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The characterization and understanding of crack evolution in non-uniform geological structures are crucial for predicting the mechanical response of rock-like materials or structures under varying loading conditions. In this study, an improved Peridynamic model with a degree of heterogeneity characterized by random pre-breaking “bonds” coefficients is introduced to capture the intricacies of crack initiation, propagation, and branching behaviors in heterogeneous rock-like materials. MATLAB discrete programs for heterogeneous material models and PD simulation programs based on the FORTRAN language were developed. The effectiveness of the heterogeneous PD model in simulating crack propagation and branching patterns in heterogeneous materials has been verified through dynamic and static (quasi-static) loading cases with pre-notch. The different levels of heterogeneity not only affect the direction of crack propagation but also determine the crack deflection direction and branching patterns. The crack propagation path appears to possess obvious asymmetry in the crack propagation direction. As the load applied continues to increase, the asymmetric multi-crack branching phenomenon will occur. The higher the level of heterogeneity, the more complex the behaviors of crack propagation and branching become. This research provides valuable insights into the interplay of material heterogeneity and crack evolution, offering a foundation for improved numerical simulations and contributing to the broader field of geomechanics.

The paper proposes a meta-learning-based Mandarin-Tibetan cross-lingual text-to-speech (TTS) to realize both Mandarin and Tibetan speech synthesis under a unique framework. First, we build two kinds of Tacotron2-based Mandarin-Tibetan cross-lingual baseline TTS. One is a shared encoder Mandarin-Tibetan cross-lingual TTS, and another is a separate encoder Mandarin-Tibetan cross-lingual TTS. Both baseline TTS use the speaker classifier with a gradient reversal layer to disentangle speaker-specific information from the text encoder. At the same time, we design a prosody generator to extract prosodic information from sentences to explore syntactic and semantic information adequately. To further improve the synthesized speech quality of the Tacotron2-based Mandarin-Tibetan cross-lingual TTS, we propose a meta-learning-based Mandarin-Tibetan cross-lingual TTS. Based on the separate encoder Mandarin-Tibetan cross-lingual TTS, we use an additional dynamic network to predict the parameters of the language-dependent text encoder that could realize better cross-lingual knowledge sharing in the sequence-to-sequence TTS. Lastly, we synthesize Mandarin or Tibetan speech through the unique acoustic model. The baseline experimental results show that the separate encoder Mandarin-Tibetan cross-lingual TTS could handle the input of different languages better than the shared encoder Mandarin-Tibetan cross-lingual TTS. The experimental results further show that the proposed meta-learning-based Mandarin-Tibetan cross-lingual speech synthesis method could effectively improve the voice quality of synthesized speech in terms of naturalness and speaker similarity.

It is essential to accurately describe the large shear behavior of woven fabrics in the composite preforming process. An analytical model is proposed to describe the shear behavior of fabrics with different weave patterns, in which tension-shear coupling is considered. The coupling is involved in two parts, the friction between overlapped yarns and the in-plane transverse compression between two parallel yarns. By introducing the concept of inflection points of a yarn, the model is applicable for fabrics with different weave patterns. The analytical model is validated by biaxial tension-shear experiments. A parametric study is conducted to investigate the effects of external load, yarn geometry, and weave structure on the large shear behavior of fabrics. The developed model can reveal the physical mechanism of tension-shear coupling of woven fabrics. Moreover, the model has a high computational efficiency due to its explicit expressions, thus benefiting the material design process.