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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 OSTI2021

Simulation and flow physics of a shocked and reshocked high-energy-density mixing layer

This work describes a computational investigation of multimode instability growth and multimaterial mixing induced by multiple shock waves in a high-energy-density (HED) environment, where pressures exceed 1 Mbar. The simulations are based on a series of experiments performed at the National Ignition Facility (NIF) and designed as an HED analogue of non-HED shock-tube studies of the Richtmyer–Meshkov instability and turbulent mixing. A three-dimensional computational modelling framework is presented. It treats many complications absent from canonical non-HED shock-tube flows, including distinct ion and free-electron internal energies, non-ideal equations of state, radiation transport and plasma-state mass diffusivities, viscosities and thermal conductivities. The simulations are tuned to the available NIF data, and traditional statistical quantities of turbulence are analysed. Integrated measures of turbulent kinetic energy and enstrophy both increase by over an order of magnitude due to reshock. Large contributions to enstrophy production during reshock are seen from both the baroclinic source and enstrophy–dilatation terms, highlighting the significance of fluid compressibility in the HED regime. Dimensional analysis reveals that Reynolds numbers and diffusive Péclet numbers in the HED flow are similar to those in a canonical non-HED analogue, but conductive Péclet numbers are much smaller in the HED flow due to efficient thermal conduction by free electrons. It is shown that the mechanism of electron thermal conduction significantly softens local spanwise gradients of both temperature and density, which causes a minor but non-negligible decrease in enstrophy production and small-scale mixing relative to a flow without this mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Specific features of fluorescence transfer in multiply scattering randomly inhomogeneous layers under intense laser pumping

Based on the analysis of experimental data on the effect of the pulsed laser pump intensity on the spectral properties and the size of the fluorescent response zone in randomly inhomogeneous fluorescent layers, we found that the amplification of spontaneous and stimulated emission significantly affects the statistical properties of the propagation lengths of the fluorescent field partial components in the layers. The experiments are performed with layers of SiO{sub 2} and TiO{sub 2} nanoparticles saturated with rhodamine 6G, pumped by 532-nm laser radiation in the intensity range corresponding to the transient regime from excitation of spontaneous fluorescence to random lasing in the layer. The experimental data are compared with the results of statistical modelling of fluorescence transfer. It is shown that, even at a pump intensity below the random lasing threshold, the spontaneous emission amplification in a layer leads to a significant increase in the contributions to the fluorescence response from partial components with propagation lengths much larger than the layer thickness. This can be interpreted as a manifestation of the quasi-waveguide effect, in which the probability of propagation of diffuse fluorescence components along the layer over distances many times greater than its thickness and the size of the pumped region increases significantly with a decrease in the characteristic radiation amplification length in the layer. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Bayesian-based response expansion and uncertainty quantification using sparse measurement sets

Systems subjected to dynamic loads often require monitoring of their vibrational response, but limitations on the total number and placement of the measurement sensors can hinder the data-collection process. Here, we present an indirect approach to estimate a system’s full-field dynamic response, including all uninstrumented locations, using response measurements from sensors sparsely located on the system. This approach relies on Bayesian inference that utilizes a system model to estimate the full-field response and quantify the uncertainty in these estimates. By casting the estimation problem in the frequency domain, this approach utilizes the modal frequency response functions as a natural, frequency-dependent weighting scheme for the system mode shapes to perform the expansion. This frequency-dependent weighting scheme enables an accurate expansion, even with highly correlated mode shapes that may arise from spatial aliasing due to the limited number of sensors, provided these correlated modes do not have natural frequencies that are closely spaced. Furthermore, the inherent regularization mechanism that arises in this Bayesian-based procedure enables the utilization of the full set of system mode shapes for the expansion, rather than any reduced subset. This approach can produce estimates when considering a single realization of the measured responses, and with some modification, it can also produce estimates for power spectral density matrices measured from many realizations of the responses from statistically stationary random processes. A simply supported beam provides an initial numerical validation, and a cylindrical test article excited by acoustic loads in a reverberation chamber provides experimental validation.

42 ENGINEERING↗
DOE OSTI2021

Learning-based approach to plasticity in athermal sheared amorphous packings: Improving softness

The plasticity of amorphous solids undergoing shear is characterized by quasi-localized rearrangements of particles. While many models of plasticity exist, the precise relationship between the plastic dynamics and the structure of a particle’s local environment remains an open question. Previously, machine learning was used to identify a structural predictor of rearrangements called “softness.” Although softness has been shown to predict which particles will rearrange with high accuracy, the method can be difficult to implement in experiments where data are limited and the combinations of descriptors it identifies are often difficult to interpret physically. Here, we address both of these weaknesses, presenting two major improvements to the standard softness method. First, we present a natural representation of each particle’s observed mobility, allowing for the use of statistical models that are both simpler and provide greater accuracy in limited datasets. Second, we employ persistent homology as a systematic means of identifying simple, topologically informed, structural quantities that are easy to interpret and measure experimentally. We test our methods on two-dimensional athermal packings of soft spheres under quasi-static shear. We find that the same structural information that predicts small variations in the response is also predictive of where plastic events will localize. We also find that an excellent accuracy is achieved in athermal sheared packings using simply a particle’s species and the number of nearest neighbor contacts.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Computational thermodynamics and its applications

Thermodynamics is a science concerning the state of a system, whether it is stable, metastable or un- stable, when interacting with the surroundings. In this overview, fundamentals of thermodynamics are briefly reviewed through the combination of first and second laws of thermodynamics for open and nonequilibrium systems to demonstrate that the reversible equilibrium and irreversible nonequilibrium thermodynamics can be integrated to enhance the power and utilities of thermodynamics. The recent progresses in computational thermodynamics, the remaining challenges, and potential impacts in broad scientific fields are discussed here. It is shown that computational thermodynamics enables the modeling of thermodynamics of a state as a function of both external and internal variables and quantitative calculations of a broad range of properties of a multicomponent system in terms of first and second derivatives of energy, including not only equilibrium states when there are no driving forces for any internal processes and but also non-equilibrium states with driving forces for internal processes. Consequently, external constraints such as fixed strain and internal degree of freedoms such as ordering and defects can be described in a coherent framework and applied to materials design. Furthermore, two important but largely overlooked aspects in thermodynamics will be discussed, i.e. the rigorous application of statistical thermodynamics with the probability of configurations and their contributions to system properties, and the applications of second derivatives of energy with respect to either two extensive variables or two potentials or a mixture of them in terms of understanding and predicting emergent behaviors, critical phenomena, kinetic coefficients, and mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tea consumption and risk of bladder cancer in the Bladder Cancer Epidemiology and Nutritional Determinants (BLEND) Study: Pooled analysis of 12 international cohort studies

Tea has been shown to be associated with reduced risk of several diseases including cardiovascular diseases, stroke, metabolic syndrome, and obesity. However, the results on the relationship between tea consumption and bladder cancer are conflicting. This research aimed to assess the association between tea consumption and risk of bladder cancer using a pooled analysis of prospective cohort data. Individual data from 532,949 participants in 12 cohort studies, were pooled for analyses. Cox regression models stratified by study centre was used to estimate hazard ratios (HR) and corresponding 95% CIs. Fractional polynomial regression models were used to examine the dose–response relationship. A higher level of tea consumption was associated with lower risk of bladder cancer incidence (compared with no tea consumption: HR = 0.87, 95% C.I. = 0.77–0.98 for low consumption; HR = 0.86, 95% C.I. = 0.77–0.96 for moderate consumption; HR = 0.84, 95% C.I. = 0.75–0.95 for high consumption). When stratified by sex and smoking status, this reduced risk was statistically significant among men and current and former smokers. In addition, dose–response analyses showed a lower bladder cancer risk with increment of 100 ml of tea consumption per day (HR-increment = 0.97; 95% CI = 0.96–0.98). A similar inverse association was found among males, current and former smokers while never smokers and females showed non-significant results, suggesting potential sex-dependent effect. Higher consumption of tea is associated with reduced risk of bladder cancer with potential interaction with sex and smoking status. Further studies are needed to clarify the mechanisms for a protective effect of tea (e.g. inhibition of the survival and proliferation of cancer cells and anti-inflammatory mechanisms) and its interaction with smoking and sex.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Why it is Unfortunate that Linear Machine Learning “Works” so well in Electromechanical Switching of Ferroelectric Thin Films

Machine learning (ML) is relied on for materials spectroscopy. It is challenging to make ML models fail because statistical correlations can mimic the physics without causality. Here, using a benchmark band-excitation piezoresponse force microscopy polarization spectroscopy (BEPS) dataset the pitfalls of the so-called “better”, “faster”, and “less-biased” ML of electromechanical switching are demonstrated and overcome. Using a toy and real experimental dataset, it is demonstrated how linear nontemporal ML methods result in physically reasonable embedding (eigenvalues) while producing nonsensical eigenvectors and generated spectra, promoting misleading interpretations. A new method of unsupervised multimodal hyperspectral analysis of BEPS is demonstrated using long-short-term memory (LSTM) β-variational autoencoders (β-VAEs) . By including LSTM neurons, the ordinal nature of ferroelectric switching is considered. Further, to improve the interpretability of the latent space, a variational Kullback–Leibler-divergency regularization is imposed . Finally, regularization scheduling of β as a disentanglement metric is leveraged to reduce user bias. Combining these experiment-inspired modifications enables the automated detection of ferroelectric switching mechanisms, including a complex two-step, three-state one. Ultimately, this work provides a robust ML method for the rapid discovery of electromechanical switching mechanisms in ferroelectrics and is applicable to other multimodal hyperspectral materials spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Screening of metal complexes and organic solvents using the COSMOSAC-LANL model to enhance the energy density in a non-aqueous redox flow cell: an insight into the solubility

In this paper, we have proposed a first-principles methodology to screen transition metal complexes against a particular organic solvent and organic solvents against a particular transition metal complex based on their solubility information without the knowledge of heat of fusion and melting temperature. The energy density of a non-aqueous redox flow cell directly depends on the solubility of the redox active species in the non-aqueous medium. Here, we have used the “COSMOSAC-LANL” activity coefficient model which is based on first-principles COSMO calculations where the microscopic information is passed to the macroscopic world via a dielectric continuum solvation model, followed by a post-statistical thermodynamic treatment of the self-consistent properties of the solute particle to calculate the solubility. To model the activity coefficient at infinite dilution for the binary mixtures, a 3-suffix Margules (3sM) function is introduced for the quantitative estimation of the asymmetric interactions and, for the combinatorial term, the Staverman–Guggenheim (SG) form is used. The new activity coefficient model is separately called the “LANL” activity coefficient model. The metal complex and the organic solvent have been treated as a simple binary mixture. The present model has been applied to a set of 14 different organic solvents and 16 different transition metal complexes. Using the new LANL activity coefficient model in combination with the ADF-COSMOSAC-2013 model, we have shown how one can improve the solubility of a transition metal complex in an organic solvent. We applied our model to screen 84 binary mixtures to predict the compatible pair of redox active species and organic solvent to increase the energy density. The solvation mechanism of the transition metal complexes in the organic solvents was obtained using the new model. The results have been compared with the experimental and theoretical results where they are available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Advanced Laboratory and Field Arrays: Debris Modeling, Detection,& Mitigation (Task 1)

The statement of project objectives for this task was: develop tools, methods and models to assess, and mitigate the risk of damage to MHK infrastructure from woody debris. Develop the capability to detect woody debris using sonar and/or physical methods for purposes of characterizing debris statistics in river (at UAF’s Tanana River Test Site) and near-shore wave (at Yakutat, AK) environments and to activate debris mitigation measures. Develop debris impact risk maps and tables using statistics on debris size, geometry, type, prevalence, mobility and location. Improve and apply the COUPi discrete element method (DEM) to develop models of debris movement and impact on MHK infrastructure to evaluate risk of damage, and interference, to operations from debris. The proposed final deliverable for the task was a set of tools or techniques for providing estimates of the probability of debris impact, and resulting impact forces, on MHK infrastructure as a function of debris size, type, wave regime, and current velocity. Such estimates are required to assess damage risks to operational MHK infrastructure.

13 HYDRO ENERGY↗
DOE OSTI2022

Experimental measurements of fluid flow in an 84-pin hexagonal rod bundle with spacer grid for a gas-cooled fast modular reactor

A 50 MW e helium-cooled fast modular reactor (FMR) is under development, and as part of the Department of Energy Integrated Research Project (IRP), Texas A&M University is conducting the thermal-hydraulic characterization of its baseline core configuration. Here, we experimentally investigated the axial and cross flow fields characteristics in the hexagonal fuel rod bundle composed of 84 rods, a central rod, and spacer grids at a Reynolds number of 12,000. A fully transparent experimental facility resembling of one unit of the fuel assembly was constructed. Time-resolved particle image velocimetry (TR-PIV) measurements were performed to characterize hydraulic behavior downstream the spacer grid. Velocity measurements were conducted in the axial and radial direction of the rod bundle. From the PIV velocity vector fields, the full-field flow statistics were computed for the mean velocity, vorticity, and Reynolds stresses. An analysis of the energy decay downstream of the spacer grid was conducted with calculations of secondary-flow intensities, turbulent kinetic energy, power spectrum, and spatial-temporal velocity cross correlations. The vorticity field was obtained and pairs of counter-rotating vortexes were identified using a 3D reconstruction of several measurement planes. The data from this experimental campaign will be used to validate numerical models based on Computational Fluid Dynamics and other codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Time reversal symmetry breaking and odd viscosity in active fluids: Green–Kubo and NEMD results

Active fluids, which are driven at the microscale by non-conservative forces, are known to exhibit novel transport phenomena due to the breaking of time reversal symmetry. Recently, Epstein and Mandadapu [arXiv:1907.10041 (2019)] obtained Green-Kubo relations for the full set of viscous coefficients governing isotropic chiral active fluids, including the so-called odd viscosity, invoking Onsager's regression hypothesis for the decay of fluctuations in active non-equilibrium steady states. In this Communication, we test these Green-Kubo relations using molecular dynamics simulations of a canonical model system consisting of actively torqued dumbbells. We find the resulting odd and shear viscosity values from the Green-Kubo relations to be in good agreement with values measured independently through non-equilibrium molecular dynamics flow simulations. This provides a test of the Green-Kubo relations and lends support to the application of the Onsager regression hypothesis in relation to viscous behaviors of active matter systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Data-Driven Discovery of Active Nematic Hydrodynamics

Active nematics can be modeled using phenomenological continuum theories that account for the dynamics of the nematic director and fluid velocity through partial differential equations (PDEs). While these models provide a statistical description of the experiments, the relevant terms in the PDEs and their parameters are usually identified indirectly. We adapt a recently developed method to automatically identify optimal continuum models for active nematics directly from spatio-temporal data, via sparse regression of the coarse-grained fields onto generic low order PDEs. After extensive benchmarking, we apply the method to experiments with microtubule-based active nematics, finding a surprisingly minimal description of the system. Furthermore, our approach can be generalized to gain insights into active gels, microswimmers, and diverse other experimental active matter systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Fundamental limitations on photoisomerization from thermodynamic resource theories

Small, out-of-equilibrium, and quantum systems defy simple thermodynamic expressions. Such systems are exemplified by molecular switches, which exchange heat with a bath. These molecules can photoisomerize, or change conformation, or switch, on absorbing light. The photoisomerization probability depends on kinetic details that couple the molecule’s energetics to its dissipation. Therefore, a simple, general, thermodynamic-style bound on the photoisomerization probability seems out of reach. We derive such a bound using a resource theory. The resource-theory framework is a set of mathematical tools, developed in quantum information theory, used to generalize thermodynamics to small and quantum settings. From this toolkit has been derived a generalization of the second law, the thermomajorization preorder. We use thermomajorization to upper-bound the photoisomerization probability. Then, we compare the bound with an equilibrium prediction and with a Lindbladian model. We identify a realistic parameter regime in which the Lindbladian evolution saturates the thermomajorization bound. We also quantify the energy coherence in the electronic degree of freedom, and we argue that this coherence cannot promote photoisomerization. Overall, this work illustrates how quantum-information-theoretic thermodynamics can elucidate complex quantum processes in nature, experiments, and synthetics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Tracking atomic structure evolution during directed electron beam induced Si-atom motion in graphene via deep machine learning

Using electron beam manipulation, we enable deterministic motion of individual Si atoms in graphene along predefined trajectories. Structural evolution during the dopant motion was explored, providing information on changes of the Si atom neighborhood during atomic motion and providing statistical information of possible defect configurations. The combination of a Gaussian mixture model and principal component analysis applied to the deep learning-processed experimental data allowed disentangling of the atomic distortions for two different graphene sublattices. This approach demonstrates the potential of e-beam manipulation to create defect libraries of multiple realizations of the same defect and explore the potential of symmetry breaking physics. The rapid image analytics enabled via a deep learning network further empowers instrumentation for e-beam controlled atom-by-atom fabrication. Here, the analysis described in the paper can be reproduced via an interactive Jupyter notebook at https://git.io/JJ3Bx.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

What controls the interannual variation of Hadley cell extent in the Northern Hemisphere: physical mechanism and empirical model for edge variation

Abstract The Hadley circulation is the most prominent atmospheric meridional circulation, reducing the radiatively driven equator-to-pole temperature gradient. While the Hadley cell extent varies by several degrees from year to year, the detailed dynamical mechanisms behind such variations have not been well elucidated. During the expanded phase of the Hadley cell, many regions on the periphery of the subtropics experience unfavorable climatic conditions. In this study, using ERA5 reanalysis data, we examine the physical chain of events responsible for the interannual variation of the Hadley cell edge (HCE) latitude in the Northern Hemisphere. This variation is mainly caused by changing eddy activity and wave breaking from both stationary and transient waves. In particular, we show that transient waves cause the HCE to shift poleward by increasing the eddy momentum flux divergence (EMFD) and reducing the baroclinicity over 20°–40°N, shifting the region of peak baroclinicity poleward. El Niño/La Niña and the Arctic Oscillation (AO) account for a significant portion (60%) of the interannual fluctuation of the HCE latitude. Through the poleward displacement of eddy activity, La Niña and a positive AO state are associated with the poleward shift of the HCE. The analysis of 28 CMIP5 models reveals statistical relationships between EMFD, vertical shear, and HCE latitude similar to those observed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Generalized hydrodynamic analysis of transport through a finite open nanopore for two-component single-file systems

Single-file diffusion (SFD) in finite open nanopores is characterized by nonzero spatially varying tracer diffusion coefficients within a generalized hydrodynamic description. This contrasts with infinite SFD systems where tracer diffusivity vanishes. In standard tracer counterpermeation (TCP) analysis, two reservoirs, each containing a different species, are connected to opposite ends of a finite pore. Here, we implement an extended TCP analysis to allow the two reservoirs to contain slightly different mixtures of the two species. Then, determination of diffusion fluxes through the pore allows extraction of diffusion coefficients for near-constant partial concentrations of the two species. This analysis is applied for a lattice-gas model describing two-component SFD through a finite linear pore represented by a one-dimensional array of cells. Two types of particles, A and B, can hop only to adjacent empty cells with generally different rates, $h_A$ and $h_B$. Particles are noninteracting other than exclusion of multiple cell occupancy. Results reveal generalized hydrodynamic tracer diffusion coefficients which adopt small values inversely proportional to pore length in the pore center, but which are strongly enhanced near pore openings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Modeling iterative reconstruction and displacement field in the large scale structure

The next generation of galaxy surveys like the Dark Energy Spectroscopic Instrument and Euclid will provide datasets orders of magnitude larger than anything available to date. Our ability to model nonlinear effects in late time matter perturbations will be a key to unlock the full potential of these datasets, and the area of initial condition reconstruction is attracting growing attention. Iterative reconstruction developed by Marcel Schmittfull et al. is a technique designed to reconstruct the displacement field from the observed galaxy distribution. The nonlinear displacement field and initial linear density field are highly correlated. Therefore, reconstructing the nonlinear displacement field enables us to extract the primordial cosmological information better than from the late time density field at the level of the two-point statistics. This paper will test to what extent the iterative reconstruction can recover the true displacement field and construct a perturbation theory model for the postreconstructed field. We model the iterative reconstruction process with Lagrangian perturbation theory (LPT) up to third order for dark matter in real space and compare it with N-body simulations. Here we find that the simulated iterative reconstruction does not converge to the nonlinear displacement field, and the discrepancy mainly appears in the shift term, i.e., the term correlated directly with the linear density field. On the contrary, our 3LPT model predicts that the iterative reconstruction should converge to the nonlinear displacement field. We discuss the sources of discrepancy, including numerical noise/artifacts on small scales, and present an ad hoc phenomenological model that improves the agreement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Surface deformation coupled with self-organized pattern on a liquid anode of 1 atm DC glow discharge

Intricate, self-organized plasma structures observed above the surface of a liquid anode of atmospheric DC glow discharge were found to give rise to coherent, organized surface deformation and mechanical wave formation at the plasma–liquid interface. This new phenomenon indicates that the liquid is closely coupled to the plasma by the anode sheath’s electrohydrodynamic (EHD) force. A scientific question then arises: Do surface perturbations, coupled with the nonuniform surface charge distribution, enhance the electric field and induce self-organization? Using the reflective background-oriented schlieren technique, the liquid surface profile under the plasma pattern was measured for the first time. The results show that surface distortions are driven by the repulsive Coulomb force of nonuniform net-negative surface charge acted by the anode sheath field. The impacts of various operating parameters on the patterns and surface waves were examined, revealing the significance of gas heating and liquid charge relaxation time in the pattern formation mechanism. Time-resolved dynamics of a pulsed DC discharge indicated that the surface deformation only appeared after the establishment of plasma patterns. Statistically, the surface wave under the plasma has high wave numbers (8000–16000 m −1 ) and small amplitudes ($<$ 10 µm), generally found in the capillary wave regime. Yet the motion of surface deformations is in tandem with the plasma pattern and exhibits a nondispersive nature of constant phase velocity (0.1–0.4 m s −1 ), suggesting the dominant role of EHD force over the surface tension in the observed surface wave. These results indicate that the deformed liquid surface is driven by the EHD force of the plasma sheath. Although they share a similar geometry, the deformation and wave dynamics of the liquid surface do not stimulate a plasma pattern. Importantly, the complex EHD coupling in the plasma–liquid system raises awareness and new challenges for plasma control engineering, and the quantitative characteristics of the nondispersive surface wave are informative for advancing relevant theory and modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗