Abstract

Predicting the performances of a manufactured part is extremely important, especially for industries in which there is almost no room for uncertainties, such as aeronautical or automotive. Simulations performed by means of numerical methods such as Finite Element Methods represent a powerful instrument in achieving high level of predictability. However, some particular combinations of manufactured materials and manufacturing processes might lead to unfavorable conditions in which the classical mathematical models used to predict the behavior of the continuum are not anymore able to deliver predictions that are in good agreement with experimental evidence. Since the first evidences of the shortcomings of the classical model were highlighted, many non-classical continuum mechanics theories have been developed, and most of them introduce dependencies at different levels with the Plastic Strain Gradient. This manuscript aims at gathering the milestone contributions among the Strain Gradient Plasticity Theories developed so far, with the object of exploring the way they interface with the requirements posed by the challenges in simulating manufacturing operations. Finally, the most relevant examples of the applications of Strain Gradient Plasticity Theories for manufacturing simulations have been reported from literature.

Highlights

  • The topic of Strain Gradient Theories (SGT) experienced a fervent increase of interest from the scientific community in recent years

  • Multiple reasons made the SGT one of the hot topics in the field of Continuum Mechanics (CM), the main causes can be identified in the ever-increasing computational power of numerical calculators and in the demand of more sophisticated CM theories which would better predict the medium behavior under specific material deformation conditions

  • It must be mentioned that plastic deformations usually give rise to heat productions, and considering the case in which the rate of heat production is much larger than the heat flow within the material, high temperature fields are retained, and the SBs are referred to as Adiabatic Shear Bands (ASBs)

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Summary

Introduction

The topic of Strain Gradient Theories (SGT) experienced a fervent increase of interest from the scientific community in recent years. The most general feature, shared by all the SGTs, is the introduction of one or more scale lengths in the model used to describe the medium behavior This is done through the definition of additional deformation measures that are meant to capture specific phenomena which cannot be predicted by the classical CM models. The manufacturing techniques in which the strain gradient plays a bigger role result to be those in which the loads are highly localized, e.g., micro-cutting, milling, micro-bending, thin wire drawing, machining, Friction Stir Welding (FSW), sheet stamping, inverse drawing, adiabatic cutting These machining processes favor the development of rather peculiar conditions in the processed material, where a combination of separate factors contribute to produce a relatively complex scenario. The conclusions of the present review manuscript will present advantages and disadvantages of using different SGPTs to simulate different machining processes

Challenges in Manufacturing Processes Simulations
Strain Localization and Mesh-Size Dependency
Material Characterization at High Temperatures and High Strain Rates
Tool-Workpiece Contact
Historical Excursus of SGPTs in Literature
Aifantis’ Theory
Gradient of the Local Spin Vector—Fleck and Hutchinson 1993
Second Gradient of Displacement—Fleck and Hutchinson 1997
Irrotational Plastic Flow and Burgers Tensor—Gurtin and Anand 2005
The Common Framework—Gudmundson 2004
Dislocations-Enriched SGT
Gradient of Micro-Structure Rotation—Cosserat Media
Gradient of Micro-Structure Deformation—Micromorphic Media
Reported Applications of SGPTs in Manufacturing Processes Simulation
Scalar SGPT Applied to Flat Punch Molding
SGPT Used to Model Rolling at Small Scale
MSGT Applied to Orthogonal Cutting
Micromorphic Media Applied to Forming
Findings
Conclusions
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