CN105136623A - Potential energy change based method for quantitatively characterizing packing segregation state of particles after falling - Google Patents
Potential energy change based method for quantitatively characterizing packing segregation state of particles after falling Download PDFInfo
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Abstract
The invention discloses a potential energy change based method for quantitatively characterizing the packing segregation state of particles after falling. The method comprises the following steps: (1), establishing a batching model with SolidWorks; (2), introducing the batching model into LIGGGHTS; (3), establishing particle models with two particle diameters in the LIGGGHTS; (4), performing an analog experiment; (5), substituting recorded data into a segregation index calculation model after the analog experiment is finished to obtain a segregation index. The method can be used for quantitatively characterizing the mixing uniformity degree of particles with different particle diameters and the segregation degree of the particles after falling, thereby reducing the energy consumption effectively and prompting energy conservation and emission reduction.
Description
Technical field
The present invention relates to metallurgical engineering technical field, particularly relating to a kind of method based on piling up segregation status after potential variation quantitatively characterizing particles fall.
Background technology
In recent years, iron and steel situation is increasingly severe, how further to reduce smelting cost and reduces energy ezpenditure simultaneously, significant for iron and steel enterprise.Blast furnace ironmaking is as the energy consumption rich and influential family in whole technological process, and iron and steel enterprise focuses on saving blast furnace raw material more.In actual production in the past, for ensureing the direct motion of the working of a furnace, for sintering deposit, usually, require that the particle diameter into stove sintering deposit is greater than 5mm, therefore sieve sintering deposit all will turn back to sintering plant again to sinter, a large amount of returning charges not only increases raw materials cost, also increases transportation cost.Therefore, in the last few years, a lot of iron and steel enterprise started to attempt using small particle diameter furnace charge in production practices.Reduce blast furnace feeding furnace size lower limit, heating and the reducing condition of iron-bearing material will be improved widely, and make to be carried out fully in " preprocessing " process of shaft part.But on the other hand, due to the expansion of furnace charge particle size range, in blast furnace material distribution process, more easily there is the phenomenon of particle diameter segregation distribution, easily cause the voidage of local, the furnace throat place bed of material to reduce and pressure reduction rising, directly affect being uniformly distributed of Gas Flow, the direct motion of the remote effect working of a furnace then.
For particle diameter segregation, forefathers carry out a large amount of research work, and it focuses on the degree being weighed particle diameter segregation by the osmosis of resolving between particle.Meanwhile, along with improving constantly of calculating simulation technical merit, wherein, discrete element method (DEM) take individual particle as object, based on Newton second law, directly can simulate translation and the rotary state of particle, therefore the osmosis between research particle plays important role.Particularly along with the continuous enhancing of computing power, DEM is more and more extensive in the application in simulation particle flow field.
Rahman adopts the method for DEM numerical simulation, research packed bed endoparticle phenomenon of osmosis, investigates the regularity of distribution of the seepage velocity under different condition, the residence time and radial dissipation degree.Zhu is equally based on DEM method for numerical simulation, and further the self-characteristic of research particle is to chemosmotic affecting laws, and result shows the ratio of damping of particle and particle diameter than being affect two key factors interpenetrating effect between particle.
Between research particle on chemosmotic basis, in conjunction with blast fumance reality, researcher sets about the research carrying out particle diameter segregation related work.Inada develops mathematical model based on there being bell blast furnace, and under preset parameter, investigate the regularity of distribution of radial particle diameter, its propose particle diameter between bulky grain and granule than and particle velocity gradient be on the slope affect particle diameter segregation to distribute of paramount importance two factors.Li Qiang studies the cloth process of COREX-3000 shaft furnace furnace roof, and chute change of pitch angle is remarkable on the radially-arranged impact of bulk density, and inclination angle increases, and bulk density minimum value moves to furnace wall side.Therefore, also there is material impact for particle in the segregation distribution of radial direction in chute inclination angle.When Mio takes DEM method to observe the change of chute inclination angle equally, granule and bulky grain move and layering occur on chute, and wherein the former is close to chute walls the latter then away from bottom chute.
Domestic to use small particle diameter furnace charge and particle diameter segregation phenomena occurs at present, mainly through changing cloth condition, analyze particle diameter Rule of Segregation from final Particles Distribution, lack the collision behavior shown in whole flow process in conjunction with particle to a certain extent and in conjunction with key history parameters to dissect the general rule of multicompentnt granular particle diameter segregation.Therefore, particle diameter segregation behavior, the particularly small particle diameter furnace charge segregation regularity of distribution in cloth process in research cloth process, using for blast furnace and playing small grain size furnace charge advantage and save energy and reduce the cost all has important directive significance.
Summary of the invention
For prior art above shortcomings, the object of the invention is to how to solve the problem in existing cloth, size segregation being lacked to general rule, a kind of method based on piling up segregation status after potential variation quantitatively characterizing particles fall is provided, effectively can reduce energy consumption, promote energy-saving and emission-reduction.
In order to solve the problems of the technologies described above, the technical solution used in the present invention is such: a kind of method based on piling up segregation status after potential variation quantitatively characterizing particles fall, is characterized in that: comprise the following steps:
1) three-dimensional drawing software SolidWorks is utilized to set up an Alloying Ingredient Model be made up of distributing device and charge can;
2) Alloying Ingredient Model that step 1) is set up is imported in simulation software LIGGGHTS;
3) in simulation software LIGGGHTS, set up the granular model of two kinds of particle diameters, and arrange the basic parameter of Alloying Ingredient Model and the basic parameter of granular model, make Alloying Ingredient Model form analog ligand materials device, granular model forms simulation particle;
4) simulated experiment, after being mixed by simulation particle, loads distributing device, record the state parameter of now each simulation particle by different proportion; After treating simulation particles fall to charge can redistribution, again record the state parameter of each simulation particle;
5) after simulated experiment completes, recorded data is substituted into segregation index and resolve model, obtain segregation index, wherein, described segregation index resolves model and is:
K=|A
just-A
end|/A
just* 100%;
In formula, K is segregation index, A
justfor A particle potential energy under original state and the ratio of total potential energy, A
endfor A particle potential energy under last current state and the ratio of total potential energy.
Further, the height of the geomery of basic parameter distributing device of described Alloying Ingredient Model, the geomery of charge can and distributing device and charge can.
Further, the basic parameter of granular model comprises the ratio between coefficient of restitution between friction factor between particle diameter, particle Young modulus, particle Poisson ratio, particle density, the friction factor between particle and wall, the coefficient of restitution between particle and wall, particle, particle and variable grain.
Further, the simulation graininess parameter recorded comprises speed and the friction force of the simulation numbering of particle, the coordinate of three-dimensional system of coordinate Imitating particle, X-axis, Y-axis and Z axis.
Compared with prior art, tool of the present invention has the following advantages:
1, the present invention can to the quantitatively characterizing of size segregation rule, and the degree of uniformity mixed between particle is high, and experimental technique is easy to operate, and reading error is little, can obtain a large amount of experimental datas, thus makes segregation status characterization accuracy higher.
2, the present invention utilizes numerical simulation, adopts discrete element method, utilizes the accurate tracking of numerical simulation, give record to the state of each particle, analyzes the state of data quantitative characterizing particles distribution; Potential variation situation before and after count particles under state, thus Accurate Analysis is carried out to segregation index; To make in actual production process, effectively can reduce energy consumption, promote energy-saving and emission-reduction.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of Alloying Ingredient Model of the present invention.
Fig. 2 is the Particles Distribution figure before simulated experiment starts.
Fig. 3 is the Particles Distribution figure after simulation test completes.
In figure: 1-distributing device, 2-feed opening, 3-charge can.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described.
Embodiment: see Fig. 1, Fig. 2 and Fig. 3, a kind of method based on piling up segregation status after potential variation quantitatively characterizing particles fall, comprises the following steps:
1) three-dimensional drawing software SolidWorks is utilized to set up an Alloying Ingredient Model be made up of distributing device 1 and charge can 3.Wherein, described distributing device 1 is positioned at above charge can 3, and its upper end is feeding port, and lower end is feed opening 2, and its underpart is closing-in structure; The section of the inner chamber of described charge can 3 is rectangular configuration, and its upper end is open, and the aperture of charge can 3 upper end is greater than the aperture of distributing device 1 feed opening 2.
2) Alloying Ingredient Model that step 1) is set up is imported in (computer numerical) simulation software LIGGGHTS.
3) in simulation software LIGGGHTS, set up the granular model of two kinds of particle diameters, and the basic parameter of Alloying Ingredient Model and the basic parameter of granular model are set, wherein, the granular model of two kinds of particle diameters, except particle diameter is different, other factors are all identical, and make Alloying Ingredient Model form analog ligand materials device, and granular model forms simulation particle.Wherein, the height of the geomery of the basic parameter distributing device 1 of described Alloying Ingredient Model, the geomery of charge can 3 and distributing device 1 and charge can 3, its design parameter depends on testing program.The basic parameter of granular model comprises the ratio (particle of different-grain diameter mixes according to different mass ratioes when gross mass is certain) between coefficient of restitution between friction factor between particle diameter, particle Young modulus, particle Poisson ratio, particle density, the friction factor between particle from wall, the coefficient of restitution between particle with wall, particle, particle and variable grain.
4) simulated experiment, after being mixed by simulation particle, loads distributing device 1, record the state parameter of now each simulation particle by different proportion; After treating simulation particles fall to charge can 3 redistribution, again record the state parameter of each simulation particle; The simulation graininess parameter recorded comprises speed and the friction force of the simulation numbering of particle, the coordinate of three-dimensional system of coordinate Imitating particle, X-axis, Y-axis and Z axis.
5) after simulated experiment completes, recorded data is substituted into segregation index and resolve model, obtain segregation index, wherein, described segregation index resolves model and is:
K=|A
just-A
end|/A
just* 100%;
In formula, K is segregation index, A
justfor A particle potential energy under original state and the ratio of total potential energy, A
endfor A particle potential energy under last current state and the ratio of total potential energy.
The present invention is based on the discrete element method in numerical simulation, the Alloying Ingredient Model first utilizing SolidWorks software to set up a distributing device and charge can to form; Experimentally require to arrange corresponding experiment parameter; Run LIGGGHTS software, the state after the mixed packing of simulation particle, and the state after particles fall, be numbered each particle, and by following the trail of, generate each step relevant status data at present simultaneously; After experiment terminates, analyzing and processing is carried out to data.The present invention utilizes the accurate tracking of numerical simulation, gives record to the state of each particle, analyzes the state of data quantitative characterizing particles distribution; Thus quantitative segregation state sign can be carried out to the state of distribution of particles.
embodiment 1:
1) Alloying Ingredient Model be made up of distributing device 1 and charge can 3 is set up, simulation 300g alundum (Al2O3) dropping process, wherein, the length L1=200mm of charge can 3, height L2=250mm, width L3=28mm, the length L4=28mm of distributing device 1 feed opening 2, width L5=14mm, and the two lateral walls of the feed opening 2 of distributing device 1 is from the horizontal by 50 ° of angles.
2) set up the granular model of two kinds of particle diameters, wherein, two kinds of particle diameters are set to 3mm and 6mm respectively, particle Young modulus is set to 375GPa, particle Poisson ratio is set to 0.22, particle density is set to 2099kg/m
3, friction factor between particle and wall is set to 0.4, coefficient of restitution between particle and wall is set to 0.7, friction factor between particle is set to 0.5, coefficient of restitution between particle is set to 0.6,3mm granular mass: the quality=2:8 of 6mm particle.
3) Dynamic simulation software LIGGGHTS; simulated experiment; that is: first simulation particle is mixed; then mixed simulation particle is loaded distributing device 1; the state parameter of particle now respectively simulated in record; simulate particles fall state again, the situation of redistribution after waiting to simulate particles fall to charge can 3, and the state parameter of particle now respectively simulated in record.
4), after simulated experiment completes, recorded data is substituted into segregation index and resolve model: K=|A
just-A
end|/A
just* 100%.
5) segregation index is drawn: K=20.29%.
embodiment 2:
1) profit sets up a model be made up of distributing device 1 and charge can 3, simulation 300g alundum (Al2O3) dropping process, wherein, the length L1=200mm of charge can 3, height L2=250mm, width L3=28mm, the length L4=28mm of distributing device 1 feed opening 2, width L5=14mm, and the two lateral walls of the feed opening 2 of distributing device 1 is from the horizontal by 50 ° of angles.
2) set up the granular model of two kinds of particle diameters, wherein, particle diameter is set to 3mm and 6mm respectively, particle Young modulus is set to 375GPa, particle Poisson ratio is set to 0.22, particle density is set to 2099kg/m
3, friction factor between particle and wall is set to 0.4, coefficient of restitution between particle and wall is set to 0.7, friction factor between particle is set to 0.5, coefficient of restitution between particle is set to 0.6,3mm granular mass: the quality=4:6 of 6mm particle.
3) Dynamic simulation software LIGGGHTS; simulated experiment; that is: first simulation particle is mixed; then mixed simulation particle is loaded distributing device 1; the state parameter of particle now respectively simulated in record; simulate particles fall state again, the situation of redistribution after waiting to simulate particles fall to charge can 3, and the state parameter of particle now respectively simulated in record.
4), after simulated experiment completes, recorded data is substituted into segregation index and resolve model: K=|A
just-A
end|/A
just* 100%.
5) segregation index is drawn: K=6.07%.
embodiment 3:
1) model be made up of distributing device 1 and charge can 3 is set up, simulation 300g alundum (Al2O3) dropping process, wherein, the length L1=200mm of charge can 3, height L2=250mm, width L3=28mm, the length L4=28mm of feed opening 2, width L5=14mm, the two lateral walls of the feed opening 2 of distributing device 1 is from the horizontal by 50 degree of angles.
2) set up the granular model of two kinds of particle diameters, wherein, particle diameter is set to 3mm and 6mm respectively, particle Young modulus is set to 375GPa, particle Poisson ratio is set to 0.22, particle density is set to 2099kg/m
3, friction factor between particle and wall is set to 0.4, coefficient of restitution between particle and wall is set to 0.7, friction factor between particle is set to 0.5, coefficient of restitution between particle is set to 0.6,3mm granular mass: the quality=9:1 of 6mm particle.
3) Dynamic simulation software LIGGGHTS; simulated experiment; that is: first simulation particle is mixed; then mixed simulation particle is loaded distributing device 1; the state parameter of particle now respectively simulated in record; simulate particles fall state again, the situation of redistribution after waiting to simulate particles fall to charge can 3, and the state parameter of particle now respectively simulated in record.
4), after simulated experiment completes, recorded data is substituted into segregation index and resolve model: K=|A
just-A
end|/A
just* 100%.
5) segregation index is drawn: K=0.43%.
Finally it should be noted that, above embodiment is only in order to illustrate technical scheme of the present invention but not restriction technologies scheme, those of ordinary skill in the art is to be understood that, those are modified to technical scheme of the present invention or equivalent replacement, and do not depart from aim and the scope of the technical program, all should be encompassed in the middle of right of the present invention.
Claims (4)
1., based on a method of piling up segregation status after potential variation quantitatively characterizing particles fall, it is characterized in that: comprise the following steps:
1) three-dimensional drawing software SolidWorks is utilized to set up an Alloying Ingredient Model be made up of distributing device and charge can;
2) Alloying Ingredient Model that step 1) is set up is imported in simulation software LIGGGHTS;
3) in simulation software LIGGGHTS, set up the granular model of two kinds of particle diameters, and arrange the basic parameter of Alloying Ingredient Model and the basic parameter of granular model, make Alloying Ingredient Model form analog ligand materials device, granular model forms simulation particle;
4) simulated experiment, after being mixed by simulation particle, loads distributing device, record the state parameter of now each simulation particle by different proportion; After treating simulation particles fall to charge can redistribution, again record the state parameter of each simulation particle;
5) after simulated experiment completes, recorded data is substituted into segregation index and resolve model, obtain segregation index, wherein, described segregation index resolves model and is:
K=|A
just-A
end|/A
just* 100%;
In formula, K is segregation index, A
justfor A particle potential energy under original state and the ratio of total potential energy, A
endfor A particle potential energy under last current state and the ratio of total potential energy.
2. the method based on piling up segregation status after potential variation quantitatively characterizing particles fall according to claim 1, is characterized in that: the height of the geomery of basic parameter distributing device of described Alloying Ingredient Model, the geomery of charge can and distributing device and charge can.
3. the method based on piling up segregation status after potential variation quantitatively characterizing particles fall according to claim 1, is characterized in that: the basic parameter of granular model comprises the ratio between coefficient of restitution between friction factor between particle diameter, particle Young modulus, particle Poisson ratio, particle density, the friction factor between particle and wall, the coefficient of restitution between particle and wall, particle, particle and variable grain.
4. the method based on piling up segregation status after potential variation quantitatively characterizing particles fall according to claim 1, is characterized in that: the simulation graininess parameter recorded comprises speed and the friction force of the simulation numbering of particle, the coordinate of three-dimensional system of coordinate Imitating particle, X-axis, Y-axis and Z axis.
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Cited By (6)
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| CN107034327A (en) * | 2017-05-09 | 2017-08-11 | 重庆大学 | Method based on segregation status during mesh generation quantitatively characterizing particles fall |
| CN110672473A (en) * | 2018-07-03 | 2020-01-10 | 上海梅山钢铁股份有限公司 | Method for evaluating grain size distribution segregation of material in bin |
| CN111539103A (en) * | 2020-04-20 | 2020-08-14 | 东南大学 | Method for quantifying segregation degree of particles of ball mill based on lacey method |
| CN112014460A (en) * | 2020-09-01 | 2020-12-01 | 云南电网有限责任公司 | Method and device for determining components of vibration damping material in particle damper |
| CN112733326A (en) * | 2020-12-21 | 2021-04-30 | 赣江新区澳博颗粒科技研究院有限公司 | Numerical simulation method for material distribution of rotary chute at top of blast furnace |
| CN114925589A (en) * | 2022-05-30 | 2022-08-19 | 华中农业大学 | Optimization design method and system for mixing parameters in particle mixing system |
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Cited By (8)
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|---|---|---|---|---|
| CN107034327A (en) * | 2017-05-09 | 2017-08-11 | 重庆大学 | Method based on segregation status during mesh generation quantitatively characterizing particles fall |
| CN110672473A (en) * | 2018-07-03 | 2020-01-10 | 上海梅山钢铁股份有限公司 | Method for evaluating grain size distribution segregation of material in bin |
| CN111539103A (en) * | 2020-04-20 | 2020-08-14 | 东南大学 | Method for quantifying segregation degree of particles of ball mill based on lacey method |
| CN112014460A (en) * | 2020-09-01 | 2020-12-01 | 云南电网有限责任公司 | Method and device for determining components of vibration damping material in particle damper |
| CN112014460B (en) * | 2020-09-01 | 2023-08-15 | 云南电网有限责任公司 | Method and device for determining vibration reduction material components in particle damper |
| CN112733326A (en) * | 2020-12-21 | 2021-04-30 | 赣江新区澳博颗粒科技研究院有限公司 | Numerical simulation method for material distribution of rotary chute at top of blast furnace |
| CN114925589A (en) * | 2022-05-30 | 2022-08-19 | 华中农业大学 | Optimization design method and system for mixing parameters in particle mixing system |
| CN114925589B (en) * | 2022-05-30 | 2024-06-25 | 华中农业大学 | Optimal design method and system for mixing parameters in particle mixing system |
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