Gradient simulation method for optimizing hot-rolled plate controlled cooling process

Abstract

The invention discloses a gradient simulation method for optimizing a hot-rolled plate controlled cooling process, and belongs to the technical field of metal material processing. The method comprises the following steps: 1) sampling; 2) sample preparation: processing a sample block into a gradient simulation sample; 3) determining the connection position of the thermocouple; 4) simulating an experiment scheme, namely designing a thermal simulation scheme aiming at the gradient sample by combining the maximum refrigerating capacity of a field production controlled cooling system; 5) mechanical property testing: making a special mechanical experiment scheme according to the characteristics of the comprehensive simulation gradient sample; and (6) experimental data are analyzed, an optimal controlled cooling process window of the hot-rolled plate is obtained, and the field optimization production process is guided. According to the method, the microscopic structure and the mechanical property of the rolled hot-rolled plate produced by a steel mill can be pre-judged in advance, and then the production process of the hot-rolled plate is optimized.

Description

Technical Field

[0001] The present invention belongs to the technical field of metal material processing, and in particular relates to a gradient simulation method for optimizing a controlled cooling process of a hot-rolled plate. Background Art

[0002] Existing technical problems:

[0003] The controlled cooling process after hot-rolled plate rolling directly affects its microstructure and properties (such as grain size, residual stress, hardness, yield strength, impact toughness, etc.). Currently, process optimization is mainly carried out through actual production trial and error or laboratory simulation of single parameters. This is costly, time-consuming, and difficult to fully reflect the coupling of multiple factors. Traditional simulation specimens are mostly conventional homogeneous structures. The simulated specimens cannot simultaneously evaluate the influence of the material's microstructure and grain size at different cooling rates on its important mechanical properties such as hardness, impact toughness, and yield strength. This leads to a large deviation between the simulation results and the actual results.

[0004] Defects of existing technology:

[0005] There is a lack of a comprehensive experimental method that can simultaneously simulate the impact of temperature field on microstructural evolution during the controlled cooling process after hot-rolled plate rolling. Existing specimens cannot quickly and quantitatively evaluate the influence of cooling rate on final properties. Summary of the Invention

[0006] The purpose of the present invention is to provide a gradient simulation method for optimizing the controlled cooling process of hot rolled plates, which is particularly suitable for optimizing and predicting the quality of the controlled cooling process after hot rolled plates are rolled.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0008] The present invention provides a gradient simulation method for optimizing a controlled cooling process of a hot-rolled plate, comprising:

[0009] 1) Sampling: Take samples from the finished hot-rolled plate at 1 / 8, 1 / 4, and 1 / 2 of the plate width, respectively. Take 4 samples at each position and mark them as 1-1 to 1-4, 2-1 to 2-4, and 3-1 to 3-4.

[0010] 2) Sample preparation: process the sample block into a gradient simulation sample

[0011] (1) Specimen dimensions: L1 = 350 mm, a1 = 75 mm, a2 = 60 mm, L2 = 80 mm, b1 = 12 mm, b2 = 10 mm, h1 = 12 mm, h2 = 10 mm, the diameter of the cylinder in the middle is 8 mm;

[0012] (2) Description of sample design principle:

[0013] After the specimens complete the simulation experiment, areas A and B will be used to measure the microstructure, hardness, and impact toughness of the materials under the corresponding controlled cooling regimes; area C will be used to measure the microstructure, strength, yield strength, elongation, and area shrinkage of the materials under the corresponding controlled cooling process. Because there are temperature gradients in areas A, B, and C, the optimal controlled cooling process window can be predicted.

[0014] 3) Determine the thermocouple connection position: Based on the characteristics of the gradient simulation sample, thermocouples need to be connected at the middle positions of A, B, and C respectively. That is, the three sets of thermocouples are monitored and measured simultaneously. The cooling rate in area A is the set cooling rate, and the cooling rates in areas B and C are the monitored cooling rates.

[0015] 4) Simulation experiment plan: Combined with the maximum cooling capacity of the on-site production cooling control system, a thermal simulation plan for gradient specimens was designed;

[0016] 5). Mechanical properties test

[0017] According to the characteristics of comprehensive simulated gradient specimens, a special mechanical experimental plan is formulated:

[0018] (1) The samples that have undergone the thermal simulation experiment are cut along the dividing lines of areas A, B, and C in turn, and the samples in areas A and B are subjected to hardness tests. After the tests, the tested samples are reprocessed to make impact samples and U-shaped openings are opened for room temperature impact tests. The remaining samples that have completed the impact test are subjected to metallographic microstructure observation; the samples in part C are subjected to tensile tests, and their corresponding mechanical parameters such as yield strength are recorded. The broken samples are subjected to metallographic microstructure observation. All the above experimental data are recorded in Table 1.

[0019] 6). Analyze experimental data to obtain the optimal cooling process window for hot-rolled plates and guide on-site optimization of production processes.

[0020] Furthermore, the hot-rolled plate is made of Q345.

[0021] Furthermore, the thickness of the hot-rolled plate is 12 mm.

[0022] Furthermore, the impact specimen has a specification of 10 mm×10 mm×55 mm.

[0023] Furthermore, the inlet temperature range of the hot-rolled plate entering the controlled cooling system is 930°C-950°C, and the outlet temperature range is 590°C-650°C.

[0024] Furthermore, the outlet temperature of the hot-rolled plate entering the controlled cooling system ranges from 590°C to 650°C.

[0025] Furthermore, the microstructure of the hot-rolled plate is F+P.

[0026] Compared with the prior art, the present invention has the following beneficial technical effects:

[0027] The method of the present invention can predict in advance the microstructure and mechanical properties of hot-rolled plates produced by steel mills after rolling, thereby optimizing the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be further described below with reference to the accompanying drawings.

[0029] Figure 1 Schematic diagram of the gradient simulation sample. DETAILED DESCRIPTION

[0030] A gradient simulation method for optimizing the controlled cooling process of hot rolled plates, specifically comprising:

[0031] 1. Sampling: Samples are taken from finished hot-rolled plates made of Q345 with a wall thickness of 12 mm. To ensure the representativeness of the samples, samples are taken from 1 / 8, 1 / 4, and 1 / 2 of the plate width, respectively. Four samples are taken from each position and marked as 1-1 to 1-4, 2-1 to 2-4, and 3-1 to 3-4.

[0032] 2. Sample preparation: process the sample block into Figure 1 The gradient simulation specimen shown (see Figure 1 ).

[0033] (1) Specimen dimensions: (L1 = 350 mm, a1 = 75 mm, a2 = 60 mm, L2 = 80 mm, b1 = 12 mm, b2 = 10 mm, h1 = 12 mm, h2 = 10 mm), the diameter of the cylinder in the middle is 8 mm.

[0034] (2) Description of sample design principle:

[0035] After the specimens complete the simulation experiment, Areas A and B will be used to measure the material's microstructure, hardness, and impact toughness under the corresponding controlled cooling regime. Area C will be used to measure the material's microstructure, strength, yield strength, elongation, and area reduction under the corresponding controlled cooling process. Because temperature gradients exist between Areas A, B, and C, the optimal controlled cooling process window can be predicted.

[0036] 3. Determine the connection position of the thermocouple: According to the characteristics of the gradient simulation sample, thermocouples need to be connected at the middle positions of A, B, and C respectively, that is, the three groups of thermocouples are monitored and measured simultaneously, where the cooling rate in area A is the set cooling rate, and the cooling rates in areas B and C are the monitored cooling rates.

[0037] 4. Simulation experiment plan: Based on the maximum cooling capacity of the on-site production cooling control system, a thermal simulation plan for gradient specimens is designed.

[0038] 5. Mechanical properties test: Develop a special mechanical experimental plan based on the characteristics of the comprehensive simulated gradient specimen.

[0039] (1) The samples that have undergone the thermal simulation test were cut along the dividing lines of areas A, B, and C. The samples in areas A and B were subjected to hardness tests. After the tests, the tested samples were reprocessed to produce impact specimens with a specification of 10mm×10mm×55mm (with a U-shaped opening). The room temperature impact test was carried out. The remaining samples that completed the impact test were subjected to metallographic microstructure observation; the samples in part C were subjected to tensile tests, and their corresponding mechanical parameters such as yield strength were recorded. The broken samples were also subjected to metallographic microstructure observation. All the above experimental data are recorded in Tables 1 to 3.

[0040] 5. Analyze experimental data to obtain the optimal cooling process window for Q345 hot-rolled plates, and guide on-site optimization of production processes.

[0041] Table 1. Simulation results of area A

[0042]

[0043] Table 2. Monitoring results of area B

[0044]

[0045] Table 2. Monitoring results of Area C

[0046]

[0047] Analyzing the data, we concluded:

[0048] Combined with the simulated temperature of zone A, the monitored temperature of zones B and C, and the microstructure and mechanical properties of the comprehensive simulated gradient specimen, it can be seen that when the hot-rolled plate Q345 used in the experiment enters the controlled cooling system at an inlet temperature range of (930°C-950°C) and an outlet temperature range of (590°C-650°C), the corresponding microstructure (both F+P) and mechanical properties meet the product standard requirements. Beyond this temperature range, the product microstructure is (F+P+B) and the mechanical properties fluctuate greatly, failing to meet the product standard requirements. Therefore, the inlet temperature range of the hot-rolled plate with a thickness of 12mm and made of Q345 entering the controlled cooling system is 930°C-950°C, and the outlet temperature range is 590°C-650°C.

[0049] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A gradient simulation method for optimizing the controlled cooling process of hot rolled plates, characterized in that: include: 1) Sampling: Take samples from the finished hot-rolled plate at 1 / 8, 1 / 4, and 1 / 2 of the plate width, respectively. Take 4 samples at each position and mark them as 1-1 to 1-4, 2-1 to 2-4, and 3-1 to 3-4. 2) Sample preparation: process the sample block into a gradient simulation sample (1) Specimen dimensions: L1 = 350 mm, a1 = 75 mm, a2 = 60 mm, L2 = 80 mm, b1 = 12 mm, b2 = 10 mm, h1 = 12 mm, h2 = 10 mm, the diameter of the cylinder in the middle is 8 mm; (2) Description of sample design principle: After the specimens complete the simulation experiment, areas A and B will be used to measure the microstructure, hardness, and impact toughness of the materials under the corresponding controlled cooling regimes; area C will be used to measure the microstructure, strength, yield strength, elongation, and area shrinkage of the materials under the corresponding controlled cooling process. Because there are temperature gradients in areas A, B, and C, the optimal controlled cooling process window can be predicted. 3) Determine the thermocouple connection position: Based on the characteristics of the gradient simulation sample, thermocouples need to be connected at the middle positions of A, B, and C respectively. That is, the three sets of thermocouples are monitored and measured simultaneously. The cooling rate in area A is the set cooling rate, and the cooling rates in areas B and C are the monitored cooling rates. 4) Simulation experiment plan: Combined with the maximum cooling capacity of the on-site production cooling control system, a thermal simulation plan for gradient specimens was designed; 5). Mechanical properties test According to the characteristics of comprehensive simulated gradient specimens, a special mechanical experimental plan is formulated: (1) The samples that have undergone the thermal simulation experiment are cut along the dividing lines of areas A, B, and C in turn, and the samples in areas A and B are subjected to hardness tests. After the tests, the tested samples are reprocessed to make impact samples and U-shaped openings are opened for room temperature impact tests. The remaining samples that have completed the impact test are subjected to metallographic microstructure observation; the samples in part C are subjected to tensile tests, and their corresponding mechanical parameters such as yield strength are recorded. The broken samples are subjected to metallographic microstructure observation. All the above experimental data are recorded in Table 1. 6). Analyze experimental data to obtain the optimal cooling process window for hot-rolled plates and guide on-site optimization of production processes.

2. The gradient simulation method for optimizing the controlled cooling process of hot rolled plate according to claim 1, characterized in that: The hot-rolled plate is made of Q345.

3. The gradient simulation method for optimizing the controlled cooling process of hot rolled plate according to claim 1, characterized in that: The thickness of the hot-rolled plate is 12 mm.

4. The gradient simulation method for optimizing the controlled cooling process of hot rolled plate according to claim 1, characterized in that: The impact specimen has a specification of 10 mm×10 mm×55 mm.

5. The gradient simulation method for optimizing the controlled cooling process of hot rolled plate according to claim 1, characterized in that: The inlet temperature range of hot-rolled plates entering the controlled cooling system is 930℃-950℃, and the outlet temperature range is 590℃-650℃.

6. The gradient simulation method for optimizing the controlled cooling process of hot rolled plate according to claim 5, characterized in that: The outlet temperature of hot rolled plates entering the controlled cooling system ranges from 590°C to 650°C.

7. The gradient simulation method for optimizing the controlled cooling process of hot rolled plate according to claim 6, characterized in that: The microstructure of the hot-rolled plate is F+P.

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