Field measurement on the three-dimensional thermal characteristics of a single air inlet induced draft cooling tower

https://doi.org/10.1016/j.applthermaleng.2020.115167Get rights and content

Highlights

  • Field measurement is conducted on a single inlet induced draft cooling tower.

  • A 3D numerical model is developed to collaborate with field measurement.

  • Both velocity and direction of crosswind signally affect tower performance.

  • Longitudinal vortices near the air inlet weaken tower performance.

  • Correlations concerning crosswind are fitted for performance prediction.

Abstract

This study introduces the field measurement on a single air inlet induced draft cooling tower (SIDCT) under crosswind conditions. A three-dimensional numerical model is developed and validated to collaborate with the field measurement. The primary objective of this study is to evaluate the effect of environmental crosswind (both direction and velocity) on the thermal characteristics of SIDCT, such as air/water ratio, range, approach, Merkel number, heat transfer coefficient, etc. Measurement results demonstrate that as crosswind velocity rises, the ventilation and cooling performance of SIDCT are continuously enhanced under the crosswind directions of α1 and α2, while significantly decreased under α3. As air flows into SIDCT along the depth direction, the air temperature above drift eliminators decreases firstly and then increases, which follows a reverse trend to the distribution pattern of air velocity. With the increasing crosswind velocity, the water temperature drop increases in the rain zone under α1 and decreases in the fill zone under α3, while the cooling capacity decreases in the fill zone and increases in the rain zone, regardless of the crosswind direction. The fitted correlations are derived for predicting the performance parameters with respect to crosswind velocity and direction.

Introduction

Mechanical draft cooling towers (MDCTs) are extensively used in chemical, refrigeration and utility industries, with a function of dissipating exhaust heat from hot water into the ambient air. The thermal performance of MDCTs is a key concern in these industrial processes. Therefore, many scholars have conducted theoretical analysis and experimental studies on MDCTs in many regards.

According to the position of draft fan, MDCTs can be divided into forced draft cooling towers (FDCTs) and induced draft cooling towers (IDCTs). Manuel [1], [2] investigated the thermal performance of a FDCT fitted with different water distribution systems and drift eliminators in the lab. Their findings affirms the superiority of pressure water distribution systems as well as the significance of physical configuration of the drift eliminator on tower performance. Through experimental studies on FDCTs, Mehdi [3], [4] revealed the relationship between tower performance and operating parameters, including inlet water temperature, air mass flow rate and water flow rate. Arash [5] experimentally elaborated that a rotational packing could enhanced the thermal performance of a FDCT and that the enhancement is positively correlated with the rotational velocity. Kuljeet [6], [7], [8], [9] conducted a series of experimental studies on a model FDCT. Not only the effect of controlling parameters (i. e. air and water flow rates) on thermal performance but also the influence of inlet parameters (i. e. dry-bulb temperature, relative humidity, water temperature, water, and air flow rates) on exergy performance were investigated in their studies. Based on their findings, pertinent correlations have been developed for performance parameters, and then a feedback model has been further proposed for performance prediction and control. Moreover, Naik [10], Soylemez [11] and Rao [12] have provided different analysis methods to analyze and optimize the performance of FDCTs.

There are mainly two types of IDCTs, namely the single air inlet towers (SIDCTs) and the double air inlet towers (DIDCTs). Through experiments, Ruiz [13] and Lee [14] quantificationally evaluated the interaction between the SIDCT and the external environment, finding that the influencing region and the amount of drift water from SIDCT were affected by crosswind velocity and direction significantly, whereas the tower thermal performance was not involved in their experiments. Girish [15] described a mathematical model for a small SIDCT under windless conditions, finding that the distributions of air velocity, air pressure, moisture fraction, air temperature and water temperatures inside the SIDCT were extremely nonuniform. Easm [16] experimentally studied the performance of a pilot-scale DIDCT equipped with ceramic tile packing, and developed a mass transfer coefficient correlation as well as a theoretical model to predict the tower performance. On the basis of the experimental investigation into a DIDCT with two types of film packing, Farhad [17] indicated that the cooling performance of DIDCT was affected by the type and arrangement of packings and the vertical corrugated packing exerted a better impact on cooling efficiency than the horizontal one. Sandeep [18] explored the practicability of applying IDCTs to reject heat from the supercritical carbon dioxide Brayton cycle, finding that the practicability and economy of IDCTs were superior to those of the dry air cooling or direct water cooling options. Based on the first principles, Viljoen [19] developed a dynamic model of IDCT with parallel heat exchangers, pumps and cooling water network. Their model is applicative for performance optimization and control of cooling towers, which ignores the effect of crosswind. Using a new method for predicting the visible plume region from a DIDCT, Takenobu [20] indicated that the crosswind had an obvious effect on the outlet flow field. Muller [21] described and verified a modelling method for a dual circuit IDCT, which could be used for further simulation and design of cold-end system. According to the least squares support vector machine method and Merkel’s theory, Guo [22] proposed a parallel hybrid model for DIDCT to assess and predict the tower thermal performance. Based on model experiments, Kuljeet [23], [24] proposed an optimization model as well as a constrained multiple parameter inverse identification technique for performance analysis of IDCTs.

The currently used design method for cooling towers is the one-dimensional calculation method [25] without regard to environmental crosswind, which results in a difference between the designed thermal performance and the actual thermal performance. However, existing studies on the thermal performance of IDCTs hardly take account of the effects of crosswind, which are difficult to be explicitly reflected through laboratory investigations and model experiments. In recent years, some scholars have performed field measurements on natural draft cooling towers [26], [27], [28], [29], [30], verifying the crosswind effect on uniformity of circumferential inflow air, thermal performance, ventilation performance, and water droplet diameter distribution, etc.

Based on the above analysis, this study reports the field measurement on a SIDCT for the first time. A three-dimensional numerical model is developed to verify and clarify the experimental results. The primary objective of this study is to reveal the specific effect of crosswind on SIDCT thermal characteristics, such as air/water ratio, range, Merkel number, approach, heat transfer coefficient, air temperature distribution above drift eliminators, and water temperature drop and cooling capacity in each zone. According to the findings of this study, an optimization design method concerning the crosswind effect can be further developed for the thermodynamic calculation of SIDCT. The performance parameters calculated by one-dimensional calculation can be corrected using the fitted correlations derived in this study, and then a more precision design process concerning the non-uniform distribution of air and water parameter can be achieved. In addition, this study can provide a theoretical basis for the energy conservation operation and transformation of SIDCTs with due consideration of drawing on the effect of crosswind.

Section snippets

Measuring object

The measuring object in this study is a SIDCT as depicted in Fig. 1. The SIDCT has an air inlet height (Hi) of 5.8 m, an air outlet height (H) of 18 m, a depth (D) of 16 m, and a width (W) of 16 m. Besides, the fill used in the SIDCT is bidirectional wave fill, with a depth of 1.25 m, a total water spray area of 256 m2, and a bottom height of 7.4 m.

The working principle of the SIDCT is illustrated in Fig. 2. As seen in Fig. 2, a fan with a design total pressure of 157.6 Pa is placed at the air

Numerical modelling

Considering that it is difficult to directly observe some physical phenomena in a SIDCT through field measurement, a three-dimensional numerical model of which the geometric dimensions are identical to the measured SIDCT is developed to verify and clarify the experimental results. Under steady state, the airflow around the SIDCT can be described using the Reynolds Averaged Navier-Stokes equations. The interactions between air and water such as heat transfer, mass transfer and airflow resistance

Ventilation performance of the SIDCT

The thermal performance of a SIDCT depends to a great extent on its ventilation performance. Therefore, it is necessary to assess the ventilation performance using a key performance parameter, air/water ratio λ, which can be calculated by:λ=cwt1-t2kei2-i1ke=1-t2586-0.56(t2-20)where Q is the circulating water flow rate; cw is the specific heat of water; t1 and t2 are the inlet and outlet water temperature, respectively; i1 and i2 are the inlet and outlet air enthalpy value, respectively; and ke is

Uncertainty analysis

Based on the accuracy of the measurement apparatus listed in Table 1, an uncertainty analysis is conducted using theoretical procedures [34] as follows.

If ζ is a function of independent variables x1, x2,… xn, as described in Eq. (12), and ui is the uncertainty (i. e. the standard deviation) of independent variable xi, the computational formula of uncertainty (uζ) and relative uncertainty (uζ/ζ) for ζ can be calculated as Eqs. (12), (13).ζ=fx1,x2,,xnuζ=ζx1u12+ζx2u22++ζxnun2uζζ=1ζζx1u12+

Conclusions

Through the field measurement and numerical calculation on a single air induced draft cooling tower, the effects of crosswind velocity and crosswind direction on the three-dimensional thermal characteristics of the cooling tower have been demonstrated in this study, and the main conclusions are as follows.

  • (1)

    Crosswind increases the air/water ratio under the directions of α1 and α2 while decreases that under α3. When the crosswind velocity changes, the variation rate of air/water ratio under α3 is

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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