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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modeling and Analysis of a Novel Offshore Binary Species Free-Floating Longline Macroalgal Farming System

The investigation of innovative macroalgal cultivation is important and needed to optimize farming operations, increase biomass production, reduce the impact on the ecosystem, and lower system and operational costs. However, most macroalgal farming systems (MFSs) are stationary, which need to occupy a substantial coastal area, require extensive investment in farm infrastructure, and cost high fertilizer and anchoring expenses. This study aims to model, analyze, and support a novel binary species free-floating longline macroalgal cultivation concept. The expected outcomes could provide a basis for the design and application of the novel MFS to improve biomass production, decrease costs, and reduce the impact on the local ecosystem. In this paper, Saccharina latissima and Nereocystis luetkeana were modeled and validated, and coupled with longline to simulate the binary species MFS free float in various growth periods and associated locations along the US west coast. Further, the numerical predictions indicated the possibility of failure on the longline and breakage at the kelp holdfasts is low. However, the large forces due to an instantaneous change in dynamic loads caused by loss of hydrostatic buoyancy when the longline stretches out of the water would damage the kelps. Buoy-longline contact interactions could damage the buoy, resulting in the loss of the system by sinking. Furthermore, the kelp-longline and kelp-kelp entanglements could potentially cause kelp damage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Machine Learning Assisted Development of a Model for the Populations of Convective and Stratiform Clouds

Abstract Traditional parameterizations of the interaction between convection and the environment have relied on an assumption that the slowly varying large‐scale environment is in statistical equilibrium with a large number of small and short‐lived convective clouds. They fail to capture nonequilibrium transitions such as the diurnal cycle and the formation of mesoscale convective systems as well as observed precipitation statistics and extremes. Informed by analysis of radar observations, cloud‐permitting model simulation, theory, and machine learning, this work presents a new stochastic cloud population dynamics model for characterizing the interactions between convective and stratiform clouds, with the goal of informing the representation of these interactions in global climate models. Fifteen wet seasons of precipitating cloud observations by a C‐band radar at Darwin, Australia are fed into a machine learning algorithm to obtain transition functions that close a set of coupled equations relating large‐scale forcing, mass flux, the convective cell size distribution, and the stratiform area. Under realistic large‐scale forcing, the derived transition functions show that, on the one hand, interactions with stratiform clouds act to dampen the variability in the size and number of convective cells and therefore in the convective mass flux. On the other, for a given convective area fraction, a larger number of smaller cells is more favorable for the growth of stratiform area than a smaller number of larger cells. The combination of these two factors gives rise to solutions with a few convective cells embedded in a large stratiform area, reminiscent of mesoscale convective systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Toward particle-resolved accuracy in Euler–Lagrange simulations of multiphase flow using machine learning and pairwise interaction extended point-particle (PIEP) approximation

This study presents two different machine learning approaches for the modeling of hydrodynamic force on particles in a particle-laden multiphase flow. Results from particle-resolved direct numerical simulations (PR-DNS) of flow over a random array of stationary particles for eight combinations of particle Reynolds number (Re) and volume fraction (φ) are used in the development of the models. The first approach follows a two-step process. In the first flow prediction step, the perturbation flow due to a particle is obtained as an axisymmetric superposable wake using linear regression. In the second force prediction step, the force on a particle is evaluated in terms of the perturbation flow induced by all its neighbors using the generalized Faxén form of the force expression. In the second approach, the force data on all the particles from the PR-DNS simulations are used to develop an artificial neural network (ANN) model for direct prediction of force on a particle. Due to the unavoidable limitation on the number of fully resolved particles in the PR-DNS simulations, direct force prediction with the ANN model tends to over-fit the data and performs poorly in the prediction of test data. In contrast, due to the millions of grid points used in the PR-DNS simulations, accurate flow prediction is possible, which then allows accurate prediction of particle force. This hybridization of multiphase physics and machine learning is particularly important, since it blends the strength of each, and the resulting pairwise interaction extended point-particle model cannot be developed by either physics or machine learning alone.

42 ENGINEERING↗
NASA NTRS2017

Self Assembled Particles

A self-assembling structure using non-equilibrium driving forces leading to 'living crystals' and other maniputable particles with a complex dynamics. The dynamic self-assembly assembly results from a competition between self-propulsion of particles and an attractive interaction between the particles. As a result of non-equilibrium driving forces, the crystals form, grow, collide, anneal, repair themselves and spontaneously self-destruct, thereby enabling reconfiguration and assembly to achieve a desired property.

Palacci, Jeremie↗
NASA NTRS1992

Dark matter, long-range forces, and large-scale structure

If the dark matter in galaxies and clusters is nonbaryonic, it can interact with additional long-range fields that are invisible to experimental tests of the equivalence principle. We discuss the astrophysical and cosmological implications of a long-range force coupled only to the dark matter and find rather tight constraints on its strength. If the force is repulsive (attractive), the masses of galaxy groups and clusters (and the mean density of the universe inferred from them) have been systematically underestimated (overestimated). We explore the consequent effects on the two-point correlation function, large-scale velocity flows, and microwave background anisotropies, for models with initial scale-invariant adiabatic perturbations and cold dark matter.

Gradwohl, Ben-Ami↗
NASA NTRS1999

Environmental Forcing of Super Typhoon Paka's (1997) Latent Heat Structure

The distribution and intensity of total (i.e., combined stratified and convective processes) rainrate/latent heat release (LHR) were derived for tropical cyclone Paka during the period 9-21 December, 1997 from the F-10, F-11, F-13, and F-14 Defense Meteorological Satellite Special Sensor Microwave/Imager and the Tropical Rain Measurement Mission Microwave Imager observations. These observations were frequent enough to capture three episodes of inner core convective bursts that preceded periods of rapid intensification and a convective rainband (CRB) cycle. During these periods of convective bursts, satellite sensors revealed that the rainrates/LHR: 1) increased within the inner eye wall region; 2) were mainly convectively generated (nearly a 65% contribution), 3) propagated inwards; 4) extended upwards within the middle and upper-troposphere, and 5) became electrically charged. These factors may have caused the eye wall region to become more buoyant within the middle and upper-troposphere, creating greater cyclonic angular momentum, and, thereby, warming the center and intensifying the system. Radiosonde measurements from Kwajalein Atoll and Guam, sea surface temperature observations, and the European Center for Medium Range Forecast analyses were used to examine the necessary and sufficient condition for initiating and maintaining these inner core convective bursts. For example, the necessary conditions such as the atmospheric thermodynamics (i.e., cold tropopause temperatures, moist troposphere, and warm SSTs [greater than 26 deg]) suggested that the atmosphere was ideal for Paka's maximum potential intensity (MPI) to approach super-typhoon strength. Further, Paka encountered weak vertical wind shear (less than 15 m/s ) before interacting with the westerlies on 21 December. The sufficient conditions, on the other hand, appeared to have some influence on Paka's convective burst, but the horizontal moisture flux convergence values in the outer core were weaker than some of the previously examined tropical cyclones. Also, the upper tropospheric outflow generation of eddy relative angular momentum flux convergence was 4D much less than that found during moderate tropical cyclone/trough interaction. These results indicated how important the external necessary condition and the internal forcing (i.e., CRB cycle) were in generating Paka's convective bursts as compared to the external sufficient forcing mechanisms found in higher latitude tropical cyclones. Later, as Paka began to interact with the westerlies, both the necessary (i.e., strong vertical shear and colder SSTs) and sufficient (i.e., dry air intrusion) external forcing mechanisms helped to decrease Paka's rainrate.

Rodgers, Edward B.↗
DOE OSTI2024

Binding of Phosphate Species to Ca 2+ and Mg 2+ in Aqueous Solution

Phosphate derivatives and their interaction with metal cations are involved in many important biological phenomena, so an accurate characterization of the phosphate-metal interaction is necessary to properly understand the role of phosphate-metal contacts in mediating biological function. Herein, we improved the standard 12-6 Lennard-Jones (LJ) potential via the usage of the 12-6-4 LJ model, which incorporates ion-induced dipole interactions. Via parameter scanning, we fine-tuned the 12-6-4 LJ polarizability values to obtain accurate absolute binding free energies for the phosphate anions H 2 PO 4 – , HPO 4 2– , PO 4 3– coordinating with Ca 2+ and Mg 2+ . First, we modified the phosphate 12-6-4 LJ parameters to reproduce the solvation free energies of the series of phosphate anions using the thermodynamic integration (TI) method. Then, using the potential mean force (PMF) method, the polarizability of the metal-phosphate interaction was obtained. We show that the free energy profiles of phosphate ions coordinated to Ca 2+ and Mg 2+ generally show similar trends at longer metal–phosphate distances, while the absolute binding energy values increased with deprotonation. The resulting parameters demonstrate the flexibility of the 12-6-4 LJ-type nonbonded model and its usefulness in accurately describing cation–anion interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Gaussian approximation potentials for accurate thermal properties of two-dimensional materials

Two-dimensional materials (2DMs) continue to attract a lot of attention, particularly for their extreme flexibility and superior thermal properties. Molecular dynamics simulations are among the most powerful methods for computing these properties, but their reliability depends on the accuracy of interatomic interactions. While first principles approaches provide the most accurate description of interatomic forces, they are computationally expensive. In contrast, classical force fields are computationally efficient, but have limited accuracy in interatomic force description. Machine learning interatomic potentials, such as Gaussian Approximation Potentials, trained on density functional theory (DFT) calculations offer a compromise by providing both accurate estimation and computational efficiency. Here, in this work, we present a systematic procedure to develop Gaussian approximation potentials for selected 2DMs, graphene, buckled silicene, and h-XN (X = B, Al, and Ga, as binary compounds) structures. We validate our approach through calculations that require various levels of accuracy in interatomic interactions. The calculated phonon dispersion curves and lattice thermal conductivity, obtained through harmonic and anharmonic force constants (including fourth order) are in excellent agreement with DFT results. HIPHIVE calculations, in which the generated GAP potentials were used to compute higher-order force constants instead of DFT, demonstrated the first-principles level accuracy of the potentials for interatomic force description. Molecular dynamics simulations based on phonon density of states calculations, which agree closely with DFT-based calculations, also show the success of the generated potentials in high-temperature simulations.

2D Materials↗
NASA NTRS2020

Analysis of Sample Acquisition Dynamics Using Discrete Element Method

The analysis presented in this paper is conducted in the framework of the Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) project, currently under development at NASA Ames Research Center. OceanWATERS aims at designing a simulation environment which allows for testing autonomy of scientific lander missions to the icy moons of our solar system. Mainly focused on reproducing the end effector interaction with the inherent terrain, this paper introduces a novel discrete element method (DEM)-based approach to determine forces and torques acting on the lander’s scoop during the sample acquisition process. An accurate force feedback from the terrain on the scoop is required by fault-detection and autonomous decision-making algorithms to identify when the requested torque on the robotic arm’s joints exceeds the maximum available torque. Knowledge of the terrain force feedback significantly helps evaluating the arm’s links structural properties and properly selecting actuators for the joints. Models available in literature constitute a partial representation of the dynamics of the interaction. As an example, Balovnev derived an analytical expression of the vertical and horizontal force acting on a bucket while collecting a sample as a function of its geometry and velocity, soil parameters and reached depth. Although the model represents an adequate approximation of the two force components, it ignores the direction orthogonal to the scoop motion and neglects the torque. This work relies on DEM analysis to compensate for analytical models’ deficiencies and inaccuracies, i. e. provide force and torque 3D vectors, defined in the moving reference (body) frame attached to the scoop, at each instant of the sample collection process. Results from the first presented analysis relate to the specific OceanWATERS sampling strategy, which consists of collecting the sample through five consecutive passes with increasing depth, each pass following the same circularlinear- circular trajectory. Data is collected given a specific scoop design interacting with two types of bulk materials, which may characterize the surface of icy planetary bodies: snow and ice. Although specifically concerned with the OceanWATERS design, this first analysis provides the expected force trends for similar sampling strategies and allows to deduce phenomenological information about the general scooping process. In order to further instruct the community on the use of DEM tools as a solution to the sampling collection problem, two more analyses have been carried out, mainly focused on reducing the DEM computation time, which increases with a decrease in particle size. After running a set of identical simulations, where the only changing parameter is the size of the spherical particle, it is observed that the resulting force trajectories, starting from a given particle size, converge to the true trend. It is deducible that a further decrease in size yields negligible improvements in the accuracy, while it sensibly increases computation time. A final analysis aims at discussing limitations of approximating bulk material particles having a complex shape, e. g. ice fragments, with spheres, by comparing force trends resulting in the two cases for the same simulation scenario.

Catanoso, Damiana↗
NASA NTRS1983

Numerical studies of major and minor stratospheric warmings caused by orographic forcing

A primitive equation spectral model using spherical harmonics is formulated to study dynamic interactions between the troposphere and stratosphere in association with sudden stratospheric warmings. Using sigma coordinates for five tropospheric layers and log-pressure coordinates for 26 stratospheric and mesospheric layers, separate model equations for each system are combined to form single matrix governing equations. The gradual introduction of large scale topography to balanced initial states representative of observed mean winter conditions in the Northern Hemisphere is used for the generation of planetary waves during 40-day time integrations. Results of these integrations indicate that stratospheric warmings can be simulated by this orographic forcing and that mean momentum flux divergence due to zonal mean motion appears to be an essential mechanism of these simulated sudden warmings. It was found that the strength of the polar night jet can be a determining factor whether a warming becomes 'major' or 'minor'.

Koermer, J. P.↗
DOE OSTI2021

Atomic Force Microscopy and Infrared Nanospectroscopy of COVID-19 Spike Protein for the Quantification of Adhesion to Common Surfaces

The COVID-19 pandemic has claimed millions of lives worldwide, sickened many more, and has resulted in severe socio-economic consequences. As society returns to normal, understanding the spread and persistence of SARS CoV-2 on commonplace surfaces can help to mitigate future outbreaks of coronaviruses and other pathogens. We hypothesize that such an understanding can be aided from studying the binding and interaction of viral proteins with non-biological surfaces. Here, we propose a methodology for investigating the adhesion of the SARS CoV-2 spike glycoprotein on common inorganic surfaces such as aluminum-, copper-, iron-, silica-, and ceria-oxides as well as metallic gold. Quantitative adhesion was obtained from the analysis of measured forces at the nanoscale using an atomic force microscope operated under ambient conditions. Without imposing further constraints on the measurement conditions, our preliminary findings suggest that spike glycoproteins interact with similar adhesion forces across the majority of the metal oxides tested with the exception to gold, for which attraction forces ~10 times stronger than all other materials studied were observed. Ferritin, which was used as a reference protein, was found to exhibit similar adhesion forces as SARS CoV-2 spike protein. Further, this study results show that glycoprotein adhesion forces for similar ambient humidity, tip shape, and contact surface are non-specific to the properties of metal oxide surfaces, which are expected to be covered by a thin water film. The findings suggest that at ambient conditions glycoprotein adhesion to metal oxides is primarily controlled by the water capillary forces and they depend on the surface tension of the liquid (water). We discuss further strategies warranted to decipher the intricate nanoscale forces for improved quantification of the adhesion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Mean-field theory for the structure of strongly interacting active liquids

Active systems, which are driven out of equilibrium by local non-conservative forces, exhibit unique behaviors and structures with potential utility for the design of novel materials. An important and difficult challenge along the path toward this goal is to precisely predict how the structure of active systems is modified as their driving forces push them out of equilibrium. Here, we use tools from liquid-state theories to approach this challenge for a classic minimal active matter model. First, we construct a nonequilibrium mean-field framework that can predict the structure of systems of weakly interacting particles. Second, motivated by equilibrium solvation theories, we modify this theory to extend it with surprisingly high accuracy to systems of strongly interacting particles, distinguishing it from most existing similarly tractable approaches. Furthermore, our results provide insight into spatial organization in strongly interacting out-of-equilibrium systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Defect Self-Elimination in Nanocube Superlattices Through the Interplay of Brownian, van der Waals, and Ligand-Based Forces and Torques

Understanding defect healing is necessary for realizing devices based on nanoparticle-superlattices with controlled electronic and optoelectronic performance. However, key questions remain regarding nanoparticle interactions and resulting assembly dynamics and defect self-elimination. In particular, for anisotropic particles, additional degrees of freedom beyond those of spherical particles, such as rotational dynamics and toques, significantly impact phenomena. Here, in this work, we investigate nanocube (NC) superlattices by employing liquid phase transmission electron microscopy, continuum theories and molecular dynamics simulations. Analyzing interparticle forces and torques due to van der Waals, Brownian, and ligand interactions, we find that the latter dominates and that the anisotropic NC morphology introduces significant torques. In imperfect regions, unbalanced forces and torques induce NC translations and rotations that are transmitted to neighboring NCs, prompting “chain interactions” in a 2D network, which lead to defect self-elimination. This fundamental understanding will further enable design and fabrication of defect-free superlattices, as well as those with tailored defects, via assembly of anisotropic particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Structure and Dynamics of CO 2 at the Air–Water Interface from Classical and Neural Network Potentials

The accurate description of the structure and dynamics of CO 2 at the instantaneous air–water interface, along with the effects of surface fluctuations on the CO 2 -transport processes, is essential for the development of negative emission technologies aimed at minimizing climate change. In this study, we performed molecular dynamics simulations of CO 2 at the air–water interface using neural network potentials (NNPs) trained on ab initio data generated through density-functional-theory-based molecular dynamics simulations. We compared these results with classical force fields to assess their performance in modeling interfacial CO 2 behavior. Our findings revealed that the asymmetric interactions, coupled with thermal surface fluctuations at the air–water interface, significantly influence CO 2 transport into the aqueous phase. The simulations demonstrate that classical force fields underestimate both the free energy of CO 2 transport and the strength of its interactions at the interface compared with the neural network potentials. In conclusion, the free energy and the interfacial dynamics of CO 2 are primarily influenced by the distribution of water within the instantaneous interfacial water layer, responsible for creating an asymmetric intermolecular interaction environment within the interfacial region.

Ab initio molecular dynamics↗
DOE OSTI2021

Modeling swelling behavior of hydrogels in aqueous organic solvents

Hydrogel, a three-dimensional elastic structure of cross-linked polymer chains, swells or deswells when immersed in aqueous organic solutions. The swelling of hydrogels depends on temperature, solvent composition, and hydrogel structure as the thermodynamic driving forces for hydrogel swelling are due to solvent – hydrogel interactions and expansion of elastic network. Here in this work, polymer Nonrandom Two-Liquid activity coefficient model is used to account for the solvent – hydrogel interactions and a semi-empirical expression for rubber elasticity is used to describe the expansion of elastic network. The model successfully correlates data for both swelling and equilibrium phase compositions for n-isopropyl acrylamide hydrogels in water – ethanol, water – acetone, water – n-butanol, and water – methyl isobutyl ketone mixed solvents.

42 ENGINEERING↗
DOE OSTI2024

Direct observation of annealing-driven recrystallization behavior in magnesium alloy at low strain condition

Grain-twin interactions are significant in texture modification under thermodynamic driving force. In this study, annealing-driven twinning/detwinning behavior, grain growth, and corresponding texture evolution in a pre-deformed AZ31 magnesium alloy were systematically tracked and investigated via in-situ heating synchrotron X-ray diffraction and quasi in-situ electron backscattered diffraction techniques. A twinning texture is generated in the pre-deformed sample due to the activation of {$10\bar{1}2$} tensile twinning. During annealing, dislocation annihilation occurs between 100 and 280 °C, and recrystallization occurs above 280 °C, manifesting as the initial residual matrix and twins being competitively swallowed by each other, forming a bimodal texture. The recrystallization process is completed by boundary movement, which depends on the energy difference across the boundary. In addition, it is found that the grain boundaries favor movement towards the side with higher stored energy, regardless of the boundary type or the boundary energy.

In-situ observation↗
DOE OSTI2026

Geostrophic to magnetically-damped turbulence in liquid metal rotating magnetoconvection

Understanding planetary core convection dynamics requires the study of convective flows in which the Coriolis and Lorentz forces attain a leading-order, so-called magnetostrophic balance. Experimental investigations of rotating magnetoconvection (RMC) in the magnetostrophic regime are therefore essential to broadly characterize the properties of local-scale planetary core flow. Toward this end, we present here the first thermovelocimetric measurements of magnetostrophic, liquid metal convection, which are made using liquid gallium as the working fluid, at moderate rotation rates (Ekman numbers 10 -4 ≤ Ek ≤ 10 -5 ) and in the presence of dynamically strong magnetic fields (Elsasser number Λ = 1). Complementary rotating convection (RC) experiments are performed at the same rotation rates to serve as reference cases. Our RMC velocity measurements adequately follow a geostrophic turbulent scaling for cases in which local-scale convective inertial forces exceed the Lorentz forces in the fluid bulk. In cases where Lorentz forces exceed local-scale inertia (local or convective interaction parameter N ℓ or N C ≳ 3), the root-mean-square RMC velocities are magnetically damped, yielding values below the geostrophic turbulent RC scaling prediction. An enhancement in heat transfer is observed, which we attribute to the increased coherence of vertically aligned magnetostrophic convective flow. Finally, our results and comparisons to dynamo simulations suggest that the system is in the strong-field regime, where convection-scale flows are magnetically damped with N C ≳ 3).

Convective turbulence↗
DOE OSTI2026

Quasielastic $\overrightarrow{^{3}He}$ $(\overrightarrow{e},e′)$ asymmetry in the threshold region with a longitudinally polarized target

We report on the measurements of the double-spin asymmetry from electron- 3 He scattering in the threshold region of two- and three-body breakup of 3 He for 4-momentum transfer values of 0.1 and 0.2 (GeV/c) 2 . The measurement was done at Jefferson Lab using a polarized 3 He target with its spin aligned parallel to the beam direction. This asymmetry is sensitive to a combination of spin-dependent response functions not previously measured and may highlight differences in two body forces, meson-exchange currents and final-state interactions. The results of this measurement serve as a test of our understanding of few-body systems. When compared with calculations from plane wave impulse approximation and Faddeev calculations, we found that the latter, which use modern nuclear potentials and prescriptions for meson-exchange currents, demonstrate an overall good agreement with data.

Few-body nuclei↗