Yanli Hu^1,2, Peiwei Gao^3,*, Furong Li⁴, Zhiqing Zhao⁵, Zhenpeng Yu⁶

Journal of Renewable Materials, Vol.11, No.4, pp. 2055-2073, 2023, DOI:10.32604/jrm.2022.023612 - 01 December 2022

Abstract In order to examine the biaxial compression-compression properties of rubber fibre reinforced concrete (RFRC), an experimental study on RFRC under different lateral compressive stresses was carried out by considering different rubber replacement rates and polypropylene fibre contents. The failure modes and mechanical property parameters of different RFRC working conditions were obtained from the experiment to explore the effects of rubber replacement rate and polypropylene fibre content on the biaxial compression-compression properties of RFRC. The following conclusions were drawn. Under the influence of lateral compressive stress, the biaxial compression-compression failure mode gradually developed from a columnar… More >

Chunli Meng¹, Weishu Fu^1,*, Jianzeng Shen^2,*, Yisheng Su^1,2, Chunying Ye¹

Journal of Renewable Materials, Vol.11, No.2, pp. 581-598, 2023, DOI:10.32604/jrm.2022.022074 - 22 September 2022

Abstract Different rubber aggregates lead to changes in the effect of stress conditions on the mechanical behavior of concrete, and studies on the triaxial properties of self-compacting rubber concrete (SCRC) are rare. In this study, 35 cylindrical specimens taking lateral stress and rubber type as variables were prepared to study the fresh properties and mechanical behaviors of SCRC under triaxial compression, where the rubber contains two types, i.e., 380 μm rubber powder and 1–4 mm rubber particles, and four contents, i.e., 10%, 20% and 30%. The test results demonstrated that SCRC exhibited a typical oblique shear… More > Graphic Abstract

Kyungsuk Jang¹, Gun Jin Yun^2,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1091-1120, 2021, DOI:10.32604/cmc.2020.012911 - 26 November 2020

Abstract This paper first proposes a new self-learning data-driven methodology that can develop the failure criteria of unknown anisotropic ductile materials from the minimal number of experimental tests. Establishing failure criteria of anisotropic ductile materials requires time-consuming tests and manual data evaluation. The proposed method can overcome such practical challenges. The methodology is formalized by combining four ideas: 1) The deep learning neural network (DLNN)-based material constitutive model, 2) Self-learning inverse finite element (SELIFE) simulation, 3) Algorithmic identification of failure points from the self-learned stress-strain curves and 4) Derivation of the failure criteria through symbolic regression More >

Huajing Guo, Baijian Wu, Zhaoxia Li^*

Structural Durability & Health Monitoring, Vol.14, No.1, pp. 37-50, 2020, DOI:10.32604/sdhm.2020.08442 - 01 March 2020

Abstract In order to resolve the safety problem of the existing crane runway girders (CRGs) with defects, the constraint-based R6 criterion is proposed to assess their structural integrity. The existing steel CRGs with defects at the weld joint between the upper flange and web plate, are characterized to three-dimensional finite element models with a semi-ellipse surface crack. The R6 criterion has been modified by considering the constraint effect which is represented by T-stress. The analysis results illustrate that working condition of the cracked CRGs leads to high constraint level along the crack front. The crack aspect More >