scholarly journals Research on Heat Treatment Process for New Low Alloy Steel Structures

2019 ◽  
Author(s):  
Yan-xia Gu ◽  
Heng Wang
Keyword(s):  
Heat Treatment ◽  
Alloy Steel ◽  
Treatment Process ◽  
Steel Structures ◽  
Heat Treatment Process ◽  
Low Alloy Steel

scholarly journals Modeling and Composition Design of Low-Alloy Steel’s Mechanical Properties Based on Neural Networks and Genetic Algorithms

Materials ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 5316
Author(s):  
Zhenlong Zhu ◽  
Yilong Liang ◽  
Jianghe Zou
Keyword(s):  
Neural Network ◽  
Mechanical Properties ◽  
Heat Treatment ◽  
Genetic Algorithm ◽  
Alloy Steel ◽  
Deep Neural Network ◽  
Treatment Process ◽  
Mechanical Performance ◽  
Low Alloy Steel ◽  
Forward Selection

Accurately improving the mechanical properties of low-alloy steel by changing the alloying elements and heat treatment processes is of interest. There is a mutual relationship between the mechanical properties and process components, and the mechanism for this relationship is complicated. The forward selection-deep neural network and genetic algorithm (FS-DNN&GA) composition design model constructed in this paper is a combination of a neural network and genetic algorithm, where the model trained by the neural network is transferred to the genetic algorithm. The FS-DNN&GA model is trained with the American Society of Metals (ASM) Alloy Center Database to design the composition and heat treatment process of alloy steel. First, with the forward selection (FS) method, influencing factors—C, Si, Mn, Cr, quenching temperature, and tempering temperature—are screened and recombined to be the input of different mechanical performance prediction models. Second, the forward selection-deep neural network (FS-DNN) mechanical prediction model is constructed to analyze the FS-DNN model through experimental data to best predict the mechanical performance. Finally, the FS-DNN trained model is brought into the genetic algorithm to construct the FS-DNN&GA model, and the FS-DNN&GA model outputs the corresponding chemical composition and process when the mechanical performance increases or decreases. The experimental results show that the FS-DNN model has high accuracy in predicting the mechanical properties of 50 furnaces of low-alloy steel. The tensile strength mean absolute error (MAE) is 11.7 MPa, and the yield strength MAE is 13.46 MPa. According to the chemical composition and heat treatment process designed by the FS-DNN&GA model, five furnaces of Alloy1–Alloy5 low-alloy steel were smelted, and tensile tests were performed on these five low-alloy steels. The results show that the mechanical properties of the designed alloy steel are completely within the design range, providing useful guidance for the future development of new alloy steel.

Factors Affecting the Notch Toughness of Carbon and Low-Alloy Steel Forgings for Pressure Vessel and Piping Applications

1978 ◽  
Vol 100 (4) ◽  
pp. 338-347 ◽  
Author(s):  
E. G. Nisbett
Keyword(s):  
Heat Treatment ◽  
Pressure Vessel ◽  
Treatment Process ◽  
Mechanical Test ◽  
Notch Toughness ◽  
Heat Treatment Process ◽  
Low Alloy Steel ◽  
Intercritical Temperature Range ◽  
Factors Affecting

When notch toughness is required in a forging for pressure vessel or piping application, many phases of the manufacturing process are involved. Some significant aspects including the role of the material specification, chemistry balance, mechanical test locations, forging practice and heat treatment are reviewed. A variant of the heat treatment process is described which utilizes quenching from the intercritical temperature range as a means of enhancing notch toughness.

Optimization of Heat Treatment Process of ZE41A Magnesium Alloy Using Grey- Based Taguchi Method

2008 ◽  
Vol 3 (2) ◽  
pp. 63-69
Author(s):  
M. Sivapragash ◽  
◽  
V. Sateeshkumar ◽  
P.R. Lakshminarayanan ◽  
R. Karthikeyan ◽  
...  
Keyword(s):  
Heat Treatment ◽  
Magnesium Alloy ◽  
Taguchi Method ◽  
Treatment Process ◽  
Heat Treatment Process

EFFECT ON HARDNESS and MICRO STRUCTURAL BEHAVIOUR OF TOOL STEEL AFTER HEAT TREATMENT PROCESS

2017 ◽  
Vol 4 (24) ◽  
Author(s):  
Karanbir Singh ◽  
Aditya Chhabra ◽  
Vaibhav Kapoor ◽  
Vaibhav Kapoor
Keyword(s):  
Heat Treatment ◽  
Empirical Study ◽  
Tool Steel ◽  
Treatment Process ◽  
Heat Treatment Process ◽  
Structural Behaviour ◽  
Treatment Processes ◽  
En 31

This study is conducted to analyze the effect on the Hardness and Micro Structural Behaviour of three Sample Grades of Tool Steel i.e. EN-31, EN-8, and D3 after Heat Treatment Processes Such As Annealing, Normalizing, and Hardening and Tempering. The purpose of Selecting Tool Steel is Because Tool Steel is Mostly Used in the Manufacturing Industry.This study is based upon the empirical study which means it is derived from experiment and observation rather than theory.

Failure Analysis on a Counterweight Assembly of an Aeroengine

2011 ◽  
Vol 339 ◽  
pp. 342-348
Author(s):  
Hai Jun Tang ◽  
Hong Yu Yao
Keyword(s):  
Heat Treatment ◽  
Stress Concentration ◽  
Failure Analysis ◽  
Failure Mechanism ◽  
Treatment Process ◽  
Hardness Test ◽  
Heat Treatment Process ◽  
Material Loss ◽  
Structure Strength ◽  
Crucial Part

The paper presents a failure analysis on a counterweight assembly installed on crank shaft which resulted in an in-flight shutdown of a piston aeroengine. The counterweight assembly failure includes counterweight block material loss and fractured washer which is the most crucial part for in-flight shutdown in this type of aeroengine. Macro observation, fractography analysis, metallography analysis and hardness test were conducted on the failed counterweight assembly. The result shows that failure mechanism of counterweight block and washer is fatigue. The washer failure is likely due to inappropriate heat treatment process and continuous impact in flight by slightly tilted roller. Counterweight material loss is attributed to stress concentration, low structure strength and impact came from the tilted roller. Finally some safety suggestion on design and maintenance is given.

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