Variational Asymptotic Homogenization of Finitely Deformed Viscoelastic-Viscoplastic Composites
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Crustal motions in Alaska are computed by calculating the finite element solution for an elastic spherical shell problem. Very long baseline interferometry and geologic data are used and seem to be in rough agreement.
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Accuracy of biaxial test equipment to examine the nonlinear mechanical behavior of thin sheet specimens of elastomeric materials has been hampered by lack of precise determination of the force distribution along the sides of the specimen. It has been necessary to use an effective width established by approximate means to obtain the stress from the overall force applied along the edges. To avoid this experimental difficulty, individual miniature proof-ring load cells utilizing semiconductor strain gages have been developed and applied to the support hooks for the thin sheet specimens. Typical results are shown for time-dependent stress distributions for all degrees of biaxiality. An accurate evaluation of the effective specimen width is now possible.
A biaxial tester was used to obtain precise biaxial stress responses of highly filled, high strain capability elastomers. Stress-relaxation experiments show that the time-dependent part of the relaxation response can be reasonably approximated by a function which is strain and biaxiality independent. Thus, isochronal data from the stress-relaxation curves can be used to determine the stored energy density function. The complex behavior of the elastomers under biaxial deformation may be caused by dewetting.
We compute crustal motions in Alaska by calculating the finite element solution for an elastic spherical shell problem. The method we use allows the finite element mesh to include faults and very long baseline interferometry (VLBI) baseline rates of change. Boundary conditions include Pacific-North American (PA-NA) plate motions. The solution is constrained by the oblique orientation of the Fairweather-Queen Charlotte strike-slip faults relative to the PA-NA relative motion direction and the oblique orientation from normal convergence of the eastern Aleutian trench fault systems, as well as strike-shp motion along the Denali and Totschunda fault systems. We explore the effects that a range of fault slip constraints and weighting of VLBI rates of change has on the solution. This allows us to test the motion on faults, such as the Denali fault, where there are conflicting reports on its present-day slip rate. We find a pattern of displacements which produce fault motions generally consistent with geologic observations. The motion of the continuum has the general pattern of radial movement of crust to the NE away from the Fairweather-Queen Charlotte fault systems in SE Alaska and Canada. This pattern of crustal motion is absorbed across the Mackenzie Mountains in NW Canada, with strike-slip motion constrained along the Denali and Tintina fault systems. In south central Alaska and the Alaska forearc oblique convergence at the eastern Aleutian trench and the strike-shp motion of the Denali fault system produce a counterclockwise pattern of motion which is partially absorbed along the Contact and related fault systems in southern Alaska and is partially extruded into the Bering Sea and into the forearc parallel the Aleutian trench from the Alaska Peninsula westward. Rates of motion and fault slip are small in western and northern Alaska, but the motions we compute are consistent with the senses of strike-slip motion inferred geologically along the Kaltag, Kobuk Trench, and Thompson Creek faults and with the normal faulting observed in NW Alaska near Nome. The nonrigid behavior of our finite element solution produces patterns of motion that would not have been expected from rigid block models: strike-slip faults can exist in a continuum that has motion mostly perpendicular to their strikes, and faults can exhibit along-strike differences in magnitudes and directions.
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Ductile materials subject to impact loading conditions can undergo spall fracture when an incoming compressive stress wave reflects off interfaces and free surfaces as a tensile stress wave. Experimental observations suggest that in ductile materials, spall fracture is driven by the evolution of porosity. However, the presence of initial porosity in ductile materials also introduces plastic compressibility, which can attenuate the incoming compressive stress wave and, as a result, reduce the amplitude of the reflected tensile stress wave. This, in turn, can mitigate or delay spall fracture. In this work, we report on finite deformation finite element calculations that analyze the response of porous ductile materials subjected to impact loading conditions. Two sets of calculations are carried out, in the first set the material contains initial porosity values ranging from 0% to 5% while in the second set the material also undergoes stress-controlled porosity nucleation. Both sets of calculations are carried out for a wide range of imposed impact velocities. Here, our results show that porosity in ductile materials can, under certain circumstances, mitigate spall fracture by attenuating stress waves. Results correlating the effects of impact velocity, initial porosity, and porosity nucleation on spall fracture are presented and the underlying mechanisms are discussed.
Finite element method applicaions to finite axisymmetric deformations of incompressible elastic solids of revolution
This paper introduces an explicit material point method designed specifically for simulating the micropolar continuum dynamics in the finite deformation and finite microrotation regime. The material point method enables us to simulate large deformation problems while circumventing the potential mesh distortion without remeshing. To eliminate rotational motion damping and loss of angular momentum during the projection, we introduce the mapping for microinertia and angular momentum between particles and grids through the affine particle-in-cell approach. The microrotation and the curvature at each particle are updated through zero-order forward integration of the microgyration and its spatial gradient. We show that the microinertia and the angular momentum are conserved during the projections between particles and grids in our formulation. We verify the formulation and implementation by comparing with the analytical dispersion relation of micropolar waves under the small strain and small microrotation, as well as the analytical soliton solution for solids undergoing large deformation and large microrotation. Additionally we also demonstrate the capacity of the proposed computational framework to handle a wide spectrum of simulations that exhibit size effects in the geometrical nonlinear regime through three representative numerical examples, i.e., a cantilever beam torsion problem, a fragment-impact penetration problem, and a micropolar fluid discharging problem.
Collective modes emerge as the relevant degrees of freedom that govern low-energy excitations of atomic nuclei. These modes—rotations, pairing rotations, and vibrations—are separated in energy from non-collective excitations, making it possible to describe them in the framework of effective field theory. Rotations and pairing rotations are the remnants of Nambu–Goldstone modes from the emergent breaking of rotational symmetry and phase symmetries in finite deformed and finite superfluid nuclei, respectively. The symmetry breaking severely constrains the structure of low-energy Lagrangians and thereby clarifies what is essential and simplifies the description. The approach via effective field theories exposes the essence of nuclear collective excitations and is defined with a breakdown scale in mind. This permits one to make systematic improvements and to estimate and quantify uncertainties. Effective field theories of collective excitations have been used to compute spectra, transition rates, and other matrix elements of interest. In particular, predictions of the nuclear matrix element for neutrinoless double beta decay then come with quantified uncertainties. This review summarizes these results and also compares the approach via effective field theories to well-known models and ab initio computations.
Computer programs are presented which provide incremental finite-element analysis capability for problems of quasi-static, finite, elastoplastic deformation in two spatial dimensions (plane strain, plane stress, axisymmetric). Monotonic or cyclic loading of isotropic hardening materials is considered. The only restriction on the form of the stress-strain curve is that the rate of work hardening exceed some small positive value. The user's guide assumes familiarity with both finite-element analysis and FORTRAN IV programming for the CDC 6600. Sufficient information is provided to support problem solving ultization of the programs.
This work introduces a novel, gradient-free metamaterial design method based on Gaussian process regression to represent the density field of a unit cell. The dimension of the design space is determined by the covariance matrix dimension in the Gaussian process regression. We propose compressing this matrix using an autoencoder, enabling the decoder to generate the density field and effectively reduce the originally large design space to a lower-dimensional subspace. In this compressed space, we employ an active learning method, Bayesian Adaptive Direct Search (BADS), for efficient exploration of the design space. We demonstrate that for simple 2D designs aimed at maximizing unit cell stiffness, our method yields results comparable to those of standard topology optimization. Furthermore, we extend our approach to various mechanical problems, from linear elasticity to hyperelastic large deformation and elasto-plasticity under finite deformation, to 3D metamaterial design. This illustrates the method’s versatility and effectiveness across a range of applications.
Here, we present a machine-learning strategy for finite element analysis of solid mechanics wherein we replace complex portions of a computational domain with a data-driven surrogate. In the proposed strategy, we decompose a computational domain into an “outer” coarse-scale domain that we resolve using a finite element method (FEM) and an “inner” fine-scale domain. We then develop a machine-learned (ML) model for the impact of the inner domain on the outer domain. In essence, for solid mechanics, our machine-learned surrogate performs static condensation of the inner domain degrees of freedom. This is achieved by learning the map from displacements on the inner-outer domain interface boundary to forces contributed by the inner domain to the outer domain on the same interface boundary. We consider two such mappings, one that directly maps from displacements to forces without constraints, and one that maps from displacements to forces by virtue of learning a symmetric positive semi-definite (SPSD) stiffness matrix. We demonstrate, in a simplified setting, that learning an SPSD stiffness matrix results in a coarse-scale problem that is well-posed with a unique solution. We present numerical experiments on several exemplars, ranging from finite deformations of a cube to finite deformations with contact of a fastener-bushing geometry. We demonstrate that enforcing an SPSD stiffness matrix drastically improves the robustness and accuracy of FEM–ML coupled simulations, and that the resulting methods can accurately characterize out-of-sample loading configurations with significant speedups over the standard FEM simulations.