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As an art of paper folding, origami has been widely explored by artists for centuries. Only in recent decades has it gained attention from mathematicians and engineers for its complex geometry and rich mechanical properties. The surge of origami-inspired metamaterials has opened a new window for designing materials and structures. Typically, to build origami structures, a sheet of material is folded according to the creaselines that are marked with compliant mechanisms. However, despite their importance in origami fabrication, such compliant mechanisms have been relatively unexplored in the setting of origami metamaterials. In this study, we explore the relationship between the design parameters of compliant mechanisms and origami mechanical properties. In particular, we employ single hinge crease and Kresling origami, representative examples of rigid and non-rigid origami units, fabricated using a double-stitch perforation compliant mechanism design. We conduct axial compression tests using different crease parameters and fit the result into the bar-hinge origami model consisting of axial and torsional springs. We extract the relationship between the spring coefficients and crease parameters using Gaussian process regression. Our result shows that the change in the crease parameter contributes significantly to each spring element in a very different manner, which suggests the fine tunability of the compliant mechanisms depending on the mode of deformation. In particular, the spring stiffness varies with the crease parameter differently for rigid and non-rigid origami, even when the same crease parameter is tuned. Furthermore, we report that the qualitative static response of the Kresling origami can be tuned between monostable and bistable, or linear and nonlinear, by only changing the crease parameter while keeping the same fold pattern geometry. We believe that our compiled result proffers a library and guidelines for choosing compliant mechanisms for the creases of origami mechanical metamaterials. [ABSTRACT FROM AUTHOR]

Coral reef ecosystems support significant biological activities and harbor huge diversity, but they are facing a severe crisis driven by anthropogenic activities and climate change. An important behavioral trait of the coral holobiont is coral motion, which may play an essential role in feeding, competition, reproduction, and thus survival and fitness. Therefore, characterizing coral behavior through motion analysis will aid our understanding of basic biological and physical coral functions. However, tissue motion in the stony scleractinian corals that contribute most to coral reef construction are subtle and may be imperceptible to both the human eye and commonly used imaging techniques. Here we propose and apply a systematic approach to quantify and visualize subtle coral motion across a series of light and dark cycles in the scleractinian coral Montipora capricornis. We use digital image correlation and optical flow techniques to quantify and characterize minute coral motions under different light conditions. In addition, as a visualization tool, motion magnification algorithm magnifies coral motions in different frequencies, which explicitly displays the distinctive dynamic modes of coral movement. Specifically, our assessment of displacement, strain, optical flow, and mode shape quantify coral motion under different light conditions, and they all show that M. capricornis exhibits more active motions at night compared to day. Our approach provides an unprecedented insight into micro-scale coral movement and behavior through macro-scale digital imaging, thus offering a useful empirical toolset for the coral research community. [ABSTRACT FROM AUTHOR]

We studied effects of material anisotropy on impact mitigation in single column woodpile structures. Local vibrations and nonlinear contacts of cylindrical members are key mechanisms of wave modulation in woodpile structures. We numerically obtained wave propagations in single column woodpile structures by changing longitudinal and/or transverse stiffness different from stiffness along the stacking direction. We found that changes in longitudinal and/or transverse stiffness altered wave propagation tendency as well as impact mitigation rate. We observed compact and wide waves propagated through single column woodpile structures with small stiffness ratio, while disintegrated but narrow waves with large stiffness ratio. According to dynamic behavior under impact loadings and frequency responses of woodpiles, bending vibration changed from 3rd to 1st mode and low energy band moved to relatively low frequency region when the single column woodpile structures had small stiffness ratio. This leads to increase impact mitigation characteristics of single column woodpile structures. [ABSTRACT FROM AUTHOR]

In this paper, we present a review of machine health managements for the smart factory. As the Industry 4.0 leads current factory automation and intelligent machines, the machine health management for diagnostic and prognostic purposes are essential, and their importance is getting more significant for the realization of the smart factory in the Industry 4.0. After brief introductions to important concepts and definitions composing smart factory and Industry 4.0, the developments in maintenance strategies towards Prognostics and health management (PHM) of machines are summarized. The review of machine health managements is followed, classifying the references by the monitoring components, types of measurements, as well as PHM tools and algorithms. 94 existing articles are reviewed and summarized in this regard. The implementations of machine health managements within the smart factory are discussed in terms of data connectivity, communications, Cyber-physical system (CPS) and virtual factory, relating them to Internet of things (IoT), cloud computing, and big data management. [ABSTRACT FROM AUTHOR]

We assemble granular chains composed of spheres of uniform diameter in different curved configurations. We study the properties of highly nonlinear solitary waves traveling in the curved channels as a function of the curve angle and of the radius of curvature, using experiments and numerical simulations. We observe that solitary waves propagate robustly even under drastic deflection, such as $$90^{\circ }$$ and $$180^{\circ }$$ turns. When the solitary waves encounter a sharp turn with a radius of curvature as small as one spherical particle's diameter, we report the formation of secondary solitary waves resulting from the interaction with the guiding rail. We compare experimental results with numerical simulations based on a discrete element model that accounts for nonlinear and dissipative interactions between particles. This study demonstrates that granular chains are efficient wave-guides, even in complex geometrical configurations. Moreover, the findings in this study suggest that solitary waves could be used as novel information and/or energy carriers. [ABSTRACT FROM AUTHOR]

We study the stress wave propagation in curved chains of particles (granular crystals) confined by bent elastic guides. We report the frequency- and amplitude-dependent filtering of transmitted waves in relation to various impact conditions and geometrical configurations. The granular crystals studied consist of alternating cylindrical and spherical particles pre-compressed with variable static loads. First, we excite the granular crystals with small-amplitude, broadband perturbations using a piezoelectric actuator to generate oscillatory elastic waves. We find that the linear frequency spectrum of the transmitted waves creates pass- and stop-bands in agreement with the theoretical dispersion relation, demonstrating the frequency-dependent filtering of input excitations through the diatomic granular crystals. Next, we excite high-amplitude nonlinear pulses in the crystals using striker impacts. Experimental tests verify the formation and propagation of highly nonlinear solitary waves that exhibit amplitude-dependent attenuation. We show that the wave propagation can be easily tuned by manipulating the pre-compression imposed to the chain or by varying the initial curvature of the granular chains. We use a combined discrete element (DE) and finite element (FE) numerical model to simulate the propagation of both dispersive linear waves and compactly-supported highly nonlinear waves. We find that the tunable, frequency- and amplitude-dependent filtering of the incoming signals results from the close interplay between the granular particles and the soft elastic media. The findings in this study suggest that hybrid structures composed of granular particles and linear elastic media can be employed as new passive acoustic filtering materials that selectively transmit or mitigate excitations in a desired range of frequencies and amplitudes. [ABSTRACT FROM AUTHOR]

We study the wave propagation in a curved chain of spherical particles constrained by elastic guides under the axial impact of a falling mass. We characterize the force transmission properties of the chain by varying the striker's mass and the chain's curvature. Experimental tests demonstrate amplitude-dependent attenuation of compressive waves propagating through the curved chain. In particular, we observe that the curved systems present an improved transmission of small dynamic disturbances relative to that of strong excitations, resulting from the close interplay between the granular particles and the softer elastic medium. We also find that the transmission of the compressive waves through the chains is dependent on the initial curvature imposed to the system. Numerical simulations, based on an approach that combines discrete element and finite element methods, corroborate the experimental results. The findings suggest that hybrid structures composed of granular particles and linear elastic media can be employed as new passive acoustic filtering materials that selectively transmit or mitigate excitations in a desired range of pressure amplitudes. [ABSTRACT FROM AUTHOR]

Advances in machine learning have revolutionized capabilities in applications ranging from natural language processing to marketing to health care. Recently, machine learning techniques have also been employed to learn physics, but one of the formidable challenges is to predict complex dynamics, particularly chaos. Here, we demonstrate the efficacy of quasi-recurrent neural networks in predicting extremely chaotic behavior in multistable origami structures. While machine learning is often viewed as a "black box", we conduct hidden layer analysis to understand how the neural network can process not only periodic, but also chaotic data in an accurate manner. Our approach shows its effectiveness in characterizing and predicting chaotic dynamics in a noisy environment of vibrations without relying on a mathematical model of origami systems. Therefore, our method is fully data-driven and has the potential to be used for complex scenarios, such as the nonlinear dynamics of thin-walled structures and biological membrane systems. Predicting chaotic behaviour is challenging due to the sensitivity to initial conditions, noise, the environment, and unknown factors. Here, the authors apply quasi-recurrent neural networks to predict both periodic and chaotic dynamics of the triangulated cylindrical origami cells, and provide an analysis of the hidden units' distinctive responses. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

The original version of this Article contained an error in second sentence of the Acknowledgements, which incorrectly read ‘J.Y. and P.G.K. also acknowledge support from US-ARO (W911NF-15-1-0604) and US-AFOSR (FA9550-17-1-011), and P.G.K. also gratefully acknowledges support from the Stavros Niarchos Foundation via the Greek Diaspora Fellowship Program.’ The correct version states ‘US-AFOSR (FA9550-17-1-0114)’ in place of ‘US-AFOSR (FA9550-17-1-011)’. This has been corrected in both the PDF and HTML versions of the Article. [ABSTRACT FROM AUTHOR]

Energy transport properties in heterogeneous materials have attracted scientific interest for more than half of a century, and they continue to offer fundamental and rich questions. One of the outstanding challenges is to extend Anderson theory for uncorrelated and fully disordered lattices in condensed-matter systems to physical settings in which additional effects compete with disorder. Here we present the first systematic experimental study of energy transport and localization properties in simultaneously disordered and nonlinear granular crystals. In line with prior theoretical studies, we observe in our experiments that disorder and nonlinearity—which individually favor energy localization—can effectively cancel each other out, resulting in the destruction of wave localization. We also show that the combined effect of disorder and nonlinearity can enable manipulation of energy transport speed in granular crystals. Specifically, we experimentally demonstrate superdiffusive transport. Furthermore, our numerical computations suggest that subdiffusive transport should be attainable by controlling the strength of the system’s external precompression force. Wave propagation is often nonlinear in character, yet the interplay between disorder and nonlinearity remains elusive. Kim et al. use experiments and corroborating numerical simulations to investigate this phenomenon and demonstrate superdiffusive energy transport in disordered granular chains. [ABSTRACT FROM AUTHOR]