CN-121980758-A - Blast furnace burden porosity calculation method based on Monte Carlo algorithm

CN121980758ACN 121980758 ACN121980758 ACN 121980758ACN-121980758-A

Abstract

The invention discloses a blast furnace burden porosity calculation method based on a Monte Carlo algorithm, and belongs to the technical field of blast furnace ironmaking. The method comprises the steps of firstly, randomly sampling to generate the particle size of furnace charge particles according to a particle size distribution probability density function by adopting Monte Carlo, initializing, then, in a three-dimensional Cartesian coordinate system, searching space positions of newly added particles in an existing stacking system by constructing and solving a three-ball contact geometric constraint equation set, dynamically adjusting the searching radius of supporting particles and executing collision detection, and finally, calculating total volume and particle volume in a set spherical calculation domain after the total number of particles reaches a preset threshold value, and determining the porosity by adopting a moving average and moving variance statistical method. The invention overcomes the limitations of the traditional experimental method and the existing numerical model, realizes high-precision and high-efficiency calculation of the porosity of the blast furnace burden, and provides a reliable theoretical tool for optimizing the blast furnace burden distribution system and the air permeability analysis.

Inventors

GUO XIAOLIANG
YANG YANCHEN
CUI MENG
SHEN ZHIQIANG
LI ZHIYONG
ZHANG WENZHENG
Dong Guanqiu
MIAO GUANGZHI
SHI BAOLAI
FAN MIN

Assignees

天津市新天钢联合特钢有限公司

Dates

Publication Date: 20260505
Application Date: 20251224

Claims (10)

1. A blast furnace burden porosity calculation method based on a Monte Carlo algorithm is characterized by comprising the following steps: S1, on-site sampling to obtain duty ratio data of particles with different particle sizes, generating the particle size of furnace charge particles by adopting a Monte Carlo random sampling method, and initializing the radius and the center coordinate of each particle; Step S2, searching a stable space position for newly generated particles in an existing particle stacking system based on a sphere geometric equation, specifically, selecting at least three existing particles as supporting points, constructing a three-sphere contact geometric constraint equation set, solving the equation set to obtain the center coordinates of the newly added particles, selecting a set from the solution set to serve as the placement position of the newly added particles if a real solution exists in the equation set, and re-selecting the supporting particles and repeating calculation until a physically realizable stable stacking configuration is obtained if no solution exists; step S3, dynamically adjusting the radius C of a sphere generating area for screening the supporting particles, and after determining the temporary position of the newly added particles, executing collision detection to verify that the newly added particles and all existing particles meet non-overlapping geometric conditions; And S4, after the total number of the generated particles reaches a preset threshold, setting a spherical calculation domain with the radius of S by taking a coordinate origin as a center, calculating the total volume in the calculation domain and the total volume occupied by all particles in the calculation domain, determining the porosity according to the ratio of the difference between the total volume and the total volume of the calculation domain, and processing the porosity values of a plurality of sub-samples continuously generated by adopting a moving average and moving variance statistical method in the calculation process so as to evaluate the convergence and stability of a calculation result.
2. The method according to claim 1, wherein in the step S2, the initial particle accumulation system is composed of three spherical particles having equal radii, circumscribed each other and having spherical centers on the same horizontal plane to form an equilateral triangle layout.
3. The method according to claim 1, wherein in the step S2, the supporting point is selected by generating a sphere with the origin of coordinates as the center and the dynamically adjusted radius C as the radius, randomly selecting a point P on the surface of the sphere, and then searching three existing particles nearest to the point P as the supporting point.
4. A method of computing according to claim 3, wherein the set of three-sphere contact geometry constraint equations is as follows: wherein r represents the radius of the new particle falling, the radius of the three support particles is r i , wherein i=1, 2 and 3, (x, y and z) represents the position of the new particle after being stably placed on other particles, and the central coordinates of the three support particles are (x i ,y i ,z i ).
5. The calculation method according to claim 1, wherein the specific strategy for dynamically adjusting the radius C of the sphere generating area in step S3 is: initially, setting C as a first preset value; When the attempt to generate the newly added particles fails, increasing C by one-N times the radius of the smallest particles in the current particle system, wherein N is an integer greater than 1; When the newly added particles are successfully generated, C is reduced by the value of the maximum particle radius in the current particle system.
6. The method according to claim 1, wherein the collision detection in step S3 is to verify whether the geometric distance between the temporary position of the newly added particle and all the existing particles satisfies a non-overlapping condition, that is, the square of the center-to-center distance between the newly added particle and any existing particle is greater than the square of the sum of the radii of the two, and if any particle that does not satisfy the condition exists, it is determined that a volumetric collision occurs, and the support points need to be selected again and calculated iteratively until a non-overlapping and stable particle configuration is generated.
7. The method of claim 6, wherein the collision detection method comprises determining that if the radius and coordinates of the existing particles are r j and (x i ,y i ,j i ), respectively, the following conditions are: ; if any existing particle satisfies the inequality, the collision is determined, the temporary position is abandoned, and the flow returns to the step 2 to reselect the supporting point.
8. The method according to claim 1, wherein in the step S4, the porosity is calculated by using an origin as a center, and the calculation region is a sphere with a radius S, and the total volume is: ; The total volume of the particles is recorded as V b , and the calculation formula of the pore p of the stacking system is as follows by accumulating all the particle volumes completely located in the calculation domain: 。
9. The method according to claim 1, wherein in step S4, the effective volume of the particle intersecting the boundary of the calculation domain is calculated by calculating the spherical cap volume of the particle located in the calculation domain when calculating the total volume occupied by the particle in the calculation domain.
10. The calculation method according to claim 1, wherein the calculated domain radius S set in the step 4 is not less than 50 times the maximum particle diameter, and the distance between the calculated domain boundary and the nearest particle is not less than 10 times the minimum particle diameter.

Description

Blast furnace burden porosity calculation method based on Monte Carlo algorithm Technical Field The invention belongs to the technical field of blast furnace ironmaking, and particularly relates to a blast furnace burden porosity calculation method based on a Monte Carlo algorithm. Background Blast furnace iron making is one of the core processes in steel production, and its efficiency and quality directly affect the performance and cost of steel products. In the blast furnace smelting process, the porosity of the furnace burden is a key factor influencing the air permeability and smelting efficiency of the blast furnace. The porosity not only determines the distribution of the air flow in the furnace and the heat and mass transfer efficiency, but also directly influences the stability and the production efficiency of the blast furnace. Therefore, the accurate calculation of the porosity of the furnace burden has important significance for optimizing the operation of the blast furnace and improving the smelting efficiency. Traditional furnace burden porosity measurement methods mainly depend on experimental means, such as mercury porosimetry, gas adsorption methods and the like. However, these methods have a large limitation in complex particle systems, and it is difficult to accurately capture the stacking state and pore distribution characteristics between particles. In addition, the experimental method generally requires a lot of time, manpower and material resources, and is difficult to meet the requirements of real-time monitoring and optimization of the blast furnace. In recent years, with the development of computer technology and numerical simulation methods, a numerical simulation-based aperture ratio calculation method has become a research hotspot. The Monte Carlo algorithm is used as a classical random sampling method, can simulate the stacking process of particles through a large number of random tests, and accurately calculates the porosity. Compared with the traditional deterministic method, the Monte Carlo algorithm has the advantages of strong adaptability, high calculation precision, wide application range and the like, and is particularly suitable for simulation and analysis of complex particle systems. Aiming at the problems, the invention provides a blast furnace burden porosity calculation method based on a Monte Carlo algorithm. The method realizes high-precision calculation of the porosity of the blast furnace burden by optimizing the methods of particle generation and initialization, geometric description of particle accumulation, support particle selection and collision detection and void fraction calculation and statistics. The invention not only can provide a reliable theoretical tool for optimizing the blast furnace burden structure and analyzing the air permeability, but also can provide scientific basis for energy conservation, consumption reduction and high-efficiency production of the blast furnace ironmaking process, and has important theoretical value and practical application significance. Disclosure of Invention The invention aims to provide a blast furnace burden porosity calculation method based on a Monte Carlo algorithm, which can accurately calculate the burden porosity by simulating the stacking process of burden particles and provide scientific basis for optimizing the blast furnace burden structure and analyzing the air permeability. The invention discloses a blast furnace burden porosity calculation method based on a Monte Carlo algorithm, which comprises the following steps: S1, on-site sampling to obtain duty ratio data of particles with different particle sizes, generating the particle size of furnace charge particles by adopting a Monte Carlo random sampling method, and initializing the radius and the center coordinate of each particle; Step S2, searching a stable space position for newly generated particles in an existing particle stacking system based on a sphere geometric equation, specifically, selecting at least three existing particles as supporting points, constructing a three-sphere contact geometric constraint equation set, solving the equation set to obtain the center coordinates of the newly added particles, selecting a set from the solution set to serve as the placement position of the newly added particles if a real solution exists in the equation set, and re-selecting the supporting particles and repeating calculation until a physically realizable stable stacking configuration is obtained if no solution exists; step S3, dynamically adjusting the radius C of a sphere generating area for screening the supporting particles, and after determining the temporary position of the newly added particles, executing collision detection to verify that the newly added particles and all existing particles meet non-overlapping geometric conditions; And S4, after the total number of the generated particles reaches a preset threshold, setting a spherical calcula