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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Loops in AdS from conformal field theory

We propose and demonstrate a new use for conformal field theory (CFT) crossing equations in the context of AdS/CFT: the computation of loop amplitudes in AdS, dual to non-planar correlators in holographic CFTs. Loops in AdS are largely unexplored, mostly due to technical difficulties in direct calculations. We revisit this problem, and the dual 1=N expansion of CFTs, in two independent ways. The first is to show how to explicitly solve the crossing equations to the first subleading order in 1=N 2 , given a leading order solution. This is done as a systematic expansion in inverse powers of the spin, to all orders. These expansions can be resummed, leading to the CFT data for nite values of the spin. Our second approach involves Mellin space. We show how the polar part of the four-point, loop-level Mellin amplitudes can be fully reconstructed from the leading-order data. The anomalous dimensions computed with both methods agree. In the case of $\phi$ 4 theory in AdS, our crossing solution reproduces a previous computation of the one-loop bubble diagram. We can go further, deriving the four-point scalar triangle diagram in AdS, which had never been computed. In the process, we show how to analytically derive anomalous dimensions from Mellin amplitudes with an in nite series of poles, and discuss applications to more complicated cases such as the N = 4 super-Yang-Mills theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Nanoscale size dependence parameters on lattice thermal conductivity of Wurtzite GaN nanowires

Graphical abstract: Temperature dependence of calculated lattice thermal conductivity of Wurtzite GaN nanowires. Highlights: Black-Right-Pointing-Pointer A modified Callaway model is used to calculate lattice thermal conductivity of Wurtzite GaN nanowires. Black-Right-Pointing-Pointer A direct method is used to calculate phonon group velocity for these nanowires. Black-Right-Pointing-Pointer 3-Gruneisen parameter, surface roughness, and dislocations are successfully investigated. Black-Right-Pointing-Pointer Dislocation densities are decreases with the decrease of wires diameter. -- Abstract: A detailed calculation of lattice thermal conductivity of freestanding Wurtzite GaN nanowires with diameter ranging from 97 to 160 nm in the temperature range 2-300 K, was performed using a modified Callaway model. Both longitudinal and transverse modes are taken into account explicitly in the model. A method is used to calculate the Debye and phonon group velocities for different nanowire diameters from their related melting points. Effect of Gruneisen parameter, surface roughness, and dislocations as structure dependent parameters are successfully used to correlate the calculated values of lattice thermal conductivity to that of the experimentally measured curves. It was observed that Gruneisen parameter will decrease with decreasing nanowire diameters. Scattering of phonons is assumed to be by nanowire boundaries, imperfections, dislocations, electrons, and other phonons via both normal and Umklapp processes. Phonon confinement and size effects as well as the role of dislocation in limiting thermal conductivity are investigated. At high temperatures and for dislocation densities greater than 10{sup 14} m{sup -2} the lattice thermal conductivity would be limited by dislocation density, but for dislocation densities less than 10{sup 14} m{sup -2}, lattice thermal conductivity would be independent of that.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Causally‐Informed Deep Learning to Improve Climate Models and Projections

Abstract Climate models are essential to understand and project climate change, yet long‐standing biases and uncertainties in their projections remain. This is largely associated with the representation of subgrid‐scale processes, particularly clouds and convection. Deep learning can learn these subgrid‐scale processes from computationally expensive storm‐resolving models while retaining many features at a fraction of computational cost. Yet, climate simulations with embedded neural network parameterizations are still challenging and highly depend on the deep learning solution. This is likely associated with spurious non‐physical correlations learned by the neural networks due to the complexity of the physical dynamical system. Here, we show that the combination of causality with deep learning helps removing spurious correlations and optimizing the neural network algorithm. To resolve this, we apply a causal discovery method to unveil causal drivers in the set of input predictors of atmospheric subgrid‐scale processes of a superparameterized climate model in which deep convection is explicitly resolved. The resulting causally‐informed neural networks are coupled to the climate model, hence, replacing the superparameterization and radiation scheme. We show that the climate simulations with causally‐informed neural network parameterizations retain many convection‐related properties and accurately generate the climate of the original high‐resolution climate model, while retaining similar generalization capabilities to unseen climates compared to the non‐causal approach. The combination of causal discovery and deep learning is a new and promising approach that leads to stable and more trustworthy climate simulations and paves the way toward more physically‐based causal deep learning approaches also in other scientific disciplines.

Meteorology & Atmospheric Sciences↗
DOE OSTI2016

MO-FG-CAMPUS-TeP2-04: Optimizing for a Specified Target Coverage Probability

Purpose: The purpose of this work is to develop a method for inverse planning of radiation therapy margins. When using this method the user specifies a desired target coverage probability and the system optimizes to meet the demand without any explicit specification of margins to handle setup uncertainty. Methods: The method determines which voxels to include in an optimization function promoting target coverage in order to achieve a specified target coverage probability. Voxels are selected in a way that retains the correlation between them: The target is displaced according to the setup errors and the voxels to include are selected as the union of the displaced target regions under the x% best scenarios according to some quality measure. The quality measure could depend on the dose to the considered structure alone or could depend on the dose to multiple structures in order to take into account correlation between structures. Results: A target coverage function was applied to the CTV of a prostate case with prescription 78 Gy and compared to conventional planning using a DVH function on the PTV. Planning was performed to achieve 90% probability of CTV coverage. The plan optimized using the coverage probability function had P(D98 > 77.95 Gy) = 0.97 for the CTV. The PTV plan using a constraint on minimum DVH 78 Gy at 90% had P(D98 > 77.95) = 0.44 for the CTV. To match the coverage probability optimization, the DVH volume parameter had to be increased to 97% which resulted in 0.5 Gy higher average dose to the rectum. Conclusion: Optimizing a target coverage probability is an easily used method to find a margin that achieves the desired coverage probability. It can lead to reduced OAR doses at the same coverage probability compared to planning with margins and DVH functions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Designing observables for quantum interference in jets at subleading color

The large-Nc or topologically planar limit of gauge theories can be considered as a classical limit because all gauge bosons are distinguishable particles and therefore cannot exhibit interference. Quantum effects due to the flow of color therefore arise starting at subleading in 1/Nc. We introduce kinematic observables explicitly sensitive to effects at subleading color formed from the ratio of interfering to squared color-ordered amplitudes. Such observables are in general not infrared and collinear safe, so we introduce angular observables defined from appropriate multi-point energy correlators motivated by the form of color-ordered amplitudes. We demonstrate that color interference effects are manifest as sinusoidal oscillation in the simplest system, a collinear jet with three particles, and show the limitations of predicting this observable in all-purpose, leading-color parton shower Monte Carlos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Metrics for the Complexity of Material Models

Quantitative measures are proposed for characterizing the complexity of material models used in computational mechanics. The algorithms for evaluating these metrics operate on the mathematical equations in the model rather than a code implementation and are different from software complexity measures. The metrics do not rely on a physical understanding of the model, using instead only a formal statement of the equations. A new algorithm detects the dependencies, whether explicit or implicit, between all the variables. The resulting pattern of dependencies is expressed in a set of pathways, each of which represents a chain of dependence between the variables. These pathways provide the raw data used in the metrics, which correlate with the expected ease of understanding, coding, and applying the model. Usage of the ComplexityMetrics code is described, with examples.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1999

Statistical Quality Control of Moisture Data in GEOS DAS

A new statistical quality control algorithm was recently implemented in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The final step in the algorithm consists of an adaptive buddy check that either accepts or rejects outlier observations based on a local statistical analysis of nearby data. A basic assumption in any such test is that the observed field is spatially coherent, in the sense that nearby data can be expected to confirm each other. However, the buddy check resulted in excessive rejection of moisture data, especially during the Northern Hemisphere summer. The analysis moisture variable in GEOS DAS is water vapor mixing ratio. Observational evidence shows that the distribution of mixing ratio errors is far from normal. Furthermore, spatial correlations among mixing ratio errors are highly anisotropic and difficult to identify. Both factors contribute to the poor performance of the statistical quality control algorithm. To alleviate the problem, we applied the buddy check to relative humidity data instead. This variable explicitly depends on temperature and therefore exhibits a much greater spatial coherence. As a result, reject rates of moisture data are much more reasonable and homogeneous in time and space.

Dee, D. P.↗
NASA NTRS2005

Video Mosaicking for Inspection of Gas Pipelines

A vision system that includes a specially designed video camera and an image-data-processing computer is under development as a prototype of robotic systems for visual inspection of the interior surfaces of pipes and especially of gas pipelines. The system is capable of providing both forward views and mosaicked radial views that can be displayed in real time or after inspection. To avoid the complexities associated with moving parts and to provide simultaneous forward and radial views, the video camera is equipped with a wide-angle (>165 ) fish-eye lens aimed along the axis of a pipe to be inspected. Nine white-light-emitting diodes (LEDs) placed just outside the field of view of the lens (see Figure 1) provide ample diffuse illumination for a high-contrast image of the interior pipe wall. The video camera contains a 2/3-in. (1.7-cm) charge-coupled-device (CCD) photodetector array and functions according to the National Television Standards Committee (NTSC) standard. The video output of the camera is sent to an off-the-shelf video capture board (frame grabber) by use of a peripheral component interconnect (PCI) interface in the computer, which is of the 400-MHz, Pentium II (or equivalent) class. Prior video-mosaicking techniques are applicable to narrow-field-of-view (low-distortion) images of evenly illuminated, relatively flat surfaces viewed along approximately perpendicular lines by cameras that do not rotate and that move approximately parallel to the viewed surfaces. One such technique for real-time creation of mosaic images of the ocean floor involves the use of visual correspondences based on area correlation, during both the acquisition of separate images of adjacent areas and the consolidation (equivalently, integration) of the separate images into a mosaic image, in order to insure that there are no gaps in the mosaic image. The data-processing technique used for mosaicking in the present system also involves area correlation, but with several notable differences: Because the wide-angle lens introduces considerable distortion, the image data must be processed to effectively unwarp the images (see Figure 2). The computer executes special software that includes an unwarping algorithm that takes explicit account of the cylindrical pipe geometry. To reduce the processing time needed for unwarping, parameters of the geometric mapping between the circular view of a fisheye lens and pipe wall are determined in advance from calibration images and compiled into an electronic lookup table. The software incorporates the assumption that the optical axis of the camera is parallel (rather than perpendicular) to the direction of motion of the camera. The software also compensates for the decrease in illumination with distance from the ring of LEDs.

Magruder, Darby↗
DOE OSTI2015

From deep TLS validation to ensembles of atomic models built from elemental motions

Procedures are described for extracting the vibration and libration parameters corresponding to a given set of TLS matrices and their simultaneous validation. Knowledge of these parameters allows the generation of structural ensembles corresponding to these matrices. The translation–libration–screw model first introduced by Cruickshank, Schomaker and Trueblood describes the concerted motions of atomic groups. Using TLS models can improve the agreement between calculated and experimental diffraction data. Because the T, L and S matrices describe a combination of atomic vibrations and librations, TLS models can also potentially shed light on molecular mechanisms involving correlated motions. However, this use of TLS models in mechanistic studies is hampered by the difficulties in translating the results of refinement into molecular movement or a structural ensemble. To convert the matrices into a constituent molecular movement, the matrix elements must satisfy several conditions. Refining the T, L and S matrix elements as independent parameters without taking these conditions into account may result in matrices that do not represent concerted molecular movements. Here, a mathematical framework and the computational tools to analyze TLS matrices, resulting in either explicit decomposition into descriptions of the underlying motions or a report of broken conditions, are described. The description of valid underlying motions can then be output as a structural ensemble. All methods are implemented as part of the PHENIX project.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Examining the consistency relations describing the three-point functions involving tensors

It is well known that the non-Gaussianity parameter f{sub NL} characterizing the scalar bi-spectrum can be expressed in terms of the scalar spectral index in the squeezed limit, a property that is referred to as the consistency relation. In contrast to the scalar bi-spectrum, the three-point cross-correlations involving scalars and tensors and the tensor bi-spectrum have not received adequate attention, which can be largely attributed to the fact that the tensors had remained undetected at the level of the power spectrum until very recently. The detection of the imprints of the primordial tensor perturbations by BICEP2 and its indication of a rather high tensor-to-scalar ratio, if confirmed, can open up a new window for understanding the tensor perturbations, not only at the level of the power spectrum, but also in the realm of non-Gaussianities. In this work, we consider the consistency relations associated with the three-point cross-correlations involving scalars and tensors as well as the tensor bi-spectrum in inflationary models driven by a single, canonical, scalar field. Characterizing the cross-correlations in terms of the dimensionless non-Gaussianity parameters C{sub NL}{sup R} and C{sub NL}{sup γ} that we had introduced earlier, we express the consistency relations governing the cross-correlations as relations between these non-Gaussianity parameters and the scalar or tensor spectral indices, in a fashion similar to that of the purely scalar case. We also discuss the corresponding relation for the non-Gaussianity parameter h{sub NL} used to describe the tensor bi-spectrum. We analytically establish these consistency relations explicitly in the following two situations: a simple example involving a specific case of power law inflation and a non-trivial scenario in the so-called Starobinsky model that is governed by a linear potential with a sharp change in its slope. We also numerically verify the consistency relations in three types of inflationary models that permit deviations from slow roll and lead to scalar power spectra with features which typically result in an improved fit to the data than the more conventional, nearly scale invariant, spectra. We close with a summary of the results we have obtained.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Elucidating Molecular Interactions in Glycerol Adsorption at the Metal–Water Interface with Density Functional Theory

Glycerol is an extremely versatile platform molecule for chemical and fuel production, as evidenced by successful demonstrations in electrochemical and thermochemical processes, where key catalytic chemistries occur at the solid–liquid interface. Despite the remarkable progress made in enriching the first-principles-based computational tool set to reveal and characterize solvent structures in the past decade, techniques for realistic and efficient molecular-level modeling to study aqueous-phase glycerol chemistry are still far from mature. Many aqueous-phase catalytic systems are deemed too complex for routine modeling because of their highly correlated structures at the heterogeneous solid–liquid interface. This invited feature article merges recent developments in quantum mechanical solvation models and oxygenated hydrocarbon conversion chemistry by revisiting the molecular interactions of adsorbed glycerol and its dehydrogenation intermediates at the water–metal interface. Explicit participation of water through the establishment of water–adsorbate, water–water, and water–metal interactions on Pt(111) was investigated using density functional theory. In periodic models, the adsorption favors networklike structures with adsorbates as nodal points linked by coadsorbed water molecules. We also showed that these adsorption patterns actually preserve the original bond-order-based scaling relationship framework established without the consideration of solvent. This behavior can be exploited to improve computational efficiency for future analysis of catalytic polyol conversions in the aqueous-phase environment.

Shan, Nannan↗
DOE OSTI2022

Microscopic diagnosis of universal geometric responses in fractional quantum Hall liquids

Topological quantum liquids contain internal degrees of freedom that are coupled to geometric response. Yet, an explicit and microscopic identification of the geometric response remains difficult. Here, taking notable fractional quantum Hall (FQH) states as typical examples, we systematically investigate a promising protocol—the Dehn-twist deformation on the torus geometry—to probe the geometric response of correlated topological states and establish the relation between such response and universal properties of pertinent states. Based on analytical derivations and numerical simulations, we find that the geometry-induced Berry phase encodes features for a broad class of FQH states at the Laughlin, hierarchy, Halperin and non-Abelian Moore-Read fillings. Our findings conclusively demonstrate that the adiabatic Dehn-twist deformation can faithfully capture rich geometric and topological information, including the Hall viscosity and topological spin of the pertinent FQH state and the chiral central charge of the underlying edge conformal field theory. Our approach provides a powerful way to reveal topological orders of generic FQH states and address previously open questions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

3D glasma initial state for relativistic heavy ion collisions

We extend the impact-parameter-dependent Glasma model to three dimensions using explicit small-x evolution of the two incoming nuclear gluon distributions. We compute rapidity distributions of produced gluons and the early-time energy momentum tensor as a function of space-time rapidity and transverse coordinates. Finally, we study rapidity correlations and fluctuations of the initial geometry and multiplicity distributions and make comparisons to existing models for the three-dimensional initial state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Semiclassical wave-packets emerging from interaction with an environment

We study the quantum evolution in dimension three of a system composed by a test particle interacting with an environment made of N harmonic oscillators. At time zero the test particle is described by a spherical wave, i.e., a highly correlated continuous superposition of states with well localized position and momentum, and the oscillators are in the ground state. Furthermore, we assume that the positions of the oscillators are not collinear with the center of the spherical wave. Under suitable assumptions on the physical parameters characterizing the model, we give an asymptotic expression of the solution of the Schrödinger equation of the system with an explicit control of the error. The result shows that the approximate expression of the wave function is the sum of two terms, orthogonal in L{sup 2}(R{sup 3(N+1)}) and describing rather different situations. In the first one, all the oscillators remain in their ground state and the test particle is described by the free evolution of a slightly deformed spherical wave. The second one consists of a sum of N terms where in each term there is only one excited oscillator and the test particle is correspondingly described by the free evolution of a wave packet, well concentrated in position and momentum. Moreover, the wave packet emerges from the excited oscillator with an average momentum parallel to the line joining the oscillator with the center of the initial spherical wave. Such wave packet represents a semiclassical state for the test particle, propagating along the corresponding classical trajectory. The main result of our analysis is to show how such a semiclassical state can be produced, starting from the original spherical wave, as a result of the interaction with the environment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

astroABC : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation

Given the complexity of modern cosmological parameter inference where we arefaced with non-Gaussian data and noise, correlated systematics and multi-probecorrelated data sets, the Approximate Bayesian Computation (ABC) method is apromising alternative to traditional Markov Chain Monte Carlo approaches in thecase where the Likelihood is intractable or unknown. The ABC method is called"Likelihood free" as it avoids explicit evaluation of the Likelihood by using aforward model simulation of the data which can include systematics. Weintroduce astroABC, an open source ABC Sequential Monte Carlo (SMC) sampler forparameter estimation. A key challenge in astrophysics is the efficient use oflarge multi-probe datasets to constrain high dimensional, possibly correlatedparameter spaces. With this in mind astroABC allows for massive parallelizationusing MPI, a framework that handles spawning of jobs across multiple nodes. Akey new feature of astroABC is the ability to create MPI groups with differentcommunicators, one for the sampler and several others for the forward modelsimulation, which speeds up sampling time considerably. For smaller jobs thePython multiprocessing option is also available. Other key features include: aSequential Monte Carlo sampler, a method for iteratively adapting tolerancelevels, local covariance estimate using scikit-learn's KDTree, modules forspecifying optimal covariance matrix for a component-wise or multivariatenormal perturbation kernel, output and restart files are backed up everyiteration, user defined metric and simulation methods, a module for specifyingheterogeneous parameter priors including non-standard prior PDFs, a module forspecifying a constant, linear, log or exponential tolerance level,well-documented examples and sample scripts. This code is hosted online athttps://github.com/EliseJ/astroABC

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Disentangling the Effects of Temperature, Moisture, and Substrate Availability on Soil CO 2 Efflux

Soil respiration ($R_s$), the largest carbon emission flux in ecosystems, is usually modeled as an empirically parameterized function of temperature, and sometimes water availability. The likely contribution by other factors, such as carbohydrate substrate supply from photosynthesis, has been recognized, but modeling capacity to use this information is limited. Wavelet transformations of the residuals of a seasonal Q 10 temperature response model indicated structure at different temporal scales. In this work, we hypothesize that this indicates the lack of explicit representation of relevant processes in the models. Using cross-spectral analysis, we found that time series of photosynthetically active radiation explained most of the diurnal variation, temperature, explained variability at multiple time scales (diurnal-synoptic), whereas volumetric soil water content correlated with variability in Rs at scales 15-30 days. The results suggest that the time domains of influence for different driving variables of $R_s$ are discrete, and largely nonoverlapping, and represent functional relationships between soil biological activity and its constraints. Analysis of phase angles showed that $R_s$ lagged photosynthetically active radiation by 1.5-3.0 hr. As this time lag was the same in both young and mature trees, with more than fivefold difference in transport distances, we hypothesize that this finding adds to the body of literature that support the pressure-concentration-wave model of carbohydrate availability in plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Adsorption of a metalorganic complex at a metal surface: A density functional theory study vs. model description

A modification of the electronic and magnetic structure of a metalorganic complex by chemisorption at a metallic surface is addressed. The density functional theory (DFT) is applied to investigate a simplified form of a copper-dioxolene complex in a free state and connected to Au(111) surface with alkanethiol linkers. A systematic study of the dependence of the system electronic structure on the linker length is performed. It is found that the electronic structure of the complex is well preserved during the adsorption process. The magnetic moment of the Cu-dioxolene functional group is shown to be strictly correlated with the amount of the charge residing at the complex. On the basis of the DFT results, a model Hamiltonian of the adsorbed metalorganic system is proposed. The model is an extension of the Sandorfy's model of the alkanes and includes explicitly Coulomb interaction between electrons both within the alkane's backbone and the end group. We show that the latter feature is necessary to understand the evolution of the system's properties with the length of the linkers. The advantage of this approach is that it not only reproduces the main results of our DFT analysis but also provides a simple common basis to analyse a wide class of metal complexes bound to metal surfaces with alkanethiol linkers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Nuclear-spin optical rotation in xenon

We report that the nuclear-spin optical rotation (NSOR) effect, which has potential applications in correlated nuclear-spin-resonance optical spectroscopy, has previously been explored experimentally and theoretically in liquid Xe. Calculations of the Xe NSOR constant are very challenging because the result is sensitive to correlations, relativistic effects, and the choice of basis, with strong cancellation between contributions from lowest and remaining states. The relativistic configuration-interaction many-body-theory approach, presented here, is promising because this approach has been successful in predicting various properties of noble-gas atoms, such as energies, oscillator strengths (OSs), Verdet constants, and photoionization cross sections. However, correlations become stronger along the sequence of noble-gas atoms and the theoretical accuracy in Xe is not as high as, for example, in neon and argon. To improve the accuracy of the Xe Verdet and NSOR constants, which are calculated as explicit sums over the excited states, theoretical values for the several lowest levels are replaced with empirical values of energies, OSs, and hyperfine structure constants. We found that the Xe Verdet constant is in excellent agreement with accurate measurements. To take into account liquid effects, empirical data for energy shifts were also used to correct the NSOR constant. In conclusion, the resulting Xe NSOR constant is in a good agreement with experiment, although the liquid-state effect is treated quite approximately.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗