214 research outputs found

    Harnessing Geometric Frustration to Form Band Gaps in Acoustic Channel Lattices

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    We demonstrate both numerically and experimentally that geometric frustration in two-dimensional periodic acoustic networks consisting of arrays of narrow air channels can be harnessed to form band gaps (ranges of frequency in which the waves cannot propagate in any direction through the system). While resonant standing wave modes and interferences are ubiquitous in all the analyzed network geometries, we show that they give rise to band gaps only in the geometrically frustrated ones (i.e. those comprising of triangles and pentagons). Our results not only reveal a new mechanism based on geometric frustration to suppress the propagation of pressure waves in specific frequency ranges, but also opens avenues for the design of a new generation of smart systems that control and manipulate sound and vibrations

    Evolving Connectivity for Recurrent Spiking Neural Networks

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    Recurrent spiking neural networks (RSNNs) hold great potential for advancing artificial general intelligence, as they draw inspiration from the biological nervous system and show promise in modeling complex dynamics. However, the widely-used surrogate gradient-based training methods for RSNNs are inherently inaccurate and unfriendly to neuromorphic hardware. To address these limitations, we propose the evolving connectivity (EC) framework, an inference-only method for training RSNNs. The EC framework reformulates weight-tuning as a search into parameterized connection probability distributions, and employs Natural Evolution Strategies (NES) for optimizing these distributions. Our EC framework circumvents the need for gradients and features hardware-friendly characteristics, including sparse boolean connections and high scalability. We evaluate EC on a series of standard robotic locomotion tasks, where it achieves comparable performance with deep neural networks and outperforms gradient-trained RSNNs, even solving the complex 17-DoF humanoid task. Additionally, the EC framework demonstrates a two to three fold speedup in efficiency compared to directly evolving parameters. By providing a performant and hardware-friendly alternative, the EC framework lays the groundwork for further energy-efficient applications of RSNNs and advances the development of neuromorphic devices

    Consolidation considering clogging

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    In land reclamation projects, the vacuum preloading method has been widely used to strengthen dredged fills by removing water. However, during the improvement process, clogging inevitably occurs in the drains and soils, hindering water drainage and causing inhomogeneous consolidation results. Therefore, it is essential to evaluate the effect of clogging on the consolidation behavior of dredged slurry at different radii. In this study, analytical solutions are derived under an uneven strain assumption to calculate the consolidation in the clogging zone and the normal zone, with time-dependent discharge capacity and clogging in the soil considered. Results calculated by the proposed solutions indicated that the clogging effect slows down the development of consolidation, reduces the final consolidation degree, and increases the difference between consolidations at different radii. It is found that the influence of the clogging effect's varies with the speed of the discharge capacity decay, the value of the initial discharge capacity of the drain, the permeability, and the radius of the clogging zone. Finally, a practical application of the proposed solution is discussed, and the proposed solution is suggested for the calculation of consolidation when treating high-water-content slurry

    High strength mullite-bond SiC porous ceramics fabricated by digital light processing

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    Fabricating SiC ceramics via the digital light processing (DLP) technology is of great challenge due to strong light absorption and high refractive index of deep-colored SiC powders, which highly differ from those of resin, and thus significantly affect the curing performance of the photosensitive SiC slurry. In this paper, a thin silicon oxide (SiO2) layer was in-situ formed on the surface of SiC powders by pre-oxidation treatment. This method was proven to effectively improve the curing ability of SiC slurry. The SiC photosensitive slurry was fabricated with solid content of 55 vol% and viscosity of 7.77 Pa s (shear rate of 30 s-1). The curing thickness was 50 μm with exposure time of only 5 s. Then, a well-designed sintering additive was added to completely convert low-strength SiO2 into mullite reinforcement during sintering. Complexshaped mullite-bond SiC ceramics were successfully fabricated. The flexural strength of SiC ceramics sintered at 1550 °C in air reached 97.6 MPa with porosity of 39.2 vol%, as high as those prepared by spark plasma sintering (SPS) techniques.</p

    Anomalous crystalline ordering of particles in a viscoelastic fluid under high shear

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    Addition of particles to a viscoelastic suspension dramatically alters the properties of the mixture, particularly when it is sheared or otherwise processed. Shear-induced stretching of the polymers results in elastic stress that causes a substantial increase in measured viscosity with increasing shear, and an attractive interaction between particles, leading to their chaining. At even higher shear rates, the flow becomes unstable, even in the absence of particles. This instability makes it very difficult to determine the properties of a particle suspension. Here we use a fully immersed parallel plate geometry to measure the high-shear-rate behavior of a suspension of particles in a viscoelastic fluid. We find an unexpected separation of the particles within the suspension resulting in the formation of a layer of particles in the center of the cell. Remarkably, monodisperse particles form a crystalline layer which dramatically alters the shear instability. By combining measurements of the velocity field and torque fluctuations, we show that this solid layer disrupts the flow instability and introduces a new, single-frequency component to the torque fluctuations that reflects a dominant velocity pattern in the flow. These results highlight the interplay between particles and a suspending viscoelastic fluid at very high shear rates.Comment: SI Videos and future data sharing are available at https://doi.org/10.7910/DVN/K0XZ6
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