Pressure Loss & Transfer Coefficients

The new version of the software gives a graphical representation of both the transfer coefficients and pressure drop contributions of the various relevant components of the cooling tower. These values will help cooling tower designers to identify areas that can be optimised to improve cooling tower performance. Higher transfer coefficients and lower pressure drop values are generally required for optimal performance. The next two graphs give the relative contribution of the cooling tower components to the transfer and pressure drop respectively.

Transfer Contribution

Pressure Drop Contribution

Plenum Chamber & Fan Coverage

The new version of the software has a visual tool to help the designer to evaluate the fan coverage ratio and angles. These variables are checked against API recommended values. The coverage angle is indicated in green when it complies to API requirements. It will be indicated in red if the fan coverage falls outside API recommendations.

Fan Coverage

Software Convergence

The new version of the software that is under development will inform the user about the convergence of the solution algorithm. It was mentioned in a previous blog post that the software employs an iterative solution scheme. The image below shows how much the solution variables changes from one iteration to the next. The algorithm will stop when the tolerances of all the solution variables are below pre-defined values. These tolerance levels are also indicated on the graphs. It is evident that the water outlet temperature, or Two, was the last variable to reach the predefined tolerance level. The values on the y-axis are shown on a log scale.

Convergance Tolerance

The next image shows how the values of the solution variables converge to the final values.
Convergance Values

Supersaturated psychrometric chart

The new version of the software will generate psychrometric charts, showing the path of the air as it moves through the cooling tower. This visual graphical representation will aid cooling tower designers in designing hybrid cooling towers, ensuring that outlet air is unsaturated, thus eliminating visible plumes.

An example where the inlet air is already saturated with water vapour is shown below. The air becomes becomes supersaturated as it gets in contact with the water.

Psychro Supersaturated

Here is an example where the inlet air is hot and dry.

Psychro HotDry

The psychrometric saturated chart will be a standard feature of the new software.

New software version under development

I am excited to let you know that I am working on a new version of the software. The first version of the software was developed as a tool to do academic research. It was therefore not necessarily very user friendly as it included many futures that were not needed for the practical design of cooling towers. The software served its purpose as many journal articles were published using it. Some of the features in the original version will be excluded in the new version. Some of these excluded features are:
  • Input humidity profiles
  • Different integration options for the Merkel method (i.e. Simpson, trapezoidal rule)
  • Some of the iteration parameters like tolerances and the maximum number of iterations in the Poppe method will be removed.

There is unfortunately not an expected date of completion at the moment, but I will publish updates on the progress.

Cooling Tower Performance Curves

The software does not have the capability to generate performance curves. Every point on every curve needs to be calculated manually. A graph plotting application like MS Excel needs to be used to plot the curves. Manufacturors and users of cooling towers have very diverse requirements when it comes to performance curves. It is therefore easier, for a generic software package like wetcooling, to calculate the performance points manually over the required input parameter ranges.

Wetcooling Software: Design vs Verification

The wetcooling software was developed with design verification in mind, not to give optimal designs as output. The reason for this is that designers and manufaturors of cooling towers generally have their own preferences on dimensions and size ratios. It is therefore difficult to incorporate these different design preferences into the software that will satisfy all the various permutations. One enter all the current dimensations, design parameters and ambient conditionsin the software and it will calculate the water outlet temperature and the air outlet conditions. The water outlet temperature is generally the most important thermal design output variable. This is not to say that the software can’t be used for the design of cooling towers, of course it can, but it is a much more manual process, with trial and error optimisation.

Cooling Tower Design from Scratch

Where does one start when designing a mechanical draft cooling tower from scratch? This can be quite a daunting task as there are many variables and opposing objectives when optimizing the design. The steps below should give an appropriate starting point for the design process with my cooling tower software. The software is then employed to optimize the design. The process typically involves some trial-and-error to obtain the desired water outlet temperature.

For a start the following design conditions must be specified:
  • Wet Bulb Temperature
  • Design water flow rate per cell (mwi)
  • Dry Bulb Temperature
  • Hot Water Temperature
  • Cold Water Temperature.

It is also advisable at this stage to know what type of fill will be employed. The decision of the type of fill will be a function of the water quality and the fouling propensity of the fill.

The first important design decision one needs to make is what the frontal area of the fill (Afr) should be. One parameter that can guide you in this decision is the water mass velocity, Gw, where Gw = mwi/Afr. Your fill supplier should be able to tell you what the typical recommended range for Gw is.

If the recommended Gw for the fill is known Afr can now be calculated, where Afr = mwi/Gw

It is further assumed that the tower is square. The actual area of the cooling tower is larger than the area of the fill due to the area that the fill supports etc. are taking up. Lets assume for argument sake that the actual plan area is 1.05 times the area of the fill. Assuming a square tower the actual inside dimensions of the tower can now be determined.

Cooling tower fills are generally packed in layers where the layers have a fixed height. Pick any number of layers that will give a practical height, e.g. 2m.

The next decision is the required air flow rate. A first guess for the air flow rate is based on the following. According to one publication the ratio of the water and air flow mass velocities (Gw/Ga) should be between 0.75 and 1.5 for mechanical draft cooling towers. A Gw/Ga ratio of one is therefore a good first assumption, i.e. the air flow rate is equal to the water mass flow rate.

The rest of the inputs in the software should be typical for mechanical draft cooling towers. A trail and error process will now be conducted to achieve the design water outlet temperature. With the first run of the software the water outlet temperature will probably be too hot or too cold. A decision can now be made to l alter the air flow rate, the fill height or both.

When the tower design is complete a fan must be selected. Refer to the second point in the blog entry entitled “Fan Specification” on how to do this.

Fill transfer characteristics

Cooling tower transfer characteristics is one of the most, if not the most important parameters in cooling tower thermal design. Unlike heat exchangers, where transfer coefficients for various configurations are widely published, cooling tower transfer characteristics are not commonly found in the open literature. One of the reasons for this is that fill manufacturer’s regard the transfer characteristics of their fills as confidential. The following two sources do give transfer coefficients of various fills:

  • Lowe, H.J. and Christie, D.G., Heat Transfer and Pressure Drop Data on Cooling Tower Packings and Model Studies of the Resistance of Natural Draft Towers to Airflow, Proceedings of the International Heat Transfer Conference, Colorado, Part V, pp. 933-950, 1961.
  • Johnson, B.M. (ed.), Cooling Tower Performance Prediction and Improvement, Volume 1, Applications Guide, EPRI Report GS-6370, Volume 2, Knowledge Base, EPRI Report GS-6370, EPRI, Palo Alto, 1989.

If you are aware of any other sources that give fill performance data, then I would appreciate it if you can let me know about it.

The only way to be certain of what the transfer characteristics are for a fill, is to do an independent fill test. This can be a costly undertaking, but if you take the penalties involved if a cooling tower does not meet the guaranteed performance, this is a small price to pay. The only problem is that there are only a few facilities globally where tests like these can be conducted.

Numerical Instability and Convergence

The software appears to be not running if the solution algorithm becomes numerically unstable. Numerical instability during the program run is unfortunately a problem with most software packages of this nature. There are however many measures that can be taken to fix the problem from the software input windows. Here is a short summary of steps to follow to obtain solutions (numerical convergence):
  • Try different initial conditions for the design parameters in the Solution Control Window. Select “Auto” initialization so that the initial parameters are calculated by the software.
  • If the problem still persist then change the values of the relaxation parameters in the Solution Control Window. The values should be less than 1 and greater than zero. If it is too small then the software might show that the solution converged when it actually hadn’t. If the solution converged then use the applicable results in the “output.txt” file as initial values in the Solution Control Window. Use larger relaxation parameters when re-running the software with the new initial conditions.
  • Make sure that the black command window that open when the software is running is closed before attempting a new run. If the old command window is open the software can't start a new run.
  • If a cooling tower is designed from scrath it is important to select cooling tower dimentions that are realistic. It is important to update the fan diameter dimentions as well. The fan diameter is not enetered in the cooling tower specification window, but in the fan specification window.
  • If the software runs successfully for the Merkel model but not the Poppe model (and you have already tried the steps above with no success) then try the following:
  • Run the software with the Merkel method. Use the applicable outputs as initial values in the Solution Control Window. Rerun the software with the Poppe model selected.
  • If the program still not runs then select a different “Solution algorithm” from the Model Settings Window. Change the settings on the window from “Secant” to “Energy eq.” or vice versa.

Favorite Cooling Tower References

Below is a list of my favorite cooling tower references:

  • Lewis, W.K., The Evaporation of a Liquid into a Gas, Transactions of ASME, Vol. 44, pp. 325-340, May, 1922.
  • Merkel, F., Verdunstungskühlung, VDI-Zeitchrift, Vol. 70, pp. 123-128, January 1925.
  • Lewis, W.K., The Evaporation of a Liquid into a Gas – A Correction, Mechanical Engineering, Vol. 55, pp. 567-573, 1933.
  • Hutchison, W.K. and Spivey, E., Design and Performance of Cooling Towers, Transactions of the Institute of Chemical Engineers, Vol. 20, pp. 14-29, 1942.
  • Zivi, S.M. and Brand, B.B., An Analysis of the Crossflow Cooling Tower, Refrigerating Engineering, Vol. 64, pp. 31-34 & 90-92, 1956.
  • McKelvey, K.K. and Brooke, M., The Industrial Cooling Tower, Elsevier Publishing Company, Amsterdam, 1959.
  • Baker, D.R. and Shryock, H.A., A Comprehensive Approach to the Analysis of Cooling Tower Performance, Transactions of the ASME, Journal of Heat Transfer, pp. 339-350, 1961.
  • Berman, L.D., Evaporative Cooling of Circulating Water, 2nd Edition, Chapter 2, pp. 94-99, ed. Sawistowski, H., Translated from Russian by R. Hardbottle, Pergamon Press, New York, 1961.
  • Lowe, H.J. and Christie, D.G., Heat Transfer and Pressure Drop Data on Cooling Tower Packings and Model Studies of the Resistance of Natural Draft Towers to Airflow, Proceedings of the International Heat Transfer Conference, Colorado, Part V, pp. 933-950, 1961.
  • Bosnjacovic, F., Technische Thermodinmik, Theodor Steinkopf, Dresden, 1965.
  • CTI, Cooling Tower Performance Curves, The Cooling Tower Institute, Houston, 1967.
  • Nahavandi, A. N., Kershah, R.M. and Serico, B.J., The Effect of Evaporation Losses in the Analysis of Counterflow Cooling Towers, Journal of Nuclear Engineering and Design, Vol. 32, pp. 29-36, 1975.
  • Kelly, N.W., Kelly’s Handbook of Crossflow Cooling Tower Performance, Kansas City, Missouri, Neil W. Kelly and Associates, 1976.
  • Kelly, N.W., A Blueprint for the Preparation of Crossflow Cooling Tower Characteristic Curves, Paper Presented before the Cooling Tower Institute Annual Meeting, January, 1976.
  • Montakhab, A., Waste Heat Disposal to Air with Mechanical and Draft – Some Analytical Considerations, Heat Transfer Division of the ASME, Winter Annual Meeting, San Francisco, 1978.
  • Cale, S.A., Development of Evaporative Cooling Packing, Commission of European Communities, Report EUR 7709 EN, Luxembourg, 1982.
  • Missimer, J. and Wilber, K., Examination and Comparison of Cooling Tower Component Heat Transfer Characteristics, IAHR Cooling Tower Workshop, Hungary, October 12-15, 1982.
  • Stoecker, W.F. and Jones, J.W., Refrigeration and Air Conditioning, McGraw-Hill Book Co., Singapore, 1982.
  • Bourillot, C., TEFERI, Numerical Model for Calculating the Performance of an Evaporative Cooling Tower, EPRI Report CS-3212-SR, August 1983.
  • Bourillot, C., On the Hypothesis of Calculating the Water Flowrate Evaporated in a Wet Cooling Tower, EPRI Report CS-3144-SR, August 1983.
  • Majumdar, A.K., Singhal, A.K. and Spalding, D.B., Numerical Modeling of Wet Cooling Towers – Part 1: Mathematical and Physical Models, Transactions of the ASME, Journal of Heat Transfer, Vol. 105, pp. 728-735, November 1983.
  • Majumdar, A.K., Singhal, A.K., Reilly, H.E. and Bartz, J.A., Numerical Modeling of Wet Cooling Towers – Part 2: Application to Natural and Mechanical Draft Towers, Transactions of the ASME, Journal of Heat Transfer, Vol. 105, pp. 736-743, November 1983.
  • Majumdar, A.K., Singhal, A.K. and Spalding., D.B., VERA2D: Program for 2-D Analysis of Flow, Heat, and Mass Transfer in Evaporative Cooling Towers, EPRI Report CS 2923, Volume 1 and 2, March 1983.
  • Sutherland, J.W., Analysis of Mechanical-Draught Counterflow Air/Water Cooling Towers, Transactions of the ASME, Journal of Heat Transfer, Vol. 105, pp. 576-583, August 1983.
  • Poppe, M. and Rögener, H., Berechnung von Rückkühlwerken, VDI-Wärmeatlas, pp. Mh1-Mh15, 1984.
  • Li, K.W. and Priddy, A.P., Power Plant System Design, John Wiley & Sons, 1985.
  • Wilber, K.R., Yost, J.G. and Wheeler, D.E, An Examination of the Uncertainties in the Determination of Natural Draft Cooling Tower Performances, Joint AMSE/IEEE Power Generation Conference, Milwaukee, Wisconsin, October 20-24, 1985.
  • Hoffmann, J.E., Bedryfspunt Voorspelling vir Nat Koeltorings, M.Eng Thesis, University of Stellenbosch, Stellenbosch, South Africa, 1987.
  • British Standard 4485, Water Cooling Towers, Part 2: Methods for Performance Testing, 1988.
  • Dreyer, A.A., Analysis of Evaporative Coolers and Condensers, M.Eng Thesis, University of Stellenbosch, Stellenbosch, South Africa, 1988.
  • Jaber, H. and Webb, R.L., Design of Cooling Towers by the Effectiveness-NTU Method, Journal of Heat Transfer, Vol. 111, pp. 837-843, November 1989.
  • Johnson, B.M. (ed.), Cooling Tower Performance Prediction and Improvement, Volume 1, Applications Guide, EPRI Report GS-6370, Volume 2, Knowledge Base, EPRI Report GS-6370, EPRI, Palo Alto, 1989.
  • Cooling Tower Institute, CTI Code Tower, Standard Specifications, Acceptance Test Code for Water-Cooling Towers, Part I, Part II and Part III, CTI Code ATC-105, Revised, February 1990.
  • Surridge, A.D., Swanepoel, D.J.deV., Held, G., Research on Thermal Feedback Caused by Dry-Cooling Power Generating Stations, Confidential Report, EMA-C 9086, CSIR, Pretoria, 1990.
  • Feltzin, A.E. and Benton D., A More Exact Representation of Cooling Tower Theory, Cooling Tower Institute Journal, Vol. 12, No. 2, pp. 8-26, 1991.
  • Osterle, F., On the Analysis of Counter-Flow Cooling Towers, International Journal of Heat and Mass Transfer, Vol. 34, No. 4/5, pp. 1313-1316, 1991.
  • Poppe, M. and Rögener, H., Berechnung von Rückkühlwerken, VDI-Wärmeatlas, pp. Mi 1-Mi 15, 1991.
  • Hensley, J., Maximize Tower Power, Chemical Engineering, pp. 74-82, February, 1992.
  • Willa, J.L., Evolution of the Cooling Tower, CTI Journal, Vol. 13, No. 1, pp. 40-49, 1992.
  • Becker, B.R. and Burdick, L.F., Drift Eliminators and Cooling Tower Performance, ASHRAE Journal, pp. 28-36, June 1993.
  • Kranc, SC, Performance of Counterflow Cooling Towers with Structured Packings and Maldistributed Water Flow, Numerical Heat Transfer, Part A, Vol. 23, pp. 115-127, 1993.
  • Mirsky, G.R. and Bauthier, J., Evolution of Cooling Tower Fill, CTI Journal, Vol. 14, No. 1, pp. 12-19, 1993.
  • Du Preez, A.F. and Kröger, D.G., The Influence of a Buoyant Plume on the Performance of a Natural Draft Cooling Tower, 9th IAHR Cooling Tower and Spraying Pond Symposium, Brussels, 1994.
  • Grange, J.L., Calculating the Evaporated Water Flow in a Wet Cooling Tower, Paper presented at the 9th IAHR Cooling Tower and Spraying Pond Symposium, von Karman Institute, Brussels, Belgium, September 1994.
  • Bernier, M.A., Thermal Performance of Cooling Towers, ASHRAE Journal, pp. 56-61, April 1995.
  • Bland, C., A Cool Solution to a Hot Problem, Process Engineering, pp. 33, June, 1995.
  • Conradie, A.E., Performance Optimization of Engineering Systems with Particular Reference to Dry-Cooled Power Plants, Ph.D. Thesis, University of Stellenbosch, South Africa, 1995.
  • Ibrahim, G.A., Nabhan, M.B.W. and Anabtawi M.Z., An Investigation into a Falling Film Type Cooling Tower, International Journal of Refrigeration, Vol. 18, No. 8, pp. 557-564, 1995.
  • Kintner-Meyer, M. and Emery, A.F., Cost-Optimal Design for Cooling Towers, ASHRAE Journal, pp. 46-55, April 1995.
  • Mills, A.F., Basic Heat and Mass Transfer, Irwin, Chicago, 1995.
  • Liffick, G.W. and Cooper, Jr, J.W., Thermal Performance Upgrade of the Arkansas Nuclear One Cooling Tower: A “Root Cause” Analysis Approach, Proceedings of the American Power Conference, Vol. 57, No. 2, pp. 1357-1362, 1995.
  • Oosthuizen, P.C., Performance Characteristics of Hybrid Cooling Towers, M.Eng. Thesis, University of Stellenbosch, Stellenbosch, South Africa, 1995.
  • Sadasivam, M. and Balakrishnan, A.R., On the Effective Driving Force for Transport in Cooling Towers, Transactions of the ASME, Journal of Heat Transfer, Vol. 117, pp. 512-515, May 1995.
  • Mohiuddin, A.K.M. and Kant, K., Knowledge Base for the Systematic Design of Wet Cooling Towers. Part I: Selection and Tower Characteristics, International Journal of Refrigeration, Vol. 19, No. 1, pp. 43-51, 1996.
  • Mohiuddin, A.K.M. and Kant, K., Knowledge Base for the Systematic Design of Wet Cooling Towers. Part II: Fill and other Design Parameters, International Journal of Refrigeration, Vol. 19, No. 1, pp. 52-60, 1996.
  • Bowman, C.F. and Benton, D.J., Oriented Spray-Assisted Cooling Tower, CTI Journal, Vol. 18, No. 1, 1997.
  • Cooling Tower Institute, CTI Code Tower, Standard Specifications, Acceptance Test Code for Water-Cooling Towers, Vol. 1, CTI Code ATC-105(97), Revised, February 1997.
  • De Villiers, E. and Kröger, D.G., Analysis of Heat, Mass and Momentum Transfer in the Rain Zone of Counterflow Cooling Towers, Proceedings of the 1997 IJPGC, Vol.2, PWR-Vol. 32, pp. 141-149, Denver, November 1997.
  • El-Dessouky, H.T.A., Al-Haddad, A. and Al-Juwayhel, F., A Modified Analysis of Counter Flow Wet Cooling Towers, Journal of Heat Transfer, Vol. 119, No. 3, pp. 617-626, 1997.
  • Hoffmann, J.E., The Influence of Temperature Stratification in the Lower Atmospheric Boundary Layer on the Operating Point of a Natural Draft Dry-Cooling Tower, Ph.D Thesis, University of Stellenbosch, Stellenbosch, South Africa, 1997.
  • Huser, A., Nilsen, P.J. and Skatun, H., Application of k-ε Model to the Stable ABL: Pollution in Complex Terrain, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 67 and 68, pp. 425-436, 1997.
  • Al-Nimr, M.A., Dynamic Thermal Behaviour of Cooling Towers, Energy Conversion Management, Vol. 39. No. 7, pp. 631-636, 1998.
  • Baard, T.W., Performance Characteristics of Expanded Metal Cooling Tower Fill, M.Eng Thesis, University of Stellenbosch, Stellenbosch, South Africa, 1998.
  • Conradie, A.E., Buys, J.D. and Kroger, D.G., Performance Optimization of Dry-Cooling Systems for Power Plants through SQP Methods, Applied Thermal Engineering, Vol. 18, Nos. 1-2, pp. 25-40, 1998.
  • Kröger, D.G., Air-Cooled Heat Exchangers and Cooling Towers Thermal-Flow Performance, Evaluation and Design, Begell House, Inc., New York, 1998.
  • Streng, A., Combined Wet/Dry Cooling Towers of Cell-Type Construction, Journal of Energy Engineering, Vol. 124, No. 3, pp. 104-121, December 1998.
  • De Villiers, E. and Kröger, D.G., Inlet Losses in Counterflow Wet-Cooling Towers, Joint Power Generation Conference, Vol.2, PWR-Vol. 34, ASME, 1999.
  • Häszler, R., Einflusz von Kondensation in der Grenzschicht auf die Wärme- und Stoffübertragung an einem Rieselfilm, Fortschritt-Berichte VDI, Reihe 3, Nr. 615, 1999.
  • Söylemez, M.S., Theoretical and Experimental Analysis of Cooling Towers, ASHRAE Transactions: Research, Vol. 105, No. 1, pp. 330-337, 1999.
  • Wallis, J.S. and Aull, R.J., Improving Cooling Tower Performance, Hydrocarbon Engineering, pp. 92-95, May, 1999.
  • Aull, R.J., and Krell, T., Design Features of Cross-Fluted Film Fill and Their Effect on Thermal Performance, CTI Journal, Vol. 21, No. 2, pp. 12-33, 2000.
  • Castro, M.M., Song, T.W. and Pinto, J.M., Minimization of Operational Costs in Cooling Water Systems, Transactions of the Institution of Chemical Engineers, Vol. 78, Part A, pp. 192-201, March, 2000.
  • Goshayshi, H.R. and Missenden, J.F., The Investigation of Cooling Tower Packing in Various Arrangements, Applied Thermal Engineering, Vol. 20, pp. 69-80, 2000.
  • Goyal, O.P., Maintenance and Retrofitting, Guidelines and Troubleshooting, Hydrocarbon Processing, Vol. 79, No. 1, p. 69, 2000.
  • Makkinejad, N., Temperature Profile in Countercurrent/Cocurrent Spray Towers, International Journal of Heat and Mass Transfer, Vol. 44, pp. 429-442, 2001.
  • Milosavljevic, N. and Heikkilä, P., A Comprehensive Approach to Cooling Tower Design, Applied Thermal Engineering, Vol. 21, pp. 899-915, 2001.
  • Roth, M., Fundamentals of Heat and Mass Transfer in Wet Cooling Towers. All Well Known or are Further Developments Necessary? 12th IAHR Symposium in Cooling Towers and Heat Exchangers, UTS, Sydney, Australia, pp. 100-107, November, 2001.
  • Turpin, J.R. (ed.), Want to Save Energy? Look at your Cooling Tower, Engineered Systems, Vol. 18, No. 10, p. 48, 2001.
  • Busch, D., Harte, R., Krätzig, W.B. and Montag, U., New Natural Draft Cooling Tower of 200 m of Height, Engineering Structures, Vol. 24, pp. 1509-1521, 2002.
  • Fisenko, S.P., Petruchik, A.I. and Solodukhin, A.D., Evaporative Cooling of Water in a Natural Draft Cooling Tower, International Journal of Heat and Mass Transfer, Vol. 45, pp. 4683-4694, 2002.
  • Harte, R. and Krätzig, W.B., Large-Scale Cooling Towers as Part of an Efficient and Cleaner Energy Generating Technology, Thin-Walled Structures, Vol. 40, pp. 651-664, 2002.
  • Hawlader, M.N.A. and Lui, B.M., Numerical Study of the Thermal-Hydraulic Performance of Evaporative Natural Draft Cooling Towers, Applied Thermal Engineering, Vol. 22, pp. 41-59, 2002.

Software calibration

The software is an analytical package that employs many semi-empirical equations that calculates the airflow loss coefficients (pressure drops) over the different components of the cooling tower. These air stream losses include:
  • Tower support losses
  • Drift eliminator losses
  • Spray zone losses
  • Fill losses
  • Tower inlet losses
  • Rain zone losses
  • Expansion losses
  • Inlet louvre loses
  • Fill support losses
  • Water distribution system losses
  • Contraction losses
and for mechanical draft towers, these losses as well:
  • Fan upstream losses
  • Fan downstream losses
  • Plenum losses
  • Fan diffuser losses
It is highly unlikely that the geometry of the actual tower that you want to analyze is 100% consistent with the geometry used when the empirical equations were determined. It is therefore unlikely that the software will 100% predict the actual cooling tower performance at the first attempt. Having said that, the semi-empirical equations employed in the software are very robust and are obtained from leading published research. The software will therefore give results that are pretty close to the actual cooling tower, if the software is used correctly.

How do you match the software solution to an actual tower?
For some of the losses mentioned above, only the loss coefficient can be specified. Some recommended loss coefficients for these are given in the literature. If the cooling tower performance does not match actual cooling tower performance closely then it is advisable to play around with these loss coefficients until the cooling tower performance matches closely. The cooling tower is then calibrated to the actual cooling tower.

Parametric studies
Even if the performance predicted by the software is not 100% matched to the actual cooling tower performance, the software can still be used with confidence to do parametric studies, i.e. to answer all those what-if questions. For example, what will the percentage heat load change be if the water flow rate is increased by 10%?

The software and CFD

The wetcooling software package does not use multidimensional CFD, instead it is a one-dimentional analytical model. The multidimentional effects are addressed in the semi-empirical equations of the transfer and pressure drop coefficients. These semi-empirical equations are derived from numerical and experimental studies. The wetcooling software is therefore very cost effective when compared to CFD.

The big question is how do the accuracy of the wetcooling software compare to the accuracy of CFD. Experience has shown that the analytical based models (like the wetcooling software) give results of the same order of magnitude than full-blown CFD simulations. The results of the wetcooling software are, however, obtained at a fraction of the time and cost of the CFD simulations.

Why are CFD models of cooling towers not necessarily more accurate than analytical models? The geometry of a cooling tower is very complex. The water distribution system with the support structure, pipes and nozzles are difficult to accurately model in CFD. Add the water droplets, fill, fill support structure and fan to the CFD model and you can appreciate the increase in complexity of the model. CFD models are therefore simplified by many simplifying assumptions. Some transfer and loss coefficients are obtained from experimental research. These are the same semi-empirical models that are employed in the analytical models. Therefore the same models are used in both CFD and the analytical models and the end results are therefore not too different.

CFD has its place, but...
Having said the above, CFD is still a very powerful and useful tool to analyze cooling tower performance. It can run many scenarios that will be impossible to do with analytical tools. When you consider the cost and time to do CFD analyses, analytical models like the wetcooling software, will always be in demand.

CFD reference
If you are interested in the application of CFD in the analysis of cooling towers I can highly recommend the PhD thesis of N.J.Williamson as a starting point. His thesis is entitled Numerical Modelling of Heat and Mass Transfer and Optimisation of a Natural Draft Wet Cooling Tower, The University of Sydney, Australia, 2009.

Software limitations

The software is based on a semi-empirical analytical approach. The semi empirical equations are used to calculate the following:
  • Airflow loss coefficients through the different components of the tower.
  • Transfer characteristics (Merkel Numbers) in the different transfer zones and especially in the rain zone.
These semi-empirical equations are only valid for certain parameter ranges and operational conditions. The software may therefore not cater for all possible cooling tower sizes and operational conditions. The software will give an answer, but the equations will be extrapolated where the accuracy is unknown. The software will, however, warn the user if some equations are used outside the specified ranges for the design parameters. The software was specifically designed for relatively large industrial cooling towers, and should work without any problem for these towers.

Many different numerical schemes are used in the software to obtain convergence of the equations. There may be some cases where numerical instabilities may occur and the solution process will fail. There are, however, corrective measures implemented in the code that automatically prevents these instabilities. It must be stressed that these cases are very rare. A user familiar with the software can solve the numerical instabilities when they occur by changing the solution control parameters. This is similar to steps taken to ensure stable solutions in CFD software packages.

Fan Specification

The airflow through mechanical draft cooling towers can determined/specified in two different ways:
  1. Firstly, the fan curve can be entered into the software by specifying up to a sixth order polynomial. This case is used when the fan is known. The polynomial (equation) that gives the fan static pressure vs volumetric flow can be entered into the software. The fan curve should be given by the fan manufacturer. The fan curve is only valid for one specific fan configuration, i.e. if the number of fan blades or the blade angle changes then a new curve should be entered into the software for the new configuration. Some fan manufacturers provide software with their fans which generate fan curves for all possible fan configurations. The polynomial that represents the fan curve should be determined by the user by using a curve fitting procedure. Microsoft Excel is commonly used for curve fitting. By using the fan curve the software will determine the operating point of the cooling tower by iteratively solving the draft and energy equations. The fan speed or other cooling tower parameters, like the fill height, can then be varied to achieve the required cooling load.
  2. The second approach is to specify the air flow through the cooling tower that will achieve the required cooling load. The pressure drop through the cooling tower is calculated by the software. The pressure drop and flow rate can then be used to specify a fan that will meet all the geometrical and operational requirements
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