Development of a VR simulator for educating CFD-computed internal environment of piglet house

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ScienceDirect journal homepage: www.elsevier.com/locate/issn/15375110

Research Paper

Development of a VR simulator for educating CFDcomputed internal environment of piglet house Rack-woo Kim a,1, Jun-gyu Kim a,1, In-bok Lee a,b,*, Uk-hyeon Yeo a, Sang-yeon Lee a a

Department of Rural Systems Engineering, Research Institute for Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, 599, Gwanakno, Gwanakgu, Seoul 151-921, Republic of Korea b Center for Green Eco Engineering, Institute of Green Bio Science and Technology, Seoul National University, 1447 Pyeongchang-daero, Pyeongchang-gun, Gangwon-do, 25354, Republic of Korea

article info

In terms of maintaining an optimum micro-climates in livestock facilities, many problems

Article history:

exist. In particular, many consultants, as well as farmers, have misunderstand the process

Received 7 April 2019

and often made wrong judgements on ventilation. Airflow is the main mechanism of in-

Received in revised form

ternal environmental distribution. However, airflow is invisible and difficult to predict and

4 September 2019

measure. Computational fluid dynamics (CFD) simulations have been used to analyse the

Accepted 25 October 2019

aerodynamics of livestock building micro-climates. CFD-computed results can be used to

Published online 14 November 2019

educate farmers and consultants. However, they can be of limited use when providing education via a two-dimensional screen. This could be improved by visualising the

Keywords:

computed results in a three-dimensional space rather than on a two-dimensional surface.

Aerodynamic environment

This could be accomplished using virtual reality (VR). In this study, CFD-computed results

Computational fluid dynamics

were combined with VR technology to develop an educational simulator. Firstly, an

Environmental control

extensive review was carried out of research papers, reports, journals, and publications on

Piglet house

the livestock industry, to find seasonally representative problems that occurred at piglet

Simulator

rearing houses in Korea. Then, a CFD simulation model was designed for computing the

Virtual reality

micro-climate of a piglet house according to its external climate and ventilation type. These CFD models were designed based on a 2009 Korean standard for piglet houses using validation results of a previous study (Kim et al., 2017). The CFD-computed results, such as internal airflow, air temperature, humidity, and gas, were then applied to a VR simulator for educating farmers and consultants. Finally, a user interface was developed to maximise accessibility and usability for VR users. © 2019 IAgrE. Published by Elsevier Ltd. All rights reserved.

* Corresponding author. 599, Gwanakno, Gwanakgu, Seoul 08826, Republic of Korea. Fax: þ82 2 873 2087. E-mail address: [email protected] (I.-b. Lee). 1 Co-main authors. https://doi.org/10.1016/j.biosystemseng.2019.10.024 1537-5110/© 2019 IAgrE. Published by Elsevier Ltd. All rights reserved.

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Nomenclature AR CFD CPU F e0 HMD ICT i and j MWPS p DP QA qj RMSE R1 ; R2 Ti ui ; uj UDF UI USD v VR WP dij m r tij

1.

Augmented reality Computational fluid dynamics Central processing unit Floor contamination Total energy (kg m2 s2 kg1) Head mounted display Information and communication technologies Cartesian coordinated indices Mid-west plan service Static pressure (kg m1 s2) Pressure variation in the porous zone (pa) Ammonia gas generation rate (g h1) Heat flux (W m2) Root mean square errors Internal resistance coefficient, viscosity resistance coefficient Air temperature inside room ( C) Speeds of direction (m s1) User defined function User interface United States dollar Flow rate in the porous medium volume (m s1) Virtual reality Weight of piglets (kg) Kronecker delta function Viscosity coefficient of air (kg m2 s1) density (kg m3) Stress tensor (kg m1 s2)

Introduction

Domestic agricultural production in Korea increases every year. The production of the livestock industry had a value approximately 17 billion USD in 2017, reaching 44% of total agricultural production (Statistics Korea, 2018). The annual production of pigs is estimated to reach approximately 5 billion USD, making it the largest contributor among all other species. With the continuous growth of the pig industry, the operation and scale of domestic pig facilities is also changing. The number of household pig farms has been constantly decreasing since 2000, whereas the number of pig farms is steadily increasing every year. This means that the pig rearing facilities are becoming enlarged and densely packed (Statistics Korea, 2018). Along with the increase in the number of largescale pig facilities, the development of smart farms has also been promoted, including development of modern technologies for the ease of management and operation. However, despite the introduction of modern technologies, various considerations for maximising production in livestock facilities must also be considered (see Table 1). While there are four very distinguishable seasons in Korea, it is essential to improve the quality of the feed and breeding and to optimise the internal growth environment to increase the yield in a large-sized facility (Kwon, Lee, & Ha, 2016). In the

case of young pigs that are susceptible to changes in the outside environment, a proper growth environment should be established to avoid the occurrence of disease and mortality, which results in low productivity. Therefore, to reduce the mortality rate and increase the productivity in a large-sized facility, it is very important to control the optimum microclimate inside the facility throughout the year. In South Korea, the average daily air temperatures in summer and winter during the last 30 years have been 24.9  C  C, respectively (Korea Meteorological and 2.4 Administration, 2019). Because of these distinctive climate characteristics, proper control of the growth environment is considered very important. In the case of the winter season, cold stress can occur if external air flows directly into the facility. In this scenario, most farms provide minimal ventilation to prevent cold stress, but this results in low air quality inside the facility. In some situations, external air enters through the unplanned openings or poorly sealed gaps resulting in uneven air temperatures and increased in heating energy costs. These can lead to difficulties in controlling the inside environment of the pig houses (Schiffman, 1998). During the summer season, heat inside the pig houses accumulates, creating a high-temperature and high-humidity environment. If fresh air is not sufficiently provided, the feed efficiency and the weight gain of the pigs may be reduced (Yoo et al., 2010). This is especially true in a large-scale facility, where it is more difficult to maintain uniformity, such that the control of the internal growth environment has the largest impact on productivity. Thus, it is very important to have proper environmental management inside a large-scale facility and a good understanding of air flow. As air flow is the main mechanism for change in indoor air quality such as air temperature, humidity, gas, and flow, it is necessary to maintain the uniformity of the air environment inside the facility through a ventilation system. A series of studies evaluating the air quality in pig facilities owing to ventilation has been conducted (Blanes & Pedersen, 2005; Chen et al., 2014; Daskalov, 1997; Huynh et al., 2005; Kwon et al., 2016; Ogilvie, Barber, & Randall, 1990; Seedorf et al., 1998; Van’t Klooster & Heitlager, 1994; Yoo et al., 2010). In recent years, studies have been actively conducted using computational fluid dynamics (CFD), which can easily analyse problems involving various ventilation structures and types of facilities, and which can quantitatively comprehend the air flow (Bjerg, Rong, & Zhang, 2018; Ha, Lee, Kwon, & Lee, 2018; Hong et al., 2017; Jacobsen, Nielsen, & Morsing, 2004; Kim et al., 2018a,b; Kwon et al., 2016; Lee et al., 2013; Lee, Lee, & Kim, 2018; Li, Rong, & Zhang, 2017; Norton, Sun, Grant, Fallon, & Dodd, 2007; Park et al., 2018; Seo et al., 2008; Yeo, Lee, Seo, & Kim, 2018; Zhang, Choi, Bartzanas, Lee, & Kacira, 2018). Results from these research papers suggested that proper education should be conducted for farmers and consultants to improve facility operation and maximise production. However, the education of farmers and consultants using these results has had many difficulties. Farming education is more effective when conducted directly in the field, but access to facilities is restricted, owing to the need to prevent infectious diseases. In addition, because of recently security problems in the operation of large facilities, interactions among farmers

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Table 1 e Survey results of the main problems in piglet houses based on the literature review. Season Winter

Problems Cold stress

Ammonia & Oder Non-uniformity

Summer

Infiltration Animal density Heat stress Ammonia & Oder

Non-uniformity Wind stress Animal density

References (Bjerg et al., 2018; Hayes et al., 2013; Jeong, Kim, Khan, Han, & Kwag, 2014; Kim, Song, & Choi, 2012; Kwon et al., 2016; Kwon et al., 2010; Moon, Kim, Nah, Kim, & Kim, 2015; Song & Choi, 2005; Young, 1981) etc. (Kim, Moon, Lee, Choi, & Lee, 2004; Kim et al., 2008; Lee & Lee, 2010; Lee et al., 2005; Lee et al., 2006; Ni, 1999; Schiffman, 1998; Seo et al., 2008; Song et al., 2005) etc. (Bjerg et al., 2018; Kim, Lee, Choi, Kim, & Park, 2005; Kwon et al., 2016; Seo et al., 2008) etc. (Hong et al., 2012, 2017; Seo et al., 2008; Song et al., 2005) etc. (Kwon, Lee, Zhang, & Ha, 2015; Moon et al., 2015; Seo et al., 2008) etc. (Blanes & Pedersen, 2005; Kim, Ko, & Kim, 2012; Kwon et al., 2010; Kwon et al., 2015; Moon et al., 2015; Song et al., 2005; Young, 1981) etc. (Blanes & Pedersen, 2005; Den Brok, van der Peet-Schwering, & Vrielink, 1997; Jacobsen et al., 2004; Kim et al., 2008; Lee & Lee, 2010; Lee et al., 2006; Ni, 1999; Ni, Heber, Diehl, & Lim, 2000; Schiffman, 1998; Song et al., 2005; Van’t Klooster & Heitlager, 1994; Yasuhara, Fuwa, & Jimbu, 1984) etc. (Bjerg et al., 2018; Kim et al., 2005; Kwon et al., 2016; Seo et al., 2008) etc. (Chen et al., 2014; Lee, Jeon, & Song, 2014; Moon et al., 2015; Seo, Lee, Moon, & Kwon, 2014) etc. (Kwon et al., 2015; Moon et al., 2015; Seo et al., 2008) etc.

are blocked. Further, quantitative results such as air temperature, humidity, and airflow may not be easily understood by farmers and consultants, especially because the flow of air is invisible. The behaviour of airflows cannot be grasped intuitively, and existing research results are not easy to understand, as they are represented by a two-dimensional crosssections. Recently, with the 4th industrial revolution, Virtual Reality (VR) technology is rapidly emerging, and is being used in various fields such as medical care, education, and entertainment (Aretz, 1991; Choi, Han, Kim, & Cha, 2010; Greenwald, Wang, Funk, & Maes, 2017; Gunn, Jones, Bridge, Rowntree, & Nissen, 2018; Kim et al., 2018a,b; Shanaham, 2016). In the field of education, VR has been mainly used in firefighting and disaster simulation training, where an actual situation is difficult to recreate. Although VR has been widely used as an educational method in various industrial fields, there have been only a few attempts to incorporate it in the field of agriculture, and almost no development for education and consulting on agriculture. When VR is applied to agriculture facilities, the main environmental factors of airflow and air quality inside the facility can be understood more easily and clearly, and a three-dimensional experiential education is possible, instead of a two-dimensional cross-section. In particular, as the importance of the 4th industrial revolution and corresponding smart farms is on the rise, it is necessary to research adding VR and its many advantages in agricultural facilities. Therefore, for an effective farmhouse education, it is necessary to develop virtual reality (VR) to overcome the aforementioned limitations. In this study, to develop a VR simulator for education, a CFD model was developed, to simulate the airflow and internal environment according to the ventilation structure while the target animal house was a piglet house because of high mortality during this period. The CFD model was developed based on a turbulence model and grid independence test results that were validated in a previous study

(Kim et al., 2017). A three-dimensional virtual space and visualisation method was developed, and a VR simulator for education was developed and then combined with CFDcomputed results.

2.

Materials and methods

In this study, a field survey and a literature survey were conducted to elucidate typical aerodynamic problems occurring in the piglet houses. Based on the results of these surveys, CFD modelling and simulation were conducted. The CFD model was previously validated using field experiment data in a previous study (Kim et al., 2017). From the CFD-computed results, the air quality of the piglet house was analysed, and the CFD database was extracted by coordinates to link the CFD data to the VR. For the development of the VR simulator, a three-dimensional structure and piglet model were designed and placed in the virtual space. The CFD database was linked to the virtual space, and the computed results were visualised. Finally, for user convenience and accessibility, a user interface (UI) was created, and a performance test was conducted (see Fig. 1).

2.1.

Target facility

In this study, the central area of South Korea is selected as the representative domestic climate conditions. Farmers are encouraged to use standardised facilities, but the penetration rate of the standardised facilities is remarkably low. Therefore, the size of the target facility was selected based on a 2009 Korean standard (Fig. 2), so that it can be subsequently distributed (Korea Pork Producers Association, 2009). Various types of inlets and outlets were considered for analysis because many farms use various ventilation structures. It is important to control the environment in the piglet room because piglets are susceptible to environmental changes.

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Fig. 1 e Flow chart of the study for development of virtual reality (VR) simulator for farmers and consultants.

Fig. 2 e The schematic diagram of piglet room of the 2009 Korean standard for computational fluid dynamics (CFD) simulation and virtual reality (VR) simulator (Korea Pork Producers Association, 2009).

Therefore, a piglet room was selected as a experimental facility.

2.2.

Field and literature survey

The main problems of domestic piglet houses were surveyed to utilise them in CFD analysis and in useful educational materials for farmers and consultants. To determine the main problems, actual farms were visited and surveys were

conducted (Fig. 3). As field surveys require a large amount of time and money, literature resources such as research papers, report data, farming materials issued by major national agencies, and related news and articles were also utilised. The problems and causes of domestic piglet houses were summarised by season, and the causes and solutions of the main problems were analysed so that they could be used as educational data. From the survey results, a UI of the VR simulator was constructed.

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Fig. 3 e Field experiments for monitoring and collecting main problems seasonally inside the pig farm.

2.3.

Computational fluid dynamics (CFD)

CFD is a simulation method that analyses the physical and chemical phenomena of an object by calculating physical quantities such as force, pressure, velocity and temperature, by designing and numerically analysing a grid in the system including the fluid. CFD is composed of three processing steps: pre-processing, main processing, and post-processing. The pre-processing step is a process involving design of an object’s shape or the topography. In contrast, the main processing is concerned with computing the flow of each fluid and energy in the grid designed in the pre-processing step. The postprocessing step visually displays the results of the main processing step. To numerically analyse the physical quantities of the individual grid in the main computation stage, mass, momentum, and energy conservation laws are applied using the Navier-Stokes equation, which is a nonlinear algebraic partial differential equation obtained for a small test volume. The mass, momentum, and energy conservation equations applied to each grid are given by the following Eqs (1)e(3).
vr v þ ruj ¼ 0 vt vxj

(1)




v v v v ðrui Þ þ rui uj ¼  pdij þ tij vt vxj vxj vxj

(2)



v v v  v ðre0 Þ þ u j p þ qj þ ruj e0 ¼  ui tij vt vxj vxj vxj

(3)

In the above equations, uj and ui are the i and j speeds of direction (m s1), p is a static pressure (kg m1 s2), e0 is the total energy (kg m2 s2 kg1), qj is the heat flux (W m2), r is the density (kg m3), tij is a stress tensor (kg m1 s2), and dij is the Kronecker delta function (1 for i ¼ j, 0 for i sjÞ.

2.4.

Virtual reality (VR)

VR refers to a virtual environment or situation created by artificial technology, using equipment such as computers. Among the next generation of information and communication technologies (ICT), VR and augmented reality (AR) are attracting attention as leaders in the 4th industrial revolution because of their application and satisfaction among users (Guttentag, 2010). In comparison with AR, VR displays additional information on a virtual screen. In addition, VR

interacts with a simulation through senses of sight and hearing in an artificial environment. First-generation VR allowed a user to experience a virtual image in a space through a 4D screen. Second-generation VR was developed to experience a virtual space through an image display with head-mounted-display (HMD) equipment. Third-generation VR will be an experience through brainwave interworking, but more development of the technology is needed (Jeong, 2017).

2.5.

Experimental procedure

2.5.1.

Cases of Cfd simulation

Because various ventilation systems are used in domestic piglet houses and the distributions of the internal environment according to the ventilation systems are different, CFD simulations were conducted to build database for all the ventilation types used in Korea (Fig. 4). To define the cold stress problem, the excessive accumulation of humidity and ammonia gas problem in winter, cases were classified according to inlet and outlet types. Inlet types were classified as 30 , 45 , and 90 as the angles of the side slot type, and 45 and 90 as the angles of ceiling slot type and ceiling hole type, respectively (Fig. 5). The outlet types of the exhaust fan were classified as side wall, chimney, and pit types. Ventilation rates were set as the minimum ventilation rate in the 2009 Korean standard and a modified ventilation rate, respectively. Results from field and literature surveys revealed that many farmers utilise a heating box and heater to prevent low temperatures during winter. Therefore, these were included in the simulation cases, because they might affect the internal airflow. A total of 104 cases were selected during the winter season to evaluate the main problems and the improvement of the internal environment. Similarly, in the case of summer, various ventilation systems were considered. As the ventilation rate is maximum in summer, combination of three ventilation fans was considered, such as side fan with chimney fan, side fan with pit fan and all fans. In addition, the type of the fence in the piglet group, which can affect the air current inside the piglet room and environment around the piglet group, was simulated. In summer, the maximum ventilation rate of the 2009 Korean standard (Korea Pork Producers Association, 2009) is similar to the “Mid-West Plan Service” (MWPS) standard (Midwest Plan Service, 1988), but it is nevertheless suggested to calculate the maximum ventilation

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Fig. 4 e The cases of CFD models for aerodynamic analysis during winter and summer seasons.

case of ammonia gas generation, the temperatures near the slurry in winter and summer are assumed to be 20  C and 30  C, respectively, and the total number of piglets is 180. Considering that the average weight of the 7-week-old piglets was 24 kg, the total weight was calculated as 4320 kg (Ni, 1999).
QA ¼ 54:22F þ 12:02 R2 ¼ 0:723

(4) 1

In Eq. (4), QA is the ammonia gas generation rate (g h ), and F is the floor contamination (dimensionless).
F ¼ 1:82  1010 Ti 7 þ 1:97  1019 WP 5 R2 ¼ 0:811

Fig. 5 e The schematic design of a piglet house and all ventilation system configurations.

rate according to domestic climate conditions. However, as the basis for calculating the ventilation rate is ambiguous, it can be smaller as well in some situation than the actual performance and effect of the ventilation fan. Thus, cases were selected according to the calculation method of the ventilation rate. The total number of cases covering summer was 120.

2.5.2.

Design of the Cfd model and boundary condition setting

In consideration of the various analysis cases, the inlet types are arranged in a side slot, ceiling slot, and ceiling hole. To analyse the change of the internal flow according to the angle, the side slot type has 30 , 45 , and 90 angles. The ceiling slot type has 45 and 90 angles. The outlet types are side outlet, chimney outlet, and pit outlet. The CFD models were designed according to all of the ventilation types (Fig. 5). In this study, a three-dimensional piglet model was used to consider the influence of the micro-climate around the piglets, and the effects of heat and moisture caused by the respiration of piglets. Seo et al. (2008) simulated the temperature at the piglet surface, considering the convergence of the CFD simulation and reasonable grid design results. The surface temperature of piglets in this study was based on that previous research. To consider the effects of ammonia gas generation and diffusion in the piglet room, an internal space of the pit was designed, and the ammonia gas and moisture generation were calculated by following Eqs. (4) and (5). In the

(5)

In Eq. (5), Ti is the air temperature inside room ( C), and WP is the weight of piglets (kg). In the case of moisture generation, the water content in the bottom was simulated using an experimental result of measuring an amount of moisture generation without cleaning, in an area of the same size as the target facility (Hayes et al., 2013). To imitate the moisture generated by breathing, the amount of water production was simulated considering the piglet respiration rate in winter and summer, and the size of the mouth (9.8  104 m2). For efficiency of computation, the bottom was designed as a porous medium, and the effect of the diffusion of ammonia gas inside the pit and the effect on the internal air flow were considered. When passing through the porous zone, the resistance factor against the flow in the x, y, z axes can be calculated by the following Eq. (6) (Bjerg, Zhang, & Kai, 2008). Considering the shape of the bottom slot, vertical flow exists, and horizontal airflow is limited. DP ¼ 0:5  R1  r  v2 þ m  R2 v

(6)

In Eq. (6), DP is the pressure variation in the porous zone (pa), R1 is the internal resistance coefficient, R2 the is viscosity resistance coefficient, r is the density of air (kg m3), v is the flow rate in the porous medium volume (m s1), and m is the viscosity coefficient of air (kg m2 s1). In this model, previous research results were used to obtain the porous characteristics of the bottom slots (Bjerg et al., 2008). Outside weather conditions were selected based on results of the weather data analysis for the last 30 years. Weather data for the winter and summer were used for analysis under extreme environmental conditions. The temperature of the wall surface was set based on the previous research. The

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surface temperatures of piglets were determined on the basis of measured surface temperatures through a thermal imaging camera for 7-week-old piglets during the winter and summer season. The ammonia gas generation rate under the pit was calculated using the results of previous research (Ni, 1999). The total weight of the 7-week-old piglets was calculated considering 180 piglets, and the mean air temperature inside the piglet room was assumed to be 20  C in winter and 30  C in summer. Based on previous research, the moisture generation can be classified into that from respiration, the surface of the manure, and areas near the water nipple (Hayes et al., 2013). The amount of water generated (18 l min1) through respiration was set to an inlet type in each piglet’s mouth, considering the mouth size. The ventilation rate was calculated using the method in the 2009 Korean standard (Eqs. (7)e(9)). It is suggested to modify the ventilation rate in the summer, considering the specific climate conditions (Korea Pork Producers Association, 2009).
Ventilation rate ðmild weatherÞ m3 hr1 ¼meanweighthead 1:3 (7)
Minimum Ventilation rate m3 hr1 ¼mildventilationrate 0:2
Maximum Ventilation rate m3 hr1 ¼mildventilationrate 350

(8)

(9)

Figure 6 presents the results of three-dimensional modelling of piglet house and the grid formation. Kim et al. (2017) conducted a grid independence test to determine the accuracy of results according to the grid size inside a piglet house. Grid sizes of 0.1, 0.2, 0.3, and 0.4 (m) were analysed, and the grid size of 0.1 (m) was selected, in consideration of the accuracy of computation results and efficiency of computation time. Thus, in this study, 0.1 (m) size was used, and the number of grids was approximately 6 million. The minimum value of the orthogonal quality was 0.219, and the optimum quality was over 0.01. The skewness value, which is a statistical index for evaluating the accuracy of a grid, was 0.85, which is a proper level of 0.95 or less. In addition, turbulence is a factor that has a great influence on the convergence and accuracy of the computation and the numerical analysis. Kim et al. (2017) compared simulation results obtained by using the

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standard k-ε, RNG k-ε, Realisable k-ε, Standard k-u, and SST ku turbulence models. The comparison of each computed data and field experiment data showed that the errors were 9.1, 10.1, 11.4, 5.8, and 10.7, and the root mean square errors (RMSE) were 11.3, 13.7, 14.2, 7.5, and 13.8, respectively. In the case of using a standard k-u turbulence model, the mean error and RMSE were smaller than those of the other turbulence models, and were simulated to be the closest to field experiments. Therefore, in this study, the standard k-u turbulence model was used.

2.5.3.

Development of VR simulator

To design the virtual space, the three-dimensional structures and a piglet model were designed. To maximise the performance and user experience, a Head-mount-display (VIVE, HTC Inc., Taiwan) was used. HMD equipment allows users to experience visual and auditory effect based on motion tracker. In the virtual space, users can directly experience the VR by using the room scale setting. In addition, a glove-type controller that can be selected and manipulated intuitively was added, and various motions were made through a sensor that detects a positional movement of the user’s wrist (Fig. 7). Unity software is a game engine that provides an environment for two-dimensional and three-dimensional video games, and is an integrated production tool for creating interactive content such as three-dimensional animation, architectural visualisation, and VR. A variety of personalised asset materials are provided for interworking. In this study, virtual spaces were created using open source Unity software that does not require licences. For the user to feel the reality in the virtual space, the visual effect recognised by the user and the number of frames shown in the virtual space should be well-balanced. If the number of frames is too small, the user may feel dizziness, and the reality may deteriorate. Thus, a high-performance graphics card and PC hardware should be equipped to increase the number of frames. Therefore, in this study, an i9 central processing unit (CPU) with 32 GB of memory and a GTX 1080ti graphic card were used. In addition, an optimal number of frames (25e30 frames s1) was applied through modelling optimisation. Figure 8 depicts the development process. In Fig. 8 (a), based on the three-dimensional structure and piglet models, the objects of the virtual piglet and piglet house were constructed in virtual space. Using the Unity software, the same scale was associated inside as the actual shape, and the three-

Fig. 6 e Computational domain and mesh design for the target piglet house.

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Fig. 7 e (a) The equipment for displaying the VR space and controlling the movement in the VR simulator, (b) glove-type controller and tracker for tracking the gestures in the VR simulator.

Fig. 8 e Development process of the virtual simulator with the three-dimensional model and visualization of CFD-computed results in virtual space.

dimensional objects were inserted at each coordinate. The material and shape of actual structures were realised, so that user can feel reality. The basic coordinate axes were unified with the CFD model coordinate axes, so that the CFD analysis results can be visualised. When the user selected a ventilation system inside the piglet house, an animation effect was inserted to realise the change of the structure, and in the case of the exhaust fan, the blade was set to rotate. To design a realistic three-dimensional piglet model, many materials were used. Additionally, a variety of motions was added to make the model more natural. The greater the number of polygons in the piglet model, the more realistic the piglet model appears. However, if the number of polygons increases, polygon optimization should be performed, because this

requires high performance to calculate many frames in the VR space. When the user was in the piglet room, the lighting and texture were expressed so as to maximise the realism. As the contrast of the surrounding structure changes according to the position of the light source, and the shape recognition can be changed according to a shadow effect, an accurate position of the lighting is captured and located. In the case of a surface texture, it was based on photographs taken from field experiments. In Fig. 8 (b), to visualise the CFD-computed results, user-defined function (UDF) codes were developed for extracting the computed results. The database was constructed based on the same time-interval data using the UDF codes. In addition, coordinate interpolation of air temperature, humidity, gas concentration, and airflow data were

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Table 2 e Input values for the boundary conditions of the computational fluid dynamics (CFD) simulation used in this study. Boundary Condition

Value

Reference

Winter

Summer

2.5 ( C) 0.0023 (kg kg1 da1)

30.5 ( C) 0.0196 (kg kg1 da1)

Ammonia

Surface temperature of the piglet Surface temperature of the ceiling Surface temperature of the indoor wall Surface temperature of the outside wall Surface temperature of the floor Ammonia generation rate from manure

39.6 ( C) 20.3 ( C) 19.7 ( C) 19.2 ( C) 18.6 ( C) 3.808e7 (kg m2 s1)

39.7 ( C) 31.3 ( C) 30.4 ( C) 31.2 ( C) 26.2 ( C) 5.304e7 (kg m2 s1)

Humidity

Moisture generation

Heating

Heater

4.332 (g s1) 0.4832 (g s1) 149.7 ( C)

7.932 (g s1) 1.0432 (g s1) e

Weather

Outside

Temperature

Air temperature Absolute humidity

Breath Manure

conducted through the UDF codes. The database can be changed in the starting coordinate point and the number of data. In this study, the database was extracted considering the load of the simulator performance. The database was visualised by using contour, vector, and smoke effects in the same coordinates in the virtual space. Various colours and shapes were used for visualisation, and the most expressive method that the user could understand was used. The customisable UI with high accessibility was designed, so that user could select and experience the proper scenario. The design of the UI is based on the intuitive touch method in consideration of the usability of the controller, and the operator functions used are for a beginner who is inexperienced using the VR simulator. In Fig. 8 (c), the initial version of the simulator was connected to demonstrate the UI and visualisation, and the stability of the VR equipment was tested to find errors. Finally, performance tests were conducted to complete the training simulator.

3.

Results and discussion

Using CFD simulation, the internal air temperature, humidity, ammonia concentration, and airflow were analysed according to the various ventilation systems in the piglet house. The outside weather conditions were classified into winter (104 cases) and summer (120 cases), and all the comprehensive analysis according to the ventilation systems are contained in my paper (Kim, 2019). Among them, some representative cases were presented as an example (see Table 2).

3.1.

CFD analysis of aerodynamic problems in winter

In the winter season, airflow is significantly different because of the minimised ventilation, so the distributions of the internal air temperature, humidity, and ammonia gas concentration are different. In particular, the route of airflow varies according to the type of inlet and outlet. The outside air temperature is 2.5  C in winter, and the minimum ventilation rate is 18.7 m3 min1. The CFD-computed results are

30-year weather data analysis of target site Winter night & summer daytime (poor condition) Seo et al. (2008) Seo et al., 2008; Bjerg et al., 2013; Choi et al., 2014; etc.

(Kwon, Son, & Choi, 2008); Lee & Lee, 2010; Kam et al., 2011 etc. Hayes et al., 2013 etc. Kwon et al., 2008

shown in Table 3 and Fig. 9. The ventilation system can be divided into the airflow entering from the corridor of the side wall, and that entering through the ceiling. When the inlet type of side wall (90 open) is used, the average air temperature around the piglets is 22.8  C, which is below the air temperature of 25.9  C in winter, according to field experiment reports of the Animal and Plant Quarantine Agency (APQA, 2008). In addition, near the area where outside air flows directly, the lowest temperature is 12.0  C, which shows a very poor temperature distribution. The inlet type through the side wall is considered to be inappropriate, as the inflow path of the outside air is too short for the air to warm up. The slot angle of the side wall could be formed to partially prevent the low air temperature stress. As a result of forming the angle, it was confirmed that the air temperature was improved by 5  C or more. As shown in Fig. 10(b), the angle of the side wall can guide airflow to the top of the piglet room. As shown in Fig. 10 (c, d), when the air entered through the ceiling space, the average air temperature around the piglets was distributed over 24  C, and the low temperature stress problem did not occur. The average air temperature near the piglets was approximately 1e2  C higher than that of the side inlet when the inlet was the ceiling hole. This is similar to the results of the field experiment (Song et al., 2002). When the outside air passes through the ceiling space, the air temperature can be buffered because of a buoyancy effect. If the ceiling hole is used as the inlet, the airflow rate can be further lowered, which is considered to be advantageous for warming. In terms of air temperature uniformity around the piglets, when the air entered from the inlet of the side wall, lowtemperature air was concentrated near the side wall, and the coefficient of variation was 1.4 or more. This means that the air temperature near the piglets was non-uniform. In contrast, when the outside air entered through the ceiling, the temperature deviation was small near the piglets, because the air fell down slowly from the upper part of the piglet room. The coefficient of variation was 0.09. It was evaluated that the pit outlet type is suitable for improving uniformity, because it can exhaust the air slowly through several holes.

252

Table 3 e CFD-computed results of air temperature and ammonia concentration according to ventilation systems in winter. Inlet

Outlet Side outlet

Side slot 90 Side slot 45 Side slot 30 Ceiling hole

Ceiling slot 90 Ceiling slot 45

Minimum Temperature ( C)

Ammonia Concentration (ppm)

Average Temperature ( C)

Minimum Temperature ( C)

Pit outlet Ammonia Concentration (ppm)

Average Temperature ( C)

Minimum Temperature ( C)

Ammonia Concentration (ppm)

Standard Deviation

Average

Standard Deviation

Average

Standard Deviation

Average

Coefficient of variation

Maximum

Coefficient of variation

Maximum

Coefficient of variation

Maximum

22.8 3.43 0.15 23.1 3.34 0.14 23.0 3.32 0.14 25.5 2.53 0.10 24.5 3.2160 0.13 25.1 3.03 0.12

12.0

17.6

17.8

20.2

18.2

19.0

22.58 55.62 e 23.01 49.10 e 22.29 43.33 e 29.96 78.28 e 26.07 68.72 e 31.13 90.79 e

22.8 3.47 0.15 23.1 3.35 0.15 23.2 3.34 0.14 25.6 2.54 0.10 24.4 3.21 0.13 24.8 3.10 0.13

12.4

16.8

18.5

20.2

17.9

19.3

22.84 51.00 e 24.08 56.86 e 23.10 52.73 e 29.56 65.66 e 26.73 69.69 e 27.30 68.70 e

25.2 2.81 0.11 24.7 2.71 0.11 24.6 3.16 0.13 26.8 2.48 0.09 26.2 2.50 0.10 25.8 2.56 0.10

10.8

16.7

18.9

20.3

19.9

20.1

27.04 58.13 e 25.72 58.41 e 28.22 59.61 e 24.50 52.47 e 23.28 57.04 e 23.53 49.85 e

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Average Temperature ( C)

Chimney outlet

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Fig. 9 e Example CFD-computed results of air temperature, relative humidity, and ammonia concentration in winter.

Ammonia gas from the manure inside the pit can spread around the piglets (Fig. 11). In most farms, ammonia gas may accumulate excessively if the minimum ventilation rate is used to prevent the inflow of cold air. As shown in Fig. 12, when fresh air entered from the inlet of the side wall, the ammonia gas concentration near the side wall was low. However, it accumulates around the outlet of the exhaust fan. In the case of ceiling hole inlet type, the average ammonia concentration was formed at 29e30 ppm, owing to insufficient fresh air around the piglets. It was considered that the ammonia gas removal efficiency was poor. The ammonia gas concentration was different according to the type of outlet. The use of a pit exhaust fan resulted in a 3e5 ppm reduction effect as compared to the use of side wall and chimney fans. Because ammonia gas is generated from the manure, an exhaust fan located above the piglets can make the ammonia gas rise through and around the piglets. By contrast, the pit exhaust fan located under the piglet can prevent ammonia gas from spreading around the piglets. The moisture generation inside the piglet room was simulated to occur from the breathing of piglets and the manure. There was no significant difference in the relative humidity according to the ventilation system (Fig. 13). The relative humidity distribution showed a similar trend to the air temperature distribution. It is considered that an appropriate relative humidity can be maintained through controlling the air temperature.

3.2.

CFD analysis of aerodynamic problems in summer

Owing to the sunlight outside the facility and the heat of a piglet’s body during the summer, high temperature problems can arise easily. Therefore, maximum ventilation is needed to reduce the heat inside the piglet room. Humidity and ammonia gas concentration problems rarely occur, because the maximum ventilation rate is sufficient to provide fresh air inside the piglet room. However, operating at an excessively high ventilation rate may be inefficient because of wind stress, overload of the exhaust fan, and a high electricity cost. The MWPS offers a method of calculating a ventilation rate (Midwest Plan Service, 1988), and it is recommended that the ventilation rate should be raised, considering the local weather conditions in the 2009 Korean standard (Korea Pork Producers Association, 2009). The distributions of the internal environment according to the two methods of calculating ventilation rate were compared and analysed. In addition, the air flow according to the fence type was analysed. Figure 14 and Table 4 show that when the outside air temperature is 30.5  C, the maximum ventilation rate is 327 m3 min1 according to the 2009 Korean standard, and 178 m3 min1 according to the MWPS. Figure 14 shows that there is almost no significant difference in the temperature distribution between the 2009 Korean standard and MWPS. In both methods, the average air temperature inside the piglet room was close to the appropriate

254

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Fig. 10 e Examples of CFD-computed results (air temperature) according to inlet type in piglet house (the side view-the location of the inlet & the top view-the height of the piglet). temperature range of 30.0e32.0  C. As the air temperature difference between the two methods is small at 0.6  C, there was no significant effect on the upward adjustment of the ventilation rate. In Fig. 15, the reason for the air temperature difference appearing around the piglets is the airflow. The airflow is too fast to reach the piglets. In the case of the side wall inlet type, the average flow velocity was more than 2.0 m s1, and the airflow appeared above the piglets. Fresh air was provided near the entry point when the air entered through the ceiling slot inlet type. However, it was estimated that high temperature stress could occur in other areas. Therefore, it was assessed that operating the maximum ventilation rate in the summer season with the method of the 2009 Korean standard would be inefficient in preventing high temperature stress. Meanwhile, the excessive operating of the exhaust fan can cause the piglets to have wind stress, and cause premature ageing of the exhaust fan. To reduce heat stress, it is important to reduce the body temperature of the piglets. Therefore, the computed results are analysed according to the shape of the fence that can affect the airflow around the piglets, as shown in Fig. 16. It has been shown that using a pane-type fence can cause heat accumulation, because the airflow is not smooth around the piglets. Meanwhile, when a pipe-type fence was used, the airflow was free, and fresh air could be provided around the piglets. Therefore, it would be better to avoid blocking the airflow because of the fence type, to provide fresh air around the piglets.

Humidity and ammonia gas inside the piglet room are sufficiently controlled through the maximum ventilation rate in the summer. Moreover, owing to the high ventilation rate, the odour and dust inside the piglet room can be considerably discharged to the outside.

3.3.

Development of VR simulator

3.3.1.

Three-dimensional model in VR simulator

To develop a VR simulator for education, objects to be placed in the virtual space need to be designed first. The threedimensional objects were divided into geometry data, external shapes, and a texture of the surface. The geometry was designed based on the physical size, and the same coordinate system was used to link with the CFD-computed results. In addition, the target facility was developed to be equal to the actual size ratio, so that the user did not feel awkward in the virtual space. Simplified or omitted parts in the CFD model were implemented realistically in the virtual space. The most significant performance impact is the number of polygons in the object geometry. If a large number of polygons are used in VR, the number of frames increases. This can cause overload, or the VR image may be truncated, causing dizziness to the users. Thus, the existing polygons were preserved, and all of the polygons that were not in the user’s view were removed. The reality of the object was improved by creating a texture image based on a real photo from a field experiment. Figure 17 shows the results of assembling objects made of precise

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Fig. 11 e Examples of CFD-computed results (ammonia concentration) according to inlet type in piglet house (the side viewthe location of the inlet & the top view-the height of the piglet).

Fig. 12 e Examples of CFD-computed results (Ammonia concentration) according to outlet type in piglet house (the side view-the location of the inlet & the top view-the height of the piglet).

specifications, such as piglet house structures, ventilation systems, and feeders. Modelling software (zBrush, Pixologic, USA) was used to design the piglet objects. The shape of the piglet object was created by comparing it with a photograph directly, using the zBrush software. The ratio of each body part was determined based on a skeletal diagram of the piglet. The shapes of the fat

and muscle were made by adding shading. The surface geometry consists of textures, and each texture is based on a grid point located on the geometry. The distance of the grid points determines the resolution of the surface texture, and the piglet model was designed by covering the natural image. The total of 12 piglet objects were made for the VR simulator (Fig. 18).

256

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Fig. 13 e Examples of CFD-computed results (relative humidity) according to inlet type in piglet house (the side view-the location of the inlet & the top view-the height of the piglet).

Fig. 14 e Examples of CFD-computed results of air temperature, relative humidity, ammonia concentration, and velocity in summer.

Table 4 e CFD-computed results of average air temperature and wind velocity around the piglets in summer according to the ventilation system. Inlet

Outlet Ventilation rate of 2009 Korean standard

Side slot 90 Side slot 45 Side slot 30 Ceiling hole Ceiling slot 90 Ceiling slot 45

Side fan + Pit fan

Side fan + Chimney fan + Pit fan

Average Temperature ( C)

Average Velocity (m s1)

Average Average Average Average Temperature Velocity Temperature Velocity ( C) (m s1) ( C) (m s1)

32.6

1.00

32.6

0.79

32.6

32.6

1.32

32.6

0.99

32.8

1.29

32.7

32.2 32.4

0.33 1.41

32.4

1.42

Side fan + Chimney fan

Side fan + Pit fan

Average Temperature ( C)

Average Velocity (m s1)

Average Average Temperature Velocity ( C) (m s1)

0.82

32.7

0.55

33.0

32.6

0.98

32.6

0.69

1.13

32.8

1.08

32.7

32.3 32.5

0.27 1.13

32.2 32.6

0.27 1.13

32.4

1.10

32.5

1.10

Side fan + Chimney fan + Pit fan Average Temperature ( C)

Average Velocity (m s1)

0.41

32.9

0.43

32.6

0.57

32.6

0.59

0.78

32.7

0.60

32.6

0.55

32.3 32.6

0.21 0.76

32.5 32.7

0.17 0.64

32.3 32.7

0.18 0.64

32.5

0.74

32.6

0.60

32.6

0.62

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Side fan + Chimney fan

Ventilation rate of Mid-West Plan Service (MWPS)

257

258

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Fig. 15 e Examples of CFD-computed results (air temperature) according to ventilation rate in piglet house (the side view-the location of the inlet & the top view-the height of the piglet).

Fig. 16 e Examples of CFD-computed results (vector field & air temperature) according to fence type in piglet house (the top view-the height of the piglet). Based on the objects of the three-dimensional structures and piglets, each part of the appropriate object was assembled in the virtual space. The inlet and outlet objects are divided

into individual objects, so that users can reflect what they choose in the UI (see Fig. 19).

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259

Fig. 17 e Development of three-dimensional structure object and equipment object using Maya software based on piglet house of a 2009 Korean standard.

3.3.2.

Importing CFD-computed data in VR simulator

After creating the virtual space, the CFD-computed results were imported to visualise the data according to the case study. CFD-computed results can be overloaded in the data loading process, because they create numerous points when linked with VR. Thus, all computed data was re-extracted into optimised grid points. To interpolate the data by coordinate, pixel colour interpolation of the shader was conducted. A shader is a set of instructions that calculates a rendering effect, which is an effect that makes the space between the grids appear infinite. To calculate this, as shown in Fig. 20, the data value of the pixel r in one grid is obtained by using 8 data values (k1 to k8). The value between k1 and k2 is calculated as the floor (k, k2, x2) function using the value x2 of r(x)-k(x). Similarly, the values of r2, r4, and r5 are calculated as the floor (r1, r2, y2) function using the value y2 of r(y)ek(y). In the same way, the value of r6 is obtained, and the final r value between r3 and r6 is obtained as a function of the floor (r3, r6, z2) function using the value z2 of r(z)ek(z). Based on the CFD-computed results, a UDF code was developed that could extract data by determining the number and distances in the x, y, and z directions from the initial coordinates. UDF codes were used to obtain scalar values of the air temperature, relative humidity, ammonia concentration, and velocity at the specified coordinates. In addition, a vector field representing the airflow was extracted from the u, v, and w directions, and the values

for each direction vector were extracted. Based on all of the data, a VR database file was constructed for all CFD cases.

3.3.3.

Visualisation of CFD-computed data in VR

Based on the UDF codes, 37,740 coordinates were extracted for each CFD case in the VR database. In the cases of air temperature, relative humidity, and ammonia gas, a contour plane was formed based on the data, and an RGB value was applied so that the user can intuitively understand it. In addition, it was composed of an x-plane, y-plane, and z-plane, so that it can be represented according to the position of the contour. In the virtual space, an alpha value was applied, so as not to disturb the peripheral vision owing to the contour colour. To express the air flow, a vector field was developed by visualizing the vector values of the u, v, and w directions of the grid points. As the vector was represented by the threedimensional data of each point, it can interfere with the user’s view (Fig. 21 (a)). To overcome this problem, a vector plane was designed with velocity values and directional values, after eliminating the normal vector values of a given plane. In the case of vector planes, direction and speed values should be visualised so that users can understand them easily, and at the same time, the distribution of flow within the piglet room in virtual spaces should be visible. Thus, various shapes and images were designed through demonstration, with the highest

Fig. 18 e Development of piglet geometry and grid point for real shape in VR space.

260

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Fig. 19 e Development of VR space using the structure objects according to the cases of CFD simulation.

Fig. 20 e Scheme of coordinate calculation for (a) data interpolation between the grids of CFD-computed results, (b) vector coordinates, and (c) vector field.

preference being selected (Fig. 21 (b)). As the plane can be moved by the user’s gesture, it has the advantage of being able to grasp all the flows in the VR. Because the vector plane represents only the velocity and direction of a specific point, it was difficult to understand the flow by time steps. Therefore, stream line data representing the position of each particle by time step is extracted and visualised. The stream line data represents the path from the

inlet to the outlet. An effect of smoke generation was added, so that the users could experience the wind flow more realistically (Fig. 22). Finally, the user selected the expression method that best understood air temperature, relative humidity, ammonia gas concentration, and flow rate, and it was developed as an example, as shown in Fig. 23. The developed contour and vector planes were designed to allow the user to move freely,

Fig. 21 e Result of three-dimensional vector field using CFD-computed data.

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261

Fig. 22 e Visualisation of smoke effect using stream line data in VR simulator.

Fig. 23 e Data visualisation technology to show environmental factors (air temperature, relative humidity and ammonia concentration) in VR piglet house.

Fig. 24 e Development of user interface which can select all the ventilation type and external environment condition easily. and to identify ventilation structures and environmental elements. In the case of vector planes, data from grid points were developed to experience air flow intuitively, by adding animation effects that move according to flow rate and direction data values.

3.3.4.

Development of user interface

Early versions of VR simulators were readily available to developers and experts, but training subjects have a lot of difficulties in using them. Thus, to enhance user accessibility and convenience, the separate set of configurations was developed for professionals and beginners. First, the contents of the UI are composed of terms familiar to farmers based on the results of field research and literature research, and the

visualised case scenarios were created based on problems typically generated by pig house that were easily selected and developed for experience. Various demonstrations were held to collect opinions from users and to make a series of corresponding modifications. Various VR contents were reviewed, and the optimal behaviour was selected and applied to the production of the user interface (Fig. 24). In addition, the narration was inserted for users to understand the scenario more easily while experiencing the VR.

3.3.5.

Optimisation of VR simulator

Optimisation is essential for the commercialisation of VR simulator. Therefore, a performance improvement was carried out based on the developed three-dimensional VR model

Fig. 25 e The computing load of the simulator according to the rendering method.

262

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Fig. 26 e Final version of VR simulator for educating farmers and consultants. and the CFD-computed results. As the three-dimensional model in VR is to appear identical to the actual one, the rendering time of the simulator may become longer. This can result in an unnatural screen shift for the user to experience. As the VR equipment required a lot of performance, it combined “Frustum Culling” and “Occlusion Culling” technology to eliminate unnecessary loading, and to compute the area included in the viewing angle of the user. Frustum Culling is a function that invalidates the rendering of objects outside the viewing angle, and Occlusion Culling is a function that invalidates the rendering of all overdrawn objects obscured by other objects in the viewing angle (Fig. 25). When the CFD database was visualised in the virtual space, the image modification was conducted, so that the experience was not hindered by visual factors. Excessive increases in contrast or chroma may result in poor subscription and an awkward virtual environment. In addition, if an animation effect was inserted at the same time, the user may experience dizziness. Therefore, several performance tests were performed so as not to have a sense of disturbance while maintaining a proper number of frames. After conducting the performance tests, a build-up demonstration was conducted for users, to improve the accessibility and convenience of the UI. Based on the results of the demonstration, the UI was updated by a simple entry method (Fig. 26).

imported all CFD-computed results. Users can also learn various improvement of these problems using VR simulator. Through the UI considering the accessibility and convenience of the user, the VR simulator can be used variously such as farmers, consultants and students. In addition, it is expected that the development of VR for various animals and facilities with CFD simulation will expand the application of VR simulator.

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.

Acknowledgments This work was carried out with the support of the “Advanced development of 1st generation smart plant farm/animal farm (Project No. 319018-01)” Ministry of Agriculture, Food and Rural Affairs, Republic of Korea.

references

4.

Conclusions

It is important of maintaining an optimum micro-climate in the piglet house for maximising production. However, the air flow which is the main mechanism of change of internal air qualities such as air temperature, humidity and ammonia gas is invisible and difficult to predict and measure. Aerodynamically analysis using CFD simulation can be used to educate farmers and consultants, however, there is a limit to farmer education with CFD-computed results of internal environment in piglet house through two-dimensional screens. To overcome this limitation, in this study, educational VR simulator using CFD simulation technology was developed. Through the developed VR simulator, farmers and consultants can receive effective education in a threedimensional VR space. Especially, they can experience the internal airflow and various environmental factors according to the ventilation type and operation. It was possible to experience the seasonal problems caused by misuse of ventilation type and operation through the VR simulator

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