MXPA02005631A - An on line device for predicting at least one fluid flow parameter in a process - Google Patents

Abstract

There is described an on line device for predicting at least one fluid flow parameter in a process. In embodiment, the process in question comprises a flow domain having disposed therein a pre determined portion in which a fluid flows and the device comprises a computer having:(i) a memory for receiving a database, the database comprising relative information in respect of a plurality of nodes or a plurality of particle pathways in the pre determined portion;(ii) means to receive input data from the process;and (iii) means to calculate the at least one fluid flow parameter from the database and the input data. In another embodiment the process in question comprises a bounded flow domain having disposed therein a pre determined matrix and the device comprises a computer having:(i) a memory for receiving a database, the database comprising location information for a plurality of nodes or particle pathways in the matrix;(ii) means to receive input data from the process;and (iii) means to calculate the at least one fluid flow parameter fromthe database and the input data. The device is particularly advantageously employed as a UV dosimeter.

Description

AN ONLINE DEVICE TO FORECAST AT LEAST ONE PARAMETER OF FLUID OF FLUID IN A PROCEDURE TECHNICAL FIELD In one of its aspects, the present invention relates to an online device for predicting at least one fluid flow parameter in a method. In another of its aspects, the present invention relates to an online UV dosimeter for predicting equivalent doses of bioassay for a given microorganism in a UV disinfection process. In still another of its aspects, the present invention relates to a method for online prediction of at least one fluid flow parameter in a method.

BACKGROUND OF THE INVENTION Generally, fluid treatment systems are known in the art. For example, the patents of E.U.A. 4,482,809, 4,872,980 and ,006,244 (all in the name of Maarschalkerweerd and all assigned to the assignee of the present invention, and hereinafter referred to as the # 1 patents of Maarschalkerweerd) all describe gravity feed fluid treatment system employing ultraviolet (UV) radiation .

Such systems include an array of UV lamp frames, which include several UV lamps, each of which is mounted within sleeves extending between and supported by a pair of limbs that are attached to a crosspiece. The sleeves thus supported (containing the UV lamps) are immersed in a fluid to be treated, which is then irradiated as required. The amount of radiation to which the fluid is exposed is determined by the proximity of the fluid to the lamps, the output wattage of the lamps and the fluid flow velocity beyond the lamps. Typically, one or more UV sensors may be employed to verify the UV output of the lamps and the fluid level is typically controlled, to some degree, downstream of the treatment device through the level composite or the like. The patents of E.U.A. 5,418,370, 5,539,210 and 5,590,390 (all in the name of Maarschaikerweerd and all assigned to the assignee of the present invention and hereinafter referred to as the # 2 patents of Maarschaikerweerd) all describe fluid treatment systems employing UV radiation. More specifically, the Maarschaikerweerd patents # 2 teach an ultraviolet radiation treatment system arranged in an open channel comprising a flow of fluid fed by gravity. In a preferred embodiment, after treatment, the fluid is then discharged into a stream, estuary, river, lake or other body of water, ie, this mode represents the application of the system in a municipal wastewater treatment facility. Conventionally, in the technique of UV radiation treatment systems, the radiation dose in a given irradiation zone has been calculated using the equation: UU l - tp rom ed ¡o X 'average where tpromed¡0 is the time average that a microbe spends in the irradiation zone, and lpromedia is the average UV intensity integrated over the volume in the irradiation zone. Recently, it has been suggested that this calculation can relatively, in certain cases, lead to inaccuracies in the dose that is actually delivered to the fluid being treated, see, "Hydrodynamic behavior in open-channel UV systems: Effects on microbial inactivation" (K. Chiu, DA Lyn, and ER Blatchley III, CSCE / ASCE Envirommental Engineering Conference (1997), pp. 1189-1199). This can have important consequences, since many UV radiation treatment systems are largely specified using such calculation. In addition, the calculation presumes that the system is operating in an optimal state at all times and in this way, for example, could not take into account a situation where one or more of the UV radiation sources is not operating properly or not at all . Accordingly, there is a need in the art for a device that can allow to predict with improved accuracy the dose delivered to the fluid flow. It can also be advantageous if said device has been widely used further to predict dose delivered to a fluid flow in a UV radiation treatment system, ie, beyond the use of a dosimeter.

COMPENDIUM OF THE INVENTION It is an object of the present invention to avoid or mitigate at least one of the aforementioned disadvantages of the prior art. It is another object of the present invention to provide a novel online device for predicting at least one fluid flow parameter in a method. It is another object of the present invention to provide a novel method for online prediction of at least one fluid flow parameter in a method. In one of its aspects, the present invention provides an on-line device for predicting at least one fluid flow parameter in a method, the method comprises a limited flow domain having a predetermined matrix disposed therein, the device comprises a computer having: (i) a memory for receiving a database, the database comprising location information for a plurality of nodes or particle trajectories in the array, (ii) means for receiving input data from the procedure, and (iii) means for calculating at least one fluid flow parameter from the database and the input data. In another of its aspects, the present invention provides an online device for forecasting at least one fluid flow parameter in a method, the method comprises a flow domain having therein disposed a predetermined portion in which a fluid flows , the device comprises a computer having: (i) a memory for receiving a database, the database comprising relative information with respect to a plurality of nodes or a plurality of particle paths in the predetermined portion; (ii) means for receiving the input data of the method, and (iii) means for calculating at least one fluid flow parameter of the database and the input data. In another of its aspects, an in-line UV dosimeter device for predicting an equivalent dose of bioassay for a given microorganism in a UV disinfection process, the UV disinfection process comprising a flow domain in which a fluid flows, the device comprises a computer that has: (i) A memory to receive a database, the database comprising relative dose information with respect to a plurality of fluid path through the flow domain; (ii) means for receiving input data from the process, the input data selected from the group comprising UV transmission of the fluid, fluid flow velocity and field of intensity in the fluid domain; and (iii) means for calculating the equivalent dose of bioassay for the microorganism given from the database and the input data. In another of its aspects, the present invention provides a method for online prediction of at least one fluid flow parameter in a method, the method comprises a flow domain having therein a predetermined portion where it flows a fluid, the method comprises the steps of: (i) storing in a memory of a computer database, the database comprising relative information with respect to a plurality of nodes or a plurality of particle paths in the predetermined portion; (ii) obtain input data from the procedure; (iii) transport the input data to the computer; and (iv) calculating at least one fluid flow parameter of the database and the input data. A fundamental understanding of a chemical, photochemical or biological procedure is the key to forecast and control the productions of the procedure. Most of these types of procedure involve fluid flow, and fluid behavior can significantly affect the efficiency of the procedure. The better the understanding of fluid flow, the better the prediction and control of the procedure. An advantage of the present invention is an on-line prediction of at least one fluid flow parameter such as speed, pressure, temperature and turbulence parameters preferably calculated through computational fluid dynamics (CFD) and coupled with certain important parameters measured online at discrete points in the procedure of interest. If all the important flow parameters are known through the flow domain of interest, a much better prediction of the response of the system can be achieved, which leads to a better control of the procedure. For example, the invention can be applied to predict dose distribution profiles in a UV radiation fluid treatment system, mitigating and / or avoiding the aforementioned disadvantages of the prior art. Of course, those skilled in the art will recognize that the present invention can be used in a variety of other applications such as photochemical processes, chemical process, biological procedures, and the like.

BEST MODE FOR CARRYING OUT THE INVENTION The device of the present invention comprises a computer. The computer includes a memory to receive a database. The database comprises location information for a plurality of nodes in the array. The database can be obtained by determining the distribution of the flow parameters within a flow domain (for example, a channel or pipeline to contain a fluid in the process of interest). This can be achieved online or offline. If the database is obtained offline, there are two general techniques that can be used. The first comprises a "direct measurement" that uses techniques such as Doppler Laser Anemometry, Hot Wire Anemometry and Particle Image Velocimetry. The second comprises "numerical / computational techniques" typically referred to as CFD (Computational Fluid Dynamics), see, for example, "An introduction to Computational Fluid Dynamics" by Versteeg et al., (1995). If the database is obtained online, it is preferred to use numerical / computational techniques. More details on these techniques can be obtained from one or more of: 1. "Hot Wire Anemonetry", G. Compte-Bellot, Annu. Rev. Fluid Mech., Vol. 8, p. 209-231 (1976); 2. "Laser Velocimetry", Ronald J. Adrián, Chapter 5, in "Fluid Mechanics Measurements", Edited by Richard J. Goldstein, 1983; 3. "Digital Particle Image Velocimetry", C. E. Willert and M, Gharib, Experiments in Fluids 10, 181-193 (1991); 4. TSI Inc. at the website "http: / www. Tsi.com/"; 5. DANTEC Measurement Technology at the website: "http: / www. Dantecmt.com/"; 6. Fluentd Users Guide. Fluent Incorporated, Lebanon, NH, USA; and 7. Versteeg, H. K. and W. Malalasekera. An Introduction to Computational Fluid Dynamics. Longman Group Ltd., nineteen ninety five. In the preferred application of the present invention (ie, a UV dosimeter), the database, which is stored in the memory of the computer, must include location information for each of the plurality of nodes in the predetermined matrix in the limited flow domain. Preferably, the location information for each node includes: spatial position of the node, velocity vector components, pressure and some turbulence measurement, such as turbulence kinetic energy and turbulence dissipation velocity. The preferred aspect for determining the flow parameters within the flow domain through direct measurement is to establish a database of the parameters by measuring them through the a priori domain (for example, off-line), under conditions which are similar to those experienced in the procedure of interest. In the case of a UV disinfection reactor, for example, velocity, pressure and turbulence parameters can be measured at node locations of a thin three-dimensional grid (ie, the matrix) within the reactor at high flow rates for the operating conditions for the reactor. By repeating the measurements for different volume flow rate conditions, a representative database of variable flow conditions can be established. Essentially, the database consists of x, y, z positions of nodes representing physical measurement locations, and for each of the different volume flow rate, the important flow parameters (velocity, pressure, turbulence intensity, etc.), measured at each node. The preferred aspect for determining the flow parameters within the flow domain through numerical / computational techniques is to use CFD. By molding the flow within a reactor in a computer, an adequate database can be established comprising the necessary location information. If the database comprising the necessary location information is established experimentally or numerically, it is desirable that it be correlated with the online conditions. This is accomplished by measuring the important bulk flow parameters. In the case of a UV disinfection reactor, the important parameter may very well be the volume flow rate. At In the case of an online CFD system, a new database can be generated comprising location information, as the volume flow rate changes. On the other hand, if the database comprising the location information was generated offline (using CFD or direct measurement) then interpolation or escalation techniques can be used to closely approximate the online conditions of the conditions available in the database. Once the flow through the reactor has been determined for the given on-line conditions, transport equations can be solved to determine important process functions (as mentioned above). In the application of the invention to a UV disinfection reactor, the interest lies in the operation of the reactor, or specifically the inactivation of the target pathogen reactor. Biological inactivation can be modeled as a UV dose function applied using equations that consider first-order kinetics, microbial particle association, and microbial repair procedures.

Under first-order kinetics, biological inactivation can be modeled by: NL = e "kD (1) Not where N0 is the number of viable microbes before disinfection and N is the number of viable microbes after disinfection. The constant k depends on the type of microbe that is being inactive and D is the dose delivered.The dose is defined as the germicidal intensity against exposure time. In a real reactor, the UV intensity will vary with the spatial position within the reactor (less UV intensity in regions away from the lamp) and with the UV transmittance (UVT) of the water. Since the position of the lamps is known (the geometry of the reactor is known) and the UVT can be measured online, the field of intensity inside the reactor can be calculated and correlated with in-line sensor readings. As the microbes move through the reactor, due to the movement of the fluid (in this case water), they will pass through the intensity field. Clearly, the trajectory of a microbe will experience varying degrees of intensity as it moves through the reactor. The integration of the intensity field with the trajectory traveled and the exposure time to UV will produce a dose value for each microbe. A UV reactor will have an infinite number of trajectory lines that the microbes will track, each distinct trajectory receiving a different dose, D ,. Since a reactor will have an infinite number of trajectories that a microbe can follow, the net inactivation of the reactor can be written as: where f, is the fraction of particles that receive a dose D ,, so that: S i * I? = 1- Inactivation of the reactor can be molded as N_ = e-kDeqv (3) No where N0 is now the flow of viable microbes upstream of the reactor (or the total number of viable microbes in the case of a collimated beam study) and N is the flow of viable microbes downstream of the reactor, after disinfection. Deqv is the dose supplied by the reactor. The "dose" that the reactor supplies or the "equivalent dose" can be determined by combining Equations (2) and (3) to give: N e ° S i »! í »- * '' (4) Essentially, the performance of the reactor is determined by integrating all the microbial paths through the reactor. Computationally, this can be determined from the database comprising the location information for each node. There are two conventional CFD methods that can be used to accomplish this task: 1.- The Eulerian / scalar aspect and 2.- The Lagrangian particle tracking aspect. In the Eulerian aspect, the dose, D, is treated as a scale, and the equation for scalar transport integrated with the intensity field and the database comprising the location information can be used to determine a dose distribution in the output of the reactor. The integration of the output dose distribution with the volume fraction of output volume flow and equation (5) will provide a reactor performance value based on the target organism inactivation constant, k. The difficulty with the Eulerian aspect is that the scalar equations represent turbulent diffusion and mixing that averages the dose. In reality, each microbe is a discrete unit and should be treated as such and thus should not be averaged. Commercial CFD software can be used to implement the equations more easily, see, for example, the operator's manual for the Fluent ™ CFD software. It should be emphasized that a database can be used both numerically and experimentally generated, comprising information from location with conventionally CFD software. The preferred aspect is to use Lagrangian particle tracking. With this aspect, the database comprising the location information for each node is used to determine the movement of discrete particles through the reactor. The particle path can be integrated with the known intensity field to determine the dose delivered to each particle. Each particle will have its own trajectory and while two trajectories are not identical, a sufficient representation of dose distribution can be achieved by calculating the trajectories of, for example, 100 particles. In this aspect, Equations (4) and (5) can be used directly, with the upper limit of the sum set at n, where n is the number of trajectories of representative particles and fj = 1 / n. In a preferred embodiment of the invention, the database comprises location information for a plurality of particle lanes in at least a portion of the array (i.e., in place of the location information for a plurality of nodes through of the matrix). In this way, the database is obtained independently of the intensity field. In other words, instead of storing the database comprising the location information online, the database can be used to establish a database of a priori particle lanes, and only the particle lanes needed to be stored. online. This improvement reduces computational effort even more.

As indicated above, a fundamental understanding of a chemical, photochemical or biological procedure is the key to forecasting and controlling the productions of the procedure. For example, the present invention can be applied to the prediction of disinfection performance in a UV radiation fluid treatment system, mitigating and / or avoiding the disadvantages of the aforementioned prior art. More specifically, a preferred embodiment of the in-line device of the present invention is a UV dosimeter used to predict the equivalent bioassay dose in a given UV disinfection system and method.

In this preferred embodiment of the device of the present invention, the database comprises dose data for a plurality of virtual particles that pass through a UV disinfection process, wherein each virtual particle can represent a microbe, an aggregation of microbes and another material, or a molecule of a chemical. The dose for each virtual particle as it passes through the reactor can be determined by integrating the UV intensity experienced by the particle in the trajectory in which the particle travels through the UV disinfection process. Mathematically, this relationship can be expressed as: í = 0 where: D, is the UV dose in mJ / cm2 experienced by the virtual particle after it has traveled through the UV disinfection procedure; l (x, y, z) is the UV intensity in W / cm2 experienced by the particle in the position (x, y, z) on its path through the UV disinfection procedure; and t is the time in seconds, where t = 0 represents the time in which the particle enters the UV disinfection process and t = tr represents the time in which the particle leaves the UV disinfection procedure. The trajectory that travels to the virtual particle as it passes through the reactor can be determined through "direct measurement" using techniques such as Doppler laser anemometry, hot wire anemometry or particle image velocimetry. "O the trajectory can be predicted using "numerical / computational techniques", typically referred to as computational fluid dynamics (CFD). Those skilled in the art will recognize that CFD techniques allow physical attributes to be attributed to virtual particles in order to model the effects of forces such as gravity in virtual particles When using these methods, the trajectory of virtual particles will typically be defined using a space-time coordinate system (x, y, z, t), where x, y, z define a Three-dimensional, spatial coordinate system and t represent time. Those skilled in the art will recognize that radial or polar coordinate systems can be used and that considerations of symmetry will allow virtual particle trajectories through some UV disinfection procedures to be represented by one or two dimensional spatial coordinate systems as opposed to the three-dimensional systems. Since the trajectories of the virtual particles through the UV disinfection procedures will typically be represented using consecutive series of space-time coordinates, the dose delivered to each particle will be written using the addition notation as: Where the particle trajectory jth through the UV disinfection procedure is represented by determinations of space-time coordinates kj. The UV intensity at the position (x, y, z) within a UV disinfection procedure can be calculated using standard optical techniques using any radial intensity model as described by: C. Hass and C. P. Sakellaropoulos (1979) "Rational analysis of ultraviolet disinfection", National Conference on Envirommental Engineering, Proc. ASCE Specialty Conf., San Francisco, CA, Jui 9-11, p. 540-547; Or by the sum of point source as described by: S. M. Jacob and J. S. Dranoff (1970) "Light intensity profiles in a perfectly mixed photoreactor", AlChE Journal, Vol. 16, No. 3, p. 359-363; or by the Point Source Sum modified to include refraction effects as per: JR Bolton (1999) "Significance of refraction and reflection in the calculation of ultraviolet fluence rate distributions in annular ultraviolet disinfection reactor using broadband medium-pressure mercury UV lamps" . Those skilled in the art will recognize that a plurality of intensity models can be defined for UV disinfection procedures and that each model can offer a reasonable prediction of UV intensity depending on the UV absorbance characteristics of the water being treated and the configuration of the UV reactor. The convenience of the intensity model can be tested using any UV intensity measurement through a radiometer, actinometry, or some other recognized measurements for UV light. In the preferred application of the present invention for a UV disinfection process using more than one UV lamp, the dose delivered to the virtual particle for each UV lamp operating at a total energy is calculated and stored in the database. Therefore, if the UV disinfection procedure uses "L" UV lamps, for each virtual particle, the database contains the dose delivered to that particle by the first UV lamp, the second UV lamp, and so on until the Lth lamp UV In a possible manifestation of the database, the information for a three-lamp reactor can be structured as set forth in Table 1. Those skilled in the art will recognize that the path taken by each virtual particle as it passes through the UV disinfection procedure, will depend on the flow rate and other characteristics of the water. The database may contain dose data for a plurality of flow rates through the disinfection process and a plurality of water characteristics. However, in a preferred application of the invention, only a limited number of flow conditions are stored in the database and dose values for other conditions are obtained by scaling the stored numbers. For example, the dose delivered to a virtual particle at a flow rate x can be calculated from the dose at the flow rate and multiplying that dose by the ratio of flow velocity and flow velocity x. Those skilled in the art will also recognize that the intensity experienced by each virtual particle as it passes through the UV disinfection procedure will depend on the UV transmission of the water being treated. The database may contain dose data for a plurality of UV transmission values. However, in a preferred application of the invention, the dose dependence provided by a given lamp at a given flow rate to each virtual particle as a function of UV transmission can be modeled using some function and the function coefficients can be stored within the database. For example, the dose delivered to a virtual particle by a given lamp at a given flow rate can be described as a function of UV transmission varying from 30 to 99%, using a polynomial function of the fifth order. In that case, the database only needs to contain the five coefficients associated with that polynomial function to describe the dose on that UV transmission scale.

TABLE 1 Those skilled in the art will further recognize that UV lamps may be operating at different energy levels and that their UV production may vary from lamp to lamp, due to factors such as the age of the lamp and the incrustation of the lamp sleeve. In a manifestation of the present invention, the dose delivered to each virtual particle by a given lamp can be scaled by the electrical energy set for that lamp. In another manifestation, the dose delivered to each virtual particle can be scaled by the ratio of the UV intensity measured using a UV sensor calibrated to UV intensity calculated by that sensor using the appropriate or expected UV intensity model of sensor measurements obtained using new lamps, non-incrusted lamp sleeves and non-inlay sensor detection windows. The net dose experienced by the virtual particle ith as it passes through the UV disinfection procedure can be calculated by adding up the contribution to that particle of each lamp inside the reactor. In a preferred manifestation, the net dose per virtual particle can be calculated as: (Net Dose) ,. H.H ? ^ se ^ l? T) / " where: QCFD is the flow velocity associated with the space-time coordinates of the virtual particle lanes stored in the database; Q is the actual flow velocity that passes through the UV disinfection procedure; DosiSjn (UVT) is the dose delivered to the virtual particle i by the lamp n to a UVT UVT transmission; and Fn is the scale factor for the n lamp to represent the energy setting of the lamp and sensor measurements that indicate the incrustation or age of the lamp. In order to forecast the dose supply of the UV disinfection procedure, the dose delivered to a plurality of virtual particles must be calculated. The trajectories of the particles must start inside the inlet pipe upstream of the UV disinfection procedure. The starting location of the virtual particles within the inlet pipe must be sufficiently upstream of the reactor that delivers the dose to the virtual particles through the UV disinfection procedure that is not significantly affected by the movement of that additional upstream location. . In a preferred application of the invention, the starting locations of the virtual particles lie in a plane perpendicular to the bulk flow and are uniformly distributed across that plane. Those skilled in the art will recognize that the inlet pipe to a UV disinfection process may vary from one installation to the next. Since the configuration of the inlet pipe will have an impact on the path of the virtual particles as they pass through the UV disinfection process, an advantage of the present invention is the ability to determine site-specific considerations that agree on the operation of the UV disinfection procedure. In a typical application of the invention, the delivery of doses to more than 250 virtual particles is determined. Those skilled in the art will recognize that two particles will not follow the same path through the UV disinfection process. Therefore, two particles will not receive exactly the same dose UV Accordingly, the dose delivery to a UV reactor can be presented as a dose histogram. In addition, the dose histogram can be modeled using a probability distribution, which can be combined with treatment kinetics to predict the net impact of the UV disinfection procedure. The net performance of the UV disinfection process can be calculated by adding the impact of the net doses delivered to each of the virtual particles. The impact of doses can be described using determined kinetic equations using standard laboratory practice. In the case of UV disinfection, the kinetics of UV inactivation for a particular microbe can be determined by exposing a stirred suspension of those microbes to a collimated beam of UV light of known UV intensity. Through several exposure times, several doses are applied. The kinetics of inactivation can be obtained by plotting the inactivation achieved as a function of dose delivered. An inactivation graph as a dose function can be modeled using first order kinetics.

N / No = exp (-k Dosage) where: It is not the concentration of viable microbes before exposure to UV; N is the concentration of viable microbes after the exposure to a UV dose; K is the first-order inactivation constant of microbes. Those skilled in the art will recognize that the kinetics of microbial inactivation do not always follow the first-order kinetics. In those cases, a serial event model, a double exponential model or some other conventional function may be more appropriate to describe the relationship between inactivation of the dose.

Given a g (Dosage) function that describes the kinetics of microbial inactivation, the net reactor performance can be calculated using: % 0 = 2 ^ ((D ° sisNeta) .V '" where m is the total number of virtual particles that are considered to have passed through the UV treatment procedure. The net yield of the reactor can be associated with a dose equivalent value using inactivation kinetics by solving: g (Dose Equivalent) = ¿g ((Net Dose),) / In the case of first-order kinetics, these equations can be written as: % fo ß? e p (* (Net Dose),) / m Y . í_. r Equivalent of Dose = »-In I ^ exp (fc (Net Dose),) / m / k.

Although the invention has been described to preferred embodiments and specifically illustrated, it will, of course, be understood by those skilled in the art that various modifications to these preferred and illustrated embodiments may be made without departing from the spirit and scope of the invention. All publications, patents and patent applications referred to herein are hereby incorporated by reference in their entirety to the same degree as each publication, patent or individual patent application will be specifically and individually indicated as being incorporated by reference in its entirety.

Claims (53)

1. - An online device for predicting at least one fluid flow parameter in a procedure, the method comprises a limited flow domain having a predetermined matrix disposed therein, the device comprising a computer having: (i) a memory for receiving a database, the database comprising location information for a plurality of nodes or particle trajectory in the matrix, (ii) means for receiving procedural input data, and (iii) means for calculating minus a fluid flow parameter of the database and the input data.

2. The device according to claim 1, wherein the database is independently generated and stored in the memory for at least one predetermined flow state.

3. The device according to claim 2, wherein the database is independently generated using a particle tracking routine of the Lagrangian type.

4. The device according to claim 2, wherein the database is independently generated using a scalar convection diffusion routine of the Eulerian type.

5. The device according to any of claims 1-4, further comprising means for adjusting the database in the event that the input data does not correspond to at least one predetermined flow state.

6. The device according to any of claims 1-5, wherein the database is generated online through computational fluid dynamics.

7. The device according to any of claims 1-6, wherein the matrix comprises a one-dimensional arrangement of nodes.

8. The device according to any of claims 1-6, wherein the matrix comprises a two-dimensional array of nodes.

9. The device according to any of claims 1-6, wherein the matrix comprises a three-dimensional arrangement of nodes.

10. The device according to any of claims 1-9, wherein the method comprises a method of treating radiation fluid.

11. The device according to claim 10, wherein at least one fluid flow parameter comprises radiation dose.

12. The device according to any of claims 1-9, wherein the method comprises a chemical process.

13. The device according to claim 12, wherein at least one fluid flow parameter comprises the concentration of at least one chemical in the procedure.

14. The device according to any of claims 1-9, wherein the method comprises a biological process.

15. The device according to claim 14, wherein at least one fluid flow parameter comprises viability of an organism in the biological process.

16. The device according to any of claims 1-15, wherein the limited flow domain 10 comprises an open reactor, wherein the process is conducted.

17. The device according to claim 16, wherein the open reactor comprises a channel through which it flows - a fluid.

18. The device according to any of claims 1-15, wherein the limited flow domain comprises a closed reactor wherein the process is conducted.

19. The device according to claim 18, wherein the closed reactor comprises a channel through which a fluid is contained.

20. The device according to any of claims 1-20, further comprising means to mean the calculation of at least one fluid flow parameter.

21. The device according to claim 20, in where the means to mean comprise a visible indicator.

22. The device according to claim 20, where the visible indicator comprises a presentation.

23. The device according to claim 20, wherein the visible indicator comprises a color indicator.

24. The device according to claim 20, wherein the means to signify comprise an audible indicator.

25. The device defined according to claim 20, wherein the means to signify comprise a visible indicator and an audible indicator.

26. The device according to any of claims 1-25, further comprising means for controlling the method in consequence to a calculation of at least one fluid flow parameter.

27. The device according to claim 26, wherein the means for controlling comprise means for comparing the calculation of at least one fluid flow parameter with a predetermined threshold value for at least one fluid flow parameter .

28. The device according to any of claims 1-27, wherein the means for receiving input data of the method comprises a keyboard.

29. The device according to any of claims 1-27, wherein the means for receiving input data of the method comprises an electronic controller.

30. - The device according to any of claims 1-30, wherein the computer is located in a first location and the procedure is located at a second location away from the first location.

31. The device according to claim 30, wherein the computer further comprises a telecommunications link to allow communication between the first location and the second location.

32.- An online device for predicting at least one fluid flow parameter in a method, the method comprises a flow domain having a predetermined portion disposed therein, wherein a fluid flows, the device comprises a computer having: (i) a memory for receiving a database, the database comprising relative information with respect to a plurality of nodes or a plurality of particle paths in the predetermined portion; (I) means for receiving input data from the method, and (iii) means for calculating at least one fluid flow parameter of the database and the input data.

33. The device according to claim 32, wherein the database is independently generated and stored in the memory for at least one predetermined flow state.

34- The device according to claim 33, in where the database is independently generated using a Lagrangian particle tracking routine.

35. The device according to claim 33, wherein the database is independently generated using a scalar convection broadcast routine of the Eulerian type.

36. The device according to any of claims 32-35, further comprising means for adjusting the database in the event that the input data does not correspond to at least a predetermined flow state.

37.- The device according to any of claims 32-36, wherein the database is generated online through computational fluid dynamics.

38.- The device according to any of claims 32-37, wherein the predetermined portion comprises a one-dimensional array of nodes.

39.- The device according to any of claims 32-37, wherein the predetermined portion comprises a two-dimensional array of nodes.

40.- The device according to any of claims 32-37, wherein the predetermined portion comprises a three-dimensional array of nodes.

41. The device according to any of claims 32-40, wherein the method comprises a method of treatment of radiation fluid.

42.- The device according to claim 41, in wherein at least one fluid flow parameter comprises radiation dose.

43.- The device according to any of claims 32-40, wherein the method comprises a chemical process.

44. The device according to claim 43, wherein at least one fluid flow parameter comprises the concentration of at least one chemical in the process.

45.- The device according to any of claims 32-41, wherein the method comprises a biological procedure.

46.- The device according to claim 45, wherein at least one fluid flow parameter comprises viability of an organism in the biological process.

47. The device according to any of claims 32-46, wherein the predetermined portion is composed of a limited flow domain.

48. The device according to claim 47, wherein the limited flow domain comprises an open reactor in which the process is conducted.

49.- The device according to claim 48, wherein the open reactor comprises a channel through which a fluid flows.

50.- The device according to claim 47, wherein the limited flow domain comprises a reactor closed in where the procedure is conducted.

51. The device according to claim 50, wherein the closed reactor comprises a channel through which a fluid is contained.

52. The device according to any of claims 32-51, further comprising means for meaning- ing the calculation of at least one fluid flow parameter.

53. - The device according to claim 52, wherein the means for meaning comprise a visible indicator. 54.- The device according to claim 52, wherein the visible indicator comprises a presentation. 55.- The device according to claim 52, wherein the visible indicator comprises a color indicator. 56.- The device according to claim 52, wherein the means to signify comprise an audible indicator. 57.- The device defined according to claim 52, wherein the means to signify comprise a visible indicator and an audible indicator. 58.- The device according to any of claims 32-57, further comprising means for controlling the method in consequence to a calculation of at least one fluid flow parameter. 59.- The device according to claim 58, wherein the means for controlling comprise means for comparing the calculation of at least one fluid flow parameter with a predetermined threshold value for at least one fluid flow parameter. 60.- The device according to any of claims 32-59, wherein the means for receiving input data of the method comprises a keyboard. 61.- The device according to any of claims 32-59, wherein the means for receiving input data of the method comprises an electronic controller. * 62.- The device according to any of the 10 claims 32-61, wherein the computer is located in a first location and the procedure is located in a second location away from the first location. 63.- The device according to claim 62, in * where the computer also comprises a telecommunications link to allow communication between the first location and the second location. 64.- An online UV dosimeter device to predict an equivalent dose of bioassay for a given microorganism in a UV disinfection procedure, the procedure of 20 UV disinfection comprises a flow domain where a fluid flows, the device comprises a computer having: (i) A memory to receive a database, the database comprising relative dose information with respect to a plurality of trajectories of fluid through the flow domain; 25 (ii) means to receive input data from the procedure, the input data selected from the group comprising UV transmission of the fluid, fluid flow velocity and intensity field in the fluid domain; and (iii) means for calculating the equivalent dose of bioassay 5 for the given microorganism from the database and the input data. 65.- A method for online prediction of at least one parameter of fluid flow in a procedure, the procedure ** __ includes a flow domain that has a disposition in it The predetermined portion in which a fluid flows, the method comprises the steps of: (i) storing in a memory of a computer database, the database comprising relative information with respect to a plurality of nodes or a plurality of particle trajectories in the predetermined portion; (ii) obtain input data from the procedure; (iii) transport the input data to the computer; and (iv) calculating at least one fluid flow parameter of the database and the input data.