Hypocrystalline ceramic aerogels for thermal insulation at extreme conditions.

Thermal insulation under extreme conditions requires materials that can withstand complex thermomechanical stress and retain excellent thermal insulation properties at temperatures exceeding 1,000 degrees Celsius1-3. Ceramic aerogels are attractive thermal insulating materials; however, at very high temperatures, they often show considerably increased thermal conductivity and limited thermomechanical stability that can lead to catastrophic failure4-6. Here we report a multiscale design of hypocrystalline zircon nanofibrous aerogels with a zig-zag architecture that leads to exceptional thermomechanical stability and ultralow thermal conductivity at high temperatures. The aerogels show a near-zero Poisson's ratio (3.3 × 10-4) and a near-zero thermal expansion coefficient (1.2 × 10-7 per degree Celsius), which ensures excellent structural flexibility and thermomechanical properties. They show high thermal stability with ultralow strength degradation (less than 1 per cent) after sharp thermal shocks, and a high working temperature (up to 1,300 degrees Celsius). By deliberately entrapping residue carbon species in the constituent hypocrystalline zircon fibres, we substantially reduce the thermal radiation heat transfer and achieve one of the lowest high-temperature thermal conductivities among ceramic aerogels so far-104 milliwatts per metre per kelvin at 1,000 degrees Celsius. The combined thermomechanical and thermal insulating properties offer an attractive material system for robust thermal insulation under extreme conditions.

Discovering time-varying aerodynamics of a prototype bridge by sparse identification of nonlinear dynamical systems.

Vortex-induced vibrations (VIVs) have been observed on a long-span suspension bridge. The nonstationary wind in the field characterized by the time-varying mean wind speed is likely to lead to time-varying aerodynamics of the wind-bridge system during VIVs, which is different from VIVs induced by stationary or even steady wind in wind tunnels. In this paper, data-driven methods are proposed to reveal the time-varying aerodynamics of the wind-bridge system during VIV events based on field measurements on a long-span suspension bridge. First, a variant of the sparse identification of nonlinear dynamics algorithm is proposed to identify parsimonious, time-varying aerodynamical systems that capture VIV events of the bridge. Thus we are able to posit new, data-driven, and interpretable models highlighting the aeroelastic interactions between the wind and bridge. Second, a density-based clustering algorithm is applied to discovering the potential modes of dynamics during VIV events. As a result, the time-dependent model is obtained to reveal the evolution of the aerodynamics of the wind-bridge system over time during an entire VIV event. It is found that the level of self-excited effects of the wind-bridge system is significantly time varying with the real-time wind speed and bridge motion state. The simulations of VIVs by the obtained time-dependent models show high accuracies of the models with an averaged normalized mean-square error of 0.0023. The clustering of obtained models shows underlying distinct dynamical regimes of the wind-bridge system, which are distinguished by the level of self-excited effects.