CN110929460B - Flow field optimization method and system for desulfurization wastewater zero-emission flue evaporation process - Google Patents
Flow field optimization method and system for desulfurization wastewater zero-emission flue evaporation process Download PDFInfo
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Abstract
The invention discloses a flow field optimization method and a flow field optimization system for a desulfurization wastewater zero-emission flue evaporation process, wherein the method comprises the following steps: grid modeling is carried out based on the current nozzle type and position of the flue and the layout of the guide plates, so as to obtain a grid model of the flue; controlling the movement and evaporation process of the fog drops in a calculation domain based on the grid model; judging whether fog drops are completely evaporated and do not collide with walls through numerical simulation calculation, if yes, determining the type and the position of a nozzle of a current flue and the layout of a flow field distribution of a desulfurization wastewater zero-emission flue evaporation process, and if no, determining that the nozzle type and the position of the current flue and the layout of a flow guide plate are the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process: and (3) adjusting the type, the position and the layout of the guide plates of the flue until the fog drops are completely evaporated and no wall is bumped, and determining the type, the position and the layout of the guide plates of the flue after adjustment 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-emission flue evaporation processes, in particular to a flow field optimization method and a flow field optimization system for a desulfurization wastewater zero-emission flue evaporation process.
Background
At present, the flow of the desulfurization wastewater zero-emission flue evaporation process is shown in figure 1, the desulfurization wastewater after treatment is sent into a flue between an air preheater and an electric dust collector, the desulfurization wastewater is changed into fog drops under the atomization effect of a nozzle, the fog drops are subjected to the heat of flue gas in the flue, the fog drops are evaporated into solid particles, and the solid particles are collected by the electric dust collector 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 desulfurization wastewater zero-emission flue evaporation process is a precondition for obtaining an ideal wastewater evaporation effect. Factors influencing the flow field distribution include nozzle type, location, arrangement of baffles in the stack, etc.
Therefore, how to effectively optimize the flow field of the desulfurization wastewater zero-emission 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 desulfurization wastewater zero-emission flue evaporation process, which can improve the effectiveness and rationality of a flow field optimization design scheme through continuous iterative adjustment based on a numerical simulation result so as to obtain a better wastewater evaporation effect.
The invention provides a flow field optimization method for a desulfurization wastewater zero-emission flue evaporation process, which comprises the following steps:
grid modeling is carried out based on the current nozzle type and position of the flue and the layout of the guide plates, so as to obtain a grid model of the flue;
controlling the movement and evaporation process of the fog drops in a calculation domain based on the grid model;
in the process of movement and evaporation of the fog drops in the calculation domain, carrying out numerical simulation calculation;
based on the numerical simulation calculation result, judging whether fog drops are completely evaporated and do not collide with the wall, if yes, determining the type and the position of the nozzle of the current flue and the layout of the flow guide plate as flow field distribution of the desulfurization wastewater zero-emission flue evaporation process, and if no, determining that:
and (3) adjusting the type, the position and the layout of the guide plates of the flue until the fog drops are completely evaporated and no wall is bumped, and determining the type, the position and the layout of the guide plates of the flue after adjustment as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
Preferably, in the process of movement and evaporation of the fog drops in the calculation domain, performing numerical simulation calculation comprises:
in the process of movement and evaporation of the fog drops in the calculation domain, numerical simulation calculation is carried out through a gas movement model, a gas component model, a fog drop evaporation model and a fog drop movement model.
Preferably, in the process of movement and evaporation of the droplets in the calculation domain, numerical simulation calculation is performed through a gas movement model, a gas composition model, a droplet evaporation model and a droplet movement model, including:
inputting gas phase temperature and gas flow parameters into the gas movement model, and solving to obtain the velocity field distribution and the pressure field distribution of the gas at different positions of the flue by combining the droplet movement velocity parameters in the droplet movement model;
inputting gas phase temperature, gas flow and gas component parameters into the gas component model, and solving to obtain concentration field distribution and component partial pressure of the gas at different positions of a flue by combining speed field distribution and pressure field distribution in the gas motion model and the quantity of liquid converted into gas in the droplet evaporation model;
inputting liquid phase temperature, saturated vapor pressure of wastewater solution and desulfurization wastewater amount parameters into the fog drop evaporation model, and solving to obtain the evaporation rate of fog drops by combining the gas phase temperature, gas flow and water component partial pressure parameters in the gas phase model;
and inputting liquid phase temperature, saturated vapor pressure of the wastewater solution, desulfurization wastewater quantity, droplet ejection speed and droplet particle size distribution parameters into the droplet motion model, and solving to obtain the droplet speed field distribution parameters by combining the speed field distribution and 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 distance statistical length or the maximum statistical time of the fog drops is preset.
Preferably, the method further comprises:
the grid of nozzle areas is locally encrypted.
A flow field optimization system for a desulfurization wastewater zero emission flue evaporation process, comprising:
the modeling module is used for conducting grid modeling based on the current nozzle type and position of the flue and the layout of the guide plate to obtain a grid model of the flue;
the control module is used for controlling the movement and evaporation process of the fog drops in the calculation domain based on the grid model;
the simulation calculation module is used for carrying out numerical simulation calculation in the process of movement and evaporation of the fog drops in the calculation domain;
the judging module is used for judging whether the fog drops are completely evaporated and do not collide with the wall based on the numerical simulation calculation result;
the determining module is used for determining the type and the position of the current nozzle 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 when the fog drops are completely evaporated and no wall is bumped;
the adjusting module is used for adjusting the type and the position of the 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 also used for determining the type and the position of the nozzle of the adjusted 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 a process of executing movement and evaporation of mist droplets in a calculation domain:
in the process of movement and evaporation of the fog drops in the calculation domain, numerical simulation calculation is carried out through a gas movement model, a gas component model, a fog drop evaporation model and a fog drop movement model.
Preferably, the simulation calculation module is specifically configured to, when performing numerical simulation calculation through the gas motion model, the gas composition model, the droplet evaporation model and the droplet motion model in the process of executing movement and evaporation of the droplet in the calculation domain:
inputting gas phase temperature and gas flow parameters into the gas movement model, and solving to obtain the velocity field distribution and the pressure field distribution of the gas at different positions of the flue by combining the droplet movement velocity parameters in the droplet movement model;
inputting gas phase temperature, gas flow and gas component parameters into the gas component model, and solving to obtain concentration field distribution and component partial pressure of the gas at different positions of a flue by combining speed field distribution and pressure field distribution in the gas motion model and the quantity of liquid converted into gas in the droplet evaporation model;
inputting liquid phase temperature, saturated vapor pressure of wastewater solution and desulfurization wastewater amount parameters into the fog drop evaporation model, and solving to obtain the evaporation rate of fog drops by combining the gas phase temperature, gas flow and water component partial pressure parameters in the gas phase model;
and inputting liquid phase temperature, saturated vapor pressure of the wastewater solution, desulfurization wastewater quantity, droplet ejection speed and droplet particle size distribution parameters into the droplet motion model, and solving to obtain the droplet speed field distribution parameters by combining the speed field distribution and pressure field distribution parameters in the gas phase model and the droplet evaporation rate in the droplet evaporation model.
Preferably, the system further comprises:
the setting module is used for presetting the maximum distance statistical length or the maximum statistical time of the fog drops.
Preferably, the system further comprises:
and the grid processing module is used for locally encrypting 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 the 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 flow guide plate to obtain a grid model of the flue, then, the movement and evaporation process of fog drops in a calculation domain is controlled based on the grid model, the numerical simulation calculation is performed in the movement and evaporation process 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 collide with walls is judged, if yes, the nozzle type and position of the current flue and the layout of the flow guide plate are determined to be the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process, if no: and (3) adjusting the type, the position and the layout of the guide plates of the flue until the fog drops are completely evaporated and no wall is bumped, and determining the type, the position and the layout of the guide plates of the flue after adjustment 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 scheme through continuous iterative adjustment based on the numerical simulation result, so as to obtain better waste water evaporation effect.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow diagram of a desulfurization wastewater zero emission flue evaporation process disclosed in the prior art;
FIG. 2 is a flow chart of an example 1 of a flow field optimization method for a desulfurization wastewater zero emission flue evaporation process;
FIG. 3 is a flow chart of the simulation calculation of the evaporation value of the zero emission flue of the desulfurization wastewater;
FIG. 4 is a diagram of flue gas flow in the zero release flue of desulfurization wastewater disclosed by the invention;
FIG. 5 is a schematic view of a grid near a nozzle in accordance with the present disclosure;
FIG. 6 is a structural model diagram of a desulfurization wastewater zero-emission flue disclosed in an example of the invention;
FIG. 7 is a grid sectional view of a desulfurization wastewater zero release flue disclosed in an example of the present invention;
FIG. 8 is a diagram of the movement trace of droplets in a flue when the nozzles disclosed in the example of the present invention are staggered;
FIG. 9 is a graph showing the variation of the evaporation rate of droplets with the average movement path according to the embodiment of the present invention;
FIG. 10 is a graph of the trajectory of droplet motion in a flue with symmetrical placement of nozzles as disclosed in the examples of the present invention;
fig. 11 is a schematic structural diagram of an embodiment 1 of a flow field optimizing system for a desulfurization wastewater zero-emission flue evaporation process.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 2, a flow chart of an embodiment 1 of a flow field optimization method for a desulfurization wastewater zero-emission flue evaporation process disclosed in the present invention is shown, and the method 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 plate to obtain a grid model of the flue;
when the 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 plate, so as to obtain a grid model of the flue.
S202, controlling the movement and evaporation process of fog drops in a calculation domain based on a grid model;
after the grid model of the flue is constructed, the grid model is further used for controlling the movement and evaporation process of fog drops in the grid, so that the fog drops accord with objective physical rules.
S203, carrying out numerical simulation calculation in the process of movement and evaporation of the fog drops in the calculation domain;
and further performing 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 fog drops are completely evaporated and do not collide with walls based on a numerical simulation calculation result, if so, entering S205, and if not, entering S206:
and when the calculation is converged, judging whether the fog drops are completely evaporated and have no collision wall according to 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;
when the fog drops are completely evaporated and no wall is bumped, the current nozzle type, the current position and the current layout of the flow guide plates of the flue are determined to be the optimal flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
S206, adjusting the type and the position of the nozzles of the flue and the layout of the guide plates until the fog drops are completely evaporated and no wall collision exists.
And when the fog drops are not evaporated completely or the fog drops have collision walls, or the fog drops are not evaporated completely and the fog drops have collision walls, adjusting the nozzle type, the position and the layout of the guide plates of the flue, repeating the numerical simulation calculation again aiming at the nozzle type, the position and the layout of the guide plates of the flue after adjustment, judging whether the fog drops are evaporated completely and the collision walls are absent through a new numerical simulation calculation result, and when the judgment result is negative, adjusting the nozzle type, the position and the layout of the guide plates of the flue again, repeating the numerical simulation calculation process until the fog drops are evaporated completely and the collision walls are absent, stopping adjusting the nozzle type, the position and the layout of the guide plates of the flue, and determining the nozzle type, the position and the layout of the guide plates of the current flue as the optimal flow field distribution of the desulfurization waste water zero discharge flue evaporation process.
In summary, the above embodiment improves the effectiveness and rationality of the flow field optimization design scheme by continuous iterative adjustment based on the numerical simulation result, so as to obtain a better wastewater evaporation effect.
Specifically, in the above embodiment, in the process of moving and evaporating the droplets in the calculation domain, numerical simulation calculation is mainly performed by using a gas movement model, a gas composition 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 models, as shown in fig. 3.
Specifically, parameters such as gas phase temperature, gas flow and the like are input into the gas movement model, and the speed field distribution, the pressure field distribution and the like of the gas at different positions of the flue can be obtained by combining the parameters such as the fog drop movement speed and the like in the fog drop movement model.
The gas motion model comprises a gas mass conservation equation, a momentum conservation equation and an energy conservation equation:
wherein ρ is g Is the gas density; u (u) g 、u p Velocity vectors of the gas and particles, respectively;
is mass flow, p is pressure; k is the turbulent energy; mu, mu t Aerodynamic viscosity and turbulent viscosity, respectively; c (C) D Is the drag coefficient; d, d p Is the particle diameter; h g 、H s Specific enthalpy values of the gas phase and the water vapor, respectively; lambda (lambda) g Is the thermal conductivity of the gas; c (C) p Is the specific heat capacity; t (T) g Is the gas temperature; q (Q) C Is a convective heat transfer term.
Parameters such as gas phase temperature, gas flow, gas components and the like are input into the gas component model, and the concentration field distribution, the partial pressure of each component and the like of the gas at different positions of the flue can be obtained by combining the speed field distribution, the pressure field distribution and the like in the gas motion model and the quantity of the liquid converted into the gas in the fog drop evaporation model. Gas composition equation:
wherein Y is C Is the mass fraction of the gas component; s is S C Is the corresponding source item, namely the water component content of the wastewater solution after evaporation.
Parameters such as liquid phase temperature, saturated vapor pressure of the wastewater solution, desulfurization wastewater amount and the like are input into the fog drop evaporation model, and the evaporation rate of fog drops can be obtained by solving the parameters such as gas phase temperature, gas flow, water component partial pressure and the like in the gas phase model. The saturated vapor pressure of the wastewater solution is an important parameter for judging whether the fog drop evaporation process can occur or not. Can be obtained by experimental determination methods or by consulting related literature manuals.
Mist evaporation equation:
if the mist droplets are below the boiling point,
if the fog drops are higher than the boiling point, the evaporation rate is controlled by heat transfer,
wherein m is p Is the mass of the fog drops; d, d p Is the particle diameter; d (D) g Is a binary diffusion coefficient; sh is Sherwood number; b (B) M Is the number of Spalding mass transfer criteria.
Parameters such as liquid phase temperature, saturated vapor pressure of wastewater solution, desulfurization wastewater amount, droplet ejection speed, droplet particle size distribution and the like are input into the droplet motion model, and the parameters such as speed field distribution, pressure field distribution and the like in the gas phase model and the droplet evaporation rate in the droplet evaporation model are combined, so that the parameters such as the speed 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 and the like.
Equation of droplet motion:
the temperature change rate of the fog drops is as follows:
wherein F is dis Is turbulent diffusion force, T p Is the particle temperature, Q M Is a heat source item generated by the mass transfer of the particles.
Furthermore, in the simulation method of the present invention, the influence of the different shapes of the mist droplets (spherical, elliptical, or spherical cap shape) on the drag coefficient is considered. The droplet shape is characterized by Eotvos dimensionless numbers.
C D (non-sphere) =max (C D (ellipsoid), C D (spherical cap)) (13)
C D ＝max(C D (ball), C D (non-ball)) (14)
Wherein sigma is the surface tension of the liquid phase; re is the Reynolds number.
Specifically, the treatment of the vortex region may be further performed on the basis of the above embodiment: as the flue gas often has turbulence as it flows in the flue, as shown in fig. 4. The fog drops at the vortex positions can continuously do circular motion in the space, so that the motion path of a part of fog drops in the flue in the simulation result is unreasonably increased, the calculation resources are wasted, and errors are brought to the simulation result. The invention can further reduce the influence of vortex existence 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 airflow velocity, for example, a straight flue with a length L (m), and the airflow velocity v (m/s), and then the maximum statistical length is generally not less than 2L (m), and the maximum statistical time is not less than 2L/v(s).
Specifically, because of the large number of mist droplets near the nozzle, the gas-liquid heat exchange degree is intense, and the gas-liquid coupling effect is strong, the temperature gradient, the speed gradient and the like of the area are greatly changed. Therefore, it is difficult for the sparse grid to accurately capture the airflow and the movement state of the mist droplets thereat. In order to improve the calculation accuracy, the present invention may further perform local encryption on the grid of the nozzle area, as shown in fig. 5.
In order to more accurately describe the technical scheme provided by the invention, the following detailed description is given by taking specific examples as examples:
as shown in fig. 6, the flue geometry for the inlet front end of an electrostatic precipitator of a project includes: a flue gas inlet 1, a 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×5.1m, and the flue section of the two flue gas outlets 4 is 4.5m×4.5m. The atomizing nozzles are arranged at the flue inlet 1 and are arranged on two sides, 3 nozzles are arranged on each side, the distance between adjacent nozzles is 2.8m, and the distance between the outermost nozzles and the wall surface is 1.97m. A baffle 2 is provided at the flue turn to improve the airflow. The meshing is shown in fig. 7. The parameters of the flue gas and desulfurization wastewater used in the numerical simulation process are shown in table 1.
TABLE 1 flue gas and desulfurization wastewater parameters
On the premise of the initial flow field design scheme, the flow field simulation method is adopted to carry out numerical calculation. Firstly, carrying out preliminary calculation on a gas-phase flow field, then injecting fog drops into a calculation area from a flue gas inlet, calculating the stress of the fog drops according to the gas-phase flow field information obtained by the previous calculation, and updating the speed and the position of the fog drops. According to the gas phase temperature field information, calculating the temperature change of the fog drops in a certain time step, and combining the vapor pressure change curve of the calcium chloride solution (wastewater solution) to obtain the mass loss of the fog drops through an evaporation model. The gas-liquid interaction is embodied by the Ishii-Zuber model. Meanwhile, the BM value is updated so as to calculate the next mist evaporation rate. And then performing the next iterative calculation of the flow field.
Through calculation, the movement track of the fog drops in the flue can be obtained when the nozzles are arranged in a staggered mode, and the movement track is shown in fig. 8. And some key evaporation information (movement path, evaporation rate, etc.) of the mist droplets can be obtained through statistics, as shown in fig. 9. From the graph, the evaporation speed of the fog drops gradually decreases after the fog drops start to evaporate relatively rapidly, and the fog drops gradually flatten finally, and the fog drops evaporate completely. The curve well captures the evaporation characteristic of salt-containing mist drops in high-temperature flue gas. When evaporation is started, the moisture content of fog drop particles is high, and after the fog drop particles are heated by flue gas, the moisture on the surface layer of the fog drop particles is rapidly evaporated; as the moisture on the surface layer of the fog drops evaporates, the grain 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; and continuing to evaporate water and generate crystal water, so that the water capable of being evaporated by the fog drops is reduced until the evaporation is complete.
Through statistics, when the nozzles are arranged in a staggered mode, fog drops are evaporated completely, but a large number of fog drops collide with the wall surface under the action of air flow, so that the flue structure and corrosion problems can be caused. In this case, the flow field is optimized by changing the nozzle arrangement mode, the nozzle arrangement mode is adjusted to be symmetrical arrangement, and the simulation result is shown in fig. 10. Through adjustment, the fog drops are completely evaporated, and the phenomenon of wall collision is less generated, so that the engineering design requirement is met.
In summary, the invention establishes a design concept of determining the flow field optimization scheme of the desulfurization waste water flue evaporation process through continuous iteration, takes whether waste water is completely evaporated and whether fog drops collide with walls as a judging basis of flow field quality, realizes the evaporation process of salt-containing fog drops in a flue through self-defined programming numerical values, fully considers the mutual influence among a gas motion model, a gas component model, a fog drop evaporation model and a fog drop motion model through bidirectional coupling calculation, reduces the influence of vortex existence on a numerical simulation result through presetting the maximum path statistical length (time) of the fog drops, reduces the consumption of calculation resources and rapidly obtains an effective conclusion. Under scientific and reasonable judgment basis, the current flow field optimization design scheme can be continuously checked and iterated by adopting a numerical calculation model with high precision and high accuracy, so that the flow field optimization design scheme finally meets engineering design requirements.
As shown in fig. 11, a schematic structural diagram of an embodiment 1 of a flow field optimizing system for a desulfurization wastewater zero-emission flue evaporation process according to the present invention may include:
the modeling module 1101 is configured to perform grid modeling based on a current nozzle type and a current position of the flue and a layout of the deflector, so as to obtain a grid model of the flue;
the control module 1102 is used for controlling the movement and evaporation process of the fog drops in the calculation domain based on the grid model;
the simulation calculation module 1103 is used for performing numerical simulation calculation in the process of movement and evaporation of the fog drops in the calculation domain;
a judging module 1104, configured to judge whether the fog drops evaporate completely and do not collide with the wall based on the numerical simulation calculation result;
the determining module 1105 is configured to determine the type and the position of the nozzle of the current flue and the layout of the deflector as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process when the fog drops are completely evaporated and no wall is bumped;
an adjustment module 1106 for adjusting the nozzle type, position, and layout of the deflector of the flue when the droplet evaporation is incomplete and/or hits the wall, until the droplet evaporation is complete and there is no hit;
the determining module 1105 is further configured to determine the nozzle type, the position, and the layout of the deflector of the adjusted flue as a flow field distribution of the desulfurization wastewater zero-emission flue evaporation process.
The principle of the flow field optimizing system for the desulfurization wastewater zero-emission flue evaporation process disclosed in the embodiment is the same as that corresponding to fig. 2 to 10, and is not described herein again.
The method comprises the steps that a setting module is used for presetting the maximum distance statistical length or the maximum statistical time of fog drops; the grid of the nozzle area is locally encrypted by a grid processing module.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
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 elements and steps are described above generally in terms of functionality in order to clearly illustrate the 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 solution. 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. The software modules may be disposed 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 (6)
1. The flow field optimization method for the desulfurization wastewater zero-emission flue evaporation process is characterized by comprising the following steps of:
grid modeling is carried out based on the current nozzle type and position of the flue and the layout of the guide plates, so as to obtain a grid model of the flue;
controlling the movement and evaporation process of the fog drops in a calculation domain;
in the process of movement and evaporation of the fog drops in the calculation domain, carrying out numerical simulation calculation through a gas movement model, a gas component model, a fog drop evaporation model and a fog drop movement model; based on the numerical simulation calculation result, judging whether fog drops are completely evaporated and do not collide with the wall, if yes, determining the type and the position of the nozzle of the current flue and the layout of the flow guide plate as flow field distribution of the desulfurization wastewater zero-emission flue evaporation process, and if no, determining that:
adjusting the type, the position and the layout of the guide plates of the flue until the fog drops are completely evaporated and no wall is bumped, and determining the type, the position and the layout of the guide plates of the flue after adjustment as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process;
in the process of movement and evaporation of the fog drops in the calculation domain, carrying out numerical simulation calculation through a gas movement model, a gas component model, a fog drop evaporation model and a fog drop movement model, wherein the numerical simulation calculation comprises the following steps:
inputting gas phase temperature and gas flow in the gas motion model, and solving to obtain the velocity field distribution and pressure field distribution of the gas at different positions of the flue by combining the velocity field distribution of the fog drops in the fog drop motion model;
inputting gas phase temperature, gas flow and gas components into the gas component model, and solving to obtain concentration field distribution and component partial pressure of the gas at different positions of a flue by combining speed field distribution and pressure field distribution of the gas at different positions of the flue in the gas movement model and the amount of liquid converted into gas in the droplet evaporation model;
inputting liquid phase temperature, saturated vapor pressure of wastewater solution and desulfurization wastewater quantity into the fog drop evaporation model, and solving to obtain fog drop evaporation rate by combining the gas phase temperature, gas flow and partial pressure of each component in the gas component model;
inputting liquid phase temperature, desulfurization waste water amount, fog drop injection speed and fog drop particle size distribution into the fog drop motion model, and solving to obtain the speed field distribution of fog drops by combining the speed field distribution and the pressure field distribution of gas in the gas motion model at different positions of a flue and the fog drop evaporation rate in the fog drop evaporation model;
the gas motion model comprises a gas mass conservation equation, a gas momentum conservation equation and a gas energy conservation equation, wherein the gas mass conservation equation and the gas energy conservation equation are respectively as follows:
wherein ρ is g Is the gas density;
is mass flow; k is the turbulent energy; mu, mu t Aerodynamic viscosity and turbulent viscosity, respectively; c (C) D Is the drag coefficient; d, d p Is the particle diameter; h g 、H s Specific enthalpy values of the gas phase and the water vapor, respectively; lambda (lambda) g Is the thermal conductivity of the gas; c (C) p Is the specific heat capacity; t (T) g Is the gas temperature; q (Q) C Is a convective heat transfer item;
the gas composition equation is:
in the fog drop evaporation equation: if the mist droplets are below the boiling point,
if the fog drops are higher than the boiling point, the evaporation rate is controlled by heat transfer,
wherein m is p Is the mass of the fog drops; d (D) g Is a binary diffusion coefficient; sh is Sherwood number; b (B) M Is a Spalding mass transfer criterion;
the fogdrop motion equation is:
wherein F is dis Is a turbulent diffusion force.
2. The method as recited in claim 1, further comprising:
the maximum distance statistical length or the maximum statistical time of the fog drops is preset.
3. The method as recited in claim 2, further comprising:
the grid of nozzle areas is locally encrypted.
4. A flow field optimization system for a desulfurization wastewater zero emission flue evaporation process, comprising:
the modeling module is used for conducting 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 movement and evaporation process of the fog drops in the calculation domain;
the simulation calculation module is used for carrying out numerical simulation calculation through the gas movement model, the gas component model, the fog drop evaporation model and the fog drop movement model in the process of movement and evaporation of fog drops in the calculation domain;
the judging module is used for judging whether the fog drops are completely evaporated and do not collide with the wall based on the numerical simulation calculation result;
the determining module is used for determining the type and the position of the current nozzle 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 when the fog drops are completely evaporated and no wall is bumped;
the adjusting module is used for adjusting the type and the position of the 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 also used for determining the type and the position of the nozzle of the adjusted flue and the layout of the guide plate as the flow field distribution of the desulfurization wastewater zero-emission flue evaporation process;
the simulation calculation module is used for carrying out numerical simulation calculation through a gas movement model, a gas component model, a fog drop evaporation model and a fog drop movement model in the process of movement and evaporation of fog drops in a calculation domain, and is specifically used for:
inputting gas phase temperature and gas flow in the gas motion model, and solving to obtain the velocity field distribution and pressure field distribution of the gas at different positions of the flue by combining the velocity field distribution of the fog drops in the fog drop motion model;
inputting gas phase temperature, gas flow and gas components into the gas component model, and solving to obtain concentration field distribution and component partial pressure of the gas at different positions of a flue by combining speed field distribution and pressure field distribution of the gas at different positions of the flue in the gas movement model and the amount of liquid converted into gas in the droplet evaporation model;
inputting liquid phase temperature, saturated vapor pressure of wastewater solution and desulfurization wastewater quantity into the fog drop evaporation model, and solving to obtain fog drop evaporation rate by combining the gas phase temperature, gas flow and partial pressure of each component in the gas component model;
inputting liquid phase temperature, desulfurization waste water amount, fog drop injection speed and fog drop particle size distribution into the fog drop motion model, and solving to obtain the speed field distribution of fog drops by combining the speed field distribution and the pressure field distribution of gas in the gas motion model at different positions of a flue and the fog drop evaporation rate in the fog drop evaporation model;
the gas motion model comprises a gas mass conservation equation, a gas momentum conservation equation and a gas energy conservation equation, wherein the gas mass conservation equation and the gas energy conservation equation are respectively as follows:
wherein ρ is g Is the gas density;
is mass flow; k is the turbulent energy; mu, mu t Respectively areAerodynamic viscosity and turbulent viscosity; c (C) D Is the drag coefficient; d, d p Is the particle diameter; h g 、H s Specific enthalpy values of the gas phase and the water vapor, respectively; lambda (lambda) g Is the thermal conductivity of the gas; c (C) p Is the specific heat capacity; t (T) g Is the gas temperature; q (Q) C Is a convective heat transfer item;
the gas composition equation is:
in the fog drop evaporation equation: if the mist droplets are below the boiling point,
if the fog drops are higher than the boiling point, the evaporation rate is controlled by heat transfer,
wherein m is p Is the mass of the fog drops; d (D) g Is a binary diffusion coefficient; sh is Sherwood number; b (B) M Is a Spalding mass transfer criterion;
the fogdrop motion equation is:
wherein F is dis Is a turbulent diffusion force.
5. The system of claim 4, further comprising:
the setting module is used for presetting the maximum distance statistical length or the maximum statistical time of the fog drops.
6. The system of claim 5, further comprising:
and the grid processing module is used for locally encrypting the grid of the nozzle area.
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