Comparison of response surface methodology with artificial neural network for prediction of the tensile properties of friction stir-processed surface composites

Butola, Ravi; Singari, Ranganath M.; Murtaza, Qasim; Tyagi, Lakshay

doi:10.1177/09544089211036833

Cited by 12 publications

(5 citation statements)

References 35 publications

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“…Experimental results were validated with ANN. Butola et al 54) compared RSM with ANN to predict tensile characteristic of FSPed composite. ANN results revealed better predictive capacity in comparison to RSM.…”

Section: Figure 2 Schematic Layout Of Fsp Processmentioning

confidence: 99%

An Overview of Recent Development and Application of Friction Stir Processing Technique

Maurya¹,

Maurya²,

Kumar³

2022

Evergreen

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In current scenario, friction stir processing (FSP) is used for the development of surface composite. This process improves the grain refinement, which refines the localize grain size of the material near the stir zone. Owing to grain refinement, tensile strength and hardness of the material are significantly improved. Several studies have been reported related to research work performed by various researchers on FSP in the archival literature. The main emphasis of this study is to evaluate the mechanical properties investigated by the various researchers. This article presents the summary of research work performed on different types of material, reinforcement material used for the development of composite and application of FSP process.

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Section: Figure 2 Schematic Layout Of Fsp Processmentioning

confidence: 99%

An Overview of Recent Development and Application of Friction Stir Processing Technique

Maurya¹,

Maurya²,

Kumar³

2022

Evergreen

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“…How to make the new town not completely "start a new stove" but reflect the urban characteristics; continue the green space layout, historical context, and other traditions of the old city; and whether the existing green space system planning is still applicable in the construction of new towns with policy tendencies are the breakthrough points of introducing artificial neural network (ANN) [13][14][15][16] to evaluate the existing green space system planning in this article.…”

Section: Overall Research Frameworkmentioning

confidence: 99%

Urban Green Space Planning and Design for Sponge City

Hong

Han

2022

Scientific Programming

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Urban green space designed based on the concept of sponge city is an important sponge carrier. Guided by the theory of landscape ecology, this article introduces the artificial neural network (ANN) model and uses the research method of landscape pattern index to establish a model for the proportion of urban green space types and the characteristics and dynamic changes of landscape spatial pattern. Based on the optimal landscape pattern index, the theoretical value of the optimal proportion of ecological green space, community park, comprehensive park, roadside green space, protective green space, and strip green space is obtained through the model. Based on this proportion value, combined with the ANN model, the reasonable evaluation results of patch density and average perimeter area ratio, spread degree, and diversity index of planned green space are obtained. Then, according to the influence of various green spaces on each landscape index, the development trend of urban green space construction in the future is predicted.

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“…Researchers have successfully fabricated surface composites on aluminum [12,13], copper [14,15], magnesium [16,17], titanium [18,19], steel [20,21] etc making this an effectual processing technique which has to be investigated in further aspects.…”

Section: Introductionmentioning

confidence: 99%

Role of process parameters in defining the characteristics of copper surface composites fabricated via friction stir processing

Vinoj,

Raja,

Thankachan

et al. 2023

Eng. Res. Express

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This research deals with investigating the effects of amount of hybrid reinforcement, rotational speed and traverse speed on the mechanical and wear characteristics of copper surface composites fabricated via friction stir processing. Aluminum oxide and boron carbide at 1:1 ratio was dispersed onto copper substrate at various volume fractions (5, 10 and 15 vol. %) at different traverse speed (40, 60 and 80 mm/min) and rotational speed (800, 950 and 1300 rpm). Microstructural characterization of developed copper surface composites dispersed with varying volume fraction of hybrid reinforcement proved reduction in grain size and homogenous distribution of ceramic particles. Results stated that the percentage of particles dispersed, traverse speed and rotational speed have high impact in defining the property of developed copper surface composites. A positive trend in mechanical strength was observed throughout the study. Increase in hybrid reinforcement dispersion and traverse speed increases the microhardness value of developed surface composites while increase in rotational speed leads to reduction in microhardness value.

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Comparison of response surface methodology with artificial neural network for prediction of the tensile properties of friction stir-processed surface composites

Cited by 12 publications

References 35 publications

An Overview of Recent Development and Application of Friction Stir Processing Technique

An Overview of Recent Development and Application of Friction Stir Processing Technique

Urban Green Space Planning and Design for Sponge City

Role of process parameters in defining the characteristics of copper surface composites fabricated via friction stir processing

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