Prediction and Key Computer Programming of Mechanical Properties of Hot Rolled Plate Based on BP Neural Network

2009 ◽  
Author(s):  
Qinghua Zou ◽  
Li Chen ◽  
Naixue Xiong ◽  
Shengzhong Zou ◽  
Chuanbing Wang
Keyword(s):  
Neural Network ◽  
Mechanical Properties ◽  
Bp Neural Network ◽  
Computer Programming ◽  
Rolled Plate ◽  
Hot Rolled

Correlation among Microstructure, Texture, and Properties along the Thickness Direction in As-Hot-Rolled and As-Solution-Quenched Al7055 Thick Plates

2021 ◽  
Vol 1026 ◽  
pp. 65-73
Author(s):  
Kai Zhu ◽  
Hong Wei Yan
Keyword(s):  
Mechanical Properties ◽  
Yield Strength ◽  
Tensile Tests ◽  
Rolled Plate ◽  
Uniaxial Tensile ◽  
Thickness Direction ◽  
Electron Backscattered Diffraction ◽  
Thick Plates ◽  
Aluminum Plates ◽  
Hot Rolled

Both microstructure inhomogeneity and mechanical property diversity along the thickness direction in rolled thick aluminum plates have been considered to have a remarkable impact on the performance and properties of the products made from the plates. In this study, scanning electron microscopy (SEM) and electron backscattered diffraction (EBSD) characterizations of microstructure and texture types along the thickness directions of Al7055 thick plate specimens prepared using two conditions, hot-rolling and solution-quenching, were performed. To examine the mechanical properties, uniaxial tensile tests were also carried out on specimens machined from both types of thick plates, using a layered strategy along the thickness direction. The results indicate that both the microstructure and mechanical properties are inhomogeneous under the two conditions. Furthermore, it is evident that there is a hereditary relationship between the mechanical properties of the two plates—areas with higher yield strength in the as-hot-rolled plate correspond to areas with the higher yield strength in the as-solution-quenched plate

Application of Quenching-Partitioning-Tempering Process in Hot Rolled Plate Fabrication

2010 ◽  
Vol 654-656 ◽  
pp. 82-85 ◽  
Author(s):  
Shu Zhou ◽  
Ying Wang ◽  
Nai Lu Chen ◽  
Yong Hua Rong ◽  
Jian Feng Gu
Keyword(s):  
Mechanical Properties ◽  
Retained Austenite ◽  
High Strength Steels ◽  
High Strength ◽  
Significant Fraction ◽  
Rolled Plate ◽  
Quenching And Partitioning ◽  
Good Ductility ◽  
Hot Rolled ◽  
Rolled Plates

The quenching-partitioning-tempering (Q-P-T) process, based on the quenching and partitioning (Q&P) treatment, has been proposed for producing high strength steels containing significant fraction of film-like retained austenite and controlled amount of fine martensite laths. In this study, a set of Q-P-T processes for C-Mn-Si-Ni-Nb hot rolled plates are designed and realized. The steels with Q-P-T processes present a combination of high strength and relatively good ductility. The origin of such mechanical properties is revealed by microstructure characterization.

Study on Sensor with Mechanical Properties in Nuclear Power Plant with Application of BP Neural Network to Fault Tolerant Control

2013 ◽  
Vol 644 ◽  
pp. 56-59
Author(s):  
Jin Yang Li ◽  
Hong Xia ◽  
Shou Yu Cheng
Keyword(s):  
Neural Network ◽  
Mechanical Properties ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Bp Neural Network ◽  
Nuclear Power ◽  
Control Method ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Level Sensor

All kinds of sensor with mechanical properties often can go wrong in nuclear power plant. In this kind of situation, it puts forward a kind of active fault tolerant control method based on the improved BP neural network. Firstly, the method will train sensor by BP neural network. Secondly, it will be established dynamic model bank in all kinds of running state. The system will be detected by using BP neural network real time. When the sensor goes wrong, it will be controled by reconstruction. Taking pressurizer water-level sensor as the case, a simulation experiment was performed on the nuclear power plant simulator. The results showed that the proposed method is valid for the fault tolerant control of sensor in nuclear power plant.

Prediction of Coiling Temperature of Hot Rolled Strip Based on BP Neural Network

2014 ◽  
Vol 633-634 ◽  
pp. 679-683
Author(s):  
En Yang Liu ◽  
Wen Peng ◽  
Ning Cao ◽  
Si Rong Yu ◽  
Jun Xu ◽  
...  
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Rolled Strip ◽  
Laminar Cooling ◽  
Coiling Temperature ◽  
Online Application ◽  
Hot Rolled Strip ◽  
Highly Nonlinear ◽  
Rolling Plant ◽  
Hot Rolled

Coiling temperature of hot rolled strip is one of the important parameters which affect performances of hot rolled strip. The control of coiling temperature is highly nonlinear and time-varying. Based on the laminar cooling control system of a hot rolling plant, a coiling temperature prediction model based on BP neural network was established. Many factors which affect coiling temperature control were taken into account, and the BP neural network was trained by actual production data. The simulation was carried out, which indicates that coiling temperature can be predicted precisely, and the BP neural network model has the prospect of online application.

Prediction of Heating Processing-Properties of Ti2AlC/TiAl Compound Materials Based on BP Neural Network

2011 ◽  
Vol 306-307 ◽  
pp. 823-826
Author(s):  
Ming Wen ◽  
Yun Long Yue ◽  
Hai Tao Zhang ◽  
Yang Li
Keyword(s):  
Neural Network ◽  
Mechanical Properties ◽  
Heat Treatment ◽  
Bp Neural Network ◽  
Bending Strength ◽  
Treatment Temperature ◽  
Preparation Technology ◽  
Bp Artificial Neural Network ◽  
Processing Properties ◽  
Compound Materials

Parameters of processing (heat treatment temperature, holding time) and properties (Bending strength and Microhardness) of Ti2AlC/TiAl compound materials were obtained through mechanical properties examination, the network model was built by BP artificial neural network. The results show that the built model can reflect the relationships between processing and properties very well and has certain accuracy. It can be used for the prediction of the properties of Ti2AlC/TiAl compound materials after heating processing under different experiment conditions. Meanwhile, the model can also serve as a guide for the preparation technology of Ti2AlC/TiAl compound materials.

Performance Analysis of Bentonite-PVA Fiber Cement-Based Composites for Building Based on BP Neural Network

2020 ◽  
Vol 852 ◽  
pp. 209-219
Author(s):  
Zhe Shen
Keyword(s):  
Neural Network ◽  
Mechanical Properties ◽  
Thermal Conductivity ◽  
Composite Materials ◽  
Influencing Factors ◽  
Bp Neural Network ◽  
Analysis Method ◽  
System Input ◽  
Prediction And Simulation ◽  
Pva Fiber

The paper will use BP neural network analysis method to study the thermal conductivity of bentonite and its influencing factors as a system. The heat conduction of bentonite was used as the output of the system, and its influencing factors were used as the system input to simulate. The corresponding simulation model was established to verify the thermal conductivity data. In addition, the analysis of the mechanical properties of the bentonite-PVA fiber cement-based composite materials for construction has not only laid a theoretical and realistic foundation for the prediction and simulation of the thermal conductivity of bentonite, but also has opened up the mechanical properties of the bentonite-PVA fiber cement-based composite materials a new path.

Thixoforming of Semisolid Slurry with High Fraction Solid Fabricated by Partial Melting of Commerical Wrought Aluminum Alloys

2019 ◽  
Vol 285 ◽  
pp. 210-218
Author(s):  
Ju Fu Jiang ◽  
Ying Zhe Liu ◽  
Guan Fei Xiao ◽  
Ying Wang
Keyword(s):  
Mechanical Properties ◽  
Partial Melting ◽  
Recrystallization Temperature ◽  
Rolled Plate ◽  
Continuous Heating ◽  
Semisolid Slurry ◽  
Semisolid State ◽  
High Fraction ◽  
Hot Rolled ◽  
Wrought Aluminum

Semisolid slurries of four wrought alloys were fabricated via partial melting of commerical wrought aluminum alloy. Thixoforming experiments of four typical parts were performed. The results showed that a large amount of equiaxed grains before soaking in semisolid state were created due to recrystallization occurred in the continuous heating from room temperature to a given temperature above recrystallization temperature. It provides a desirable microstructure to form spheroidal grains during the next soaking process in semisolid state. The microstructure of the 2A12,7A04 and 7075 semisolid slurry consisted of fine and spheroidal grains. The elongation of the thixoformed parts were higher those of the hot-rolled plate. The UTS of the thixoformed parts were close or ever higher than those of the hot-rolled plate. Although the grain size and roundness of the 5A06 semisolid slurry are not very desirable, the mechanical properties of the thixoformed part are close or ever than those of the hot-rolled plate. The high mechanical properties of the thixoformed parts further confirmed the feasibility of short-process thixoforming route

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