Assessing response surface methodology for modelling air distribution in an experimental pig room to improve air inlet design based on computational fluid dynamics
Introduction
Increasing heat removal is an efficient way to reduce the heat stress and provide thermal comfort for the animals during hot seasons. Air velocity and distribution in the AOZ in livestock buildings has significant impact on the heat removal and consequently animal performance (van Wagenberg and de Leeuw, 2003). There are a number of studies showing that the heat removal, especially convective heat removal from animals, was highly correlated to the air speed in the buildings and higher air velocity will lead to higher convective heat transfer (Gebremedhin, 1987, Li et al., 2016b, Mitchell, 1976, Mitchell, 1985, Monteith and Unsworth, 2013, Wathes and Clark, 1981). In farm animal housing, the air distribution is highly linked with ventilation design. Therefore, it is essential to generate an effective distribution of fresh air within animal occupied space with desired air speed, to enable good thermal comfort for the animals during summer.
The inlet configurations are essential for control of the air motion and distribution in the building, and strongly affect the air speed in AOZ (Bjerg et al., 2002, Zhang et al., 2002). To reduce heat stress of animals, the inlet with jet supplying the air directly to the AOZ has been proved significant effect on the temperature distribution (Bjerg and Zhang, 2013). Additionally, the downward jet has also shown better performance on increasing the convective heat transfer from animal compared with conventional jet inlet with upward or horizontal initial air jet direction at the same flow rate from numerical simulation (Li et al., 2016a). However, further research on the relationship between air speed distribution in AOZ and the inlet parameters is still necessary for the optimal inlet design and control.
It is difficult to measure the real air speed in AOZ directly. Most of the studies in testing the ventilation system use empty rooms to make the measurement of air speeds in AOZ more easily (Bjerg et al., 2002, Randall, 1980, Zong et al., 2015). But the results of those studies can be different from the real condition, since the block effect of pigs are not considered. To measure the air speed in AOZ with pigs involved, van Wagenberg and de Leeuw (2003) use cages to protect the ultrasonic anemometers and place the anemometers in AOZ to measure the air speed. Although the air speed can be measured this way, the blocking from cage may still have effects on the air speed or turbulence intensity. With the development of the computational power of computers, research activity combining with CFD simulation on ventilation and indoor climate of the animal buildings is increasing, due to the lower cost on investigation setups and easier control of study parameters compared to conventional experimental method. Numbers of studies have been conducted on the ventilation study inside the livestock building using CFD method (Blanes-Vidal et al., 2008, Bustamante et al., 2015, Kwon et al., 2015, Lee et al., 2013, Mistriotis et al., 1997, Norton et al., 2009, Norton et al., 2010a, Rong et al., 2015, Wu et al., 2012). Animal models in real geometry are also used in some of CFD studies for environment parameters inside animal buildings to make the simulation results more reliable (Bjerg et al., 2008, Gebremedhin and Wu, 2005, Li et al., 2016b, Seo et al., 2012). Therefore, CFD method was adopted in this study to generate the air speed data in different configurations of the inlet.
The relationship between the air speed in AOZ and the selected parameters of inlet configurations is important for both the inlet configuration study and the inlet control model development. To identify the relationship, statistical data-based models, i.e. the meta-model method, can be used (Wang and Shan, 2007). One of the most well-established and easy-to-use meta-modelling technique is the Response Surface Methodology (RSM) (Simpson et al., 2001). With a proper experimental design, RSM can generate high precision prediction model with reduced number of experiments compared with full factory design. RSM has been used in many research aspects in the field of building ventilation study. For instance, the ventilation rate in the natural ventilated building has been modelled based on the parameters of air speed, air direction, and opening size with RSM (Shen et al., 2012, Shen et al., 2013a, Shen et al., 2013b). Based on RSM, the indoor environment was also studied with different ventilation configurations (Ng et al., 2008, Norton et al., 2010b). All the studies showed RSM has strong potential to build the model in the ventilation study. Concerning the inlet design, the feasibility of RSM method is worthwhile to be investigated.
Thus, the objective of this study is to assess the feasibility of RSM method in developing the model for the average air speed inside the animal occupied zone (AOZ) as a function of the parameters of inlet configurations. The established RSM model will be verified based on simulation data in other setup. Finally, sensitivity analyses will be conducted to identify the key parameter in the developed RSM modelling for the inlet design.
Section snippets
Response surface methodology design
RSM is a combination of mathematical and statistical techniques for formulating the regression model between the selected variables and targeted responses (Anderson and Whitcomb, 2005). Normally, the RSM model can be solved by following four stages, i.e., design of experiment, conduction of the experiments, building the response surface model, and solution optimization.
The RSM model design is highly dependent on the parameters selected as model variables. Before the experiment design, to
Validation of the CFD model
The simulation results agreed with the experimental results well (Fig. 3). It indicated that the CFD model is applicable in the simulation of the air speed which is the main purpose in the study. Therefore, the CFD approach was adopted for the AOZ air speed model development in the following parts with pig models and different inlet designs.
Development of RSM model
Table 3 shows the simulation results of different cases following the experimental design. In general, the cases with downward inlets in 22.5° or 45° showed
Conclusion
In the current work, the RSM has been proven to be a powerful technique in analysing air speeds distribution with respect to various combinations of three design variables. Based on the least square method, first and second order models were used to fit on the simulation generated data in accordance with the Box-Behnken method. Based on the criteria of achieving the highest adjusted R2 and predicted R2, the RSM models in predicting average air speed were developed. Verified with the data
Acknowledgements
Thanks to the support from research grant of Innovation Fund Denmark/Advanced Technology Foundation, New hot climate ventilation system for poultry and pigs (j.nr. 17-2013-3). And the thanks extend to China Scholarship Council (CSC) for the scholarship (201306350135) of Hao Li Ph.D. study in Denmark.
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