Data-Driven Computing in Dynamics

We formulate extensions to Data Driven Computing for both distance minimizing and entropy maximizing schemes to incorporate time integration. Previous works focused on formulating both types of solvers in the presence of static equilibrium constraints. Here formulations assign data points a variable relevance depending on distance to the solution and on maximum-entropy weighting, with distance minimizing schemes discussed as a special case. The resulting schemes consist of the minimization of a suitably-defined free energy over phase space subject to compatibility and a time-discretized momentum conservation constraint. The present selected numerical tests that establish the convergence properties of both types of Data Driven solvers and solutions.Comment: arXiv admin note: substantial text overlap with arXiv:1702.0157

A multiscattering series for impedance tomography in layered media

We introduce an inversion algorithm for tomographic images of layered media. The algorithm is based on a multiscattering series expansion of the Green function that, unlike the Born series, converges unconditionally. Our inversion algorithm obtains images of the medium that improves iteratively as we use more and more terms in the multiscattering series. We present the derivation of the multiscattering series, formulate the inversion algorithm and demonstrate its performance through numerical experiments

A harmonic/anharmonic energy partition method for lattice statics computations

A method of lattice statics analysis is developed. Consideration of anharmonic effects is restricted to finite regions surrounding lattice defects. All displacements of the crystal are expressed as the effect of unknown forces applied to a perfect harmonic lattice of infinite extent. Displacements are related to the unknown applied forces by means of the Green function of the perfect harmonic lattice, so that equilibrating forces need only be applied to the anharmonic region. The unknown forces are determined so as to maximize the complementary energy of the crystal, which yields a lower bound to the potential energy. The method does not require the explicit enforcement of equilibrium or compatibility conditions across the boundary between the harmonic and anharmonic regions. The performance of the method is assessed on the basis of selected numerical examples. The rate of convergence of the method with increasing domain size is found to be cubic. This is one or two orders of magnitude faster than rigid boundary methods based on the harmonic and continuum solutions, respectively

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

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

Data driven problems in elasticity

We consider a new class of problems in elasticity, referred to as Data-Driven problems, defined on the space of strain-stress field pairs, or phase space. The problem consists of minimizing the distance between a given material data set and the subspace of compatible strain fields and stress fields in equilibrium. We find that the classical solutions are recovered in the case of linear elasticity. We identify conditions for convergence of Data-Driven solutions corresponding to sequences of ap- proximating material data sets. Specialization to constant material data set sequences in turn establishes an appropriate notion of relaxation. We find that relaxation within this Data-Driven framework is fundamentally different from the classical relaxation of energy functions. For instance, we show that in the Data-Driven framework the relaxation of a bistable material leads to material data sets that are not graphs.Comment: Result now covers the two well problem in full generality. Proof simplified. New Figure 9 illustrates geometry of separatio

Morphing surfaces for the control of boundary layer transition

A structure configured to modify its surface morphology between a smooth state and a rough state in response to an applied stress. In demonstrated examples, a soft (PDMS) substrate is produced, and is pre-strained. A relatively stiff overlayer of a metal, such as chromium and gold, is applied to the substrate. When the pre-strained substrate is allowed to relax, the free surface of the stiff overlayer is forced to become distorted, yielding a free surface having a roughness of less than 1 millimeter. Repeated application and removal of the applied stress has been shown to yield reproducible changes in the morphology of the free surface. An application of such morphing free surface is to control a boundary layer transition of an aerodynamic fluid flowing over the surface