Finite element modelling of rate-dependent ratcheting in granular materials

International audienceThe present paper introduces a comprehensive model that is capable of describing the behaviour, under cyclic loading, of the granular materials used in railway tracks and road pavement. Its main thrust is the introduction of the ''Chicago'' law in a continuum approach to account for the ratcheting effects. It also emphasizes rate-dependency as a dissipative mechanism that acts independently or jointly with the ratcheting effect as well as the non-associated plasticity. The numerical procedure is based on the return mapping algorithm, where Newton's method is used to calculate the nonlinear consistency parameter of the flow rule and to obtain a consistent tangent modulus. The model was applied to specific numerical examples including multi-axial and cyclic loading conditions

Experimental Investigation and Failure Analysis of Fastened GRP under Bending Using Finite Element Method and Artificial Neural Networks

This paper presents a novel approach that predicts the strength and failure modes of jointed Glass Reinforced Polyester (GRP) samples under bending using Finite Element Method (FEM) and Artificial Neural Network (ANN). The mechanical behavior of fastened glass fiber reinforced plastics composites under bending have been experimentally investigated. Samples were obtained from Amiantit Oman, a manufacturing company operating in Russail Industrial Zone in the Sultanate of Oman. The experimental program involved the conduct of three point bending tests as well as bending tests of mechanically fastened joints under static loads. The experimental results showed that the dimensions of the specimen such as the bending span length, specimen width, and specimen pitch affect GRP strength and stiffness. FEM and ANN results predicted accurately the types of failure modes and their locations along the specimens and compared well with the experimental results

Experimental Investigation and Failure Analysis of Fastened GRP under Bending Using Finite Element Method and Artificial Neural Networks

This paper presents a novel approach that predicts the strength and failure modes of jointed Glass Reinforced Polyester (GRP) samples under bending using Finite Element Method (FEM) and Artificial Neural Network (ANN). The mechanical behavior of fastened glass fiber reinforced plastics composites under bending have been experimentally investigated. Samples were obtained from Amiantit Oman, a manufacturing company operating in Russail Industrial Zone in the Sultanate of Oman. The experimental program involved the conduct of three point bending tests as well as bending tests of mechanically fastened joints under static loads. The experimental results showed that the dimensions of the specimen such as the bending span length, specimen width, and specimen pitch affect GRP strength and stiffness. FEM and ANN results predicted accurately the types of failure modes and their locations along the specimens and compared well with the experimental results

Optimization of Cement–Rubber Composites for Eco-Sustainable Well Completion: Rheological, Mechanical, Petrophysical, and Creep Properties

To ensure well integrity, wellbore must be strongly cased using durable cement slurries with essential additives during downhole completion. The rubber materials that come from industrial waste are becoming extremely encouraged in the use as an additive in preparing cement slurries due to their growing environmental footprint. However, the proper design of cement slurry strongly depends on its rheological, mechanical, petrophysical, and creep properties, which can be altered by changing additives. This study aimed to examine the cement properties under alteration in different chemical admixtures to create efficient binding properties, and to estimate the optimum cement–rubber slurry composition for eco-sustainable completion. Three cement samples with different mesh sizes of the crumb rubber particles were prepared. This study examined the variation in rheological behaviors, elastic and failure characteristics, permeability, and creep behavior of the cement–rubber composites for petroleum well construction. The experimental study showed that the addition of 15% or more crumb rubber to the cement resulted in very thick slurries. Moreover, it was shown that the addition of crumb rubber with various particle sizes to the cement reduced the strength by more than 50%, especially for a higher amount of rubber added. It was also revealed that the addition of a superplasticizer resulted in an 11% increase in compressive strength. The results showed that cement–crumb-rubber composites with 12% by weight of cement (BWOC) represented the optimum composite, and considerably improved the properties of the cement slurry. Water-permeability tests indicated the addition of 12% BWOC with 200-mesh crumb rubber decreased the permeability by nearly 64% compared to the base cement. Creep tests at five different stress levels illustrated that the neat cement was brittle and did not experience strain recovery at all stress levels. Cement slurries with the largest rubber-particle size were elastic and demonstrated the highest amount of strain recovery. Finally, a relationship was established between the permeability, average strain, and mesh size of the rubber particles, which offered the strain recovery, satisfied the zonal isolation, and consequently reduced the microannulus problem to ensure the cement’s integrity

Optimization of Cement–Rubber Composites for Eco-Sustainable Well Completion: Rheological, Mechanical, Petrophysical, and Creep Properties

To ensure well integrity, wellbore must be strongly cased using durable cement slurries with essential additives during downhole completion. The rubber materials that come from industrial waste are becoming extremely encouraged in the use as an additive in preparing cement slurries due to their growing environmental footprint. However, the proper design of cement slurry strongly depends on its rheological, mechanical, petrophysical, and creep properties, which can be altered by changing additives. This study aimed to examine the cement properties under alteration in different chemical admixtures to create efficient binding properties, and to estimate the optimum cement–rubber slurry composition for eco-sustainable completion. Three cement samples with different mesh sizes of the crumb rubber particles were prepared. This study examined the variation in rheological behaviors, elastic and failure characteristics, permeability, and creep behavior of the cement–rubber composites for petroleum well construction. The experimental study showed that the addition of 15% or more crumb rubber to the cement resulted in very thick slurries. Moreover, it was shown that the addition of crumb rubber with various particle sizes to the cement reduced the strength by more than 50%, especially for a higher amount of rubber added. It was also revealed that the addition of a superplasticizer resulted in an 11% increase in compressive strength. The results showed that cement–crumb-rubber composites with 12% by weight of cement (BWOC) represented the optimum composite, and considerably improved the properties of the cement slurry. Water-permeability tests indicated the addition of 12% BWOC with 200-mesh crumb rubber decreased the permeability by nearly 64% compared to the base cement. Creep tests at five different stress levels illustrated that the neat cement was brittle and did not experience strain recovery at all stress levels. Cement slurries with the largest rubber-particle size were elastic and demonstrated the highest amount of strain recovery. Finally, a relationship was established between the permeability, average strain, and mesh size of the rubber particles, which offered the strain recovery, satisfied the zonal isolation, and consequently reduced the microannulus problem to ensure the cement’s integrity

Automated Assessment Tool for 3D Computer-Aided Design Models

Computer-aided design (CAD) has become an integral part of engineering education, particularly for those studying mechanical engineering. By providing practical skills that are highly valued in the engineering industry, proficiency in CAD systems enhances students’ employability. Generally, CAD systems provide students with the tools and knowledge necessary to excel in their engineering education and future careers. In order to help teachers to give the best training to their students and to make the right evaluations, an automatized tool is needed to support the evaluation of CAD models during training sessions. After an extensive bibliographical search, this paper proposes a CAD Model Automatized Assessment (MAA) Tool for mechanical courses called the CAD MAA Tool. This tool is mainly based on a developed model that takes into account different aspects of modeling, such as geometric, feature-based, and parametric modeling. To correctly evaluate a given part compared to a reference one, the proposed model uses different coefficients fixed by the teacher according to their teaching strategies or course objectives