This work utilized a combination of experimental evidence and fractal geometric method to assess the effect of crack extension concerning the thermal shock on residual strength of ceramics. Sintered alumina (Al ₂ O ₃ ) ceramic slabs were bundled and quenched in water under different thermal shock temperatures. The fractal dimension of thermal shock crack patterns on the interior surface and the cooled surface was calculated by the Box‐counting method. Fracture energy of a fractal pattern of microcracks in quasi‐brittle solids was employed to explain the relationship between crack length and fractal dimensions. The results show that if the crack propagation has the same crack length but a larger fractal dimension, it will absorb more fracture energy. The thermal shock crack patterns of Al ₂ O ₃ ceramics with different grain sizes were analyzed, and the smaller grain size ceramic had a higher fractal dimension of crack patterns than the larger one.

Fatigue assessment is especially important in long-term physical work and training to avoid injury caused by muscle fatigue. The surface electromyography (sEMG) signal has been widely used to detect muscle fatigue states. The purpose of this paper is to establish muscle functional networks and provide a comprehensive assessment of muscle fatigue using multi-channel sEMG signals from the back muscles. A muscle functional network is constructed based on the Pearson correlation coefficients between the channels of sEMG signals, and we explore how the economic properties and small-world properties of the muscle network change with cost. Then, the network threshold is determined by changes in small-world properties. We extract network parameters through complex network methods to quantify and analyze the differences in muscle functional networks under different fatigue states. The most significant results of this novel approach indicate that the economic and small-world properties of the muscle network gradually decrease with increasing fatigue, and network parameters decrease significantly after fatigue. The method presented in this paper provides a new foundation for assessing muscle fatigue.

Ceramics are commonly used as high-temperature structural materials which are easy to fracture because of the propagation of thermal shock cracks. Characterizing and controlling crack propagation are significant for the improvement of the thermal shock resistance of ceramics. However, observing crack morphology, based on macro and SEM images, costs much time and potentially includes subjective factors. In addition, complex cracks cannot be counted and will be simplified or omitted. Fractals are suitable to describe complex and inhomogeneous structures, and the multifractal spectrum describes this complexity and heterogeneity in more detail. This paper proposes a crack characterization method based on the multifractal spectrum. After thermal shocks, the multifractal spectrum of alumina ceramics was obtained, and the crack fractal features were extracted. Then, a deep learning method was employed to extract features and automatically classify ceramic crack materials with different strengths, with a recognition accuracy of 87.5%.

The accurate characterization of the surface microstructure of ultra-high temperature ceramics after thermal shocks is of great practical significance for evaluating their thermal resistance properties. In this paper, a fractal reconstruction method for the surface image of Ultra-high temperature ceramics after repeated thermal shocks is proposed. The nonlinearity and spatial distribution characteristics of the oxidized surfaces of ceramics were extracted. A fractal convolutional neural network model based on deep learning was established to realize automatic recognition of the classification of thermal shock cycles of ultra-high temperature ceramics, obtaining a recognition accuracy of 93.74%. It provides a novel quantitative method for evaluating the surface character of ultra-high temperature ceramics, which contributes to understanding the influence of oxidation after thermal shocks.