7,664 research outputs found

    Modeling dislocation sources and size effects at initial yield in continuum plasticity

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    Size effects at initial yield (prior to stage II) of idealized micron-sized specimens are modeled within a continuum model of plasticity. Two different aspects are considered: specification of a density of dislocation sources that represent the emission of dislocation dipoles, and the presence of an initial, spatially inhomogeneous excess dislocation content. Discreteness of the source distribution appears to lead to a stochastic response in stress-strain curves, with the stochasticity diminishing as the number of sources increases. Variability in stress-strain response due to variations of source distribution is also shown. These size effects at initial yield are inferred to be due to physical length scales in dislocation mobility and the discrete description of sources that induce internal-stress-related effects, and not due to length-scale effects in the mean-field strain-hardening response (as represented through a constitutive equation)

    Novel anisotropic continuum-discrete damage model capable of representing localized failure of massive structures. Part II: identification from tests under heterogeneous stress field

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    In Part I of this paper we have presented a simple model capable of describing the localized failure of a massive structure. In this part, we discuss the identification of the model parameters from two kinds of experiments: a uniaxial tensile test and a three-point bending test. The former is used only for illustration of material parameter response dependence, and we focus mostly upon the latter, discussing the inverse optimization problem for which the specimen is subjected to a heterogeneous stress field.Comment: 18 pages, 12 figures, 6 table

    Lensing reconstruction from line intensity maps: the impact of gravitational nonlinearity

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    We investigate the detection prospects for gravitational lensing of three-dimensional maps from upcoming line intensity surveys, focusing in particular on the impact of gravitational nonlinearities on standard quadratic lensing estimators. Using perturbation theory, we show that these nonlinearities can provide a significant contaminant to lensing reconstruction, even for observations at reionization-era redshifts. However, we show how this contamination can be mitigated with the use of a "bias-hardened" estimator. Along the way, we present an estimator for reconstructing long-wavelength density modes, in the spirit of the "tidal reconstruction" technique that has been proposed elsewhere, and discuss the dominant biases on this estimator. After applying bias-hardening, we find that a detection of the lensing potential power spectrum will still be challenging for the first phase of SKA-Low, CHIME, and HIRAX, with gravitational nonlinearities decreasing the signal to noise by a factor of a few compared to forecasts that ignore these effects. On the other hand, cross-correlations between lensing and galaxy clustering or cosmic shear from a large photometric survey look promising, provided that systematics can be sufficiently controlled. We reach similar conclusions for a single-dish survey inspired by CII measurements planned for CCAT-prime, suggesting that lensing is an interesting science target not just for 21cm surveys, but also for intensity maps of other lines.Comment: 40+18 pages, 13 figures, 5 tables. v2: JCAP published version, with typos fixed and clarifications adde

    Concurrent Multiscale Computing of Deformation Microstructure by Relaxation and Local Enrichment with Application to Single-Crystal Plasticity

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    This paper is concerned with the effective modeling of deformation microstructures within a concurrent multiscale computing framework. We present a rigorous formulation of concurrent multiscale computing based on relaxation; we establish the connection between concurrent multiscale computing and enhanced-strain elements; and we illustrate the approach in an important area of application, namely, single-crystal plasticity, for which the explicit relaxation of the problem is derived analytically. This example demonstrates the vast effect of microstructure formation on the macroscopic behavior of the sample, e.g., on the force/travel curve of a rigid indentor. Thus, whereas the unrelaxed model results in an overly stiff response, the relaxed model exhibits a proper limit load, as expected. Our numerical examples additionally illustrate that ad hoc element enhancements, e.g., based on polynomial, trigonometric, or similar representations, are unlikely to result in any significant relaxation in general

    On-the-fly adaptivity for nonlinear twoscale simulations using artificial neural networks and reduced order modeling

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    A multi-fidelity surrogate model for highly nonlinear multiscale problems is proposed. It is based on the introduction of two different surrogate models and an adaptive on-the-fly switching. The two concurrent surrogates are built incrementally starting from a moderate set of evaluations of the full order model. Therefore, a reduced order model (ROM) is generated. Using a hybrid ROM-preconditioned FE solver, additional effective stress-strain data is simulated while the number of samples is kept to a moderate level by using a dedicated and physics-guided sampling technique. Machine learning (ML) is subsequently used to build the second surrogate by means of artificial neural networks (ANN). Different ANN architectures are explored and the features used as inputs of the ANN are fine tuned in order to improve the overall quality of the ML model. Additional ANN surrogates for the stress errors are generated. Therefore, conservative design guidelines for error surrogates are presented by adapting the loss functions of the ANN training in pure regression or pure classification settings. The error surrogates can be used as quality indicators in order to adaptively select the appropriate -- i.e. efficient yet accurate -- surrogate. Two strategies for the on-the-fly switching are investigated and a practicable and robust algorithm is proposed that eliminates relevant technical difficulties attributed to model switching. The provided algorithms and ANN design guidelines can easily be adopted for different problem settings and, thereby, they enable generalization of the used machine learning techniques for a wide range of applications. The resulting hybrid surrogate is employed in challenging multilevel FE simulations for a three-phase composite with pseudo-plastic micro-constituents. Numerical examples highlight the performance of the proposed approach

    Size effects and idealized dislocation microstructure at small scales: predictions of a phenomenological model of Mesoscopic Field Dislocation Mechanics: Part I

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    A Phenomenological Mesoscopic Field Dislocation Mechanics (PMFDM) model is developed, extending continuum plasticity theory for studying initial-boundary value problems of small-scale plasticity. PMFDM results from an elementary space-time averaging of the equations of Field Dislocation Mechanics (FDM), followed by a closure assumption from any strain-gradient plasticity model that attempts to model effects of geometrically-necessary dislocations (GND) only in work-hardening

    The 1999 Center for Simulation of Dynamic Response in Materials Annual Technical Report

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    Introduction: This annual report describes research accomplishments for FY 99 of the Center for Simulation of Dynamic Response of Materials. The Center is constructing a virtual shock physics facility in which the full three dimensional response of a variety of target materials can be computed for a wide range of compressive, ten- sional, and shear loadings, including those produced by detonation of energetic materials. The goals are to facilitate computation of a variety of experiments in which strong shock and detonation waves are made to impinge on targets consisting of various combinations of materials, compute the subsequent dy- namic response of the target materials, and validate these computations against experimental data

    Klein-Nishina Effects in the Spectra of Non-Thermal Sources Immersed in External Radiation Fields

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    We study Klein-Nishina (KN) effects in the spectrum produced by a steady state, non-thermal source where rapidly accelerated electrons cool by emitting synchrotron radiation and Compton upscattering ambient photons produced outside the source. We focus on the case where the radiation density inside the source exceeds that of the magnetic field. We show that the KN reduction in the electron Compton cooling rate causes the steady-state electron spectrum to harden at energies above \gamma_{KN}, where \gamma_{KN}= 1/4\epsilon_0 and \epsilon_0=h\nu_0/m_ec^2 is the characteristic ambient photon energy. The source synchrotron spectrum thus shows a high-energy ``bump'' or excess even though the electron acceleration spectrum has no such excess. In contrast, the low-energy Compton gamma-ray spectrum shows little distortion because the electron hardening compensates for the KN decline in the scattering rate. For sufficiently high electron energies, however, Compton cooling becomes so inefficient that synchrotron cooling dominates -- an effect omitted in most previous studies. The hardening of the electron distribution thus stops, leading to a rapid decline in Compton gamma-ray emission, i.e., a strong spectral break whose location does not depend on the maximum electron energy. This break can limit the importance of Compton gamma-ray pair production on ambient photons and implies that a source's synchrotron luminosity may exceed its Compton luminosity even though the source magnetic field energy density is smaller than the ambient radiation energy density. We discuss the importance of these KN effects in blazars, micro-quasars, and pulsar binaries.Comment: 36 pages, 10 figures. MNRAS LaTeX. Abtract slightly shortened. Submitted to Monthly Notice
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