2015Suxing gongcheng xuebaoRequires access

High temperature flow behaviors and neural network based constitutive model of aluminum-tungsten alloy

Guo La-fen

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Abstract

The flow behaviors of the as-extruded aluminum-tungsten alloy were studied through single-pass compression experiments by using Gleeble1500 simulator within temperature range of 450℃~540℃ and strain rate range of 0.001s-1~1s-1.And the constitutive relationship model for this alloy was successfully developed by using BP neural network.In the proposed model,the input variables are strain,strain rate and temperature,while the flow stress is the output variable.It was found that the established constitutive relationship model could provide a good representation of the test data and better describe the whole deforming process compared with that by the traditional method.Moreover,the suggested model is available to provide a convenient and effective way to develop the constitutive relationship for aluminum-tungsten alloys.

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What this paper is about

The flow behaviors of the as-extruded aluminum-tungsten alloy were studied through single-pass compression experiments by using Gleeble1500 simulator within temperature range of 450℃~540℃ and strain rate range of 0.001s-1~1s-1.And the constitutive relationship model for this alloy was successfully developed by using BP neural network.In the proposed model,the input variables are strain,strain rate and temperature,while the flow stress is the output variable.It was found that the established constitutive relationship model could provide a good representation of the test data and better describe the whole deforming process compared with that by the traditional method.Moreover,the suggested model is available to provide a convenient and effective way to develop the constitutive relationship for aluminum-tungsten alloys.

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Available abstract

The flow behaviors of the as-extruded aluminum-tungsten alloy were studied through single-pass compression experiments by using Gleeble1500 simulator within temperature range of 450℃~540℃ and strain rate range of 0.001s-1~1s-1.And the constitutive relationship model for this alloy was successfully developed by using BP neural network.In the proposed model,the input variables are strain,strain rate and temperature,while the flow stress is the output variable.It was found that the established constitutive relationship model could provide a good representation of the test data and better describe the whole deforming process compared with that by the traditional method.Moreover,the suggested model is available to provide a convenient and effective way to develop the constitutive relationship for aluminum-tungsten alloys.

Key concepts: Constitutive equation, Flow stress, Materials science, Alloy, Strain rate, Aluminium, Compression (physics), Artificial neural network

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