Computational modeling of fracture in concrete: A review

filig, Luth; Mauludin, Muhammad; Oucif, Chahmi

doi:10.1007/s11709-020-0573-z

Cited by 21 publications

(13 citation statements)

References 117 publications

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“…Stiffer capsule inclusion delayed the initiation and growth of the crack, but did not change the ultimate crack length in their simulated regime. While the numerical studies provide additional insight into the design of self‐healing materials, they are still limited owing to the complexity of the healing process 110 . Moreover, controlled fabrication and mechanical characterization of self‐healing microcapsules should be precisely and carefully performed to experimentally validate the results from these numerical studies.…”

Section: Application Of Mechanically Tailored Soft Microparticlesmentioning

confidence: 99%

“…While the numerical studies provide additional insight into the design of self-healing materials, they are still limited owing to the complexity of the healing process. 110 Moreover, controlled fabrication and mechanical characterization of self-healing microcapsules should be precisely and carefully performed to experimentally validate the results from these numerical studies. In fact, researchers have recently utilized microfluidic techniques 111 for the controlled fabrication of microcapsules (Figure 21A) and AFM 112,113 or microcompression 114 techniques for mechanical characterization of microcapsules.…”

Section: Self-healingmentioning

confidence: 99%

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Mechanical characterization of soft microparticles prepared by droplet microfluidics

Kim

Lee

2022

Journal of Polymer Science

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Droplet microfluidics is one of the most promising approaches that allows preparation of microparticles with tailored structure and composition. Various functional microparticles have been developed using microfluidics, where their controlled structure shows high potential for a wide range of applications. Among these, soft polymeric microparticles which exhibit low elastic modulus compared to ceramics and metals are extensively investigated in biomedical applications due to their biocompatibility, high surface‐to‐volume ratio, as well as soft and deformable nature. As the mechanical properties of soft microparticles play important role in determining how they function in each application, it is essential to adequately characterize them for the optimal design of functional microparticles. In this review, we mainly discuss the mechanical characterization methods of soft microparticles and their elastic property. A brief overview of the droplet microfluidics‐assisted fabrication of microparticles is also provided before discussing the mechanical characterization techniques. We then describe the general characterization methods and models employed to determine the elastic properties of microparticles. In addition, we discuss the relationship between the physical parameters (size, composition, and structure) and the elastic properties of the microparticles, followed by the role of elastic properties in various applications including microcarrier, bioink, and self‐healing to name a few.

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Section: Application Of Mechanically Tailored Soft Microparticlesmentioning

confidence: 99%

Section: Self-healingmentioning

confidence: 99%

Mechanical characterization of soft microparticles prepared by droplet microfluidics

Kim

Lee

2022

Journal of Polymer Science

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“…Rabczuk (2013) presented the review of computational modeling of brittle and quasi-brittle materials with the main focus on discrete fracture cracks. Mauludin and Oucif (2020) also presented the review of computational fracture modeling of concrete with a major focus on the comparison of macroscopic models and microscopic models. From the last few decades, extensive work is done on the numerical applications of concrete behavior under local and nonlocal approaches.…”

Section: Introductionmentioning

confidence: 99%

“…studies were presented in the literature. Their extensive reviews for quasi-brittle materials can be found in the literature (Jenabidehkordi, 2019; Mauludin and Oucif, 2020; Rabczuk, 2013). Besson (2010) reviewed the material constitutive models (which integrates physical bases to integrate the structure with damage and permanent strains) and computational tools (to enhance the efficiency of a structure by reducing weight and increasing service life).…”

Section: Introductionmentioning

confidence: 99%

A review of continuum damage and plasticity in concrete: Part II – Numerical framework

Voyiadjis

Ahmed

Park

2021

International Journal of Damage Mechanics

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In this part II, companion article, we present the numerical review of continuum damage mechanics and plasticity in the context of finite element. The numerical advancements in local, nonlocal, and rate-dependent models are presented. The numerical algorithms, type of elements utilized in numerical analysis, the commercial software’s or in-house codes used for the analysis, iterative schemes, explicit or implicit approaches to solving finite element equations, and degree of continuity of element are discussed in this part. Lastly, some open issues in concrete damage modeling and future research needed are also discussed.

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“…Brittle materials are materials in which cracks of atomic sharpness, such as ceramics, glasses, and some metal alloys, [1,2] basically spread by bond ruptures. In engineering, in operation or fabrication, fine length scale cracks exit.…”

Section: Introductionmentioning

confidence: 99%

Prediction Method of Three‐Dimensional Crack Propagation Path Based on Deep Learning Application

et al. 2020

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In engineering, most structural components suffer from local damage in service or fabrication. Under different loading conditions, such local damage will further expand to large cracks and structural collapse. For ensuring longevity and reliability, the study of brittle crack growth is important. In structural damage prediction, various methodologies are commonly used and have demonstrated success in the past. Most traditional simulation methods, however, have the problems of large calculation quantities and long calculation times. At the same time, the mutual influence of crack opening stress and crack image on crack widening is rarely considered in existing works based on the deep learning framework. Herein, a deep learning model is developed to predict the spread of fracture of brittle materials under stress to improve the aforementioned problems. By developing a nonlinear relationship between crack stress and damage effects, this approach predicts crack growth, thus avoiding the loss of required information on crack growth behavior. The model emphasizes repeatability and extensibility, which is verified using extended finite element method (XFEM) Abaqus software through multiple sets of material crack data generated. This model's potential applications are material design and evaluation of residual life.

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Computational modeling of fracture in concrete: A review

Cited by 21 publications

References 117 publications

Mechanical characterization of soft microparticles prepared by droplet microfluidics

Mechanical characterization of soft microparticles prepared by droplet microfluidics

A review of continuum damage and plasticity in concrete: Part II – Numerical framework

Prediction Method of Three‐Dimensional Crack Propagation Path Based on Deep Learning Application

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