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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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A method is proposed for analytical determination of the normal machining force in grinding by elastic abrasive wheels. The method takes into account that abrasive wheels with elastoviscous properties cannot completely recover their shape within a single rotation.
Abstract In this paper, a hybrid Lagrangian–Eulerian topology optimization (LETO) method is proposed to solve the elastic force equilibrium with the Material Point Method (MPM). LETO transfers density information from freely movable Lagrangian carrier particles to a fixed set of Eulerian quadrature points. This transfer is based on a smooth radial kernel involved in the compliance objective to avoid the artificial checkerboard pattern. The quadrature points act as MPM particles embedded in a lower‐resolution grid and enable a subcell multidensity resolution of intricate structures with a reduced computational cost. A quadrature‐level connectivity graph‐based method is adopted to avoid the artificial checkerboard issues commonly existing in multiresolution topology optimization methods. Numerical experiments are provided to demonstrate the efficacy of the proposed approach.
The crystal nucleation from liquid in most cases is too rare to be accessed within the limited time scales of the conventional molecular dynamics (MD) simulation. Here, we developed a “persistent embryo” method to facilitate crystal nucleation in MD simulations by preventing small crystal embryos from melting using external spring forces. We applied this method to the pure Ni case for a moderate undercooling where no nucleation can be observed in the conventional MD simulation, and obtained nucleation rate in good agreement with the experimental data. Moreover, the method is applied to simulate an even more sluggish event: the nucleation of the B2 phase in a strong glass-forming Cu-Zr alloy. The nucleation rate was found to be 8 orders of magnitude smaller than Ni at the same undercooling, which well explains the good glass formability of the alloy. In conclusion, our work opens a new avenue to study solidification under realistic experimental conditions via atomistic computer simulation.
The results of an experimental study of the modification of probes for critical-dimension atomicforce microscopy (CD-AFM) by the deposition of carbon nanotubes (CNTs) to improve the accuracy with which the surface roughness of vertical walls is determined in submicrometer structures are presented. Methods of the deposition of an individual CNT onto the tip of an AFM probe via mechanical and electrostatic interaction between the probe and an array of vertically aligned carbon nanotubes (VACNTs) are studied. It is shown that, when the distance between the AFM tip and a VACNT array is 1 nm and the applied voltage is within the range 20–30 V, an individual carbon nanotube is deposited onto the tip. On the basis of the results obtained in the study, a probe with a carbon nanotube on its tip (CNT probe) with a radius of 7 nm and an aspect ratio of 1:15 is formed. Analysis of the CNT probe demonstrates that its use improves the resolution and accuracy of AFM measurements, compared with the commercial probe, and also makes it possible to determine the roughness of the vertical walls of high-aspect structures by CD-AFM. The results obtained can be used to develop technological processes for the fabrication and reconditioning of special AFM probes, including those for CD-AFM, and procedures for the interoperational express monitoring of technological process parameters in the manufacturing of elements for micro- and nanoelectronics and micro- and nanosystem engineering.
A method for visualization via atomic-force microscopy of the internal structure of photoactive layers of polymer solar cells using an ultramicrotome for photoactive layer cutting is proposed and applied. The method creates an opportunity to take advantage of atomic-force microscopy in structural investigations of the bulk of soft samples. Such advantages of atomic-force microscopy include a high contrast and the ability to measure various surface properties at nanometer resolution. Using the proposed method, samples of the photoactive layer of polymer solar cells based on a mixture of PTB7 polythiophene and PC{sub 71}BM fullerene derivatives are studied. The disclosed details of the bulk structure of this mixture allow us to draw additional conclusions about the effect of morphology on the efficiency of organic solar cells.
Abstract—A possibility of changing the magnetic type structure of multilayer CoPt films under action of the magnetic field of the atomic force microscope probe is demonstrated. A new method of non-contact magnetic-force measurements based on artificial increase in the electrostatic interaction between the probe and the film is proposed. This method enables one to controllably change the distance between a probe and a film, thus changing the strength of the magnetic interaction. Using it, one can create from a uniformly magnetized state both a labyrinth domain structure and isolated domains, which are apparently magnetic skyrmions.
Disclosed here is a three-dimensional electronic scaffold, comprising a porous scaffold and a plurality of micro-strain gauges distributed spatially inside the porous scaffold, wherein the micro-strain gauges are adapted to detect contraction force. Also disclosed is a method comprising detecting and mapping intra-tissue cardiac contraction force of one or more cardiac cells or tissues disposed in a three-dimensional electronic scaffold, wherein the three-dimensional electronic scaffold comprises a porous scaffold and a plurality of micro-strain gauges distributed spatially inside the porous scaffold and in contact with the cardiac cells or tissues, and wherein the micro-strain gauges are adapted to detect contraction force of the cardiac cells or tissues.
Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We explore the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.
Hair cell mechanotransduction happens in tens of microseconds, involves forces of a few picoNewtons, and is mediated by nanometer-scale molecular conformational changes. As proteins involved in this process become identified and their high resolution structures become available, multiple tools are being used to explore their “single-molecule responses” to force. Optical tweezers and atomic force microscopy offer exquisite force and extension resolution, but cannot reach the high loading rates expected for high frequency auditory stimuli. Molecular dynamics (MD) simulations can reach these fast time scales, and also provide a unique view of the molecular events underlying protein mechanics, but its predictions must be experimentally verified. Thus a combination of simulations and experiments might be appropriate to study the molecular mechanics of hearing. Here I review the basics of MD simulations and the different methods used to apply force and study protein mechanics in silico. Simulations of tip link proteins are used to illustrate the advantages and limitations of this method.
The adjoint method for the study of runaway electron dynamics in momentum space Liu et al (2016 Phys. Plasmas 23 010702) is rederived using the Green's function method, for both the runaway probability function (RPF) and the expected loss time (ELT). The RPF and ELT obtained using the adjoint method are presented, both with and without the synchrotron radiation reaction force. In conclusion, the adjoint method is then applied to study the runaway electron avalanche. Both the critical electric field and the growth rate for the avalanche are calculated using this fast and novel approach.
We propose a Dynamical generalized Polynomial Chaos (DgPC) method to solve time-dependent stochastic partial differential equations (SPDEs) with white noise forcing. The long-time simulation of SPDE solutions by Polynomial Chaos (PC) methods is notoriously difficult as the dimension of the stochastic variables increases linearly with time. Exploiting the Markovian property of white noise, DgPC implements a restart procedure that allows us to expand solutions at future times in terms of orthogonal polynomials of the measure describing the solution at a given time and the future white noise. The dimension of the representation is kept minimal by application of a Karhunen–Loeve (KL) expansion. Using frequent restarts and low degree polynomials on sparse multi-index sets, the method allows us to perform long time simulations, including the calculation of invariant measures for systems which possess one. We apply the method to the numerical simulation of stochastic Burgers and Navier–Stokes equations with white noise forcing. Our method also allows us to incorporate time-independent random coefficients such as a random viscosity. We propose several numerical simulations and show that the algorithm compares favorably with standard Monte Carlo methods.
Purpose: The advent of magnetic resonance imaging (MRI) guided radiotherapy systems demands the incorporation of the magnetic field into dose calculation algorithms of treatment planning systems. This is due to the fact that the Lorentz force of the magnetic field perturbs the path of the relativistic electrons, hence altering the dose deposited by them. Building on the previous work, the authors have developed a discontinuous finite element space-angle treatment of the linear Boltzmann transport equation to accurately account for the effects of magnetic fields on radiotherapy doses. Methods: The authors present a detailed description of their new formalism and compare its accuracy to GEANT4 Monte Carlo calculations for magnetic fields parallel and perpendicular to the radiation beam at field strengths of 0.5 and 3 T for an inhomogeneous 3D slab geometry phantom comprising water, bone, and air or lung. The accuracy of the authors’ new formalism was determined using a gamma analysis with a 2%/2 mm criterion. Results: Greater than 98.9% of all points analyzed passed the 2%/2 mm gamma criterion for the field strengths and orientations tested. The authors have benchmarked their new formalism against Monte Carlo in a challenging radiation transport problem with a high density material (bone) directly adjacent to a very low density material (dry air at STP) where the effects of the magnetic field dominate collisions. Conclusions: A discontinuous finite element space-angle approach has been proven to be an accurate method for solving the linear Boltzmann transport equation with magnetic fields for cases relevant to MRI guided radiotherapy. The authors have validated the accuracy of this novel technique against GEANT4, even in cases of strong magnetic field strengths and low density air.
A method for measuring the thickness of block-structured films by atomic-force microscopy and selective chemical etching is proposed. The method is tested for thin bismuth films formed on mica by thermal evaporation in vacuum.
The Coriolis force is a significant source of systematic phase errors and dephasing in atom interferometry and is often compensated by counter-rotating the interferometry laser beam against Earth's rotation. We present a novel method for performing Coriolis force compensation for long-baseline atom interferometry, which mitigates atom-beam misalignment due to beam rotation, an effect which is magnified by the long lever arm of the baseline length. The method involves adjustment of the angle of the interferometer beam prior to a magnifying telescope, enabling the beam to pivot around a tunable position along the interferometer baseline. By tuning the initial atom kinematics and adjusting the angle with which the interferometer beam pivots about this point, we can ensure that the atoms align with the center of the beam during the atom optics laser pulses. This approach will be used in the MAGIS-100 atom interferometer and could also be applied to other long-baseline atom interferometers. An additional challenge associated with long baseline interferometry is that since long-baseline atom interferometers are often located outside of typical laboratory environments, facilities constraints may require lasers to be housed in a climate-controlled room a significant distance away from the main experiment. Nonlinear effects in optical fibers restrict the use of fiber-based transport of the high-power interferometry beam from the laser room to the experiment. We present the design of and prototype data from a laser transport system for MAGIS-100 that maintains robustness against alignment drifts despite the absence of a long fiber.
The effects of small-scale topography-induced land surface heterogeneity are not well represented in current Earth System Models (ESMs). In this study, a new topography-based subgrid structure referred to as topographic units (TGU) designed to better capture subgrid topographic effects, and methods to downscale atmospheric forcing to the land TGUs have been implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). Effects of the subgrid scheme and downscaling methods on ELM simulated land surface processes are evaluated over the conterminous United States (CONUS). For this purpose, ELM simulations are performed using two configurations without (NoD ELM) and with (D ELM) downscaling, both using TGUs derived for the 0.5-degree grids and the same land surface parameters. Simulations using the two ELM configurations are compared over the CONUS domain, regional levels, and at observational sites (e.g., SNOTEL). The CONUS-level results suggest that D ELM simulates more snowfall and snow water equivalent (SWE), higher runoff, and less ET during spring and summer. Regional-level results suggest more pronounced impacts of downscaling over regions dominated by higher elevation TGUs and regions with maximum precipitation occurring during cool seasons. Results at the SNOTEL sites suggest that D ELM has superior capability of reproducing the observed SWE at 83% of the sites, with more pronounced performance over topographically heterogeneous TGUs with their maximum precipitation occurring during cool seasons. The results highlight the importance of improving representation of small-scale surface heterogeneity in ESMs and motivate future research to understand their effects on land-atmosphere interactions, streamflow, and water resources management over mountainous regions.
Density functional tight binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard density functional theory (DFT) approaches. However, DFTB models can be challenging to determine for individual systems of interest, especially for metallic and interfacial systems where different bonding arrangements can lead to significant changes in electronic states. In this regard, we have created a rapid-screening approach for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. Our method leverages a recent reactive molecular dynamics force field where many-body interactions are represented by linear combinations of Chebyshev polynomials. This allows for the efficient creation of multi-center representations with relative ease, requiring only a small investment in initial DFT calculations. Here, we have focused our workflow on TiH 2 as a model system and show that a relatively small training set based on unit-cell-sized calculations yields a model accurate for both bulk and surface properties. Our approach is easy to implement and can yield reliable DFTB models over a broad range of thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.
The J-integral vs. crack growth resistance curve (J-R curve) is a useful tool for evaluating material fracture toughness in the ductile condition. A widely accepted practice for conducting tests to obtain J-R curves is ASTM standard E1820, in which the normalization method was introduced as an alternative method for determining the J-R curve. The normalization method requires solely force-displacement data, together with initial and final crack size measurements from a specimen to derive the J-R curve. Because of the elimination of the compliance measurement, the normalization method significantly simplifies testing requirements to obtain J-R curve. Despite these advantages, the analysis procedures of the normalization method are quite complicated to follow, which may limit the wide application of this method. To address this, we have developed a software with user-friendly graphic interface to perform automated normalization analysis. Any users, even without detailed knowledge of the normalization analysis, can use this software to derive J-R curves based on the ASTM E1820 normalization method.
This paper presents mathematical formulations and methods to predict the effect of forced-flight variance reduction on Monte Carlo tally variance and calculation time. This includes deducing biasing operators that are then used to construct a history-score probability density function (HSPDF), which represents all possible Monte Carlo random walks and gives the probability of a Monte Carlo history scoring in a tally from a particular phase-space position. The history-score moment equations (HSMEs), the statistical moments of the HSPDF, are then derived to calculate the statistical behavior of the Monte Carlo tally when forced-flight variance reduction is applied. In addition, the future-time equation (FTE) is derived to predict the Monte Carlo computational time as a result of applying forced-flight variance reduction. The solutions of the HSMEs and FTE can be used to predict Monte Carlo computational cost. Furthermore, this work also describes a discrete ordinates method to solve the forced-flight HSMEs and FTE. Several 1-D and 2-D test problems verify that the derivations are performed and implemented correctly.