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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 253 records · Page 14

Accounting for nonuniformity of bulk‐solvent: A mosaic model

Abstract A flat mask‐based model is almost universally used in macromolecular crystallography to account for disordered (bulk) solvent. This model assumes any voxel of the crystal unit cell that is not occupied by the atomic model is occupied by the solvent. The properties of this solvent are assumed to be exactly the same across the whole volume of the unit cell. While this is a reasonable approximation in practice, there are a number of scenarios where this model becomes suboptimal. In this work, we enumerate several of these scenarios and describe a new generalized approach to modeling the bulk‐solvent which we refer to as mosaic bulk‐solvent model. The mosaic bulk‐solvent model allows nonuniform features of the solvent in the crystal to be accounted for in a computationally efficient way. It is implemented in the computational crystallography toolbox and the Phenix software.

Afonine, Pavel V.↗

Three-state majority-vote model on small-world networks

Abstract In this work, we study the opinion dynamics of the three-state majority-vote model on small-world networks of social interactions. In the majority-vote dynamics, an individual adopts the opinion of the majority of its neighbors with probability 1- q , and a different opinion with chance q , where q stands for the noise parameter. The noise q acts as a social temperature, inducing dissent among individual opinions. With probability p , we rewire the connections of the two-dimensional square lattice network, allowing long-range interactions in the society, thus yielding the small-world property present in many different real-world systems. We investigate the degree distribution, average clustering coefficient and average shortest path length to characterize the topology of the rewired networks of social interactions. By employing Monte Carlo simulations, we investigate the second-order phase transition of the three-state majority-vote dynamics, and obtain the critical noise $$q_c$$ q c , as well as the standard critical exponents $$\beta /\nu$$ β / ν , $$\gamma /\nu$$ γ / ν , and $$1/\nu$$ 1 / ν for several values of the rewiring probability p . We conclude that the rewiring of the lattice enhances the social order in the system and drives the model to different universality classes from that of the three-state majority-vote model in two-dimensional square lattices.

99 GENERAL AND MISCELLANEOUS↗

Scientific machine learning for modeling and simulating complex fluids

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.

Science & Technology - Other Topics↗

Universal Responses of Cyclic-Oxidation Models Studied

Oxidation is an important degradation process for materials operating in the high-temperature air or oxygen environments typical of jet turbine or rocket engines. Reaction of the combustion gases with the component material forms surface layer scales during these oxidative exposures. Typically, the instantaneous rate of reaction is inversely proportional to the existing scale thickness, giving rise to parabolic kinetics. However, more realistic applications entail periodic startup and shutdown. Some scale spallation may occur upon cooling, resulting in loss of the protective diffusion barrier provided by a fully intact scale. Upon reheating, the component will experience accelerated oxidation due to this spallation. Cyclic-oxidation testing has, therefore, been a mainstay of characterization and performance ranking for high-temperature materials. Models simulate this process by calculating how a scale spalls upon cooling and regrows upon heating (refs. 1 to 3). Recently released NASA software (COSP for Windows) allows researchers to specify a uniform layer or discrete segments of spallation (ref. 4). Families of model curves exhibit consistent regularity and trends with input parameters, and characteristic features have been empirically described in terms of these parameters. Although much insight has been gained from experimental and model curves, no equation has been derived that can describe this behavior explicitly as functions of the key oxidation parameters.

Smialek, James L.↗

MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine learning↗

Mated aerodynamic characteristics investigation for 0.04-scale model Boeing 747 CAM/external tank (model AX1284 E-5) combination in the University of Washington Aeronautical Laboratory F. K. Kirsten Wind Tunnel (CA11)

Experimental investigations of the aerodynamic characteristics of a 0.04-scale external tank (ET) force model in combination with a 0.04-scale Boeing 747 force model were conducted. Test purposes were: (1) to determine ET airloads for selected configurations and (2) to determine the effectiveness of ET position, incidence, and support structure and 747 vertical stabilizing surfaces on stability, control, and performance of 747/ET combinations. The 747 was tested alone to establish baseline data and to verify test results. Six-component aerodynamic force and moment data were recorded for the 747 CAM and ET combination. Six-component force and moment data were also recorded for the ET, which was mounted on an internal balance supported by the 747. Data were recorded for angles of attack from -4 deg to +24 deg in 2 deg increments and angles of sideslip of - deg to + or - 20 deg. Testing was conducted at Mach 0.15 with dynamic pressure deg at 36 psf and unit Reynolds number of 1.3 million per foot. Photographs of test configurations are shown.

Source record↗

Dynamics of the O ( 4 ) critical point in QCD: Critical pions and diffusion in model G

We present a detailed study of the finite momentum dynamics of the O ( 4 ) critical point of QCD, which lies in the dynamic universality class of “model G.” The critical scaling of the model is analyzed in multiple dynamical channels. For instance, the finite momentum analysis allows us to precisely extract the pion dispersion curve below the critical point. The pion velocity is in striking agreement with the predictions relation and static universality. The pion damping rate and velocity are both consistent with the dynamical critical exponent ζ = 3 / 2 of model G. Similarly, although the critical amplitude for the diffusion coefficient of the conserved O ( 4 ) charges is small, it is clearly visible both in the restored phase and with finite explicit symmetry breaking, and its dynamical scaling is again consistent with ζ = 3 / 2 . We determine a new set of universal dynamical critical amplitude ratios relating the diffusion coefficient to a suitably defined order parameter relaxation time. We also show that in a finite volume simulation, the chiral condensate diffuses on the coset manifold in a manner consistent with dynamical scaling, and with a diffusion coefficient that is determined by the transport coefficients of hydrodynamic pions. Finally, the amplitude ratios (together with other nonuniversal amplitudes also reported here) compile all relevant information for further studies of model G both in and out of equilibrium. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Gravity and count probabilities in an expanding universe

The time evolution of nonlinear clustering on large scales in cold dark matter, hot dark matter, and white noise models of the universe is investigated using N-body simulations performed with a tree code. Count probabilities in cubic cells are determined as functions of the cell size and the clustering state (redshift), and comparisons are made with various theoretical models. We isolate the features that appear to be the result of gravitational instability, those that depend on the initial conditions, and those that are likely a consequence of numerical limitations. More specifically, we study the development of skewness, kurtosis, and the fifth moment in relation to variance, the dependence of the void probability on time as well as on sparseness of sampling, and the overall shape of the count probability distribution. Implications of our results for theoretical and observational studies are discussed.

Bouchet, Francois R.↗

Policy-Driven Sustainable Saline Drainage Disposal and Forage Production in the Western San Joaquin Valley of California

Environmental policies to address water quality impairments in the San Joaquin River of California have focused on the reduction of salinity and selenium-contaminated subsurface agricultural drainage loads from westside sources. On 31 December 2019, all of the agricultural drainage from a 44,000 ha subarea on the western side of the San Joaquin River basin was curtailed. This policy requires the on-site disposal of all of the agricultural drainage water in perpetuity, except during flooding events, when emergency drainage to the River is sanctioned. The reuse of this saline agricultural drainage water to irrigate forage crops, such as ‘Jose’ tall wheatgrass and alfalfa, in a 2428 ha reuse facility provides an economic return on this pollutant disposal option. Irrigation with brackish water requires careful management to prevent salt accumulation in the crop root zone, which can impact forage yields. The objective of this study was to optimize the sustainability of this reuse facility by maximizing the evaporation potential while achieving cost recovery. This was achieved by assessing the spatial and temporal distribution of the root zone salinity in selected fields of ‘Jose’ tall wheatgrass and alfalfa in the drainage reuse facility, some of which have been irrigated with brackish subsurface drainage water for over fifteen years. Electromagnetic soil surveys using an EM-38 instrument were used to measure the spatial variability of the salinity in the soil profile. The tall wheatgrass fields were irrigated with higher salinity water (1.2–9.3 dS m -1 ) compared to the fields of alfalfa (0.5–6.5 dS m -1 ). Correspondingly, the soil salinity in the tall wheatgrass fields was higher (12.5 dS m -1 –19.3 dS m -1 ) compared to the alfalfa fields (8.97 dS mm -1 –14.4 dS mm -1 ) for the years 2016 and 2017. Better leaching of salts was observed in the fields with a subsurface drainage system installed (13–1 and 13–2). The depth-averaged root zone salinity data sets are being used for the calibration of the transient hydro-salinity computer model CSUID-ID (a one-dimensional version of the Colorado State University Irrigation Drainage Model). This user-friendly decision support tool currently provides a useful framework for the data collection needed to make credible, field-scale salinity budgets. In time, it will provide guidance for appropriate leaching requirements and potential blending decisions for sustainable forage production. This paper shows the tie between environmental drainage policy and the role of local governance in the development of sustainable irrigation practices, and how well-directed collaborative field research can guide future resource management.

54 ENVIRONMENTAL SCIENCES↗

3D inelastic analysis methods for hot section components

The objective is to develop analytical tools capable of economically evaluating the cyclic time dependent plasticity which occurs in hot section engine components in areas of strain concentration resulting from the combination of both mechanical and thermal stresses. Three models were developed. A simple model performs time dependent inelastic analysis using the power law creep equation. The second model is the classical model of Professors Walter Haisler and David Allen of Texas A and M University. The third model is the unified model of Bodner, Partom, et al. All models were customized for linear variation of loads and temperatures with all material properties and constitutive models being temperature dependent.

Dame, L. T.↗

Gravitational wave imprints of left-right symmetric model with minimal Higgs sector

We study the gravitational wave imprints of left-right symmetric model equipped with universal seesaw mechanism allowing for the natural generation of hierarchical masses of the Standard Model fermions. The scalar sector of this model is the minimal one, consisting of only two Higgs doublets. Following the construction of the full thermal potential for this model, we perform a scan of the entire parameter space and identify the region in which the cosmic phase transition associated with the left-right symmetry breaking gives gravitational wave signals detectable by a variety of planned space-based interferometers. Then we also discuss the relevant collider implications of this beyond the Standard Model scenario.

79 ASTRONOMY AND ASTROPHYSICS↗

A nonhydrostatic version of the Penn State-NCAR Mesoscale Model - Validation tests and simulation of an Atlantic cyclone and cold front

A nonhydrostatic extension to the Pennsylvania State University-NCAR Mesoscale Model is presented, which employs reference pressure as the basis for a terrain-following vertical coordinate, and the fully compressible system of equations. It is shown that this model, combined with the existing initialization techniques and the physics of the current hydrostatic model, is capable of real-data simulations on any scale, limited only by data quality and resolution and by computer resources. An example of an explosive cyclone simulation is presented, demonstrating the capability of the nonhydrostatic model to reproduce the hydrostatic model results at large scales.

Dudhia, Jimy↗

Effects of primordial fluctuations on the abundances of light elements

Some of the effects of primordial inhomogeneities on the production of H-2, He-3, and Li-7 are investigated. For the most part, temperature fluctuations have only small effects on the abundances. The density fluctuations are modeled by a unimodal distribution so that the Universe is characterized by the mean density and the relative amplitude of the density variations. It has been found that the constraint which H-2 production imposes on the mean mass density is eased somewhat by allowing for density inhomogeneities. However, unless the composition of the interstellar matter is atypical of most of the matter in the Universe, the mass density will be at least a factor of 3 below the critical density. For reasonable estimates of the pregalactic abundances, sufficient He-3 and Li-7 cannot be produced in the same model universe. Production of both Li-7 and H-2 requires large-amplitude primordial fluctuations, while sufficient He-3 and H-2 can be formed in very low-density, fairly homogeneous universes.

Epstein, R. I.↗

Turbulence: The chief outstanding difficulty of our subject

A review of interesting current topics in turbulence research is decorated with examples of popular fallacies about the behavior of turbulence. Topics include the status of the Law of the Wall, especially in compressible flow; analogies between the effects of Reynolds numbers, pressure gradient, unsteadiness and roughness change; the status of Kolmogorov's universal equilibrium theory and local isotropy of the small eddies; turbulence modelling, with reference to universality, pressure-strain modelling and the dissipation equation; and chaos. Fallacies include the mixing-length concept; the effect of pressure gradient on Reynolds shear stress; the separability of time and space derivatives; models of the dissipation equation; and chaos.

Bradshaw, Peter↗

A diagnostic study of vertical fluxes in cumulus clouds using model output data

Midlatitude supercell, Florida sea-breeze convection, and tropical squall line simulations were performed using the Colorado State University Regional Atmospheric Modeling System which employed the non-hydrostatic, fully compressible, equations with parameterized microphysics. The time evolution of the vertical velocity variance (VVV) is especially interesting since it is a measure of the strength of convection. This variance exhibits striking similarities when analyzed for the aforementioned cases which may indicate that all convection is fundamentally similar. Vertical mass and moisture covariances appear strongly linked to VVV, so it may be the appropriate variable on which to base a hybrid cumulus parameterization scheme.

Weissbluth, M. J.↗