A methodology to predict the roughness of shot peened surfaces

Taro, Mandikizinoyou; Chaise, Thibaut; Nélias, Daniel

doi:10.1016/j.jmatprotec.2014.10.016

Cited by 35 publications

(11 citation statements)

References 32 publications

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“…It was reported that shot shape had effects on SP products, 27,83 although many investigations on SP simulation did not consider shot shape as an influential parameter and hence used spherical shots. 26,49,78 However, an early investigation was conducted by Meguid et al 84 who used steel ellipsoids with different aspect ratios as shots.…”

Section: Shot Shape and Materialsmentioning

confidence: 99%

Literature review of numerical simulation and optimisation of the shot peening process

Chen

Desai

Heyns

et al. 2019

Advances in Mechanical Engineering

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This work provides a comprehensive review of numerical simulation and optimisation of the shot peening found in the existing literature over the past 10 years. The review found that the developed numerical models coupling finite elements with discrete elements became increasingly mature and showed their advantages in incorporating flow behaviour and randomness of shots. High emphasis must be placed on the constitutive equations of target material where its strain-rate sensitivity, cyclic behaviour and Bauschinger effects are recommended to be incorporated in the numerical material model simultaneously since considering one of them in isolation may lead to unreliable distribution of residual stresses. Furthermore, material hardening is a critical benefit of shot peening; however, it has not received its deserved attention from the existing investigations, neither in simulation nor in optimisation. The study found that intensity and coverage are two critical control parameters recommended to be constraints for optimisation of shot peening. Finally, this work also found that developed heuristic algorithms, such as genetic algorithms have recently showed their advantages for searching optimal combinations of peening parameters. It is plausible that in the near future, the synergy of combining these algorithms with approximation models can be expected to gain more attention by researchers.

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Section: Shot Shape and Materialsmentioning

confidence: 99%

Literature review of numerical simulation and optimisation of the shot peening process

Chen

Desai

Heyns

et al. 2019

Advances in Mechanical Engineering

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“…For the three effects of shot peening on the target material, residual stresses on the top layer is beneficial to improve the fatigue resistance of the material, hence it should be maximised. While, the material hardening may lead to stress relaxation of compressive residual stress on one hand [15]; and on the other hand surface roughness, more exactly the height of the cavities caused by impacts has a potential to weaken the benefits of compressive residual stresses and cause corrosive cracks [18]. Further, the material hardening could be calculate by the measurement of the material plastic strain at the yield point of the material and the cold work could be calculate by the measurement of the plastic strain of the peened surface [19].…”

Section: Formulation Of Optimisationmentioning

confidence: 99%

Numerical Optimisation of Shot Peening Process on a Steam Turbine Blade

Chen¹,

Desai²,

Heyns³

et al. 2017

Proceedings of the 2017 6th International Conference on Measurement, Instrumentation and Automation (ICMIA 2017)

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Abstract. This article provides a broad and extensive literature survey on optimisation of shot peening process that have been developed and applied in the past decades and summarises the knowledge that has been gained and then points out the shortages of the important investigations in optimisation of shot peening process. On this basis, optimisation function is formulated and genetic algorithm is chosen to conduct the optimisation. This optimisation screens out the influential parameters and provides the weights of different parameters in terms of their influence of shot peening outputs.

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“…Likewise, in the case of shot peening, most studies have based their comparison on the frequently used parameters of Ra and Rz, even if surfaces with similar values of this latter can exhibit quite different behavior due to a different overall surface features arrangement and a different texture. Numerous studies [40][41][42][43][44][45] have been performed on the numerical investigation of surface roughness prediction induced by peening, taking for granted the validity of the standard roughness parameters.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Homogeneity of Surface Features Induced by Impact-Based Surface Treatments

et al. 2021

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Impact surface treatments are well-known for their efficiency in enhancing the mechanical properties of metallic materials, especially under cyclic loadings. These processes, which encompass a wide range of surface treatments based on repetitive impacts of tools of various types, induce surface plastic deformation, compressive residual stresses, and grain refinement alter the surface roughness as a side effect. Thus, it is essential to have suitable indexes to quantify the surface features caused by the typically random nature of these treatments. Herein, we evaluated the rationality of using standard roughness parameters for describing the morphological characteristics of surfaces treated by shot peening as a representative and widely used treatment of the category. A detailed numerical model of the peening process was developed. The output data were elaborated to extract the surface roughness parameters following the standard procedures. The results revealed the validity of the surface roughness parameters to describe the topography of material treated with adequate surface coverage, also highlighting the necessity to use a set of parameters rather than the common practice of relying on single parameters. Not considering a comprehensive set of amplitude and spacing parameters can result in significant, inconsistent, and misleading results while comparing the performance of surfaces.

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A methodology to predict the roughness of shot peened surfaces

Cited by 35 publications

References 32 publications

Literature review of numerical simulation and optimisation of the shot peening process

Literature review of numerical simulation and optimisation of the shot peening process

Numerical Optimisation of Shot Peening Process on a Steam Turbine Blade

Evaluating the Homogeneity of Surface Features Induced by Impact-Based Surface Treatments

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