A method for optimizing silicon carbide vacuum sintering furnace based on computational heat transfer simulation

Abstract

The present invention discloses a method for optimizing a silicon carbide vacuum sintering furnace based on computational heat transfer simulation, comprising the following steps: establishing a heat radiation and heat conduction model of the vacuum sintering furnace during the heating process according to the parameters of the vacuum sintering furnace body; performing computational heat transfer simulation to obtain a temperature rise curve of the vacuum sintering furnace during the entire heating process; optimizing the original furnace type by calculating and comparing the temperature rise curves of workpieces under different heating rates, different graphite heating tube diameters, and different graphite heating tube-to-effective heating zone spacings, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece. The present invention provides a reference for the performance optimization of the vacuum sintering furnace by studying the effects of different heating rates, different graphite heating tube diameters, and different graphite heating tube-to-effective heating zone spacings on the heating efficiency and furnace temperature uniformity of the vacuum sintering furnace, meets the process production requirements of the silicon carbide vacuum sintering furnace, and improves the heating efficiency and furnace temperature uniformity of the heating system.

Description

Technical Field

[0001] The invention relates to the technical field of heat transfer, and in particular to a method for optimizing a silicon carbide vacuum sintering furnace based on computational heat transfer simulation. Background Art

[0002] At present, silicon carbide ceramic products have excellent properties such as high hardness, high temperature strength, strong high temperature oxidation resistance, small thermal expansion coefficient, high thermal conductivity, thermal shock resistance, good thermal stability, good wear resistance and chemical corrosion resistance. They are widely used in the fields of automobiles, mechanical chemicals, environmental protection, space technology, information electronics, aerospace, etc. The pressureless sintering of silicon carbide requires negative pressure debonding, pre-burning, sintering, cooling and other processes. Under the current technical conditions, the production efficiency of the equipment is low and the constant temperature field design is difficult to meet the requirements, resulting in excessive temperature difference inside the workpiece and distortion. Therefore, it is particularly important to optimize the heating system of the vacuum sintering furnace and improve the furnace temperature uniformity and heating efficiency. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a silicon carbide vacuum sintering furnace optimization method based on computational heat transfer simulation with a simple algorithm.

[0004] The technical solution of the present invention to solve the above technical problems is: a method for optimizing a silicon carbide vacuum sintering furnace based on computational heat transfer simulation, comprising the following steps:

[0005] Step 1: Establish the heat radiation and heat conduction model of the vacuum sintering furnace during the heating process according to the parameters of the vacuum sintering furnace body;

[0006] Step 2: Perform computational heat transfer simulation, start the energy equation and discrete ordinate DO radiation model, set temperature monitoring points on the surface and core of the workpiece, and obtain the temperature rise curve of the vacuum sintering furnace during the entire heating process;

[0007] Step 3: By calculating and comparing the workpiece temperature rise curves under different heating rates, different graphite heating tube diameters, different graphite heating tube and effective heating zone spacings, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece, the heating efficiency of the original furnace is optimized while meeting the production process requirement of the temperature difference between the surface and the core of the same workpiece <5°C.

[0008] In the above-mentioned optimization method of silicon carbide vacuum sintering furnace based on computational heat transfer simulation, in step 1, the absolute pressure in the vacuum sintering furnace is 80 Pa, and convection heat transfer is ignored. The energy equation is: Where ρ is the density, kg·m -3 ;c p is the specific heat capacity at constant pressure, J·kg -1 ·K -1 ; T is temperature, K; t is time, s; is the Hamiltonian operator; λ is the thermal conductivity, W·m -1 ·K -1 ; Q is the internal heat source, W·m -3 .

[0009] In the above-mentioned optimization method of silicon carbide vacuum sintering furnace based on computational heat transfer simulation, in step 1, a discrete ordinate DO radiation model is adopted, and the radiation heat transfer model is: Among them, r is the normal vector of the radiation azimuth; l is the radiation length vector along the path, l′ is the scattering direction; α is the material absorption coefficient; σ l is the heat dissipation coefficient; I(r,l) is the radiation intensity; n is the refractive index; σ is the blackbody radiation constant; Φ(l,l′) is the energy source term; Ω′ is the radiation solid angle.

[0010] In the above-mentioned silicon carbide vacuum sintering furnace optimization method based on computational heat transfer simulation, in the step three, the temperature rise curves of the workpieces under different heating rates, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece are compared, and the heating efficiency of the original furnace type is optimized as follows: while meeting the production process requirement that the temperature difference between the surface and the core of the same workpiece is <5°C, the working condition with the largest heating rate is selected. At this time, the time required for the system to heat to the specified temperature is the shortest, and the heating efficiency is the highest.

[0011] In the above-mentioned silicon carbide vacuum sintering furnace optimization method based on computational heat transfer simulation, in the step three, the temperature rise curves of the workpieces under different graphite heating tube diameters, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece are compared, and the heating efficiency of the original furnace type is optimized as follows: under the production process requirement that the temperature difference between the surface and the core of the same workpiece is <5°C, the working condition with the highest workpiece surface temperature and the smallest temperature difference between the vertex workpiece and the center workpiece is selected. At this time, the time required for the system to heat to the specified temperature is the shortest, and the heating efficiency is the highest.

[0012] In the above-mentioned silicon carbide vacuum sintering furnace optimization method based on computational heat transfer simulation, in the step three, the temperature rise curve of the workpiece under different distances between the graphite heating tube and the effective heating zone, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece are compared, and the heating efficiency of the original furnace type is optimized as follows: under the production process requirement that the temperature difference between the surface and the core of the same workpiece is <5°C, the working condition with the highest workpiece surface temperature and the smallest temperature difference between the vertex workpiece and the center workpiece is selected. At this time, the time required for the system to heat to the specified temperature is the shortest, and the heating efficiency is the highest.

[0013] The beneficial effects of the present invention are as follows: the optimization method of the present invention provides a reference for the performance optimization of the vacuum sintering furnace by studying the influence of different heating rates, different graphite graphite heating tube diameters, and different distances between the graphite heating tube and the effective heating zone on the heating efficiency and furnace temperature uniformity of the vacuum sintering furnace; the vacuum sintering furnace heating system optimization scheme is adopted, and after optimization, the heating time is reduced by 60 minutes, the heating efficiency is improved by 30%, the temperature difference between the vertex workpiece and the center workpiece is reduced from 10.85°C to 9.25°C, and the temperature difference between the surface and the core of the same workpiece is <5°C, which meets the process production requirements of the silicon carbide vacuum sintering furnace and improves the heating efficiency and furnace temperature uniformity of the heating system. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The figure is a flow chart of the optimization method of the present invention.

[0015] Figure 2 This is a cross-sectional view of the furnace structure before the vacuum sintering furnace of an embodiment of the present invention is optimized.

[0016] Figure 3 This is a graph showing how the specific heat capacity and thermal conductivity of graphite vary with temperature in an embodiment of the present invention.

[0017] Figure 4 This is a load simulation model diagram of a vacuum sintering furnace according to an embodiment of the present invention.

[0018] Figure 5 Schematic diagram of the position of workpiece monitoring points in an embodiment of the present invention.

[0019] Figure 6 This is a graph showing the temperature rise of a workpiece at different heating rates according to an embodiment of the present invention.

[0020] Figure 7 Schematic diagram of the temperature difference between the vertex workpiece and the center workpiece at different heating rates in an embodiment of the present invention.

[0021] Figure 8 Schematic diagram of the temperature difference between the surface and the core of the same workpiece at different heating rates according to an embodiment of the present invention.

[0022] Fig. 9 This is a graph showing the temperature rise of a workpiece under different heating tube diameters according to an embodiment of the present invention.

[0023] Fig.10 Schematic diagram of the temperature difference between the vertex workpiece and the center workpiece under different heating tube diameters in an embodiment of the present invention.

[0024] Fig.11 Schematic diagram of the temperature difference between the surface and the core of the same workpiece under different heating tube diameters according to an embodiment of the present invention.

[0025] Fig.12 This is a temperature rise curve of the workpiece under different distances between the heating tube and the effective heating area according to an embodiment of the present invention.

[0026] Fig.13 Schematic diagram of the temperature difference between the vertex workpiece and the center workpiece under different distances between the heating tube and the effective heating area in an embodiment of the present invention.

[0027] Fig.14 Schematic diagram of the temperature difference between the surface and the core of the same workpiece at different distances between the heating tube and the effective heating zone according to an embodiment of the present invention.

[0028] Fig.15 This is a cross-sectional view of the furnace body structure after optimization of the vacuum sintering furnace according to an embodiment of the present invention.

[0029] Fig.16 This is a graph showing the temperature rise of the workpiece before and after the optimization of the vacuum sintering furnace system according to an embodiment of the present invention.

[0030] Fig.17 Schematic diagram of the temperature difference between the vertex workpiece and the center workpiece before and after optimization of the vacuum sintering furnace system in an embodiment of the present invention.

[0031] Fig.18 Schematic diagram of the temperature difference between the surface and core of the same workpiece before and after optimization of the vacuum sintering furnace system in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0033] like Figure 1 As shown, a method for optimizing a silicon carbide vacuum sintering furnace based on computational heat transfer simulation comprises the following steps:

[0034] Step 1: Establish the heat radiation and heat conduction model of the vacuum sintering furnace during the heating process according to the parameters of the vacuum sintering furnace body.

[0035] The original furnace type is ZSD4.5-1150C vacuum high temperature sintering furnace. During the heating process of the vacuum sintering furnace, energy is mainly transferred in the form of heat radiation and heat conduction. The gas in the vacuum sintering furnace is extremely rarefied. The absolute pressure in the vacuum sintering furnace is 80Pa. Ignoring convection heat transfer, the energy equation is: Where ρ is the density, kg·m -3 ;c p is the specific heat capacity at constant pressure, J·kg -1 ·K -1 ; T is temperature, K; t is time, s; is the Hamiltonian operator; λ is the thermal conductivity, W·m -1 ·K -1 ; Q is the internal heat source, W·m -3 .

[0036] Using the discrete ordinate DO radiation model, the radiation heat transfer model is: Among them, r is the normal vector of the radiation azimuth; l is the radiation length vector along the path, l′ is the scattering direction; α is the material absorption coefficient; σ l is the heat dissipation coefficient; I(r,l) is the radiation intensity; n is the refractive index; σ is the blackbody radiation constant; Φ(l,l′) is the energy source term; Ω′ is the radiation solid angle.

[0037] The physical properties of the furnace material are shown in Table 1. The rarefied gas density ρ in the furnace is 1×10 -10 kg·m -3 , the thermal conductivity λ is 1×10 -20 W·m -1 ·K -1 , the viscosity coefficient ν is 1×10 -15 kg·m -1 ·s -1 , the absorption coefficient is 1×10 -18 m -1 , the scattering coefficient is 1×10 -18 m -1 , the emissivity ε is 0.50; the specific heat capacity and thermal conductivity of the graphite heating tube change with temperature, such as Figure 3 As shown, piecewise linear function is used in numerical calculation; the graphite heating tube is set as a surface heat source, heated to 1200℃ according to the rated heating rate, and then the temperature is kept constant. It is set as UDF function for heating in simulation calculation; the water cooling system is simplified as a wall surface, which is set as a constant temperature boundary; the initial temperature of the calculation domain is set to T0=25℃.

[0038] Table 1 Physical properties of furnace materials

[0039]

[0040] Step 2: Perform computational heat transfer simulation, start the energy equation and discrete ordinate DO radiation model, set temperature monitoring points on the surface and core of the workpiece, and obtain the temperature rise curve of the vacuum sintering furnace during the entire heating process.

[0041] Step 3: By calculating and comparing the workpiece temperature rise curves under different heating rates, different graphite heating tube diameters, different graphite heating tube and effective heating zone spacings, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece, the heating efficiency of the original furnace is optimized while meeting the production process requirement of the temperature difference between the surface and the core of the same workpiece <5°C.

[0042] The silicon carbide vacuum sintering furnace of the present invention is based on computational heat transfer simulation, and its components are composed of Figure 2 The components of the vacuum sintering furnace shown are the same, mainly including five parts: effective heating zone, graphite heating tube, insulation layer, vacuum insulation chamber, and water cooling system. The process includes negative pressure debonding, pre-firing, sintering and cooling processes. Figure 2 and Fig.15 In the figure, 1 is the water cooling system, 2 is the insulation layer, 3 is the graphite heating tube, 4 is the effective heating area, and 5 is the vacuum insulation chamber. Figure 3 , the specific heat capacity and thermal conductivity of graphite heating tubes change with temperature, and piecewise linear functions are used in numerical calculations. Figure 4 The vacuum furnace load state model has a total of 128 workpieces. The workpiece diameter in the figure is 50mm, and the other structural dimensions of the furnace body are consistent with the no-load model. Figure 5 , intercepting 1 / 2 of the workpiece area, indicating the position of the workpiece monitoring point, the coordinates are S1(75,70,950), C1(75,70,900), S2(225,210,350), C2(225,210,300). Figure 6-Figure 8 As the heating rate increases, the heating time decreases, the temperature difference between the vertex and center of the workpiece increases, and the temperature difference between the surface and the core of the same workpiece increases; at the beginning of heating, the temperature difference of the workpiece increases significantly, then tends to be gentle, and the temperature difference gradually decreases during the insulation period; therefore, under the production process requirement of the temperature difference between the surface and the core of the same workpiece <5℃, the maximum heating rate is selected, that is, the heating rate is 9℃ / min. At this time, the system takes the least time to heat to the specified temperature and the heating efficiency is the highest. Figure 9-11 , the heating rate is constant. As the diameter of the heating tube increases, the surface temperature of the workpiece increases, the temperature difference between the surface and the core of the same workpiece increases, and the temperature difference between the vertex and the center of the workpiece decreases; therefore, under the production process requirement of the temperature difference between the surface and the core of the same workpiece <5°C, the diameter of the heating tube is selected to be 45mm. At this time, the surface temperature of the workpiece is the highest, the temperature difference between the vertex and the center of the workpiece is the smallest, the system takes the least time to heat to the specified temperature, and the heating efficiency is the highest. Figure 12-14 , the heating rate is constant. As the distance between the heating tube and the effective heating zone increases, the heating trends of different workpieces are very close. It can be seen that the change in the distance between the heating tube and the effective heating zone has the least effect on the heating efficiency of the workpiece; therefore, under the production process requirement of the temperature difference between the surface and the core of the same workpiece <5°C, the distance between the heating tube and the effective heating zone is selected to be 50mm. At this time, the surface temperature of the workpiece is the highest, the temperature difference between the vertex workpiece and the center workpiece is the smallest, the time required for the system to heat to the specified temperature is the shortest, and the heating efficiency is the highest.

[0043] See also Fig.15 The characteristics of the high-efficiency vacuum sintering furnace of the present invention are: heating rate of 9°C / min; graphite heating tube diameter of 45mm; distance between graphite heating tube and effective heating zone of 50mm; thickness of insulation layer of 130mm; heating rate is increased relative to the original furnace type, graphite heating tube diameter is increased relative to the original furnace type, and distance between graphite heating tube and effective heating zone is reduced relative to the original furnace type, and the specific dimensions meet the optimization obtained by numerical simulation using computational heat transfer and heat transfer analysis of various structures of vacuum sintering furnace.

[0044] The following is a further description of the present invention using the original furnace type ZSD4.5-1150C vacuum high temperature sintering furnace as the optimization object. Figure 2 . The size of the furnace shell is φ1450mm×2000mm, the size of the effective heating zone is 550mm×500mm×1600mm, the size of the graphite heating tube is φ35mm×600mm, and the distance between the graphite heating tube and the effective heating zone is 65mm; the size of the insulation layer is 1050mm×1000mm×2000mm, and the thickness is 130mm. The design temperature of the vacuum furnace is 1200℃, the design heating rate is 6℃ / min, and the absolute pressure in the furnace is 80Pa. According to the parameters of the vacuum sintering furnace body, a numerical model of thermal radiation and conduction of the vacuum sintering furnace during the heating process is established, and computational heat transfer simulation is carried out to obtain the temperature rise curve of the vacuum furnace during the entire heating process. By calculating and comparing the temperature rise curve of the workpiece under different heating rates, different graphite heating tube diameters, and the distance between the graphite heating tube and the effective heating zone, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece, the original furnace type is optimized. The following modifications were made while keeping the size and thickness of the vacuum furnace shell and insulation layer unchanged: (1) The size of the graphite heating tube was increased from 35 mm to 45 mm. Fig.15 (2) The distance between the graphite heating tube and the effective heating area is reduced from 65mm to 50mm. Fig.15 (3) The heating rate is increased from 6℃ / min to 9℃ / min, as shown in Fig.15 The optimized vacuum furnace was numerically simulated to obtain the workpiece temperature rise curve before and after system optimization, the temperature difference between the vertex workpiece and the center workpiece before and after system optimization, and the temperature difference between the surface and the core of the same workpiece, as shown in Fig.16 , Fig.17 , Fig.18 As shown. Figure 16-Figure 18 It can be seen that after the optimization scheme of the vacuum sintering furnace heating system is adopted, the heating time is reduced by 60 minutes, the heating efficiency is increased by 30%, the temperature difference between the vertex workpiece and the center workpiece is reduced from 10.85℃ to 9.25℃, and the temperature difference between the surface and the inside of the same workpiece is <5℃, which meets the process production requirements of the silicon carbide vacuum sintering furnace and improves the heating efficiency and furnace temperature uniformity of the heating system.

Claims

1. A method for optimizing a silicon carbide vacuum sintering furnace based on computational heat transfer simulation, characterized in that: The following steps are involved: Step 1: Establish the heat radiation and heat conduction model of the vacuum sintering furnace during the heating process according to the parameters of the vacuum sintering furnace body; Step 2: Perform computational heat transfer simulation, start the energy equation and discrete ordinate DO radiation model, set temperature monitoring points on the surface and core of the workpiece, and obtain the temperature rise curve of the vacuum sintering furnace during the entire heating process; Step 3: By calculating and comparing the workpiece temperature rise curves under different heating rates, different graphite heating tube diameters, different graphite heating tube and effective heating zone spacings, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece, the heating efficiency of the original furnace is optimized while meeting the production process requirement that the temperature difference between the surface and the core of the same workpiece is less than 5°C; In the step 3, the temperature rise curves of the workpieces under different heating rates, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece are compared to optimize the heating efficiency of the original furnace type: under the production process requirement that the temperature difference between the surface and the core of the same workpiece is less than 5°C, the working condition with the largest heating rate is selected, at which time the system takes the least time to heat to the specified temperature and the heating efficiency is the highest; In the step 3, the temperature rise curves of the workpieces under different graphite heating tube diameters, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the center of the same workpiece are compared to optimize the heating efficiency of the original furnace type: under the production process requirement that the temperature difference between the surface and the center of the same workpiece is less than 5°C, the working condition with the highest surface temperature of the workpiece and the smallest temperature difference between the vertex workpiece and the center workpiece is selected. At this time, the system takes the least time to heat to the specified temperature and has the highest heating efficiency; In the step three, the temperature rise curves of the workpieces under different distances between the graphite heating tube and the effective heating zone, the temperature difference between the vertex workpiece and the center workpiece, and the temperature difference between the surface and the core of the same workpiece are compared, and the heating efficiency of the original furnace type is optimized as follows: while meeting the production process requirement of the temperature difference between the surface and the core of the same workpiece being <5°C, the working condition with the highest surface temperature of the workpiece and the smallest temperature difference between the vertex workpiece and the center workpiece is selected. At this time, the time required for the system to heat to the specified temperature is the shortest, and the heating efficiency is the highest.

2. The method for optimizing a silicon carbide vacuum sintering furnace based on computational heat transfer simulation according to claim 1, characterized in that: In the step 1, the absolute pressure in the vacuum sintering furnace is 80 Pa, and convection heat transfer is ignored. The energy equation is: Where ρ is the density, kg·m -3 ;c p is the specific heat capacity at constant pressure, J·kg -1 ·K -1 ; T is temperature, K; t is time, s; is the Hamiltonian operator; λ is the thermal conductivity, W·m -1 ·K -1 ; Q is the internal heat source, W·m -3 .

3. The method for optimizing a silicon carbide vacuum sintering furnace based on computational heat transfer simulation according to claim 2, characterized in that: In the step 1, a discrete ordinate DO radiation model is used, and the radiation heat transfer model is: Among them, r is the radiation azimuth normal vector; l is the radiation length vector, l′ is the scattering direction; α is the material absorption coefficient; σ l is the heat dissipation coefficient; I(r,l) is the radiation intensity; n is the refractive index; σ is the blackbody radiation constant; Φ(l,l′) is the energy source term; Ω′ is the radiation solid angle.

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