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At least 1,225 records · Page 68

Application of two procedures for dual-point design of transonic airfoils

Two dual-point design procedures were developed to reduce the objective function of a baseline airfoil at two design points. The first procedure to develop a redesigned airfoil used a weighted average of the shapes of two intermediate airfoils redesigned at each of the two design points. The second procedure used a weighted average of two pressure distributions obtained from an intermediate airfoil redesigned at each of the two design points. Each procedure was used to design a new airfoil with reduced wave drag at the cruise condition without increasing the wave drag or pitching moment at the climb condition. Two cycles of the airfoil shape-averaging procedure successfully designed a new airfoil that reduced the objective function and satisfied the constraints. One cycle of the target (desired) pressure-averaging procedure was used to design two new airfoils that reduced the objective function and came close to satisfying the constraints.

Mineck, Raymond E.↗

National Airspace System Delay Estimation Using Weather Weighted Traffic Counts

Assessment of National Airspace System performance, which is usually measured in terms of delays resulting from the application of traffic flow management initiatives in response to weather conditions, volume, equipment outages and runway conditions, is needed both for guiding flow control decisions during the day of operations and for post operations analysis. Comparison of the actual delay, resulting from the traffic flow management initiatives, with the expected delay, based on traffic demand and other conditions, provides the assessment of the National Airspace System performance. This paper provides a method for estimating delay using the expected traffic demand and weather. In order to identify the cause of delays, 517 days of National Airspace System delay data reported by the Federal Aviation Administration s Operations Network were analyzed. This analysis shows that weather is the most important causal factor for delays followed by equipment and runway delays. Guided by these results, the concept of weather weighted traffic counts as a measure of system delay is described. Examples are given to show the variation of these counts as a function of time of the day. The various datasets, consisting of aircraft position data, enroute severe weather data, surface wind speed and visibility data, reported delay data and number of aircraft handled by the Centers data, and their sources are described. The procedure for selecting reference days on which traffic was minimally impacted by weather is described. Different traffic demand on each reference day of the week, determined by analysis of 42 days of traffic and delay data, was used as the expected traffic demand for each day of the week. Next, the method for computing the weather weighted traffic counts using the expected traffic demand, derived from reference days, and the expanded regions around severe weather cells is discussed. It is shown via a numerical example that this approach improves the dynamic range of the weather weighted traffic counts considerably. Time histories of these new weather weighted traffic counts are used for synthesizing two statistical features, six histogram features and six time domain features. In addition to these enroute weather features, two surface weather features of number of major airports in the United States with high mean winds and low mean visibility are also described. A least squares procedure for establishing a functional relation between the features, using combinations of these features, and system delays is explored using 36 days of data. Best correlations between the estimated delays using the functional relation and the actual delays provided by the Operations Network are obtained with two different combinations of features: 1) six time domain features of weather weighted traffic counts plus two surface weather features, and 2) six histogram features and mean of weather weighted traffic counts along with the two surface weather features. Correlation coefficient values of 0.73 and 0.83 were found in these two instances.

Chatterji, Gano B.↗

Characterization of the major cyanogen bromide fragment of alpha-A crystallin

Alpha crystallin from the bovine lens has been digested with cyanogen bromide, and the major fragment (CB-1) has been purified using reverse phase HPLC. Characterization of this fragment by Edman degradation and antisera to synthetic peptides indicates that it originates from alpha-A crystallin, but lacks the N-terminal methionine and the last 35 amino acids from the C-terminus of the molecule. The purified CB-1 fragment binds as well as native alpha crystallin to lens membrane, but is unable to self-assemble into the correct size of high molecular weight oligomeric complexes characteristic of the intact alpha-A chain. Together, these results demonstrate that the alpha-A chain is comprised of at least two functional domains, one of which is involved in binding of alpha-A crystallin to lens membrane, and another which is necessary for correct self-assembly of the molecule into high molecular weight oligomers.

Non-NASA Center↗

Truss topology optimization with simultaneous analysis and design

Strategies for topology optimization of trusses for minimum weight subject to stress and displacement constraints by Simultaneous Analysis and Design (SAND) are considered. The ground structure approach is used. A penalty function formulation of SAND is compared with an augmented Lagrangian formulation. The efficiency of SAND in handling combinations of general constraints is tested. A strategy for obtaining an optimal topology by minimizing the compliance of the truss is compared with a direct weight minimization solution to satisfy stress and displacement constraints. It is shown that for some problems, starting from the ground structure and using SAND is better than starting from a minimum compliance topology design and optimizing only the cross sections for minimum weight under stress and displacement constraints. A member elimination strategy to save CPU time is discussed.

Sankaranarayanan, S.↗

Entanglement features of random neural network quantum states

Restricted Boltzmann machines (RBMs) are a class of neural networks that have been successfully employed as a variational ansatz for quantum many-body wave functions. Here, we develop an analytic method to study quantum many-body spin states encoded by random RBMs with independent and identically distributed complex Gaussian weights. By mapping the computation of ensemble-averaged quantities to statistical mechanics models, we are able to investigate the parameter space of the RBM ensemble in the thermodynamic limit. We discover qualitatively distinct wave functions by varying RBM parameters, which correspond to distinct phases in the equivalent statistical mechanics model. Notably, there is a regime in which the typical RBM states have near-maximal entanglement entropy in the thermodynamic limit, similar to that of Haar-random states. However, these states generically exhibit nonergodic behavior in the Ising basis, and do not form quantum state designs, making them distinguishable from Haar-random states.

36 MATERIALS SCIENCE↗

Improved energies and local energies with weighted variational Monte Carlo

Neural network parametrizations have increasingly been used to represent the ground and excited states in variational Monte Carlo (VMC) with promising results. However, traditional VMC methods only optimize the wave function in regions of peak probability. The wave function is uncontrolled in the tails of the probability distribution, which can limit the accuracy of the trained wave function. To improve the approximation accuracy in the probability tails, this paper interprets VMC as a gradient flow in the space of wave functions, followed by a projection step. From this perspective, arbitrary probability distributions can be used in the projection step, allowing the user to prioritize accuracy in different regions of state space. Motivated by this theoretical perspective, the paper tests a weighted VMC method on the antiferromagnetic Heisenberg model for a periodic spin chain. Compared to traditional VMC, weighted VMC reduces the error in the ground state energy by a factor of 2, and it reduces the errors in the local energies away from the mode by large factors of 10 2 –10 4 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Window convolution of the galaxy clustering bispectrum

In galaxy survey analysis, the observed clustering statistics do not directly match theoretical predictions but rather have been processed by a window function that arises from the survey geometry including the sky footprint, redshift-dependent background number density and systematic weights. While window convolution of the power spectrum is well studied, for the bispectrum with a larger number of degrees of freedom, it poses a significant numerical and computational challenge. In this work, we consider the effect of the survey window in the tripolar spherical harmonic decomposition of the bispectrum and lay down a formal procedure for their convolution via a series expansion of configuration-space three-point correlation functions, which was first proposed by Sugiyama et al. (2019). We then provide a linear algebra formulation of the full window convolution, where an unwindowed bispectrum model vector can be directly premultiplied by a window matrix specific to each survey geometry. To validate the pipeline, we focus on the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) luminous red galaxy (LRG) sample in the South Galactic Cap (SGC) in the redshift bin 0.4 ≤ z ≤ 0.6. We first perform convergence checks on the measurement of the window function from discrete random catalogues, and then investigate the convergence of the window convolution series expansion truncated at a finite of number of terms as well as the performance of the window matrix. This work highlights the differences in window convolution between the power spectrum and bispectrum, and provides a streamlined pipeline for the latter for current surveys such as DESI and the Euclid mission.

79 ASTRONOMY AND ASTROPHYSICS↗

Tailoring Binder Molecular Weight to Enhance Slurry-Cast NMC Cathodes for Sulfide Solid-State Batteries

We demonstrate for the first time the critical influence of binder molecular weight on the performance of slurry-cast lithium nickel manganese cobalt oxide (NMC) cathodes in sulfide-based all-solid-state batteries (SSBs). SSBs are increasingly recognized as a safer and potentially more efficient alternative to traditional Li-ion batteries, owing to the superior ionic conductivities and inherent safety features of sulfide solid electrolytes. However, the integration of high-voltage NMC cathodes with sheet-type sulfide solid electrolytes presents significant fabrication challenges. Our findings reveal that higher molecular weight binders not only enhance the discharge capacity and cycle life of these cathodes but also ensure robust adhesion and structural integrity. By optimizing binder molecular weights, we effectively shield the active materials from degradation and mechanical stress, significantly boosting the functionality and longevity of SSBs. These results underscore the paramount importance of binder properties in advancing the practical application of high-performance all-solid-state batteries.

25 ENERGY STORAGE↗

Correspondence between neuroevolution and gradient descent

Abstract We show analytically that training a neural network by conditioned stochastic mutation or neuroevolution of its weights is equivalent, in the limit of small mutations, to gradient descent on the loss function in the presence of Gaussian white noise. Averaged over independent realizations of the learning process, neuroevolution is equivalent to gradient descent on the loss function. We use numerical simulation to show that this correspondence can be observed for finite mutations, for shallow and deep neural networks. Our results provide a connection between two families of neural-network training methods that are usually considered to be fundamentally different.

97 MATHEMATICS AND COMPUTING↗

Reductive halocyclosilazane polymerization

The synthesis of a chloro-functionalized six-membered cyclosilazane (Si5N) is reported on. Subsequent reductive polymerizations yielded low molecular weight polysilazanes. 1 H and 29 Si NMR characterization suggest the identity of the reducing metal influences the polysilazane structure.Furthermore, optical characterization is consistent with extended σ-conjugation upon polymerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Constraints on the two-dimensional pseudospin-$\frac{1}{2}$Mott insulator description of $\mathrm{Sr_2IrO_4}$

Sr 2 IrO 4 has often been described via a simple, one-band pseudospin-$\frac{1}{2}$ model subject to electron-electron interactions on a square lattice, fostering analogies with cuprate superconductors believed to be well described by a similar model. In this work we argue - based on a detailed study of the low-energy electronic structure by circularly polarized spin and angle-resolved photoemission spectroscopy combined with dynamical mean-field theory calculations - that a pseudospin-$\frac{1}{2}$ model fails to capture the full complexity of the system. We show instead that a realistic multiband Hubbard Hamiltonian, accounting for the full correlated t 2g manifold, provides a detailed description of the interplay between spin-orbital entanglement and electron-electron interactions and yields quantitative agreement with experiments. Our analysis establishes that the j 3/2 states make up a substantial percentage of the low-energy spectral weight, i.e., approximately 74% as determined from the integration of the j-resolved spectral function in the 0 to -1.64eV energy range. Therefore, the results in our work are of relevance not only to Ir-based materials but also more generally to multiorbital materials with closely spaced energy scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

LightMAT - Pediction of Aluminum/Steel Joint Failure

Develop a predictive model of dissimilar metallic spot joints and their behavior during fracture; specifically, whether the joint fractures via interfacial fracture or button pull-out as a function of alloy, sheet thickness, faying interface microstructure, and thermal-mechanical treatment of the weld nugget and heat affected zone. Having the ability to model whether a given joint structure would fracture inter-facially or via button pullout will reduce development time and provide savings to vehicle design programs. This would provide a significant step function improvement in reducing the time-to-market for this multi-material, weight-saving technology.

36 MATERIALS SCIENCE↗

Impact tensile testing of wires

The test consists of fixing one end of a wire specimen and allowing a threaded falling weight to strike the other. Assuming the dynamic stress in the wire to be a function only of its strain, energy considerations show for negligible wire inertia effects that the governing dynamic stress-strain law can be determined directly from impact energy vs. wire elongation data. Theoretical calculations are presented which show negligible wire inertia effects for ratios of wire mass to striking mass of the order of .01 or less. The test method is applied to soft copper wires and the dynamic stress-strain curve so determined is found to be about 30 percent higher than the corresponding static curve.

Dawson, T. H.↗

Laboratory measurements of physical, chemical, and optical characteristics of Lake Chicot sediment waters

Reflectance, chromaticity, diffuse attenuation, beam attenuation, and several other physical and chemical properties were measured for various water mixtures of lake bottom sediment. Mixture concentrations range from 5 ppm to 700 ppm by weight of total suspended solids in filtered deionized tap water. Upwelled reflectance is a nonlinear function of remote sensing wave lengths. Near-infrared wavelengths are useful for monitoring highly turbid waters with sediment concentrations above 100 ppm. It is found that both visible and near infrared wavelengths, beam attenuation correlates well with total suspended solids ranging over two orders of magnitude.

Witte, W. G.↗

Thioredoxins in evolutionarily primitive organisms

Thioredoxins are low molecular weight redox proteins, alternating between the S-S (oxidized) and SH (reduced) states, that function in a number of biochemical processes, including DNA synthesis, DNA replication, and enzyme regulation. Until recently, reduced ferredoxin was known to serve as the source of reducing power for the reduction of thioredoxins only in oxygenic photosynthetic cells. In all other organisms, the source of hydrogen (electrons) for thioredoxin reduction was considered to be NADPH. It was found that Clostridium pasteurianum, an anaerobic organism normally living in the soil unexposed to light, resembles photosynthetic cells in using ferredoxin for the reduction of thioredoxin. The results reveal the existence of a pathway in which ferredoxin, provides the reducing power for the reduction of thioredoxin via the flavoprotein enzyme, ferredoxinthioredoxin reductase. In related studies, it was found that Chromatium vinosum, an anaerobic photosynthetic purple sulfur bacterium, resembles evolutionarily more advanced micro-organisms in having an NADP-thioredoxin system composed of a single thioredoxin which is reduced by NADPH via NADP-thioredoxin reductase. The adoption of the NADP-thioredoxin system by Chromatium seems appropriate in view of evidence tha the organi sm utilizes ATP-driven reverse electron transport. Finally, results of research directed towards the identification of target enzymes of the ferredoxin/thioredoxin system in a cyanobacterium (Nostoc muscorum), show that thioredoxin-linked photosynthetic enzymes of cyanobateria are similar to those of chloroplasts. It now seems that the ferredoxin/thioredoxin system functions in regulating CO2 assimilation via the reductive pentose phosphate cycle in oxygenic but not anoxygenic photosynthetic cells.

Buchanan, B. B.↗

Connectionist model-based stereo vision for telerobotics

Autonomous stereo vision for range measurement could greatly enhance the performance of telerobotic systems. Stereo vision could be a key component for autonomous object recognition and localization, thus enabling the system to perform low-level tasks, and allowing a human operator to perform a supervisory role. The central difficulty in stereo vision is the ambiguity in matching corresponding points in the left and right images. However, if one has a priori knowledge of the characteristics of the objects in the scene, as is often the case in telerobotics, a model-based approach can be taken. Researchers describe how matching ambiguities can be resolved by ensuring that the resulting three-dimensional points are consistent with surface models of the expected objects. A four-layer neural network hierarchy is used in which surface models of increasing complexity are represented in successive layers. These models are represented using a connectionist scheme called parameter networks, in which a parametrized object (for example, a planar patch p=f(h,m sub x, m sub y) is represented by a collection of processing units, each of which corresponds to a distinct combination of parameter values. The activity level of each unit in the parameter network can be thought of as representing the confidence with which the hypothesis represented by that unit is believed. Weights in the network are set so as to implement gradient descent in an energy function.

Hoff, William↗

An applicational process for dynamic balancing of turbomachinery shafting

The NASA Lewis Research Center has developed and implemented a time-efficient methodology for dynamically balancing turbomachinery shafting. This methodology minimizes costly facility downtime by using a balancing arbor (mandrel) that simulates the turbomachinery (rig) shafting. The need for precision dynamic balancing of turbomachinery shafting and for a dynamic balancing methodology is discussed in detail. Additionally, the inherent problems (and their causes and effects) associated with unbalanced turbomachinery shafting as a function of increasing shaft rotational speeds are discussed. Included are the design criteria concerning rotor weight differentials for rotors made of different materials that have similar parameters and shafting. The balancing methodology for applications where rotor replaceability is a requirement is also covered. This report is intended for use as a reference when designing, fabricating, and troubleshooting turbomachinery shafting.

Verhoff, Vincent G.↗

An enhanced integrated aerodynamic load/dynamic optimization procedure for helicopter rotor blades

An enhanced integrated aerodynamic load/dynamic optimization procedure is developed to minimize vibratory root shears and moments. The optimization is formulated with 4/rev vertical and 3/rev inplane shears at the blade root as objective functions and constraints, and 4/rev lagging moment. Constraints are also imposed on blade natural frequencies, weight, autorotational inertia, centrifugal stress, and rotor thrust. The 'Global Criteria Approach' is used for formulating the multi-objective optimization. Design variables include spanwise distributions of bending stiffnesses, torsional stiffness, nonstructural mass, chord, radius of gyration, and blade taper ratio. The program CAMRAD is coupled with an optimizer, which consists of the program CONMIN and an approximate analysis, to obtain optimum designs. The optimization procedure is applied to an advanced rotor as a reference design. Optimum blade designs, obtained with and without a constraint on the rotor thrust, are presented and are compared to the reference blade. Substantial reductions are obtained in the vibratory root forces and moments. As a byproduct, improvements are also found in some performance parameters, such as total power required, which were not considered during optimization.

Chattopadhyay, Aditi↗