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Concrete features significant microstructural heterogeneity which affects its mechanical behavior. Strain localization in the matrix phase of concrete has received significant attention due to its relation to microcracking and our ability to quantify it with X-ray computed tomography (XRCT). In contrast, stresses in sand and aggregates remain largely unmeasured but remain critical for micromechanics-based theories of failure. Here, we use a combination of in-situ XRCT, 3D X-ray diffraction (3DXRD), and scanning 3DXRD to directly measure strain and stress within sand grains in two samples of mortar containing different sand volume fractions. Our results reveal that, in contrast to inclusion theories from continuum micromechanics, aggregates feature a broad distribution of average stresses and significant gradients in their internal stress fields. Our work furnishes the first known dataset with these quantitative stress measurements and motivates improvements in micromechanics models for concrete which can capture stress heterogeneity. 

We consider a Fermi–Pasta–Ulam–Tsingou lattice with randomly varying coefficients. We discover a relatively simple condition which when placed on the nature of the randomness allows us to prove that small amplitude/long wavelength solutions are almost surely rigorously approximated by solutions of Korteweg–de Vries equations for very long times. The key ideas combine energy estimates with homogenization theory and the technical proof requires a novel application of autoregressive processes. 

We present a torsion pendulum dual oscillator sensor designed toward the direct detection of Newtonian noise. We discuss the sensitivity limitations of the system, experimental performance characterization results, and prospectives to improve performance. The sensor is being developed to contribute to the mitigation of Newtonian noise impacts in the sensitivities of next generation terrestrial gravitational-wave detectors. 

We consider a linear Fermi-Pasta-Ulam-Tsingou lattice with random spatially varying material coefficients. Using the methods of stochastic homogenization we show that solutions with long wave initial data converge in an appropriate sense to solutions of a wave equation. The convergence is strong and both almost sure and in expectation, but the rate is quite slow. The technique combines energy estimates with powerful classical results about random walks, specifically the law of the iterated logarithm.