CN110929460A - Flow field optimization method and system for flue evaporation process with zero discharge of desulfurization wastewater - Google Patents
Flow field optimization method and system for flue evaporation process with zero discharge of desulfurization wastewater Download PDFInfo
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Abstract
The invention discloses a flow field optimization method and a system for a flue evaporation process with zero discharge of desulfurization wastewater, wherein the method comprises the following steps: performing grid modeling based on the current nozzle type and position of the flue and the layout of the guide plates to obtain a grid model of the flue; controlling the motion and evaporation process of the fog drops in the calculation domain based on the grid model; through numerical simulation calculation, whether fog drops are completely evaporated and do not collide the wall is judged, if yes, the current nozzle type and position of the flue and the layout of the guide plates are determined to be the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process, and if not, the flow field distribution is determined as follows: and adjusting the type and position of a nozzle of the flue and the layout of the guide plate until the fog drops are completely evaporated and do not touch the wall, and determining the adjusted type and position of the nozzle of the flue and the layout of the guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process. The invention can improve the effectiveness and rationality of the flow field optimization design.
Description
Technical Field
The invention relates to the technical field of desulfurization wastewater zero-discharge flue evaporation processes, in particular to a flow field optimization method and system for a desulfurization wastewater zero-discharge flue evaporation process.
Background
At present, the flow of the desulfurization wastewater zero-discharge flue evaporation process is shown in fig. 1, the treated desulfurization wastewater is sent into a flue between an air preheater and an electric dust remover and is changed into fog drops under the atomization action of a nozzle, the fog drops are evaporated into solid particles by the heat of flue gas in the flue, and the solid particles are collected by the electrostatic dust remover along with fly ash. The method has the advantages of simple process, low construction cost, low energy consumption and zero wastewater discharge, and is greatly popularized and applied.
The reasonable flow field distribution of the flue evaporation process with zero discharge of the desulfurization waste water is the premise of obtaining the ideal waste water evaporation effect. Factors affecting the distribution of the flow field include the type and position of the nozzles, the arrangement of the guide plates in the flue, and the like.
Therefore, how to effectively optimize the flow field of the desulfurization wastewater zero-discharge flue evaporation process so as to obtain a better wastewater evaporation effect is a problem to be solved urgently.
Disclosure of Invention
In view of the above, the invention provides a flow field optimization method for a flue evaporation process with zero discharge of desulfurization wastewater, which can improve the effectiveness and rationality of a flow field optimization design scheme by continuous iterative adjustment based on a numerical simulation result to obtain a better wastewater evaporation effect.
The invention provides a flow field optimization method for a flue evaporation process with zero discharge of desulfurization wastewater, which comprises the following steps:
performing grid modeling based on the current nozzle type and position of the flue and the layout of the guide plates to obtain a grid model of the flue;
controlling the motion and evaporation process of the fog drops in the calculation domain based on the grid model;
carrying out numerical simulation calculation during the movement and evaporation process of the fogdrops in the calculation domain;
judging whether fog drops are completely evaporated and do not collide with the wall based on a numerical simulation calculation result, if so, determining that the type and the position of a nozzle of the current flue and the layout of a guide plate are the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process, and if not, then:
and adjusting the type and position of a nozzle of the flue and the layout of the guide plate until the fog drops are completely evaporated and do not touch the wall, and determining the adjusted type and position of the nozzle of the flue and the layout of the guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
Preferably, during the movement and evaporation of the fog drops in the calculation domain, numerical simulation calculation is performed, including:
and in the process of movement and evaporation of the fogdrops in the calculation domain, carrying out numerical simulation calculation through a gas movement model, a gas component model, a fogdrops evaporation model and a fogdrops movement model.
Preferably, in the process of motion and evaporation of the droplets in the calculation domain, the numerical simulation calculation is performed through a gas motion model, a gas component model, a droplet evaporation model and a droplet motion model, and includes:
inputting gas phase temperature and gas flow parameters into the gas motion model, and solving to obtain velocity field distribution and pressure field distribution of gas at different positions of a flue by combining the fog drop motion speed parameters in the fog drop motion model;
inputting gas phase temperature, gas flow and gas component parameters into the gas component model, and solving to obtain the concentration field distribution and each component partial pressure of the gas at different positions of the flue by combining the velocity field distribution and the pressure field distribution in the gas motion model and the amount of liquid in the droplet evaporation model converted into gas;
inputting liquid phase temperature, wastewater solution saturated vapor pressure and desulfurization wastewater quantity parameters into the fog drop evaporation model, and solving to obtain the evaporation rate of fog drops by combining gas phase temperature, gas flow and water component partial pressure parameters in the gas phase model;
and inputting the liquid phase temperature, the saturated vapor pressure of the wastewater solution, the desulfurization wastewater quantity, the droplet injection speed and the droplet particle size distribution parameters into the droplet motion model, and solving to obtain the velocity field distribution parameters of the droplets by combining the velocity field distribution and the pressure field distribution parameters in the gas phase model and the droplet evaporation rate in the droplet evaporation model.
Preferably, the method further comprises:
the maximum path statistical length or the maximum statistical time of the fogdrops is preset.
Preferably, the method further comprises:
the grid of nozzle regions is partially encrypted.
A flow field optimization system for a desulfurization wastewater zero-discharge flue evaporation process comprises:
the modeling module is used for carrying out grid modeling based on the current nozzle type and position of the flue and the layout of the guide plates to obtain a grid model of the flue;
the control module is used for controlling the motion and evaporation process of the fog drops in the calculation domain based on the grid model;
the analog computation module is used for carrying out numerical analog computation in the process of movement and evaporation of the fogdrops in the computation domain;
the judging module is used for judging whether the fog drops are completely evaporated and do not collide the wall based on the numerical simulation calculation result;
the determining module is used for determining the current nozzle type and position of the flue and the layout of the guide plates as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process when fog drops are completely evaporated and do not collide with the wall;
the adjusting module is used for adjusting the type and the position of a nozzle of the flue and the layout of the guide plate when the fog drops are not completely evaporated and/or collide with the wall until the fog drops are completely evaporated and do not collide with the wall;
the determining module is further used for determining the type and the position of the adjusted nozzle of the flue and the layout of the guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
Preferably, the simulation calculation module is specifically configured to, when performing numerical simulation calculation in the process of performing motion and evaporation of the droplets in the calculation domain:
and in the process of movement and evaporation of the fogdrops in the calculation domain, carrying out numerical simulation calculation through a gas movement model, a gas component model, a fogdrops evaporation model and a fogdrops movement model.
Preferably, the simulation calculation module is specifically configured to, when performing numerical simulation calculation through the gas motion model, the gas component model, the droplet evaporation model, and the droplet motion model in a process of performing movement and evaporation of droplets in the calculation domain:
inputting gas phase temperature and gas flow parameters into the gas motion model, and solving to obtain velocity field distribution and pressure field distribution of gas at different positions of a flue by combining the fog drop motion speed parameters in the fog drop motion model;
inputting gas phase temperature, gas flow and gas component parameters into the gas component model, and solving to obtain the concentration field distribution and each component partial pressure of the gas at different positions of the flue by combining the velocity field distribution and the pressure field distribution in the gas motion model and the amount of liquid in the droplet evaporation model converted into gas;
inputting liquid phase temperature, wastewater solution saturated vapor pressure and desulfurization wastewater quantity parameters into the fog drop evaporation model, and solving to obtain the evaporation rate of fog drops by combining gas phase temperature, gas flow and water component partial pressure parameters in the gas phase model;
and inputting the liquid phase temperature, the saturated vapor pressure of the wastewater solution, the desulfurization wastewater quantity, the droplet injection speed and the droplet particle size distribution parameters into the droplet motion model, and solving to obtain the velocity field distribution parameters of the droplets by combining the velocity field distribution and the pressure field distribution parameters in the gas phase model and the droplet evaporation rate in the droplet evaporation model.
Preferably, the system further comprises:
and the setting module is used for presetting the maximum path statistical length or the maximum statistical time of the fogdrops.
Preferably, the system further comprises:
and the grid processing module is used for carrying out local encryption on the grid of the nozzle area.
In summary, the invention discloses a flow field optimization method for a desulfurization wastewater zero-emission flue evaporation process, when a flow field of the desulfurization wastewater zero-emission flue evaporation process needs to be optimized, firstly, grid modeling is performed based on the current nozzle type and position of a flue and the layout of a guide plate to obtain a grid model of the flue, then, the movement and evaporation processes of fog drops in a calculation domain are controlled based on the grid model, numerical simulation calculation is performed during the movement and evaporation processes of the fog drops in the calculation domain, then, based on the numerical simulation calculation result, whether the fog drops are completely evaporated and do not touch a wall is judged, if yes, the current nozzle type and position of the flue and the layout of the guide plate are determined as the flow field distribution of the desulfurization wastewater flue evaporation process, and if no, the flow field distribution of the desulfurization wastewater flue evaporation process is determined: and adjusting the type and position of a nozzle of the flue and the layout of the guide plate until the fog drops are completely evaporated and do not touch the wall, and determining the adjusted type and position of the nozzle of the flue and the layout of the guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process. The invention can improve the effectiveness and the rationality of the flow field optimization design scheme through continuous iterative adjustment based on the numerical simulation result so as to obtain better wastewater evaporation effect.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a flue evaporation process with zero discharge of desulfurization waste water disclosed in the prior art;
FIG. 2 is a flow chart of a flow field optimization method of embodiment 1 of the flue evaporation process with zero discharge of desulfurization wastewater disclosed in the present invention;
FIG. 3 is a flow chart of numerical simulation calculation of evaporation of a flue with zero discharge of desulfurization wastewater disclosed by the invention;
FIG. 4 is a flue gas flow diagram in a flue with zero discharge of desulfurization waste water disclosed by the invention;
FIG. 5 is a schematic view of a grid in the vicinity of a nozzle in accordance with the present disclosure;
FIG. 6 is a model diagram of a flue structure with zero discharge of desulfurization waste water disclosed in the embodiment of the present invention;
FIG. 7 is a grid split view of a desulfurization wastewater zero-discharge flue disclosed in the embodiment of the present invention;
FIG. 8 is a diagram illustrating the movement of droplets in a flue with staggered nozzles according to an exemplary embodiment of the present disclosure;
FIG. 9 is a graph of the change in droplet evaporation rate with average path of movement as disclosed in an example of the present invention;
FIG. 10 is a diagram illustrating the trajectories of droplets in a flue when nozzles according to an embodiment of the present invention are symmetrically arranged;
fig. 11 is a schematic structural diagram of a flow field optimization system in an embodiment 1 of the flow field optimization system for a desulfurization wastewater zero-discharge flue evaporation process disclosed by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 2, which is a flow chart of a flow field optimization method of embodiment 1 of the present invention, the method for desulfurization wastewater zero-emission flue evaporation process may include the following steps:
s201, carrying out grid modeling based on the current nozzle type and position of the flue and the layout of the guide plates to obtain a grid model of the flue;
when a flow field for the desulfurization wastewater zero-emission flue evaporation process needs to be optimized, firstly, grid modeling is carried out on the flue according to the current nozzle type and the nozzle installation position of the flue and the layout scheme of the guide plates, so that a grid model of the flue is obtained.
S202, controlling the motion and evaporation process of the fog drops in a calculation domain based on a grid model;
after a grid model of the flue is constructed, the movement and evaporation process of the fog drops in the grid is further controlled by the grid model, so that the fog drops accord with objective physical laws.
S203, carrying out numerical simulation calculation during the movement and evaporation process of the fogdrops in the calculation domain;
and further carrying out corresponding numerical simulation calculation on the fog drops in the process of controlling the fog drops to move and evaporate in the calculation domain.
S204, judging whether the fog drops are completely evaporated and do not collide with the wall based on the numerical simulation calculation result, if so, entering S205, otherwise, entering S206:
when the calculation is converged, whether the fog drops are completely evaporated and do not collide the wall is judged through a numerical simulation calculation result.
S205, determining the type and the position of a nozzle of the current flue and the layout of a guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process;
and when the fog drops are completely evaporated and do not touch the wall, determining the type and the position of the nozzle of the current flue and the layout of the guide plate as the optimal flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
S206, adjusting the type and the position of a nozzle of the flue and the layout of a guide plate until the fog drops are completely evaporated without colliding the wall.
When the fog drops are not completely evaporated, or the fog drops have collision walls, or the fog drops are not completely evaporated and the fog drops have collision walls, adjusting the type and position of the nozzle of the flue and the layout of the guide plate, repeating the numerical simulation calculation again according to the adjusted type and position of the nozzle of the flue and the layout of the guide plate, judging whether the fog drops are completely evaporated and do not touch the wall according to a new numerical simulation calculation result, if not, adjusting the type and position of the nozzle of the flue and the layout of the guide plate again, and repeating the above numerical simulation calculation process until the fog drops are completely evaporated and do not touch the wall, stopping adjusting the type and position of the nozzle of the flue and the layout of the guide plate, and determining the type and position of the nozzle of the current flue and the layout of the guide plates as the optimal flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
In summary, the above embodiment improves the effectiveness and rationality of the flow field optimization design scheme through continuous iterative adjustment based on the numerical simulation result, so as to obtain a better wastewater evaporation effect.
Specifically, in the above embodiment, during the process of movement and evaporation of the droplets in the calculation domain, numerical simulation calculation is mainly performed through a gas movement model, a gas component model, a droplet evaporation model, and a droplet movement model. The four models are coupled with each other, and related parameters are transferred between the four models, as shown in fig. 3.
Specifically, parameters such as gas phase temperature and gas flow are input into the gas motion model, and parameters such as droplet motion speed in the droplet motion model are combined, so that velocity field distribution, pressure field distribution and the like of the gas at different positions of the flue can be obtained through solving.
The gas motion model comprises a gas mass conservation equation, a momentum conservation equation and an energy conservation equation:
where ρ isgIs the gas density; u. ofg、upVelocity vectors of gas and particles, respectively;
is the mass flow, p is the pressure; k is the turbulence energy; mu, mutAerodynamic and turbulent viscosities, respectively; cDIs the drag coefficient; dpIs the particle diameter; hg、HsThe specific enthalpy values of the gas phase and the water vapor respectively; lambda [ alpha ]gIs the gas thermal conductivity; cpIs the specific heat capacity; t isgIs the gas temperature; qCIs a convective heat item.
Parameters such as gas phase temperature, gas flow, gas components and the like are input into the gas component model, and by combining velocity field distribution, pressure field distribution and the like in the gas motion model and the amount of liquid in the droplet evaporation model converted into gas, the concentration field distribution, the component partial pressure and the like of the gas at different positions of the flue can be solved. Gas composition equation:
wherein, YCIs the gas component mass fraction; sCIs the corresponding source item, namely the water component content after the evaporation of the waste water solution.
Parameters such as liquid phase temperature, saturated vapor pressure of wastewater solution, desulfurization wastewater amount and the like are input into the fog drop evaporation model, and parameters such as gas phase temperature, gas flow, water component partial pressure and the like in the gas phase model are combined, so that the evaporation rate of fog drops can be obtained through solving. Wherein, the saturated vapor pressure of the wastewater solution is an important parameter for judging whether the fog drop evaporation process can occur. Can be obtained by experimental determination methods or by consulting relevant literature manuals.
Droplet evaporation equation:
if the mist droplets are below the boiling point,
if the droplets are above the boiling point, the evaporation rate is controlled by heat transfer,
wherein m ispIs the droplet mass; dpIs the particle diameter; dgIs a binary diffusion coefficient; sh is the Sherwood number; b isMIs the Spalding mass transfer norm.
Parameters such as liquid phase temperature, wastewater solution saturated vapor pressure, desulfurization wastewater amount, droplet injection speed, droplet particle size distribution and the like are input into the droplet motion model, and parameters such as velocity field distribution, pressure field distribution and the like in the gas phase model and droplet evaporation rate in the droplet evaporation model are combined, so that parameters such as velocity field distribution and the like of the droplets can be obtained through solving. The invention allows the free selection of droplet size distribution models, such as Gamma distribution, Rosin-Rammler distribution, single particle size, custom particle size distribution, etc.
Fog droplet equation of motion:
the temperature change rate of the fogdrops is as follows:
wherein, FdisIs the turbulent diffusion force, TpIs the temperature of the particles, QMIs the heat source term generated by the particles due to mass transfer.
In addition, in the simulation method of the present invention, the influence of different shapes (spherical, elliptical, or spherical crown shape) of the droplets on the drag coefficient is considered. The droplet shape is characterized by Eotvos dimensionless criterion.
CD(aspherical) ═ max (C)D(ellipsoid), CD(spherical crown)) (13)
CD＝max(CD(ball), CD(non-ball)) (14)
Wherein σ is the liquid phase surface tension; re is the Reynolds number.
Specifically, on the basis of the above embodiment, the treatment of the vortex region may be further performed: as the flue gas often has a vortex flow as it flows in the flue, as shown in figure 4. The fog drops at the vortex position can continuously do circular motion in the space, so that the motion distance of a part of fog drops in the flue in the simulation result is unreasonably increased, not only is the calculation resource wasted, but also the simulation result is provided with errors. The invention can further reduce the influence of the eddy current on the numerical simulation result by presetting the maximum path statistical length or the maximum statistical time of the fog drops. In general, the maximum statistical length or the maximum statistical time can be determined according to the actual flue structure and the flow rate of the gas flow, for example, a section of straight flue with a length of L (m), the flow rate of the gas flow v (m/s), the maximum statistical length is generally not less than 2L (m), and the maximum statistical time is not less than 2L/v(s).
Specifically, the fog drops are more near the nozzle, the gas-liquid heat exchange degree is severe, and the gas-liquid coupling effect is strong, so that the temperature gradient, the velocity gradient and the like in the region are greatly changed. Therefore, it is difficult for the sparse mesh to accurately capture the motion state of the air flow and the mist droplets therein. In order to improve the calculation accuracy, the present invention may further perform local encryption on the grid of the nozzle region, as shown in fig. 5.
In order to more accurately describe the technical scheme provided by the invention, the following detailed description takes specific examples as examples:
as shown in fig. 6, the flue geometry at the inlet front end of an electric dust collector for a project includes: the device comprises a flue gas inlet 1, a flow guide plate 2, a heat exchange tube 3 and a flue gas outlet 4. The flue section of the flue inlet 1 is 11.14m multiplied by 5.1m, and the flue sections of the two flue gas outlets 4 are both 4.5m multiplied by 4.5 m. The atomizing nozzles are arranged at the inlet 1 of the flue and are divided into two sides, 3 nozzles are arranged on each side, the distance between every two adjacent nozzles is 2.8m, and the distance between the outermost nozzle and the wall surface is 1.97 m. A deflector 2 is arranged at the flue turn to improve the airflow. The division grid is shown in fig. 7. The parameters of the flue gas and the desulfurization waste water used in the numerical simulation process are shown in table 1.
TABLE 1 flue gas and desulfurized wastewater parameters
On the premise of an initial flow field design scheme, the flow field simulation method is adopted to carry out numerical calculation. Firstly, the gas phase flow field is preliminarily calculated, then the fog drops are injected into a calculation area from a flue gas inlet, the stress of the fog drops is calculated according to the gas phase flow field information obtained by the previous calculation, and the speed and the position of the fog drops are updated. And calculating the temperature change of the fog drops within a certain time step according to the gas-phase temperature field information, and obtaining the mass loss of the fog drops through an evaporation model by combining with a vapor pressure change curve of a calcium chloride solution (a wastewater solution). Gas-liquid interactions are represented by the Ishii-Zuber model. Meanwhile, the BM value is updated so as to calculate the next droplet evaporation rate. And then performing the next iterative calculation of the flow field.
Through calculation, the movement locus of the fog drops in the flue when the nozzles are arranged in a staggered mode can be obtained, and is shown in fig. 8. And some key evaporation information (movement distance, evaporation rate, etc.) of the fog drops can be obtained through statistics, as shown in fig. 9. As can be seen from the figure, the mist droplets start to evaporate relatively quickly, then gradually decrease in evaporation rate and finally become gentle, and at this time, the mist droplets are completely evaporated. The curve captures the evaporation characteristics of the salt-containing fog drops in the high-temperature flue gas well. When evaporation is started, the water content of fog drop particles is high, and after the fog drop particles are heated by smoke, the water on the surface layer of the fog drop particles is quickly evaporated; along with the evaporation of the moisture on the surface layer of the fog drops, the particle size of the fog drops is reduced, the moisture content is reduced, the moisture in the fog drops is gradually converted into crystal water, and the evaporation speed is reduced; the water content which can be evaporated by the fog drops is less and less continuously along with the evaporation of the water content and the generation of crystal water until the evaporation is complete.
Statistics shows that when the nozzles are arranged in a staggered mode, fog drops are completely evaporated, but a large number of fog drops collide with the wall surface under the action of air flow, and the problems of flue structure and corrosion are caused. In this case, the flow field is optimized by changing the nozzle arrangement, the nozzle arrangement is adjusted to be symmetrical, and the simulation result is shown in fig. 10. Through adjustment, the fog drops are completely evaporated, and the wall collision phenomenon is rarely generated, so that the engineering design requirement is met.
In conclusion, the design concept of determining the flow field optimization scheme of the desulfurization wastewater flue evaporation process through continuous iteration is established, whether wastewater is completely evaporated and whether fog drops collide the wall is used as the basis for judging the quality of the flow field, the evaporation process of salt-containing fog drops in the flue is realized through self-defined programming numerical values, mutual influences among a gas motion model, a gas component model, a fog drop evaporation model and a fog drop motion model are fully considered through bidirectional coupling calculation, the influence of eddy current on a numerical simulation result is reduced through presetting the maximum fog drop path statistical length (time), the consumption of calculation resources is reduced, and an effective conclusion is quickly obtained. Under the scientific and reasonable judgment basis, the current flow field optimization design scheme can be continuously checked and iterated by adopting a high-precision and high-accuracy numerical calculation model, so that the engineering design requirement is finally met.
As shown in fig. 11, which is a schematic structural diagram of an embodiment 1 of a flow field optimization system for a desulfurization wastewater zero-emission flue evaporation process disclosed in the present invention, the system may include:
the modeling module 1101 is used for performing grid modeling based on the current nozzle type and position of the flue and the layout of the guide plates to obtain a grid model of the flue;
the control module 1102 is used for controlling the motion and evaporation process of the fog drops in the calculation domain based on the grid model;
the analog computation module 1103 is used for performing numerical analog computation during the motion and evaporation process of the fog drops in the computation domain;
a judging module 1104, configured to judge whether the droplets are completely evaporated and do not collide with the wall based on the numerical simulation calculation result;
the determining module 1105 is configured to determine the current nozzle type and position of the flue and the layout of the flow guide plates as flow field distribution of the desulfurization wastewater zero-emission flue evaporation process when the mist droplets are completely evaporated and do not collide with the wall;
an adjusting module 1106, configured to adjust the nozzle type, the position, and the arrangement of the flow guide plate of the flue when the mist is not completely evaporated and/or collides with the wall until the mist is completely evaporated and does not collide with the wall;
the determining module 1105 is further configured to determine the adjusted nozzle type and position of the flue and the layout of the flow guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
The principle of the flow field optimization system for the desulfurization wastewater zero-discharge flue evaporation process disclosed in this embodiment is the same as that of the flow field optimization system corresponding to fig. 2 to 10, and details are not repeated herein.
The method specifically comprises the steps that the maximum path statistical length or the maximum statistical time of fog drops is preset through a setting module; specifically, the grid of the nozzle region is locally encrypted by the grid processing module.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A flow field optimization method for a desulfurization wastewater zero-discharge flue evaporation process is characterized by comprising the following steps:
performing grid modeling based on the current nozzle type and position of the flue and the layout of the guide plates to obtain a grid model of the flue;
controlling the motion and evaporation process of the fog drops in the calculation domain;
carrying out numerical simulation calculation during the movement and evaporation process of the fogdrops in the calculation domain;
judging whether fog drops are completely evaporated and do not collide with the wall based on a numerical simulation calculation result, if so, determining that the type and the position of a nozzle of the current flue and the layout of a guide plate are the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process, and if not, then:
and adjusting the type and position of a nozzle of the flue and the layout of the guide plate until the fog drops are completely evaporated and do not touch the wall, and determining the adjusted type and position of the nozzle of the flue and the layout of the guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
2. The method of claim 1, wherein the numerical simulation calculations performed during the movement and evaporation of the droplets in the calculation domain comprise:
and in the process of movement and evaporation of the fogdrops in the calculation domain, carrying out numerical simulation calculation through a gas movement model, a gas component model, a fogdrops evaporation model and a fogdrops movement model.
3. The method of claim 2, wherein the droplets are subjected to numerical simulation calculations by a gas motion model, a gas composition model, a droplet evaporation model and a droplet motion model during the process of movement and evaporation in the calculation domain, and the numerical simulation calculations comprise:
inputting gas phase temperature and gas flow parameters into the gas motion model, and solving to obtain velocity field distribution and pressure field distribution of gas at different positions of a flue by combining the fog drop motion speed parameters in the fog drop motion model;
inputting gas phase temperature, gas flow and gas component parameters into the gas component model, and solving to obtain the concentration field distribution and each component partial pressure of the gas at different positions of the flue by combining the velocity field distribution and the pressure field distribution in the gas motion model and the amount of liquid in the droplet evaporation model converted into gas;
inputting liquid phase temperature, wastewater solution saturated vapor pressure and desulfurization wastewater quantity parameters into the fog drop evaporation model, and solving to obtain the evaporation rate of fog drops by combining gas phase temperature, gas flow and water component partial pressure parameters in the gas phase model;
and inputting the liquid phase temperature, the saturated vapor pressure of the wastewater solution, the desulfurization wastewater quantity, the droplet injection speed and the droplet particle size distribution parameters into the droplet motion model, and solving to obtain the velocity field distribution parameters of the droplets by combining the velocity field distribution and the pressure field distribution parameters in the gas phase model and the droplet evaporation rate in the droplet evaporation model.
4. The method of claim 3, further comprising:
the maximum path statistical length or the maximum statistical time of the fogdrops is preset.
5. The method of claim 4, further comprising:
the grid of nozzle regions is partially encrypted.
6. A flow field optimizing system for desulfurization waste water zero release flue evaporation process, characterized by comprising:
the modeling module is used for carrying out grid modeling based on the current nozzle type and position of the flue and the layout of the guide plates to obtain a grid model of the flue;
the control module is used for controlling the motion and evaporation process of the fog drops in the calculation domain based on the grid model;
the analog computation module is used for carrying out numerical analog computation in the process of movement and evaporation of the fogdrops in the computation domain;
the judging module is used for judging whether the fog drops are completely evaporated and do not collide the wall based on the numerical simulation calculation result;
the determining module is used for determining the current nozzle type and position of the flue and the layout of the guide plates as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process when fog drops are completely evaporated and do not collide with the wall;
the adjusting module is used for adjusting the type and the position of a nozzle of the flue and the layout of the guide plate when the fog drops are not completely evaporated and/or collide with the wall until the fog drops are completely evaporated and do not collide with the wall;
the determining module is further used for determining the type and the position of the adjusted nozzle of the flue and the layout of the guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
7. The system of claim 6, wherein the simulation computation module, when performing numerical simulation computation during the motion and evaporation of the droplets in the computation domain, is specifically configured to:
and in the process of movement and evaporation of the fogdrops in the calculation domain, carrying out numerical simulation calculation through a gas movement model, a gas component model, a fogdrops evaporation model and a fogdrops movement model.
8. The system according to claim 7, wherein the simulation computation module, when performing numerical simulation computation through the gas motion model, the gas composition model, the droplet evaporation model and the droplet motion model in the process of performing the movement and evaporation of the droplets in the computation domain, is specifically configured to:
inputting gas phase temperature and gas flow parameters into the gas motion model, and solving to obtain velocity field distribution and pressure field distribution of gas at different positions of a flue by combining the fog drop motion speed parameters in the fog drop motion model;
inputting gas phase temperature, gas flow and gas component parameters into the gas component model, and solving to obtain the concentration field distribution and each component partial pressure of the gas at different positions of the flue by combining the velocity field distribution and the pressure field distribution in the gas motion model and the amount of liquid in the droplet evaporation model converted into gas;
inputting liquid phase temperature, wastewater solution saturated vapor pressure and desulfurization wastewater quantity parameters into the fog drop evaporation model, and solving to obtain the evaporation rate of fog drops by combining gas phase temperature, gas flow and water component partial pressure parameters in the gas phase model;
and inputting the liquid phase temperature, the saturated vapor pressure of the wastewater solution, the desulfurization wastewater quantity, the droplet injection speed and the droplet particle size distribution parameters into the droplet motion model, and solving to obtain the velocity field distribution parameters of the droplets by combining the velocity field distribution and the pressure field distribution parameters in the gas phase model and the droplet evaporation rate in the droplet evaporation model.
9. The system of claim 8, further comprising:
and the setting module is used for presetting the maximum path statistical length or the maximum statistical time of the fogdrops.
10. The system of claim 9, further comprising:
and the grid processing module is used for carrying out local encryption on the grid of the nozzle area.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112014353A (en) * | 2020-09-04 | 2020-12-01 | 北京理工大学 | Method and system for determining distribution of concentration field of hydrogen jet |
| CN112426856A (en) * | 2020-10-30 | 2021-03-02 | 聂鹏飞 | Flue gas desulfurization flow field simulation method, system and device |
| CN117634340A (en) * | 2023-11-20 | 2024-03-01 | 北京科技大学 | Determination method for desulfurization effect of bottom argon blowing ladle |
| CN117634340B (en) * | 2023-11-20 | 2024-05-24 | 北京科技大学 | Determination method for desulfurization effect of bottom argon blowing ladle |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104528852A (en) * | 2014-12-31 | 2015-04-22 | 华中科技大学 | Spraying device used for treating desulfurization waste water of power plant |
| CN105668832A (en) * | 2016-01-29 | 2016-06-15 | 湖南九沣电力科技有限公司 | Desulfurization wastewater treatment system and method |
| CN106000007A (en) * | 2016-07-06 | 2016-10-12 | 福建龙净环保股份有限公司 | Simulation system and method for wet desulphurization flow fields |
| US20170319984A1 (en) * | 2016-05-03 | 2017-11-09 | Saudi Arabian Oil Company | Processes for analysis and optimization of multiphase separators, particular in regards to simulated gravity separation of immiscible liquid dispersions |
| CN110147594A (en) * | 2019-05-09 | 2019-08-20 | 上海应用技术大学 | Probe into the analogy method of FGD by spraying mist tower interior flow field distribution |
-
2019
- 2019-11-29 CN CN201911199238.0A patent/CN110929460B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104528852A (en) * | 2014-12-31 | 2015-04-22 | 华中科技大学 | Spraying device used for treating desulfurization waste water of power plant |
| CN105668832A (en) * | 2016-01-29 | 2016-06-15 | 湖南九沣电力科技有限公司 | Desulfurization wastewater treatment system and method |
| US20170319984A1 (en) * | 2016-05-03 | 2017-11-09 | Saudi Arabian Oil Company | Processes for analysis and optimization of multiphase separators, particular in regards to simulated gravity separation of immiscible liquid dispersions |
| CN106000007A (en) * | 2016-07-06 | 2016-10-12 | 福建龙净环保股份有限公司 | Simulation system and method for wet desulphurization flow fields |
| CN110147594A (en) * | 2019-05-09 | 2019-08-20 | 上海应用技术大学 | Probe into the analogy method of FGD by spraying mist tower interior flow field distribution |
Non-Patent Citations (2)
| Title |
|---|
| 张语晴: "脱硫废水烟道蒸发数值模拟研究", 《中国优秀博硕士学位论文全文数据库(电子期刊) 工程科技Ⅱ辑》 * |
| 马双忱 等: "脱硫废水烟道喷雾蒸发的数值模拟", 《计算机与应用化学》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112014353A (en) * | 2020-09-04 | 2020-12-01 | 北京理工大学 | Method and system for determining distribution of concentration field of hydrogen jet |
| CN112426856A (en) * | 2020-10-30 | 2021-03-02 | 聂鹏飞 | Flue gas desulfurization flow field simulation method, system and device |
| CN112426856B (en) * | 2020-10-30 | 2021-06-29 | 河北大唐国际王滩发电有限责任公司 | Flue gas desulfurization flow field simulation method, system and device |
| CN117634340A (en) * | 2023-11-20 | 2024-03-01 | 北京科技大学 | Determination method for desulfurization effect of bottom argon blowing ladle |
| CN117634340B (en) * | 2023-11-20 | 2024-05-24 | 北京科技大学 | Determination method for desulfurization effect of bottom argon blowing ladle |
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