear that a good understanding of the mechanical properties of granular materials under reduced gravity and at low effective stress levels is of paramount importance for the design and construction of surface and buried structures on these bodies. In order to achieve such an understanding it is desirable to develop a set of constitutive equations that describes the response of such materials as they are subjected to tractions and displacements. This presentation examines issues associated with conducting experiments on highly nonlinear granular materials under high and low effective stresses. The friction and dilatancy properties which affect the behavior of granular soils with low cohesion values are assessed. In order to simulate the highly nonlinear strength and stress-strain behavior of soils at low as well as high effective stresses, a versatile isotropic, pressure sensitive, third stress invariant dependent, cone-cap elasto-plastic constitutive model was proposed. The integration of the constitutive relations is performed via a fully implicit Backward Euler technique known as the Closest Point Projection Method. The model was implemented into a finite element code in order to study nonlinear boundary value problems associated with homogeneous as well as nonhomogeneous deformations at low as well as high effective stresses. The effect of gravity (self-weight) on the stress-strain-strength response of these materials is evaluated. The calibration of the model is performed via three techniques: (1) physical identification, (2) optimized calibration at the constitutive level, and (3) optimized calibration at the finite element level (Inverse Identification). Activities are summarized in graphic and outline form.

Macari-Pasqualino, Jose Emir↗